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wehub-resource-sync
2026-07-13 12:14:16 +08:00
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tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/BUILD
+25
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load("//tensorflow:tensorflow.default.bzl", "filegroup")
load("//tensorflow/compiler/mlir:glob_lit_test.bzl", "glob_lit_tests")
# copybara:uncomment package(default_applicable_licenses = ["//tensorflow:LICENSE"])
licenses(["notice"])
glob_lit_tests(
name = "all_tests",
data = [":test_utilities"],
driver = "@llvm-project//mlir:run_lit.sh",
test_file_exts = ["mlir"],
)
# Bundle together all of the test utilities that are used by tests.
filegroup(
name = "test_utilities",
testonly = True,
data = [
"//tensorflow/compiler/mlir/lite:flatbuffer_to_string",
"//tensorflow/compiler/mlir/lite:flatbuffer_translate",
"@llvm-project//llvm:FileCheck",
"@llvm-project//llvm:not",
],
)
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/basic_lstm.mlir
+149
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// Copyright 2026 The TensorFlow Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// ==============================================================================
// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_to_string - | FileCheck %s
func.func @main(tensor<1x384xf32>, tensor<1x96xf32>, tensor<384x480xf32>, tensor<384xf32>, tensor<1x96xf32>) -> tensor<1x96xf32> {
// CHECK: {
// CHECK-NEXT: version: 3,
// CHECK-NEXT: operator_codes: [ {
// CHECK-NEXT: deprecated_builtin_code: 16,
// CHECK-NEXT: version: 2
// CHECK-NEXT: builtin_code: LSTM
// CHECK-NEXT: } ],
// CHECK-NEXT: subgraphs: [ {
// CHECK-NEXT: tensors: [ {
// CHECK-NEXT: shape: [ 1, 384 ],
// CHECK-NEXT: buffer: 1,
// CHECK-NEXT: name: "arg0",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 1, 96 ],
// CHECK-NEXT: buffer: 2,
// CHECK-NEXT: name: "arg1",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 384, 480 ],
// CHECK-NEXT: buffer: 3,
// CHECK-NEXT: name: "arg2",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 384 ],
// CHECK-NEXT: buffer: 4,
// CHECK-NEXT: name: "arg3",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 1, 96 ],
// CHECK-NEXT: buffer: 5,
// CHECK-NEXT: name: "arg4",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 1, 96 ],
// CHECK-NEXT: buffer: 6,
// CHECK-NEXT: name: "tfl.basic_lstm",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 1, 96 ],
// CHECK-NEXT: buffer: 7,
// CHECK-NEXT: name: "tfl.basic_lstm:1",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 1, 480 ],
// CHECK-NEXT: buffer: 8,
// CHECK-NEXT: name: "tfl.basic_lstm:2",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 1, 384 ],
// CHECK-NEXT: buffer: 9,
// CHECK-NEXT: name: "tfl.basic_lstm:3",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: } ],
// CHECK-NEXT: inputs: [ 0, 1, 2, 3, 4 ],
// CHECK-NEXT: outputs: [ 5 ],
// CHECK-NEXT: operators: [ {
// CHECK-NEXT: inputs: [ 0, 1, 2, 3, 4 ],
// CHECK-NEXT: outputs: [ 5, 6, 7, 8 ],
// CHECK-NEXT: builtin_options_type: LSTMOptions,
// CHECK-NEXT: builtin_options: {
// CHECK-NEXT: fused_activation_function: RELU,
// CHECK-NEXT: cell_clip: 1.0,
// CHECK-NEXT: proj_clip: 2.0,
// CHECK-NEXT: kernel_type: BASIC
// CHECK-NEXT: },
// CHECK-NEXT: intermediates: [ ]
// CHECK-NEXT: } ],
// CHECK-NEXT: name: "main"
// CHECK-NEXT: } ],
// CHECK-NEXT: description: "MLIR Converted.",
// CHECK-NEXT: buffers: [ {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 49, 46, 49, 48, 46, 48, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
// CHECK-NEXT: } ],
// CHECK-NEXT: metadata: [ {
// CHECK-NEXT: name: "min_runtime_version",
// CHECK-NEXT: buffer: 10
// CHECK-NEXT: } ]
// CHECK-NEXT: signature_defs: [ ]
// CHECK-NEXT:}
^bb0(%arg0: tensor<1x384xf32>, %arg1: tensor<1x96xf32>, %arg2: tensor<384x480xf32>, %arg3: tensor<384xf32>, %arg4: tensor<1x96xf32>):
%0:4 = "tfl.basic_lstm"(%arg0, %arg1, %arg2, %arg3, %arg4) {fused_activation_function = "RELU", cell_clip = 1.0 : f32, proj_clip = 2.0 : f32} : (tensor<1x384xf32>, tensor<1x96xf32>, tensor<384x480xf32>, tensor<384xf32>, tensor<1x96xf32>) -> (tensor<1x96xf32>, tensor<1x96xf32>, tensor<1x480xf32>, tensor<1x384xf32>)
func.return %0#0 : tensor<1x96xf32>
}
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/bucketize.mlir
+88
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// Copyright 2026 The TensorFlow Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// ==============================================================================
// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_to_string - | FileCheck %s
func.func @main(tensor<3x2xf32>) -> tensor<3x2xi32> {
^bb0(%arg0: tensor<3x2xf32>):
// CHECK: {
// CHECK-NEXT: version: 3,
// CHECK-NEXT: operator_codes: [ {
// CHECK-NEXT: deprecated_builtin_code: 127,
// CHECK-NEXT: version: 1,
// CHECK-NEXT: builtin_code: BUCKETIZE
// CHECK-NEXT: } ],
// CHECK-NEXT: subgraphs: [ {
// CHECK-NEXT: tensors: [ {
// CHECK-NEXT: shape: [ 3, 2 ],
// CHECK-NEXT: buffer: 1,
// CHECK-NEXT: name: "arg0",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 3, 2 ],
// CHECK-NEXT: buffer: 2,
// CHECK-NEXT: name: "Const",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 3, 2 ],
// CHECK-NEXT: type: INT32,
// CHECK-NEXT: buffer: 3,
// CHECK-NEXT: name: "bucketize",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: } ],
// CHECK-NEXT: inputs: [ 0 ],
// CHECK-NEXT: outputs: [ 2 ],
// CHECK-NEXT: operators: [ {
// CHECK-NEXT: inputs: [ 1 ],
// CHECK-NEXT: outputs: [ 2 ],
// CHECK-NEXT: builtin_options_type: BucketizeOptions,
// CHECK-NEXT: builtin_options: {
// CHECK-NEXT: boundaries: [ 0.0, 10.0, 100.0 ]
// CHECK-NEXT: }
// CHECK-NEXT: } ],
// CHECK-NEXT: name: "main"
// CHECK-NEXT: } ],
// CHECK-NEXT: description: "MLIR Converted.",
// CHECK-NEXT: buffers: [ {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 0, 0, 160, 192, 0, 64, 28, 70, 0, 0, 22, 67, 0, 0, 32, 65, 0, 0, 160, 64, 0, 0, 200, 66 ]
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 50, 46, 56, 46, 48, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
// CHECK-NEXT: } ],
// CHECK-NEXT: metadata: [ {
// CHECK-NEXT: name: "min_runtime_version",
// CHECK-NEXT: buffer: 4
// CHECK-NEXT: } ],
// CHECK-NEXT: signature_defs: [ ]
// CHECK-NEXT: }
// CHECK-EMPTY:
%0 = "tfl.pseudo_const" () {value = dense<[[-5.0, 10000.0], [150.0, 10.0], [5.0, 100.0]]> : tensor<3x2xf32>} : () -> tensor<3x2xf32> loc("Const")
%1 = "tfl.bucketize"(%0) {boundaries = [0.0 : f32, 10.0 : f32, 100.0 : f32]} : (tensor<3x2xf32>) -> tensor<3x2xi32> loc("bucketize")
func.return %1 : tensor<3x2xi32>
}
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/cast_bf16.mlir
+88
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// Copyright 2026 The TensorFlow Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// ==============================================================================
// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -emit-custom-ops -o - | flatbuffer_to_string - | FileCheck %s
func.func @main(tensor<4x5xbf16>) -> tensor<4x5xbf16> {
^bb0(%arg0: tensor<4x5xbf16>):
// CHECK: {
// CHECK-NEXT: version: 3,
// CHECK-NEXT: operator_codes: [ {
// CHECK-NEXT: deprecated_builtin_code: 53,
// CHECK-NEXT: version: 7,
// CHECK-NEXT: builtin_code: CAST
// CHECK-NEXT: } ],
// CHECK-NEXT: subgraphs: [ {
// CHECK-NEXT: tensors: [ {
// CHECK-NEXT: shape: [ 4, 5 ],
// CHECK-NEXT: type: BFLOAT16,
// CHECK-NEXT: buffer: 1,
// CHECK-NEXT: name: "arg0",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4, 5 ],
// CHECK-NEXT: buffer: 2,
// CHECK-NEXT: name: "cast1",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4, 5 ],
// CHECK-NEXT: type: BFLOAT16,
// CHECK-NEXT: buffer: 3,
// CHECK-NEXT: name: "cast2",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: } ],
// CHECK-NEXT: inputs: [ 0 ],
// CHECK-NEXT: outputs: [ 2 ],
// CHECK-NEXT: operators: [ {
// CHECK-NEXT: inputs: [ 0 ],
// CHECK-NEXT: outputs: [ 1 ]
// CHECK-NEXT: }, {
// CHECK-NEXT: inputs: [ 1 ],
// CHECK-NEXT: outputs: [ 2 ]
// CHECK-NEXT: } ],
// CHECK-NEXT: name: "main"
// CHECK-NEXT: } ],
// CHECK-NEXT: description: "MLIR Converted.",
// CHECK-NEXT: buffers: [ {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 50, 46, 49, 55, 46, 48, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
// CHECK-NEXT: } ],
// CHECK-NEXT: metadata: [ {
// CHECK-NEXT: name: "min_runtime_version",
// CHECK-NEXT: buffer: 4
// CHECK-NEXT: } ],
// CHECK-NEXT: signature_defs: [ ]
// CHECK-NEXT: }
%0 = "tfl.cast" (%arg0) : (tensor<4x5xbf16>) -> tensor<4x5xf32> loc("cast1")
%1 = "tfl.cast" (%0) : (tensor<4x5xf32>) -> tensor<4x5xbf16> loc("cast2")
func.return %1 : tensor<4x5xbf16>
}
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/composite.mlir
+328
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// Copyright 2026 The TensorFlow Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// ==============================================================================
// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_to_string - | FileCheck %s
// CHECK: {
// CHECK-NEXT: version: 3,
// CHECK-NEXT: operator_codes: [ {
// CHECK-NEXT: deprecated_builtin_code: 127,
// CHECK-NEXT: version: 1,
// CHECK-NEXT: builtin_code: STABLEHLO_COMPOSITE
// CHECK-NEXT: }, {
// CHECK-NEXT: version: 1
// CHECK-NEXT: }, {
// CHECK-NEXT: deprecated_builtin_code: 41,
// CHECK-NEXT: version: 1,
// CHECK-NEXT: builtin_code: SUB
// CHECK-NEXT: } ],
// CHECK-NEXT: subgraphs: [ {
// CHECK-NEXT: tensors: [ {
// CHECK-NEXT: shape: [ 10 ],
// CHECK-NEXT: buffer: 1,
// CHECK-NEXT: name: "arg0",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 10 ],
// CHECK-NEXT: buffer: 2,
// CHECK-NEXT: name: "arg1",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ ],
// CHECK-NEXT: buffer: 3,
// CHECK-NEXT: name: "arith.constant",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ ],
// CHECK-NEXT: buffer: 4,
// CHECK-NEXT: name: "arith.constant1",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 10 ],
// CHECK-NEXT: buffer: 5,
// CHECK-NEXT: name: "vhlo.composite_v1",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 10 ],
// CHECK-NEXT: buffer: 6,
// CHECK-NEXT: name: "vhlo.composite_v11",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 10 ],
// CHECK-NEXT: buffer: 7,
// CHECK-NEXT: name: "tfl.add",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 10 ],
// CHECK-NEXT: buffer: 8,
// CHECK-NEXT: name: "tfl.sub",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: } ],
// CHECK-NEXT: inputs: [ 0, 1 ],
// CHECK-NEXT: outputs: [ 7 ],
// CHECK-NEXT: operators: [ {
// CHECK-NEXT: inputs: [ 0, 1 ],
// CHECK-NEXT: outputs: [ 4 ],
// CHECK-NEXT: builtin_options_2_type: StableHLOCompositeOptions,
// CHECK-NEXT: builtin_options_2: {
// CHECK-NEXT: name: "test.TEST_COMPOSITE",
// CHECK-NEXT: decomposition_subgraph_index: 2,
// CHECK-NEXT: composite_attributes: [ 109, 121, 95, 97, 114, 114, 97, 121, 0, 1, 97, 0, 1, 98, 0, 2, 6, 4, 20, 20, 1, 21, 1, 1, 1, 9, 40, 2, 36, 1 ]
// CHECK-NEXT: }
// CHECK-NEXT: }, {
// CHECK-NEXT: inputs: [ 4, 1 ],
// CHECK-NEXT: outputs: [ 5 ],
// CHECK-NEXT: builtin_options_2_type: StableHLOCompositeOptions,
// CHECK-NEXT: builtin_options_2: {
// CHECK-NEXT: name: "test.TEST_COMPOSITE",
// CHECK-NEXT: decomposition_subgraph_index: 1,
// CHECK-NEXT: composite_attributes: [ 109, 121, 95, 97, 114, 114, 97, 121, 0, 1, 97, 0, 1, 98, 0, 2, 6, 4, 20, 20, 1, 21, 1, 1, 1, 9, 40, 2, 36, 1 ]
// CHECK-NEXT: }
// CHECK-NEXT: }, {
// CHECK-NEXT: opcode_index: 1,
// CHECK-NEXT: inputs: [ 5, 2 ],
// CHECK-NEXT: outputs: [ 6 ],
// CHECK-NEXT: builtin_options_type: AddOptions,
// CHECK-NEXT: builtin_options: {
// CHECK-EMPTY:
// CHECK-NEXT: }
// CHECK-NEXT: }, {
// CHECK-NEXT: opcode_index: 2,
// CHECK-NEXT: inputs: [ 6, 3 ],
// CHECK-NEXT: outputs: [ 7 ],
// CHECK-NEXT: builtin_options_type: SubOptions,
// CHECK-NEXT: builtin_options: {
// CHECK-EMPTY:
// CHECK-NEXT: }
// CHECK-NEXT: } ],
// CHECK-NEXT: name: "main"
// CHECK-NEXT: }, {
// CHECK-NEXT: tensors: [ {
// CHECK-NEXT: shape: [ 10 ],
// CHECK-NEXT: buffer: 9,
// CHECK-NEXT: name: "XlaCallModule_test.TEST_COMPOSITE.impl_0_arg0",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 10 ],
// CHECK-NEXT: buffer: 10,
// CHECK-NEXT: name: "XlaCallModule_test.TEST_COMPOSITE.impl_0_arg1",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ ],
// CHECK-NEXT: buffer: 11,
// CHECK-NEXT: name: "arith.constant2",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 10 ],
// CHECK-NEXT: buffer: 12,
// CHECK-NEXT: name: "tfl.add1",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 10 ],
// CHECK-NEXT: buffer: 13,
// CHECK-NEXT: name: "tfl.add2",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: } ],
// CHECK-NEXT: inputs: [ 0, 1 ],
// CHECK-NEXT: outputs: [ 4 ],
// CHECK-NEXT: operators: [ {
// CHECK-NEXT: opcode_index: 1,
// CHECK-NEXT: inputs: [ 0, 1 ],
// CHECK-NEXT: outputs: [ 3 ],
// CHECK-NEXT: builtin_options_type: AddOptions,
// CHECK-NEXT: builtin_options: {
// CHECK-EMPTY:
// CHECK-NEXT: }
// CHECK-NEXT: }, {
// CHECK-NEXT: opcode_index: 1,
// CHECK-NEXT: inputs: [ 3, 2 ],
// CHECK-NEXT: outputs: [ 4 ],
// CHECK-NEXT: builtin_options_type: AddOptions,
// CHECK-NEXT: builtin_options: {
// CHECK-EMPTY:
// CHECK-NEXT: }
// CHECK-NEXT: } ],
// CHECK-NEXT: name: "XlaCallModule_test.TEST_COMPOSITE.impl_0"
// CHECK-NEXT: }, {
// CHECK-NEXT: tensors: [ {
// CHECK-NEXT: shape: [ 10 ],
// CHECK-NEXT: buffer: 14,
// CHECK-NEXT: name: "XlaCallModule_test.TEST_COMPOSITE.impl_0_0_arg0",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 10 ],
// CHECK-NEXT: buffer: 15,
// CHECK-NEXT: name: "XlaCallModule_test.TEST_COMPOSITE.impl_0_0_arg1",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ ],
// CHECK-NEXT: buffer: 11,
// CHECK-NEXT: name: "arith.constant3",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 10 ],
// CHECK-NEXT: buffer: 17,
// CHECK-NEXT: name: "tfl.add3",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 10 ],
// CHECK-NEXT: buffer: 18,
// CHECK-NEXT: name: "tfl.add4",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: } ],
// CHECK-NEXT: inputs: [ 0, 1 ],
// CHECK-NEXT: outputs: [ 4 ],
// CHECK-NEXT: operators: [ {
// CHECK-NEXT: opcode_index: 1,
// CHECK-NEXT: inputs: [ 0, 1 ],
// CHECK-NEXT: outputs: [ 3 ],
// CHECK-NEXT: builtin_options_type: AddOptions,
// CHECK-NEXT: builtin_options: {
// CHECK-EMPTY:
// CHECK-NEXT: }
// CHECK-NEXT: }, {
// CHECK-NEXT: opcode_index: 1,
// CHECK-NEXT: inputs: [ 3, 2 ],
// CHECK-NEXT: outputs: [ 4 ],
// CHECK-NEXT: builtin_options_type: AddOptions,
// CHECK-NEXT: builtin_options: {
// CHECK-EMPTY:
// CHECK-NEXT: }
// CHECK-NEXT: } ],
// CHECK-NEXT: name: "XlaCallModule_test.TEST_COMPOSITE.impl_0_0"
// CHECK-NEXT: } ],
// CHECK-NEXT: description: "MLIR Converted.",
// CHECK-NEXT: buffers: [ {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 0, 0, 32, 65 ]
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 0, 0, 160, 65 ]
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 0, 0, 200, 66 ]
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 50, 46, 49, 55, 46, 48, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
// CHECK-NEXT: } ],
// CHECK-NEXT: metadata: [ {
// CHECK-NEXT: name: "min_runtime_version",
// CHECK-NEXT: buffer: 19
// CHECK-NEXT: } ],
// CHECK-NEXT: signature_defs: [ ]
// CHECK-NEXT:}
func.func @main(%arg0: tensor<10xf32>, %arg1: tensor<10xf32>) -> (tensor<10xf32>) {
%cst = arith.constant dense<1.000000e+01> : tensor<f32>
%cst_0 = arith.constant dense<2.000000e+01> : tensor<f32>
%0 = "vhlo.composite_v1"(%arg0, %arg1) <{composite_attributes = #vhlo.dict_v1<{#vhlo.string_v1<"my_array"> = #vhlo.array_v1<[#vhlo.string_v1<"a">, #vhlo.string_v1<"b">]>}>, decomposition = #vhlo.string_v1<"XlaCallModule_test.TEST_COMPOSITE.impl_0_0">, name = #vhlo.string_v1<"test.TEST_COMPOSITE">, version = #vhlo.integer_v1<0 : i64>}> : (tensor<10xf32>, tensor<10xf32>) -> tensor<10xf32>
%1 = "vhlo.composite_v1"(%0, %arg1) <{composite_attributes = #vhlo.dict_v1<{#vhlo.string_v1<"my_array"> = #vhlo.array_v1<[#vhlo.string_v1<"a">, #vhlo.string_v1<"b">]>}>, decomposition = #vhlo.string_v1<"XlaCallModule_test.TEST_COMPOSITE.impl_0">, name = #vhlo.string_v1<"test.TEST_COMPOSITE">, version = #vhlo.integer_v1<0 : i64>}> : (tensor<10xf32>, tensor<10xf32>) -> tensor<10xf32>
%2 = tfl.add(%1, %cst) <{fused_activation_function = "NONE"}> : (tensor<10xf32>, tensor<f32>) -> tensor<10xf32>
%3 = tfl.sub(%2, %cst_0) <{fused_activation_function = "NONE"}> : (tensor<10xf32>, tensor<f32>) -> tensor<10xf32>
return %3 : tensor<10xf32>
}
func.func private @XlaCallModule_test.TEST_COMPOSITE.impl_0(%arg0: tensor<10xf32>, %arg1: tensor<10xf32>) -> tensor<10xf32> {
%cst = arith.constant dense<1.000000e+02> : tensor<f32>
%0 = tfl.add %arg0, %arg1 {fused_activation_function = "NONE"} : tensor<10xf32>
%1 = tfl.add(%0, %cst) <{fused_activation_function = "NONE"}> : (tensor<10xf32>, tensor<f32>) -> tensor<10xf32>
return %1 : tensor<10xf32>
}
func.func private @XlaCallModule_test.TEST_COMPOSITE.impl_0_0(%arg0: tensor<10xf32>, %arg1: tensor<10xf32>) -> tensor<10xf32> {
%cst = arith.constant dense<1.000000e+02> : tensor<f32>
%0 = tfl.add %arg0, %arg1 {fused_activation_function = "NONE"} : tensor<10xf32>
%1 = tfl.add(%0, %cst) <{fused_activation_function = "NONE"}> : (tensor<10xf32>, tensor<f32>) -> tensor<10xf32>
return %1 : tensor<10xf32>
}
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/custom_op_with_tflite_op.mlir
+131
View File
@@ -0,0 +1,131 @@
// Copyright 2026 The TensorFlow Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// ==============================================================================
// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -emit-custom-ops -o - | flatbuffer_to_string - | FileCheck %s
func.func @main(tensor<4xf32>) -> tensor<4xf32> {
^bb0(%arg0: tensor<4xf32>):
// CHECK: {
// CHECK-NEXT: version: 3,
// CHECK-NEXT: operator_codes: [ {
// CHECK-NEXT: deprecated_builtin_code: 18,
// CHECK-NEXT: version: 1
// CHECK-NEXT: builtin_code: MUL
// CHECK-NEXT: }, {
// CHECK-NEXT: deprecated_builtin_code: 32,
// CHECK-NEXT: custom_code: "MyCustomOp",
// CHECK-NEXT: builtin_code: CUSTOM
// CHECK-NEXT: }, {
// CHECK-NEXT: deprecated_builtin_code: 47,
// CHECK-NEXT: version: 1,
// CHECK-NEXT: builtin_code: EXP
// CHECK-NEXT: } ],
// CHECK-NEXT: subgraphs: [ {
// CHECK-NEXT: tensors: [ {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 1,
// CHECK-NEXT: name: "arg0",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 2,
// CHECK-NEXT: name: "Const",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 3,
// CHECK-NEXT: name: "mul",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 4,
// CHECK-NEXT: name: "MyCustomOp",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 5,
// CHECK-NEXT: name: "exp",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: } ],
// CHECK-NEXT: inputs: [ 0 ],
// CHECK-NEXT: outputs: [ 4 ],
// CHECK-NEXT: operators: [ {
// CHECK-NEXT: inputs: [ 0, 1 ],
// CHECK-NEXT: outputs: [ 2 ],
// CHECK-NEXT: builtin_options_type: MulOptions,
// CHECK-NEXT: builtin_options: {
// CHECK-EMPTY:
// CHECK-NEXT: }
// CHECK-NEXT: }, {
// CHECK-NEXT: opcode_index: 1,
// CHECK-NEXT: inputs: [ 2, 1 ],
// CHECK-NEXT: outputs: [ 3 ],
// CHECK-NEXT: custom_options: [ 102, 117, 115, 101, 100, 95, 97, 99, 116, 105, 118, 97, 116, 105, 111, 110, 95, 102, 117, 110, 99, 116, 105, 111, 110, 0, 4, 82, 69, 76, 85, 0, 105, 110, 116, 95, 97, 116, 116, 114, 0, 2, 42, 11, 2, 1, 2, 20, 2, 20, 4, 4, 36, 1 ]
// CHECK-NEXT: }, {
// CHECK-NEXT: opcode_index: 2,
// CHECK-NEXT: inputs: [ 3 ],
// CHECK-NEXT: outputs: [ 4 ],
// CHECK-NEXT: builtin_options_type: ExpOptions,
// CHECK-NEXT: builtin_options: {
// CHECK-EMPTY:
// CHECK-NEXT: }
// CHECK-NEXT: } ],
// CHECK-NEXT: name: "main"
// CHECK-NEXT: } ],
// CHECK-NEXT: description: "MLIR Converted.",
// CHECK-NEXT: buffers: [ {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 0, 0, 128, 63, 0, 0, 128, 63, 0, 0, 128, 63, 0, 0, 128, 63 ]
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 49, 46, 55, 46, 48, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
// CHECK-NEXT: } ],
// CHECK-NEXT: metadata: [ {
// CHECK-NEXT: name: "min_runtime_version",
// CHECK-NEXT: buffer: 6
// CHECK-NEXT: } ]
// CHECK-NEXT: signature_defs: [ ]
// CHECK-NEXT:}
%0 = "tfl.pseudo_const" () {value = dense<1.0> : tensor<4xf32>} : () -> tensor<4xf32> loc("Const")
%1 = "tfl.mul"(%arg0, %0) {fused_activation_function = "NONE"} : (tensor<4xf32>, tensor<4xf32>) -> tensor<4xf32> loc("mul")
// tf.MyCustomOp is the result of conversion to a Custom op
%2 = "tf.MyCustomOp"(%1, %0) {fused_activation_function = "RELU", int_attr = 2 : i32} : (tensor<4xf32>, tensor<4xf32>) -> tensor<4xf32> loc("MyCustomOp")
%3 = "tfl.exp"(%2) : (tensor<4xf32>) -> tensor<4xf32> loc("exp")
func.return %3 : tensor<4xf32>
}
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/custom_tensorlist_reserve.mlir
+37
View File
@@ -0,0 +1,37 @@
// Copyright 2026 The TensorFlow Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// ==============================================================================
// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s | flatbuffer_to_string - | FileCheck %s
func.func @main(%arg0: tensor<i32>, %arg1: tensor<i32>) -> tensor<!tf_type.variant<tensor<*xi32>>> {
%0 = "tfl.custom"(%arg0, %arg1) {custom_code = "TensorListReserve", custom_option = #tfl<const_bytes : "0x02">} : (tensor<i32>, tensor<i32>) -> tensor<!tf_type.variant<tensor<*xi32>>>
func.return %0 : tensor<!tf_type.variant<tensor<*xi32>>>
}
// CHECK: operator_codes: [ {
// CHECK: custom_code: "TensorListReserve",
// CHECK: builtin_code: CUSTOM
// CHECK: shape: [ ],
// CHECK: type: VARIANT,
// CHECK: name: "tfl.custom",
// CHECK: variant_tensors: [ {
// CHECK: shape: [ ],
// CHECK: type: INT32
// CHECK: operators: [ {
// CHECK: inputs: [ 0, 1 ],
// CHECK: outputs: [ 2 ],
// CHECK: custom_options: [ 2 ]
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/debug_metadata.mlir
+58
View File
@@ -0,0 +1,58 @@
// Copyright 2026 The TensorFlow Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// ==============================================================================
// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer --serialize-debug-metadata=true %s -o - | flatbuffer_to_string - | FileCheck %s
#loc = loc("<stdin>":0:0)
#loc5 = loc("main"(#loc))
#loc8 = loc("cond_true"(#loc))
#loc10 = loc("cond_false"(#loc))
module @jit_relu attributes {jax.uses_shape_polymorphism = false, mhlo.num_partitions = 1 : i32, mhlo.num_replicas = 1 : i32, tfl._legalize_tfl_variables = true} {
func.func @main(%arg0: tensor<1xf32>, %arg1: tensor<1xf32>) -> tensor<1xf32> {
%0 = tfl.less(%arg0, %arg1) : (tensor<1xf32>, tensor<1xf32>) -> tensor<1xi1> loc(#loc6)
%1 = "tf.If"(%0, %arg0, %arg1) <{else_branch = @cond_false, is_stateless = false, then_branch = @cond_true}> : (tensor<1xi1>, tensor<1xf32>, tensor<1xf32>) -> tensor<1xf32> loc(#loc7)
func.return %1 : tensor<1xf32> loc(#loc)
} loc(#loc5)
func.func @cond_true(%arg0: tensor<*xf32>, %arg1: tensor<*xf32>) -> tensor<*xf32> {
%0 = tfl.add %arg0, %arg1 {fused_activation_function = "NONE"} : tensor<*xf32> loc(#loc16)
func.return %0 : tensor<*xf32> loc(#loc)
} loc(#loc8)
func.func @cond_false(%arg0: tensor<*xf32>, %arg1: tensor<*xf32>) -> tensor<*xf32> {
%0 = tfl.mul %arg0, %arg1 {fused_activation_function = "NONE"} : tensor<*xf32> loc(#loc15)
func.return %0 : tensor<*xf32> loc(#loc)
} loc(#loc10)
} loc(#loc)
#loc1 = loc("tfl.less")
#loc2 = loc("tf.If")
#loc3 = loc("<ipython-input-7-340b9abeb7a8>":1:4)
#loc4 = loc("third_party/py/IPython/v3_2_3/core/interactiveshell.py":3066:16)
#loc6 = loc(fused<"tflite.importer_wrapper">[#loc1])
#loc7 = loc(fused<"tflite.importer_wrapper">[#loc2])
#loc9 = loc(callsite(#loc3 at #loc4))
#loc11 = loc(fused<"">[#loc3, #loc4])
#loc12 = loc("jit(relu)/jit(main)/max"(#loc9))
#loc13 = loc("tfl.mul"(#loc11))
#loc14 = loc("jit(relu)/jit(main)/max"(#loc12))
#loc15 = loc(fused<"tflite.importer_wrapper">[#loc13])
#loc16 = loc(fused<"tflite.importer_wrapper">[#loc14])
// CHECK: operators: [ {
// CHECK: name: "main",
// CHECK: debug_metadata_index:
// CHECK: name: "cond_true",
// CHECK: debug_metadata_index:
// CHECK: name: "cond_false",
// CHECK: debug_metadata_index:
// CHECK: metadata: [ {
// CHECK: name: "debug_metadata",
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/deduplicate_const.mlir
+205
View File
@@ -0,0 +1,205 @@
// Copyright 2026 The TensorFlow Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// ==============================================================================
// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_to_string - | FileCheck %s --check-prefix=CHECK
// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer -disable-buffer-deduping %s -o - | flatbuffer_to_string - | FileCheck %s --check-prefix=NO_DEDUPE
module {
func.func @add(%arg0: tensor<3x2xf32>) -> tensor<3x2xf32> attributes {tf.entry_function = {inputs = "serving_default_x", outputs = "outputs"}} {
%0 = "tfl.pseudo_const" () {value = dense<[[1.0, 2.0], [3.0, 4.0], [5.0, 6.0]]> : tensor<3x2xf32>} : () -> tensor<3x2xf32>
%1 = "tfl.add" (%0, %arg0) {fused_activation_function = "NONE"} : (tensor<3x2xf32>, tensor<3x2xf32>) -> tensor<3x2xf32>
func.return %1 : tensor<3x2xf32>
}
func.func @sub(%arg0: tensor<3x2xf32>) -> tensor<3x2xf32> attributes {tf.entry_function = {inputs = "serving_default_x", outputs = "outputs"}} {
%0 = "tfl.pseudo_const" () {value = dense<[[1.0, 2.0], [3.0, 4.0], [5.0, 6.0]]> : tensor<3x2xf32>} : () -> tensor<3x2xf32>
%1 = "tfl.sub" (%0, %arg0) {fused_activation_function = "NONE"} : (tensor<3x2xf32>, tensor<3x2xf32>) -> tensor<3x2xf32>
func.return %1 : tensor<3x2xf32>
}
}
// CHECK: {
// CHECK: subgraphs: [ {
// CHECK-NEXT: tensors: [ {
// CHECK-NEXT: shape: [ 3, 2 ],
// CHECK-NEXT: buffer: 1,
// CHECK-NEXT: name: "serving_default_x",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 3, 2 ],
// CHECK-NEXT: buffer: 2,
// CHECK-NEXT: name: "tfl.pseudo_const",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 3, 2 ],
// CHECK-NEXT: buffer: 3,
// CHECK-NEXT: name: "outputs",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: } ],
// CHECK: name: "add"
// CHECK-NEXT: }, {
// CHECK-NEXT: tensors: [ {
// CHECK-NEXT: shape: [ 3, 2 ],
// CHECK-NEXT: buffer: 4,
// CHECK-NEXT: name: "serving_default_x",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 3, 2 ],
// CHECK-NEXT: buffer: 2,
// CHECK-NEXT: name: "tfl.pseudo_const1",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 3, 2 ],
// CHECK-NEXT: buffer: 6,
// CHECK-NEXT: name: "outputs",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: } ],
// CHECK-NEXT: inputs: [ 0 ],
// CHECK-NEXT: outputs: [ 2 ],
// CHECK: name: "sub"
// CHECK-NEXT: } ],
// CHECK-NEXT: description: "MLIR Converted.",
// CHECK-NEXT: buffers: [ {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 0, 0, 128, 63, 0, 0, 0, 64, 0, 0, 64, 64, 0, 0, 128, 64, 0, 0, 160, 64, 0, 0, 192, 64 ]
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 49, 46, 54, 46, 48, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
// CHECK-NEXT: } ],
// CHECK: }
// NO_DEDUPE: {
// NO_DEDUPE: version: 3,
// NO_DEDUPE: operator_codes: [ {
// NO_DEDUPE: version: 1
// NO_DEDUPE: }, {
// NO_DEDUPE: deprecated_builtin_code: 41,
// NO_DEDUPE: version: 1,
// NO_DEDUPE: builtin_code: SUB
// NO_DEDUPE: } ],
// NO_DEDUPE: subgraphs: [ {
// NO_DEDUPE: tensors: [ {
// NO_DEDUPE: shape: [ 3, 2 ],
// NO_DEDUPE: buffer: 1,
// NO_DEDUPE: name: "serving_default_x",
// NO_DEDUPE: quantization: {
// NO_DEDUPE: },
// NO_DEDUPE: has_rank: true
// NO_DEDUPE: }, {
// NO_DEDUPE: shape: [ 3, 2 ],
// NO_DEDUPE: buffer: 2,
// NO_DEDUPE: name: "tfl.pseudo_const",
// NO_DEDUPE: quantization: {
// NO_DEDUPE: },
// NO_DEDUPE: has_rank: true
// NO_DEDUPE: }, {
// NO_DEDUPE: shape: [ 3, 2 ],
// NO_DEDUPE: buffer: 3,
// NO_DEDUPE: name: "outputs",
// NO_DEDUPE: quantization: {
// NO_DEDUPE: },
// NO_DEDUPE: has_rank: true
// NO_DEDUPE: } ],
// NO_DEDUPE: inputs: [ 0 ],
// NO_DEDUPE: outputs: [ 2 ],
// NO_DEDUPE: operators: [ {
// NO_DEDUPE: inputs: [ 1, 0 ],
// NO_DEDUPE: outputs: [ 2 ],
// NO_DEDUPE: builtin_options_type: AddOptions,
// NO_DEDUPE: builtin_options: {
// NO_DEDUPE: }
// NO_DEDUPE: } ],
// NO_DEDUPE: name: "add"
// NO_DEDUPE: }, {
// NO_DEDUPE: tensors: [ {
// NO_DEDUPE: shape: [ 3, 2 ],
// NO_DEDUPE: buffer: 4,
// NO_DEDUPE: name: "serving_default_x",
// NO_DEDUPE: quantization: {
// NO_DEDUPE: },
// NO_DEDUPE: has_rank: true
// NO_DEDUPE: }, {
// NO_DEDUPE: shape: [ 3, 2 ],
// NO_DEDUPE: buffer: 5,
// NO_DEDUPE: name: "tfl.pseudo_const1",
// NO_DEDUPE: quantization: {
// NO_DEDUPE: },
// NO_DEDUPE: has_rank: true
// NO_DEDUPE: }, {
// NO_DEDUPE: shape: [ 3, 2 ],
// NO_DEDUPE: buffer: 6,
// NO_DEDUPE: name: "outputs",
// NO_DEDUPE: quantization: {
// NO_DEDUPE: },
// NO_DEDUPE: has_rank: true
// NO_DEDUPE: } ],
// NO_DEDUPE: inputs: [ 0 ],
// NO_DEDUPE: outputs: [ 2 ],
// NO_DEDUPE: operators: [ {
// NO_DEDUPE: opcode_index: 1,
// NO_DEDUPE: inputs: [ 1, 0 ],
// NO_DEDUPE: outputs: [ 2 ],
// NO_DEDUPE: builtin_options_type: SubOptions,
// NO_DEDUPE: builtin_options: {
// NO_DEDUPE: }
// NO_DEDUPE: } ],
// NO_DEDUPE: name: "sub"
// NO_DEDUPE: } ],
// NO_DEDUPE: description: "MLIR Converted.",
// NO_DEDUPE: buffers: [ {
// NO_DEDUPE: }, {
// NO_DEDUPE: }, {
// NO_DEDUPE: data: [ 0, 0, 128, 63, 0, 0, 0, 64, 0, 0, 64, 64, 0, 0, 128, 64, 0, 0, 160, 64, 0, 0, 192, 64 ]
// NO_DEDUPE: }, {
// NO_DEDUPE: }, {
// NO_DEDUPE: }, {
// NO_DEDUPE: data: [ 0, 0, 128, 63, 0, 0, 0, 64, 0, 0, 64, 64, 0, 0, 128, 64, 0, 0, 160, 64, 0, 0, 192, 64 ]
// NO_DEDUPE: }, {
// NO_DEDUPE: }, {
// NO_DEDUPE: data: [ 49, 46, 54, 46, 48, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
// NO_DEDUPE: } ],
// NO_DEDUPE: metadata: [ {
// NO_DEDUPE: name: "min_runtime_version",
// NO_DEDUPE: buffer: 7
// NO_DEDUPE: } ],
// NO_DEDUPE: signature_defs: [ ]
// NO_DEDUPE: }
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/depthwise_conv2d.mlir
+122
View File
@@ -0,0 +1,122 @@
// Copyright 2026 The TensorFlow Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// ==============================================================================
// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_to_string - | FileCheck %s
func.func @main(tensor<1x224x224x3xf32>) -> tensor<1x112x112x32xf32> {
^bb0(%arg0: tensor<1x224x224x3xf32>):
// CHECK: {
// CHECK-NEXT: version: 3,
// CHECK-NEXT: operator_codes: [ {
// CHECK-NEXT: deprecated_builtin_code: 6,
// CHECK-NEXT: version: 1
// CHECK-NEXT: builtin_code: DEQUANTIZE
// CHECK-NEXT: }, {
// CHECK-NEXT: deprecated_builtin_code: 4,
// CHECK-NEXT: version: 1
// CHECK-NEXT: builtin_code: DEPTHWISE_CONV_2D
// CHECK-NEXT: } ],
// CHECK-NEXT: subgraphs: [ {
// CHECK-NEXT: tensors: [ {
// CHECK-NEXT: shape: [ 1, 224, 224, 3 ],
// CHECK-NEXT: buffer: 1,
// CHECK-NEXT: name: "arg0",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 32 ],
// CHECK-NEXT: buffer: 2,
// CHECK-NEXT: name: "Const",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 32, 3, 3, 3 ],
// CHECK-NEXT: type: UINT8,
// CHECK-NEXT: buffer: 3,
// CHECK-NEXT: name: "tfl.pseudo_qconst",
// CHECK-NEXT: quantization: {
// CHECK-NEXT: scale: [ 0.021827 ],
// CHECK-NEXT: zero_point: [ 151 ]
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 32, 3, 3, 3 ],
// CHECK-NEXT: buffer: 4,
// CHECK-NEXT: name: "tfl.dequantize",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 1, 112, 112, 32 ],
// CHECK-NEXT: buffer: 5,
// CHECK-NEXT: name: "tfl.depthwise_conv_2d",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: } ],
// CHECK-NEXT: inputs: [ 0 ],
// CHECK-NEXT: outputs: [ 4 ],
// CHECK-NEXT: operators: [ {
// CHECK-NEXT: inputs: [ 2 ],
// CHECK-NEXT: outputs: [ 3 ]
// CHECK-NEXT: }, {
// CHECK-NEXT: opcode_index: 1,
// CHECK-NEXT: inputs: [ 0, 3, 1 ],
// CHECK-NEXT: outputs: [ 4 ],
// CHECK-NEXT: builtin_options_type: DepthwiseConv2DOptions,
// CHECK-NEXT: builtin_options: {
// CHECK-NEXT: padding: VALID,
// CHECK-NEXT: stride_w: 5,
// CHECK-NEXT: stride_h: 4,
// CHECK-NEXT: depth_multiplier: 4
// CHECK-NEXT: }
// CHECK-NEXT: } ],
// CHECK-NEXT: name: "main"
// CHECK-NEXT: } ],
// CHECK-NEXT: description: "MLIR Converted.",
// CHECK-NEXT: buffers: [ {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 84, 85, 158, 191, 84, 85, 158, 191, 84, 85, 158, 191, 84, 85, 158, 191, 84, 85, 158, 191, 84, 85, 158, 191, 84, 85, 158, 191, 84, 85, 158, 191, 84, 85, 158, 191, 84, 85, 158, 191, 84, 85, 158, 191, 84, 85, 158, 191, 84, 85, 158, 191, 84, 85, 158, 191, 84, 85, 158, 191, 84, 85, 158, 191, 84, 85, 158, 191, 84, 85, 158, 191, 84, 85, 158, 191, 84, 85, 158, 191, 84, 85, 158, 191, 84, 85, 158, 191, 84, 85, 158, 191, 84, 85, 158, 191, 84, 85, 158, 191, 84, 85, 158, 191, 84, 85, 158, 191, 84, 85, 158, 191, 84, 85, 158, 191, 84, 85, 158, 191, 84, 85, 158, 191, 84, 85, 158, 191 ]
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180 ]
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 49, 46, 49, 51, 46, 49, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
// CHECK-NEXT: } ],
// CHECK-NEXT: metadata: [ {
// CHECK-NEXT: name: "min_runtime_version",
// CHECK-NEXT: buffer: 6
// CHECK-NEXT: } ]
// CHECK-NEXT: signature_defs: [ ]
// CHECK-NEXT:}
%0 = "tfl.pseudo_const" () {value = dense<-1.23697901> : tensor<32xf32>} : () -> tensor<32xf32> loc("Const")
%1 = "tfl.pseudo_qconst"() {qtype = tensor<32x3x3x3x!quant.uniform<u8<1:255>:f32, 0.021826678373682216:151>>, value = dense<-76> : tensor<32x3x3x3xi8>} : () -> tensor<32x3x3x3x!quant.uniform<u8<1:255>:f32, 0.021826678373682216:151>>
%2 = "tfl.dequantize"(%1) : (tensor<32x3x3x3x!quant.uniform<u8<1:255>:f32, 0.021826678373682216:151>>) -> tensor<32x3x3x3xf32>
%3 = "tfl.depthwise_conv_2d"(%arg0, %2, %0) {depth_multiplier = 4 : i32, dilation_h_factor = 1 : i32, dilation_w_factor = 1 : i32, fused_activation_function = "NONE", padding = "VALID", stride_h = 4 : i32, stride_w = 5 : i32} : (tensor<1x224x224x3xf32>, tensor<32x3x3x3xf32>, tensor<32xf32>) -> tensor<1x112x112x32xf32>
func.return %3 : tensor<1x112x112x32xf32>
}
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/depthwise_conv2d_v2.mlir
+124
View File
@@ -0,0 +1,124 @@
// Copyright 2026 The TensorFlow Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// ==============================================================================
// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_to_string - | FileCheck %s
func.func @main(tensor<1x224x224x3xf32>) -> tensor<1x112x112x32xf32> {
^bb0(%arg0: tensor<1x224x224x3xf32>):
// CHECK: {
// CHECK-NEXT: version: 3,
// CHECK-NEXT: operator_codes: [ {
// CHECK-NEXT: deprecated_builtin_code: 6,
// CHECK-NEXT: version: 1,
// CHECK-NEXT: builtin_code: DEQUANTIZE
// CHECK-NEXT: }, {
// CHECK-NEXT: deprecated_builtin_code: 4,
// CHECK-NEXT: version: 2,
// CHECK-NEXT: builtin_code: DEPTHWISE_CONV_2D
// CHECK-NEXT: } ],
// CHECK-NEXT: subgraphs: [ {
// CHECK-NEXT: tensors: [ {
// CHECK-NEXT: shape: [ 1, 224, 224, 3 ],
// CHECK-NEXT: buffer: 1,
// CHECK-NEXT: name: "arg0",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 32 ],
// CHECK-NEXT: buffer: 2,
// CHECK-NEXT: name: "Const",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 32, 3, 3, 3 ],
// CHECK-NEXT: type: UINT8,
// CHECK-NEXT: buffer: 3,
// CHECK-NEXT: name: "tfl.pseudo_qconst",
// CHECK-NEXT: quantization: {
// CHECK-NEXT: scale: [ 0.021827 ],
// CHECK-NEXT: zero_point: [ 151 ]
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 32, 3, 3, 3 ],
// CHECK-NEXT: buffer: 4,
// CHECK-NEXT: name: "tfl.dequantize",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 1, 112, 112, 32 ],
// CHECK-NEXT: buffer: 5,
// CHECK-NEXT: name: "tfl.depthwise_conv_2d",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: } ],
// CHECK-NEXT: inputs: [ 0 ],
// CHECK-NEXT: outputs: [ 4 ],
// CHECK-NEXT: operators: [ {
// CHECK-NEXT: inputs: [ 2 ],
// CHECK-NEXT: outputs: [ 3 ]
// CHECK-NEXT: }, {
// CHECK-NEXT: opcode_index: 1,
// CHECK-NEXT: inputs: [ 0, 3, 1 ],
// CHECK-NEXT: outputs: [ 4 ],
// CHECK-NEXT: builtin_options_type: DepthwiseConv2DOptions,
// CHECK-NEXT: builtin_options: {
// CHECK-NEXT: padding: VALID,
// CHECK-NEXT: stride_w: 5,
// CHECK-NEXT: stride_h: 4,
// CHECK-NEXT: depth_multiplier: 4,
// CHECK-NEXT: dilation_w_factor: 2,
// CHECK-NEXT: dilation_h_factor: 2
// CHECK-NEXT: }
// CHECK-NEXT: } ],
// CHECK-NEXT: name: "main"
// CHECK-NEXT: } ],
// CHECK-NEXT: description: "MLIR Converted.",
// CHECK-NEXT: buffers: [ {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 84, 85, 158, 191, 84, 85, 158, 191, 84, 85, 158, 191, 84, 85, 158, 191, 84, 85, 158, 191, 84, 85, 158, 191, 84, 85, 158, 191, 84, 85, 158, 191, 84, 85, 158, 191, 84, 85, 158, 191, 84, 85, 158, 191, 84, 85, 158, 191, 84, 85, 158, 191, 84, 85, 158, 191, 84, 85, 158, 191, 84, 85, 158, 191, 84, 85, 158, 191, 84, 85, 158, 191, 84, 85, 158, 191, 84, 85, 158, 191, 84, 85, 158, 191, 84, 85, 158, 191, 84, 85, 158, 191, 84, 85, 158, 191, 84, 85, 158, 191, 84, 85, 158, 191, 84, 85, 158, 191, 84, 85, 158, 191, 84, 85, 158, 191, 84, 85, 158, 191, 84, 85, 158, 191, 84, 85, 158, 191 ]
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180 ]
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 49, 46, 49, 51, 46, 49, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
// CHECK-NEXT: } ],
// CHECK-NEXT: metadata: [ {
// CHECK-NEXT: name: "min_runtime_version",
// CHECK-NEXT: buffer: 6
// CHECK-NEXT: } ]
// CHECK-NEXT: signature_defs: [ ]
// CHECK-NEXT:}
%0 = "tfl.pseudo_const" () {value = dense<-1.23697901> : tensor<32xf32>} : () -> tensor<32xf32> loc("Const")
%1 = "tfl.pseudo_qconst"() {qtype = tensor<32x3x3x3x!quant.uniform<u8<1:255>:f32, 0.021826678373682216:151>>, value = dense<-76> : tensor<32x3x3x3xi8>} : () -> tensor<32x3x3x3x!quant.uniform<u8<1:255>:f32, 0.021826678373682216:151>>
%2 = "tfl.dequantize"(%1) : (tensor<32x3x3x3x!quant.uniform<u8<1:255>:f32, 0.021826678373682216:151>>) -> tensor<32x3x3x3xf32>
%3 = "tfl.depthwise_conv_2d"(%arg0, %2, %0) {depth_multiplier = 4 : i32, dilation_h_factor = 2 : i32, dilation_w_factor = 2 : i32, fused_activation_function = "NONE", padding = "VALID", stride_h = 4 : i32, stride_w = 5 : i32} : (tensor<1x224x224x3xf32>, tensor<32x3x3x3xf32>, tensor<32xf32>) -> tensor<1x112x112x32xf32>
func.return %3 : tensor<1x112x112x32xf32>
}
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/disable_builtin.mlir
+24
View File
@@ -0,0 +1,24 @@
// Copyright 2026 The TensorFlow Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// ==============================================================================
// RUN: not flatbuffer_translate -mlir-to-tflite-flatbuffer -emit-builtin-tflite-ops=false %s 2>&1 | FileCheck %s
// CHECK: 'tfl.add' op is a TFLite builtin op but builtin emission is not enabled
func.func @main(tensor<3x2xi32>) -> tensor<3x2xi32> {
^bb0(%arg0: tensor<3x2xi32>):
%0 = "arith.constant"() {name = "Const2", value = dense<10> : tensor<i32>} : () -> tensor<i32>
%1 = "tfl.add"(%0, %arg0) {fused_activation_function = "NONE", name = "add"} : (tensor<i32>, tensor<3x2xi32>) -> tensor<3x2xi32>
func.return %1 : tensor<3x2xi32>
}
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/disable_custom.mlir
+29
View File
@@ -0,0 +1,29 @@
// Copyright 2026 The TensorFlow Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// ==============================================================================
// RUN: not flatbuffer_translate -mlir-to-tflite-flatbuffer %s 2>&1 | FileCheck %s
// CHECK: error: 'tf.MyCustomOp' op is neither a custom op nor a flex op
// CHECK: error: failed while converting: 'main'
// CHECK: Some ops in the model are custom ops, See instructions to implement
// CHECK: tf.MyCustomOp(tensor<4xf32>, tensor<4xf32>) -> (tensor<4xf32>, tensor<3xf32>) : {name = "MyCustomOp"}
func.func @main(tensor<4xf32>) -> tensor<4xf32> {
^bb0(%arg0: tensor<4xf32>):
%0 = "tfl.pseudo_const" () {name = "Const", value = dense<1.0> : tensor<4xf32>} : () -> tensor<4xf32>
%1 = "tfl.mul"(%arg0, %0) {fused_activation_function = "NONE", name = "mul"} : (tensor<4xf32>, tensor<4xf32>) -> tensor<4xf32>
%2:2 = "tf.MyCustomOp"(%1, %0) {name = "MyCustomOp"} : (tensor<4xf32>, tensor<4xf32>) -> (tensor<4xf32>, tensor<3xf32>)
%3 = "tfl.exp"(%2#0) {name = "exp"} : (tensor<4xf32>) -> tensor<4xf32>
func.return %3 : tensor<4xf32>
}
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/disable_flex.mlir
+30
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@@ -0,0 +1,30 @@
// Copyright 2026 The TensorFlow Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// ==============================================================================
// RUN: not flatbuffer_translate -mlir-to-tflite-flatbuffer %s 2>&1 | FileCheck %s
// CHECK: error: 'tf.Div' op is neither a custom op nor a flex op
// CHECK: error: failed while converting: 'main'
// CHECK: Some ops are not supported by the native TFLite runtime
// CHECK: tf.Div(tensor<4xf32>, tensor<4xf32>) -> (tensor<4xf32>) : {name = "div"}
func.func @main(tensor<4xf32>) -> tensor<4xf32> {
^bb0(%arg0: tensor<4xf32>):
%0 = "tfl.pseudo_const" () {name = "Const", value = dense<1.0> : tensor<4xf32>} : () -> tensor<4xf32>
%1 = "tfl.mul"(%arg0, %0) {fused_activation_function = "NONE", name = "mul"} : (tensor<4xf32>, tensor<4xf32>) -> tensor<4xf32>
// tf.div is the result of conversion to a Flex TF op
%2 = "tf.Div"(%1, %0) {name = "div"} : (tensor<4xf32>, tensor<4xf32>) -> tensor<4xf32>
%3 = "tfl.exp"(%2) {name = "exp"} : (tensor<4xf32>) -> tensor<4xf32>
func.return %3 : tensor<4xf32>
}
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/disable_flex_enable_builtin.mlir
+127
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@@ -0,0 +1,127 @@
// Copyright 2026 The TensorFlow Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// ==============================================================================
// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_to_string - | FileCheck %s
func.func @main(tensor<4xf32>) -> tensor<4xf32> {
^bb0(%arg0: tensor<4xf32>):
// CHECK: {
// CHECK-NEXT: version: 3,
// CHECK-NEXT: operator_codes: [ {
// CHECK-NEXT: deprecated_builtin_code: 18,
// CHECK-NEXT: version: 1,
// CHECK-NEXT: builtin_code: MUL
// CHECK-NEXT: }, {
// CHECK-NEXT: deprecated_builtin_code: 47,
// CHECK-NEXT: version: 1,
// CHECK-NEXT: builtin_code: EXP
// CHECK-NEXT: } ],
// CHECK-NEXT: subgraphs: [ {
// CHECK-NEXT: tensors: [ {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 1,
// CHECK-NEXT: name: "arg0",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 2,
// CHECK-NEXT: name: "Const",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 3,
// CHECK-NEXT: name: "mul0",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 4,
// CHECK-NEXT: name: "mul1",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 5,
// CHECK-NEXT: name: "exp",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: } ],
// CHECK-NEXT: inputs: [ 0 ],
// CHECK-NEXT: outputs: [ 4 ],
// CHECK-NEXT: operators: [ {
// CHECK-NEXT: inputs: [ 0, 1 ],
// CHECK-NEXT: outputs: [ 2 ],
// CHECK-NEXT: builtin_options_type: MulOptions,
// CHECK-NEXT: builtin_options: {
// CHECK-EMPTY:
// CHECK-NEXT: }
// CHECK-NEXT: }, {
// CHECK-NEXT: inputs: [ 2, 1 ],
// CHECK-NEXT: outputs: [ 3 ],
// CHECK-NEXT: builtin_options_type: MulOptions,
// CHECK-NEXT: builtin_options: {
// CHECK-EMPTY:
// CHECK-NEXT: }
// CHECK-NEXT: }, {
// CHECK-NEXT: opcode_index: 1,
// CHECK-NEXT: inputs: [ 3 ],
// CHECK-NEXT: outputs: [ 4 ],
// CHECK-NEXT: builtin_options_type: ExpOptions,
// CHECK-NEXT: builtin_options: {
// CHECK-EMPTY:
// CHECK-NEXT: }
// CHECK-NEXT: } ]
// CHECK-NEXT: name: "main"
// CHECK-NEXT: } ],
// CHECK-NEXT: description: "MLIR Converted.",
// CHECK-NEXT: buffers: [ {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 0, 0, 128, 63, 0, 0, 128, 63, 0, 0, 128, 63, 0, 0, 128, 63 ]
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 49, 46, 55, 46, 48, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
// CHECK-NEXT: } ],
// CHECK-NEXT: metadata: [ {
// CHECK-NEXT: name: "min_runtime_version",
// CHECK-NEXT: buffer: 6
// CHECK-NEXT: } ]
// CHECK-NEXT: signature_defs: [ ]
// CHECK-NEXT:}
%0 = "tfl.pseudo_const" () {value = dense<1.0> : tensor<4xf32>} : () -> tensor<4xf32> loc("Const")
%1 = "tfl.mul"(%arg0, %0) {fused_activation_function = "NONE"} : (tensor<4xf32>, tensor<4xf32>) -> tensor<4xf32> loc("mul0")
%2 = "tfl.mul"(%1, %0) {fused_activation_function = "NONE"} : (tensor<4xf32>, tensor<4xf32>) -> tensor<4xf32> loc("mul1")
%3 = "tfl.exp"(%2) : (tensor<4xf32>) -> tensor<4xf32> loc("exp")
func.return %3 : tensor<4xf32>
}
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/dynamic_shape_constant.mlir
+38
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@@ -0,0 +1,38 @@
// Copyright 2026 The TensorFlow Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// ==============================================================================
// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_to_string -
func.func @main(%arg0: tensor<2xi32>) -> tensor<2xi32> {
%cst = "tfl.pseudo_const"() {value = dense<[1, 2]> : tensor<2xi32>} : () -> tensor<?xi32>
%0 = "tfl.add"(%arg0, %cst) {fused_activation_function = "NONE"} : (tensor<2xi32>, tensor<?xi32>) -> tensor<2xi32>
func.return %0 : tensor<2xi32>
}
// CHECK: tensors: [ {
// CHECK-NEXT: shape: [ 2 ],
// CHECK-NEXT: type: INT32,
// CHECK-NEXT: buffer: 1,
// CHECK-NEXT: name: "tfl.pseudo_const",
// CHECK-NEXT: quantization: {
// CHECK-NEXT:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK: buffers: [ {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 1, 0, 0, 0, 2, 0, 0, 0 ]
// CHECK-NEXT: }, {
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/external_buffer.mlir
+48
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@@ -0,0 +1,48 @@
// Copyright 2026 The TensorFlow Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// ==============================================================================
// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_to_string - | FileCheck %s
module {
func.func public @main(%arg0: tensor<2x2xf32>) -> tensor<2x2xf32> {
%0 = "tfl.external_const"() <{external_buffer = #tfl.external_buffer<group_name = "test.bin", offset = 0, length = 13, packing = "unpacked">}> : () -> tensor<2x2xf32>
%1 = tfl.add %arg0, %0 {fused_activation_function = "NONE"} : tensor<2x2xf32>
return %1 : tensor<2x2xf32>
}
}
// CHECK: tensors: [ {
// CHECK: shape: [ 2, 2 ],
// CHECK: buffer: 1,
// CHECK: name: "arg0",
// CHECK: has_rank: true
// CHECK: }, {
// CHECK: shape: [ 2, 2 ],
// CHECK: name: "tfl.external_const",
// CHECK: has_rank: true,
// CHECK: external_buffer: 2147483648
// CHECK: }, {
// CHECK: shape: [ 2, 2 ],
// CHECK: buffer: 2,
// CHECK: name: "tfl.add",
// CHECK: has_rank: true
// CHECK: } ],
// CHECK: external_buffer_groups: [ {
// CHECK: name: "test.bin"
// CHECK: } ],
// CHECK: external_buffers: [ {
// CHECK: id: 2147483648,
// CHECK: length: 13,
// CHECK: packing: "unpacked"
// CHECK: } ]
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/fake_quant.mlir
+80
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@@ -0,0 +1,80 @@
// Copyright 2026 The TensorFlow Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// ==============================================================================
// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_to_string - | FileCheck %s
// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_translate -tflite-flatbuffer-to-mlir - -o - | FileCheck --check-prefix=IMPORT %s
func.func @main(tensor<4xf32>) -> tensor<4xf32> {
^bb0(%arg0: tensor<4xf32>):
// CHECK: {
// CHECK-NEXT: version: 3,
// CHECK-NEXT: operator_codes: [ {
// CHECK-NEXT: deprecated_builtin_code: 80,
// CHECK-NEXT: version: 1,
// CHECK-NEXT: builtin_code: FAKE_QUANT
// CHECK-NEXT: } ],
// CHECK-NEXT: subgraphs: [ {
// CHECK-NEXT: tensors: [ {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 1,
// CHECK-NEXT: name: "arg0",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 2,
// CHECK-NEXT: name: "tfl.fake_quant",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: } ],
// CHECK-NEXT: inputs: [ 0 ],
// CHECK-NEXT: outputs: [ 1 ],
// CHECK-NEXT: operators: [ {
// CHECK-NEXT: inputs: [ 0 ],
// CHECK-NEXT: outputs: [ 1 ],
// CHECK-NEXT: builtin_options_type: FakeQuantOptions,
// CHECK-NEXT: builtin_options: {
// CHECK-NEXT: min: 0.3,
// CHECK-NEXT: max: 1.4,
// CHECK-NEXT: num_bits: 6
// CHECK-NEXT: }
// CHECK-NEXT: } ],
// CHECK-NEXT: name: "main"
// CHECK-NEXT: } ],
// CHECK-NEXT: description: "MLIR Converted.",
// CHECK-NEXT: buffers: [ {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 49, 46, 53, 46, 48, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
// CHECK-NEXT: } ],
// CHECK-NEXT: metadata: [ {
// CHECK-NEXT: name: "min_runtime_version",
// CHECK-NEXT: buffer: 3
// CHECK-NEXT: } ]
// CHECK-NEXT: signature_defs: [ ]
// CHECK-NEXT: }
// IMPORT: "tfl.fake_quant"(%arg0) <{max = 1.400000e+00 : f32, min = 3.000000e-01 : f32, narrow_range = false, num_bits = 6 : i32}>
%0 = "tfl.fake_quant"(%arg0) {num_bits = 6 : i32, narrow_range = false, min = 0.3:f32, max = 1.4:f32} : (tensor<4 x f32>) -> tensor<4 x f32>
func.return %0 : tensor<4xf32>
}
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/flex_exclusively.mlir
+71
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@@ -0,0 +1,71 @@
// Copyright 2026 The TensorFlow Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// ==============================================================================
// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -emit-select-tf-ops=true -emit-builtin-tflite-ops=false -o - | flatbuffer_to_string - | FileCheck %s
func.func @main(%arg0: tensor<3x2xf32>) -> tensor<3x2xf32> {
// CHECK: {
// CHECK-NEXT: version: 3,
// CHECK-NEXT: operator_codes: [ {
// CHECK-NEXT: deprecated_builtin_code: 32,
// CHECK-NEXT: custom_code: "FlexAddV2"
// CHECK-NEXT: builtin_code: CUSTOM
// CHECK-NEXT: } ],
// CHECK-NEXT: subgraphs: [ {
// CHECK-NEXT: tensors: [ {
// CHECK-NEXT: shape: [ 3, 2 ],
// CHECK-NEXT: buffer: 1,
// CHECK-NEXT: name: "arg0",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 3, 2 ],
// CHECK-NEXT: buffer: 2,
// CHECK-NEXT: name: "tf.AddV2",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: } ],
// CHECK-NEXT: inputs: [ 0 ],
// CHECK-NEXT: outputs: [ 1 ],
// CHECK-NEXT: operators: [ {
// CHECK-NEXT: inputs: [ 0, 0 ],
// CHECK-NEXT: outputs: [ 1 ],
// CHECK-NEXT: custom_options: [ 5, 65, 100, 100, 86, 50, 0, 22, 18, 5, 65, 100, 100, 86, 50, 26, 0, 26, 0, 42, 7, 10, 1, 84, 18, 2, 48, 1, 50, 0, 0, 2, 31, 25, 20, 20, 4, 40, 1 ]
// CHECK-NEXT: } ],
// CHECK-NEXT: name: "main"
// CHECK-NEXT: } ],
// CHECK-NEXT: description: "MLIR Converted.",
// CHECK-NEXT: buffers: [ {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
// CHECK-NEXT: } ],
// CHECK-NEXT: metadata: [ {
// CHECK-NEXT: name: "min_runtime_version",
// CHECK-NEXT: buffer: 3
// CHECK-NEXT: } ]
// CHECK-NEXT: signature_defs: [ ]
// CHECK-NEXT: }
%0 = "tf.AddV2"(%arg0, %arg0) : (tensor<3x2xf32>, tensor<3x2xf32>) -> tensor<3x2xf32>
func.return %0 : tensor<3x2xf32>
}
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/flex_op_with_complex128.mlir
+85
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@@ -0,0 +1,85 @@
// Copyright 2026 The TensorFlow Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// ==============================================================================
// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -emit-select-tf-ops -o - | flatbuffer_to_string - | FileCheck %s
func.func @main(tensor<4xcomplex<f64>>, tensor<4xcomplex<f64>>) -> tensor<4xcomplex<f64>> {
^bb0(%arg0: tensor<4xcomplex<f64>>, %arg1: tensor<4xcomplex<f64>>):
// CHECK: {
// CHECK-NEXT: version: 3,
// CHECK-NEXT: operator_codes: [ {
// CHECK-NEXT: deprecated_builtin_code: 32,
// CHECK-NEXT: custom_code: "FlexAdd",
// CHECK-NEXT: builtin_code: CUSTOM
// CHECK-NEXT: } ],
// CHECK-NEXT: subgraphs: [ {
// CHECK-NEXT: tensors: [ {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: type: COMPLEX128,
// CHECK-NEXT: buffer: 1,
// CHECK-NEXT: name: "arg0",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: type: COMPLEX128,
// CHECK-NEXT: buffer: 2,
// CHECK-NEXT: name: "arg1",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: type: COMPLEX128,
// CHECK-NEXT: buffer: 3,
// CHECK-NEXT: name: "add",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: } ],
// CHECK-NEXT: inputs: [ 0, 1 ],
// CHECK-NEXT: outputs: [ 2 ],
// CHECK-NEXT: operators: [ {
// CHECK-NEXT: inputs: [ 0, 1 ],
// CHECK-NEXT: outputs: [ 2 ],
// CHECK-NEXT: custom_options: [ 3, 65, 100, 100, 0, 20, 18, 3, 65, 100, 100, 26, 0, 26, 0, 42, 7, 10, 1, 84, 18, 2, 48, 18, 50, 0, 0, 2, 27, 23, 20, 20, 4, 40, 1 ]
// CHECK-NEXT: } ],
// CHECK-NEXT: name: "main"
// CHECK-NEXT: } ],
// CHECK-NEXT: description: "MLIR Converted.",
// CHECK-NEXT: buffers: [ {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
// CHECK-NEXT: } ],
// CHECK-NEXT: metadata: [ {
// CHECK-NEXT: name: "min_runtime_version",
// CHECK-NEXT: buffer: 4
// CHECK-NEXT: } ]
// CHECK-NEXT: signature_defs: [ ]
// CHECK-NEXT:}
%0 = "tf.Add"(%arg0, %arg1) : (tensor<4xcomplex<f64>>, tensor<4xcomplex<f64>>) -> tensor<4xcomplex<f64>> loc("add")
func.return %0 : tensor<4xcomplex<f64>>
}
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/flex_op_with_f64.mlir
+85
View File
@@ -0,0 +1,85 @@
// Copyright 2026 The TensorFlow Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// ==============================================================================
// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -emit-select-tf-ops -o - | flatbuffer_to_string - | FileCheck %s
func.func @main(tensor<4xf64>, tensor<4xf64>) -> tensor<4xf64> {
^bb0(%arg0: tensor<4xf64>, %arg1: tensor<4xf64>):
// CHECK: {
// CHECK-NEXT: version: 3,
// CHECK-NEXT: operator_codes: [ {
// CHECK-NEXT: deprecated_builtin_code: 32,
// CHECK-NEXT: custom_code: "FlexAdd",
// CHECK-NEXT: builtin_code: CUSTOM
// CHECK-NEXT: } ],
// CHECK-NEXT: subgraphs: [ {
// CHECK-NEXT: tensors: [ {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: type: FLOAT64,
// CHECK-NEXT: buffer: 1,
// CHECK-NEXT: name: "arg0",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: type: FLOAT64,
// CHECK-NEXT: buffer: 2,
// CHECK-NEXT: name: "arg1",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: type: FLOAT64,
// CHECK-NEXT: buffer: 3,
// CHECK-NEXT: name: "add",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: } ],
// CHECK-NEXT: inputs: [ 0, 1 ],
// CHECK-NEXT: outputs: [ 2 ],
// CHECK-NEXT: operators: [ {
// CHECK-NEXT: inputs: [ 0, 1 ],
// CHECK-NEXT: outputs: [ 2 ],
// CHECK-NEXT: custom_options: [ 3, 65, 100, 100, 0, 20, 18, 3, 65, 100, 100, 26, 0, 26, 0, 42, 7, 10, 1, 84, 18, 2, 48, 2, 50, 0, 0, 2, 27, 23, 20, 20, 4, 40, 1 ]
// CHECK-NEXT: } ],
// CHECK-NEXT: name: "main"
// CHECK-NEXT: } ],
// CHECK-NEXT: description: "MLIR Converted.",
// CHECK-NEXT: buffers: [ {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
// CHECK-NEXT: } ],
// CHECK-NEXT: metadata: [ {
// CHECK-NEXT: name: "min_runtime_version",
// CHECK-NEXT: buffer: 4
// CHECK-NEXT: } ]
// CHECK-NEXT: signature_defs: [ ]
// CHECK-NEXT:}
%0 = "tf.Add"(%arg0, %arg1) : (tensor<4xf64>, tensor<4xf64>) -> tensor<4xf64> loc("add")
func.return %0 : tensor<4xf64>
}
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/flex_op_with_tflite_op.mlir
+130
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@@ -0,0 +1,130 @@
// Copyright 2026 The TensorFlow Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// ==============================================================================
// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -emit-select-tf-ops -o - | flatbuffer_to_string - | FileCheck %s
func.func @main(tensor<4xf32>) -> tensor<4xf32> {
^bb0(%arg0: tensor<4xf32>):
// CHECK: {
// CHECK-NEXT: version: 3,
// CHECK-NEXT: operator_codes: [ {
// CHECK-NEXT: deprecated_builtin_code: 18,
// CHECK-NEXT: version: 1,
// CHECK-NEXT: builtin_code: MUL
// CHECK-NEXT: }, {
// CHECK-NEXT: deprecated_builtin_code: 32,
// CHECK-NEXT: custom_code: "FlexDiv",
// CHECK-NEXT: builtin_code: CUSTOM
// CHECK-NEXT: }, {
// CHECK-NEXT: deprecated_builtin_code: 47,
// CHECK-NEXT: version: 1,
// CHECK-NEXT: builtin_code: EXP
// CHECK-NEXT: } ],
// CHECK-NEXT: subgraphs: [ {
// CHECK-NEXT: tensors: [ {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 1,
// CHECK-NEXT: name: "arg0",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 2,
// CHECK-NEXT: name: "Const",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 3,
// CHECK-NEXT: name: "mul",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 4,
// CHECK-NEXT: name: "div",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 5,
// CHECK-NEXT: name: "exp",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: } ],
// CHECK-NEXT: inputs: [ 0 ],
// CHECK-NEXT: outputs: [ 4 ],
// CHECK-NEXT: operators: [ {
// CHECK-NEXT: inputs: [ 0, 1 ],
// CHECK-NEXT: outputs: [ 2 ],
// CHECK-NEXT: builtin_options_type: MulOptions,
// CHECK-NEXT: builtin_options: {
// CHECK-EMPTY:
// CHECK-NEXT: }
// CHECK-NEXT: }, {
// CHECK-NEXT: opcode_index: 1,
// CHECK-NEXT: inputs: [ 2, 1 ],
// CHECK-NEXT: outputs: [ 3 ],
// CHECK-NEXT: custom_options: [ 3, 68, 105, 118, 0, 20, 18, 3, 68, 105, 118, 26, 0, 26, 0, 42, 7, 10, 1, 84, 18, 2, 48, 1, 50, 0, 0, 2, 27, 23, 20, 20, 4, 40, 1 ]
// CHECK-NEXT: }, {
// CHECK-NEXT: opcode_index: 2,
// CHECK-NEXT: inputs: [ 3 ],
// CHECK-NEXT: outputs: [ 4 ],
// CHECK-NEXT: builtin_options_type: ExpOptions,
// CHECK-NEXT: builtin_options: {
// CHECK-EMPTY:
// CHECK-NEXT: }
// CHECK-NEXT: } ]
// CHECK-NEXT: name: "main"
// CHECK-NEXT: } ],
// CHECK-NEXT: description: "MLIR Converted.",
// CHECK-NEXT: buffers: [ {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 0, 0, 128, 63, 0, 0, 128, 63, 0, 0, 128, 63, 0, 0, 128, 63 ]
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 49, 46, 55, 46, 48, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
// CHECK-NEXT: } ],
// CHECK-NEXT: metadata: [ {
// CHECK-NEXT: name: "min_runtime_version",
// CHECK-NEXT: buffer: 6
// CHECK-NEXT: } ]
// CHECK-NEXT: signature_defs: [ ]
// CHECK-NEXT:}
%0 = "tfl.pseudo_const" () {value = dense<1.0> : tensor<4xf32>} : () -> tensor<4xf32> loc("Const")
%1 = "tfl.mul"(%arg0, %0) {fused_activation_function = "NONE"} : (tensor<4xf32>, tensor<4xf32>) -> tensor<4xf32> loc("mul")
// tf.div is the result of conversion to a Flex TF op
%2 = "tf.Div"(%1, %0) : (tensor<4xf32>, tensor<4xf32>) -> tensor<4xf32> loc("div")
%3 = "tfl.exp"(%2) : (tensor<4xf32>) -> tensor<4xf32> loc("exp")
func.return %3 : tensor<4xf32>
}
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/fully_connected.mlir
+96
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@@ -0,0 +1,96 @@
// Copyright 2026 The TensorFlow Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// ==============================================================================
// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_to_string - | FileCheck %s
func.func @main(tensor<40x37xf32>, tensor<40x37xf32>) -> tensor<40x40xf32> {
^bb0(%arg0: tensor<40x37xf32>, %arg1: tensor<40x37xf32>):
// CHECK: {
// CHECK-NEXT: version: 3,
// CHECK-NEXT: operator_codes: [ {
// CHECK-NEXT: deprecated_builtin_code: 9,
// CHECK-NEXT: version: 1,
// CHECK-NEXT: builtin_code: FULLY_CONNECTED
// CHECK-NEXT: } ],
// CHECK-NEXT: subgraphs: [ {
// CHECK-NEXT: tensors: [ {
// CHECK-NEXT: shape: [ 40, 37 ],
// CHECK-NEXT: buffer: 1,
// CHECK-NEXT: name: "arg0",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 40, 37 ],
// CHECK-NEXT: buffer: 2,
// CHECK-NEXT: name: "arg1",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 40, 40 ],
// CHECK-NEXT: buffer: 3,
// CHECK-NEXT: name: "tfl.fully_connected",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 40, 40 ],
// CHECK-NEXT: buffer: 4,
// CHECK-NEXT: name: "tfl.fully_connected:1",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: } ],
// CHECK-NEXT: inputs: [ 0, 1 ],
// CHECK-NEXT: outputs: [ 2 ],
// CHECK-NEXT: operators: [ {
// CHECK-NEXT: inputs: [ 0, 1, -1 ],
// CHECK-NEXT: outputs: [ 2, 3 ],
// CHECK-NEXT: builtin_options_type: FullyConnectedOptions,
// CHECK-NEXT: builtin_options: {
// CHECK-EMPTY:
// CHECK-NEXT: }
// CHECK-NEXT: } ],
// CHECK-NEXT: name: "main"
// CHECK-NEXT: } ],
// CHECK-NEXT: description: "MLIR Converted.",
// CHECK-NEXT: buffers: [ {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 49, 46, 53, 46, 48, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
// CHECK-NEXT: } ],
// CHECK-NEXT: metadata: [ {
// CHECK-NEXT: name: "min_runtime_version",
// CHECK-NEXT: buffer: 5
// CHECK-NEXT: } ]
// CHECK-NEXT: signature_defs: [ ]
// CHECK-NEXT:}
%cst = "tfl.no_value"() {value = unit} : () -> none
%0:2 = "tfl.fully_connected"(%arg0, %arg1, %cst) {fused_activation_function = "NONE", keep_num_dims = false, weights_format = "DEFAULT"} : (tensor<40x37xf32>, tensor<40x37xf32>, none) -> (tensor<40x40xf32>, tensor<40x40xf32>)
func.return %0 : tensor<40x40xf32>
}
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/fully_connected_v2.mlir
+96
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@@ -0,0 +1,96 @@
// Copyright 2026 The TensorFlow Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// ==============================================================================
// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_to_string - | FileCheck %s
func.func @main(tensor<40x37xf32>, tensor<40x37xf32>) -> tensor<40x40xf32> {
^bb0(%arg0: tensor<40x37xf32>, %arg1: tensor<40x37xf32>):
// CHECK: {
// CHECK-NEXT: version: 3,
// CHECK-NEXT: operator_codes: [ {
// CHECK-NEXT: deprecated_builtin_code: 9,
// CHECK-NEXT: version: 2,
// CHECK-NEXT: builtin_code: FULLY_CONNECTED
// CHECK-NEXT: } ],
// CHECK-NEXT: subgraphs: [ {
// CHECK-NEXT: tensors: [ {
// CHECK-NEXT: shape: [ 40, 37 ],
// CHECK-NEXT: buffer: 1,
// CHECK-NEXT: name: "arg0",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 40, 37 ],
// CHECK-NEXT: buffer: 2,
// CHECK-NEXT: name: "arg1",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 40, 40 ],
// CHECK-NEXT: buffer: 3,
// CHECK-NEXT: name: "tfl.fully_connected",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 40, 40 ],
// CHECK-NEXT: buffer: 4,
// CHECK-NEXT: name: "tfl.fully_connected:1",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: } ],
// CHECK-NEXT: inputs: [ 0, 1 ],
// CHECK-NEXT: outputs: [ 2 ],
// CHECK-NEXT: operators: [ {
// CHECK-NEXT: inputs: [ 0, 1, -1 ],
// CHECK-NEXT: outputs: [ 2, 3 ],
// CHECK-NEXT: builtin_options_type: FullyConnectedOptions,
// CHECK-NEXT: builtin_options: {
// CHECK-NEXT: weights_format: SHUFFLED4x16INT8
// CHECK-NEXT: }
// CHECK-NEXT: } ],
// CHECK-NEXT: name: "main"
// CHECK-NEXT: } ],
// CHECK-NEXT: description: "MLIR Converted.",
// CHECK-NEXT: buffers: [ {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 49, 46, 49, 48, 46, 48, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
// CHECK-NEXT: } ],
// CHECK-NEXT: metadata: [ {
// CHECK-NEXT: name: "min_runtime_version",
// CHECK-NEXT: buffer: 5
// CHECK-NEXT: } ]
// CHECK-NEXT: signature_defs: [ ]
// CHECK-NEXT:}
%cst = "tfl.no_value"() {value = unit} : () -> none
%0:2 = "tfl.fully_connected"(%arg0, %arg1, %cst) {fused_activation_function = "NONE", keep_num_dims = false, weights_format = "SHUFFLED4x16INT8"} : (tensor<40x37xf32>, tensor<40x37xf32>, none) -> (tensor<40x40xf32>, tensor<40x40xf32>)
func.return %0 : tensor<40x40xf32>
}
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/hashtable_resource.mlir
+54
View File
@@ -0,0 +1,54 @@
// Copyright 2026 The TensorFlow Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// ==============================================================================
// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -emit-custom-ops -emit-builtin-tflite-ops=false -o - | flatbuffer_to_string - | FileCheck %s
// CHECK: {
// CHECK: version: 3,
// CHECK: operator_codes: [ {
// CHECK: deprecated_builtin_code: 32,
// CHECK: custom_code: "HashTableV2",
// CHECK: builtin_code: CUSTOM
// CHECK: } ],
// CHECK: subgraphs: [ {
// CHECK: tensors: [ {
// CHECK: shape: [ ],
// CHECK: type: RESOURCE,
// CHECK: buffer: 1,
// CHECK: name: "tf.HashTableV2",
// CHECK: quantization: {
// CHECK-EMPTY
// CHECK: }
// CHECK: } ],
// CHECK: inputs: [ ],
// CHECK: outputs: [ 0 ],
// CHECK: operators: [ {
// CHECK: inputs: [ ],
// CHECK: outputs: [ 0 ],
// CHECK: custom_options:
// CHECK: name: "main"
// CHECK: } ],
// CHECK: description: "MLIR Converted.",
// CHECK: buffers: [ {
// CHECK-EMPTY
// CHECK: }, {
// CHECK-EMPTY
// CHECK: } ]
// CHECK: }
func.func @main() -> tensor<*x!tf_type.resource> {
%0 = "tf.HashTableV2"() {container = "" , shared_name= "table", use_node_name_sharing = false, key_dtype = i32, value_dtype = i32 } : () -> tensor<*x!tf_type.resource>
func.return %0 : tensor<*x!tf_type.resource>
}
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/if_op.mlir
+204
View File
@@ -0,0 +1,204 @@
// Copyright 2026 The TensorFlow Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// ==============================================================================
// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_to_string - | FileCheck %s
// CHECK: {
// CHECK-NEXT: version: 3,
// CHECK-NEXT: operator_codes: [ {
// CHECK-NEXT: deprecated_builtin_code: 58,
// CHECK-NEXT: version: 1,
// CHECK-NEXT: builtin_code: LESS
// CHECK-NEXT: }, {
// CHECK-NEXT: deprecated_builtin_code: 118,
// CHECK-NEXT: version: 1,
// CHECK-NEXT: builtin_code: IF
// CHECK-NEXT: }, {
// CHECK-NEXT: version: 1
// CHECK-NEXT: }, {
// CHECK-NEXT: deprecated_builtin_code: 18,
// CHECK-NEXT: version: 1,
// CHECK-NEXT: builtin_code: MUL
// CHECK-NEXT: } ],
// CHECK-NEXT: subgraphs: [ {
// CHECK-NEXT: tensors: [ {
// CHECK-NEXT: shape: [ 1 ],
// CHECK-NEXT: buffer: 1,
// CHECK-NEXT: name: "arg0",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 1 ],
// CHECK-NEXT: buffer: 2,
// CHECK-NEXT: name: "arg1",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 1 ],
// CHECK-NEXT: type: BOOL,
// CHECK-NEXT: buffer: 3,
// CHECK-NEXT: name: "tfl.less",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 1 ],
// CHECK-NEXT: buffer: 4,
// CHECK-NEXT: name: "tf.If",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: } ],
// CHECK-NEXT: inputs: [ 0, 1 ],
// CHECK-NEXT: outputs: [ 3 ],
// CHECK-NEXT: operators: [ {
// CHECK-NEXT: inputs: [ 0, 1 ],
// CHECK-NEXT: outputs: [ 2 ]
// CHECK-NEXT: }, {
// CHECK-NEXT: opcode_index: 1,
// CHECK-NEXT: inputs: [ 2, 0, 1 ],
// CHECK-NEXT: outputs: [ 3 ],
// CHECK-NEXT: builtin_options_type: IfOptions,
// CHECK-NEXT: builtin_options: {
// CHECK-NEXT: then_subgraph_index: 1,
// CHECK-NEXT: else_subgraph_index: 2
// CHECK-NEXT: }
// CHECK-NEXT: } ],
// CHECK-NEXT: name: "main"
// CHECK-NEXT: }, {
// CHECK-NEXT: tensors: [ {
// CHECK-NEXT: shape: [ ],
// CHECK-NEXT: buffer: 5,
// CHECK-NEXT: name: "cond_true_arg0",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: }
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ ],
// CHECK-NEXT: buffer: 6,
// CHECK-NEXT: name: "cond_true_arg1",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: }
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ ],
// CHECK-NEXT: buffer: 7,
// CHECK-NEXT: name: "tfl.add",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: }
// CHECK-NEXT: } ],
// CHECK-NEXT: inputs: [ 0, 1 ],
// CHECK-NEXT: outputs: [ 2 ],
// CHECK-NEXT: operators: [ {
// CHECK-NEXT: opcode_index: 2,
// CHECK-NEXT: inputs: [ 0, 1 ],
// CHECK-NEXT: outputs: [ 2 ],
// CHECK-NEXT: builtin_options_type: AddOptions,
// CHECK-NEXT: builtin_options: {
// CHECK-EMPTY:
// CHECK-NEXT: }
// CHECK-NEXT: } ],
// CHECK-NEXT: name: "cond_true"
// CHECK-NEXT: }, {
// CHECK-NEXT: tensors: [ {
// CHECK-NEXT: shape: [ ],
// CHECK-NEXT: buffer: 8,
// CHECK-NEXT: name: "cond_false_arg0",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: }
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ ],
// CHECK-NEXT: buffer: 9,
// CHECK-NEXT: name: "cond_false_arg1",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: }
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ ],
// CHECK-NEXT: buffer: 10,
// CHECK-NEXT: name: "tfl.mul",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: }
// CHECK-NEXT: } ],
// CHECK-NEXT: inputs: [ 0, 1 ],
// CHECK-NEXT: outputs: [ 2 ],
// CHECK-NEXT: operators: [ {
// CHECK-NEXT: opcode_index: 3,
// CHECK-NEXT: inputs: [ 0, 1 ],
// CHECK-NEXT: outputs: [ 2 ],
// CHECK-NEXT: builtin_options_type: MulOptions,
// CHECK-NEXT: builtin_options: {
// CHECK-EMPTY:
// CHECK-NEXT: }
// CHECK-NEXT: } ],
// CHECK-NEXT: name: "cond_false"
// CHECK-NEXT: } ],
// CHECK-NEXT: description: "MLIR Converted.",
// CHECK-NEXT: buffers: [ {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 49, 46, 49, 53, 46, 48, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
// CHECK-NEXT: } ],
// CHECK-NEXT: metadata: [ {
// CHECK-NEXT: name: "min_runtime_version",
// CHECK-NEXT: buffer: 11
// CHECK-NEXT: } ]
// CHECK-NEXT: signature_defs: [ ]
// CHECK-NEXT: }
func.func @main(%arg0: tensor<1xf32>, %arg1: tensor<1xf32>) -> tensor<1xf32> {
%0 = "tfl.less"(%arg0, %arg1) : (tensor<1xf32>, tensor<1xf32>) -> tensor<1xi1>
%1 = "tf.If"(%0, %arg0, %arg1) {else_branch = @cond_false, then_branch = @cond_true, is_stateless = false} : (tensor<1xi1>, tensor<1xf32>, tensor<1xf32>) -> tensor<1xf32>
func.return %1 : tensor<1xf32>
}
func.func @cond_true(%arg0: tensor<*xf32>, %arg1: tensor<*xf32>) -> tensor<*xf32> {
%0 = tfl.add %arg0, %arg1 {fused_activation_function = "NONE"} : tensor<*xf32>
func.return %0 : tensor<*xf32>
}
func.func @cond_false(%arg0: tensor<*xf32>, %arg1: tensor<*xf32>) -> tensor<*xf32> {
%0 = tfl.mul %arg0, %arg1 {fused_activation_function = "NONE"} : tensor<*xf32>
func.return %0 : tensor<*xf32>
}
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/logical.mlir
+118
View File
@@ -0,0 +1,118 @@
// Copyright 2026 The TensorFlow Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// ==============================================================================
// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_to_string - | FileCheck %s
func.func @main(tensor<4xi1>) -> tensor<4xi1> {
^bb0(%arg0: tensor<4xi1>):
// CHECK: {
// CHECK-NEXT: version: 3,
// CHECK-NEXT: operator_codes: [ {
// CHECK-NEXT: deprecated_builtin_code: 84,
// CHECK-NEXT: version: 1,
// CHECK-NEXT: builtin_code: LOGICAL_OR
// CHECK-NEXT: }, {
// CHECK-NEXT: deprecated_builtin_code: 86,
// CHECK-NEXT: version: 1,
// CHECK-NEXT: builtin_code: LOGICAL_AND
// CHECK-NEXT: } ],
// CHECK-NEXT: subgraphs: [ {
// CHECK-NEXT: tensors: [ {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: type: BOOL,
// CHECK-NEXT: buffer: 1,
// CHECK-NEXT: name: "arg0",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: type: BOOL,
// CHECK-NEXT: buffer: 2,
// CHECK-NEXT: name: "Const1",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: type: BOOL,
// CHECK-NEXT: buffer: 3,
// CHECK-NEXT: name: "Const2",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: type: BOOL,
// CHECK-NEXT: buffer: 4,
// CHECK-NEXT: name: "logical_or",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: type: BOOL,
// CHECK-NEXT: buffer: 5,
// CHECK-NEXT: name: "logical_and",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: } ],
// CHECK-NEXT: inputs: [ 0 ],
// CHECK-NEXT: outputs: [ 4 ],
// CHECK-NEXT: operators: [ {
// CHECK-NEXT: inputs: [ 0, 2 ],
// CHECK-NEXT: outputs: [ 3 ]
// CHECK-NEXT: }, {
// CHECK-NEXT: opcode_index: 1,
// CHECK-NEXT: inputs: [ 3, 1 ],
// CHECK-NEXT: outputs: [ 4 ]
// CHECK-NEXT: } ]
// CHECK-NEXT: name: "main"
// CHECK-NEXT: } ],
// CHECK-NEXT: description: "MLIR Converted.",
// CHECK-NEXT: buffers: [ {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 1, 1, 1, 1 ]
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 0, 0, 0, 0 ]
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 49, 46, 49, 49, 46, 48, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
// CHECK-NEXT: } ],
// CHECK-NEXT: metadata: [ {
// CHECK-NEXT: name: "min_runtime_version",
// CHECK-NEXT: buffer: 6
// CHECK-NEXT: } ]
// CHECK-NEXT: signature_defs: [ ]
// CHECK-NEXT: }
// CHECK-EMPTY:
%0 = "tfl.pseudo_const" () {value = dense<true> : tensor<4xi1>} : () -> tensor<4xi1> loc("Const1")
%1 = "tfl.pseudo_const" () {value = dense<false> : tensor<4xi1>} : () -> tensor<4xi1> loc("Const2")
%2 = "tfl.logical_or"(%arg0, %1) : (tensor<4xi1>, tensor<4xi1>) -> tensor<4xi1> loc("logical_or")
%3 = "tfl.logical_and"(%2, %0) : (tensor<4xi1>, tensor<4xi1>) -> tensor<4xi1> loc("logical_and")
func.return %3 : tensor<4xi1>
}
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/low_bit_packing.mlir
+57
View File
@@ -0,0 +1,57 @@
// Copyright 2026 The TensorFlow Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// ==============================================================================
// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -emit-custom-ops -emit-builtin-tflite-ops=false -o - | flatbuffer_to_string - | FileCheck %s
func.func @main() -> tensor<4xi4> {
// CHECK: {
// CHECK: version: 3,
// CHECK: operator_codes: [ ],
// CHECK: subgraphs: [ {
// CHECK: tensors: [ {
// CHECK: shape: [ 4 ],
// CHECK: type: INT4,
// CHECK: buffer: 1,
// CHECK: name: "Const",
// CHECK: quantization: {
// CHECK-EMPTY
// CHECK: },
// CHECK: has_rank: true
// CHECK: } ],
// CHECK: inputs: [ ],
// CHECK: outputs: [ 0 ],
// CHECK: operators: [ ],
// CHECK: name: "main"
// CHECK: } ],
// CHECK: description: "MLIR Converted.",
// CHECK: buffers: [ {
// CHECK-EMPTY
// CHECK: }, {
// CHECK: data: [ 56, 190 ]
// CHECK: }, {
// CHECK: data: [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
// CHECK: } ],
// CHECK: metadata: [ {
// CHECK: name: "min_runtime_version",
// CHECK: buffer: 2
// CHECK: } ],
// CHECK: signature_defs: [ ]
// CHECK: }
// Test that i4 buffers are densely packed, i.e. [-8, 3, -2, -5] should be
// be packed low-bits-first as [0x38, 0xBE] or [56, 190]. Tensor type should
// be INT4.
%0 = "tfl.pseudo_const" () {value = dense<[-8, 3, -2, -5]> : tensor<4xi4>} : () -> tensor<4xi4> loc("Const")
func.return %0 : tensor<4xi4>
}
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/lstm.mlir
+310
View File
@@ -0,0 +1,310 @@
// Copyright 2026 The TensorFlow Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// ==============================================================================
// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_to_string - | FileCheck %s
func.func @main(tensor<1x4xf32>, tensor<4x4xf32>, tensor<4x4xf32>, tensor<4x4xf32>, tensor<4x4xf32>, tensor<4x4xf32>, tensor<4x4xf32>, tensor<4x4xf32>, tensor<4x4xf32>, tensor<4xf32>, tensor<4xf32>, tensor<4xf32>, tensor<1x4xf32>, tensor<4xf32>, tensor<4xf32>, tensor<4xf32>, tensor<4x4xf32>, tensor<4xf32>, tensor<4xf32>, tensor<4xf32>, tensor<4xf32>, tensor<4xf32>) -> tensor<1x4xf32> {
// CHECK: {
// CHECK-NEXT: version: 3,
// CHECK-NEXT: operator_codes: [ {
// CHECK-NEXT: deprecated_builtin_code: 16,
// CHECK-NEXT: version: 1,
// CHECK-NEXT: builtin_code: LSTM
// CHECK-NEXT: } ],
// CHECK-NEXT: subgraphs: [ {
// CHECK-NEXT: tensors: [ {
// CHECK-NEXT: shape: [ 1, 4 ],
// CHECK-NEXT: buffer: 1,
// CHECK-NEXT: name: "arg0",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4, 4 ],
// CHECK-NEXT: buffer: 2,
// CHECK-NEXT: name: "arg1",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4, 4 ],
// CHECK-NEXT: buffer: 3,
// CHECK-NEXT: name: "arg2",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4, 4 ],
// CHECK-NEXT: buffer: 4,
// CHECK-NEXT: name: "arg3",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4, 4 ],
// CHECK-NEXT: buffer: 5,
// CHECK-NEXT: name: "arg4",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4, 4 ],
// CHECK-NEXT: buffer: 6,
// CHECK-NEXT: name: "arg5",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4, 4 ],
// CHECK-NEXT: buffer: 7,
// CHECK-NEXT: name: "arg6",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4, 4 ],
// CHECK-NEXT: buffer: 8,
// CHECK-NEXT: name: "arg7",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4, 4 ],
// CHECK-NEXT: buffer: 9,
// CHECK-NEXT: name: "arg8",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 10,
// CHECK-NEXT: name: "arg9",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 11,
// CHECK-NEXT: name: "arg10",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 12,
// CHECK-NEXT: name: "arg11",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 1, 4 ],
// CHECK-NEXT: buffer: 13,
// CHECK-NEXT: name: "arg12",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 14,
// CHECK-NEXT: name: "arg13",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 15,
// CHECK-NEXT: name: "arg14",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 16,
// CHECK-NEXT: name: "arg15",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4, 4 ],
// CHECK-NEXT: buffer: 17,
// CHECK-NEXT: name: "arg16",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 18,
// CHECK-NEXT: name: "arg17",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 19,
// CHECK-NEXT: name: "arg18",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 20,
// CHECK-NEXT: name: "arg19",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 21,
// CHECK-NEXT: name: "arg20",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 22,
// CHECK-NEXT: name: "arg21",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 1, 4 ],
// CHECK-NEXT: name: "Const",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: is_variable: true,
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 1, 4 ],
// CHECK-NEXT: name: "Const1",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: is_variable: true,
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 1, 4 ],
// CHECK-NEXT: buffer: 25,
// CHECK-NEXT: name: "tfl.lstm",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: } ],
// CHECK-NEXT: inputs: [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 ],
// CHECK-NEXT: outputs: [ 24 ],
// CHECK-NEXT: operators: [ {
// CHECK-NEXT: inputs: [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 22, 23, 18, 19, 20, 21 ],
// CHECK-NEXT: outputs: [ 24 ],
// CHECK-NEXT: builtin_options_type: LSTMOptions,
// CHECK-NEXT: builtin_options: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: intermediates: [ ]
// CHECK-NEXT: } ],
// CHECK-NEXT: name: "main"
// CHECK-NEXT: } ],
// CHECK-NEXT: description: "MLIR Converted.",
// CHECK-NEXT: buffers: [ {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 49, 46, 55, 46, 48, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
// CHECK-NEXT: } ],
// CHECK-NEXT: metadata: [ {
// CHECK-NEXT: name: "min_runtime_version",
// CHECK-NEXT: buffer: 26
// CHECK-NEXT: } ]
// CHECK-NEXT: signature_defs: [ ]
// CHECK-NEXT: }
// CHECK-EMPTY:
^bb0(%arg0: tensor<1x4xf32>, %arg1: tensor<4x4xf32>, %arg2: tensor<4x4xf32>, %arg3: tensor<4x4xf32>, %arg4: tensor<4x4xf32>, %arg5: tensor<4x4xf32>, %arg6: tensor<4x4xf32>, %arg7: tensor<4x4xf32>, %arg8: tensor<4x4xf32>, %arg9: tensor<4xf32>, %arg10: tensor<4xf32>, %arg11: tensor<4xf32>, %arg12: tensor<1x4xf32>, %arg13: tensor<4xf32>, %arg14: tensor<4xf32>, %arg15: tensor<4xf32>, %arg16: tensor<4x4xf32>, %arg17: tensor<4xf32>, %arg18: tensor<4xf32>, %arg19: tensor<4xf32>, %arg20: tensor<4xf32>, %arg21: tensor<4xf32>):
%cst0 = "tfl.pseudo_const" () {value = dense<0.0> : tensor<1x4xf32>} : () -> tensor<1x4xf32> loc("Const")
%cst1 = "tfl.pseudo_const" () {value = dense<0.0> : tensor<1x4xf32>} : () -> tensor<1x4xf32> loc("Const")
%24 = "tfl.lstm"(%arg0, %arg1, %arg2, %arg3, %arg4, %arg5, %arg6, %arg7, %arg8, %arg9, %arg10, %arg11, %arg12, %arg13, %arg14, %arg15, %arg16, %arg17, %cst0, %cst1, %arg18, %arg19, %arg20, %arg21) ({}) {cell_clip = 0.000000e+00 : f32, fused_activation_function = "NONE", kernel_type = #tfl<lstm_kernel_type_attr FULL>, proj_clip = 0.000000e+00 : f32} : (tensor<1x4xf32>, tensor<4x4xf32>, tensor<4x4xf32>, tensor<4x4xf32>, tensor<4x4xf32>, tensor<4x4xf32>, tensor<4x4xf32>, tensor<4x4xf32>, tensor<4x4xf32>, tensor<4xf32>, tensor<4xf32>, tensor<4xf32>, tensor<1x4xf32>, tensor<4xf32>, tensor<4xf32>, tensor<4xf32>, tensor<4x4xf32>, tensor<4xf32>, tensor<1x4xf32>, tensor<1x4xf32>, tensor<4xf32>, tensor<4xf32>, tensor<4xf32>, tensor<4xf32>) -> tensor<1x4xf32>
func.return %24 : tensor<1x4xf32>
}
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/lstm_asym_attr.mlir
+310
View File
@@ -0,0 +1,310 @@
// Copyright 2026 The TensorFlow Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// ==============================================================================
// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_to_string - | FileCheck %s
func.func @main(tensor<1x4xf32>, tensor<4x4xf32>, tensor<4x4xf32>, tensor<4x4xf32>, tensor<4x4xf32>, tensor<4x4xf32>, tensor<4x4xf32>, tensor<4x4xf32>, tensor<4x4xf32>, tensor<4xf32>, tensor<4xf32>, tensor<4xf32>, tensor<1x4xf32>, tensor<4xf32>, tensor<4xf32>, tensor<4xf32>, tensor<4x4xf32>, tensor<4xf32>, tensor<4xf32>, tensor<4xf32>, tensor<4xf32>, tensor<4xf32>) -> tensor<1x4xf32> {
// CHECK: {
// CHECK-NEXT: version: 3,
// CHECK-NEXT: operator_codes: [ {
// CHECK-NEXT: deprecated_builtin_code: 16,
// CHECK-NEXT: version: 1,
// CHECK-NEXT: builtin_code: LSTM
// CHECK-NEXT: } ],
// CHECK-NEXT: subgraphs: [ {
// CHECK-NEXT: tensors: [ {
// CHECK-NEXT: shape: [ 1, 4 ],
// CHECK-NEXT: buffer: 1,
// CHECK-NEXT: name: "arg0",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4, 4 ],
// CHECK-NEXT: buffer: 2,
// CHECK-NEXT: name: "arg1",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4, 4 ],
// CHECK-NEXT: buffer: 3,
// CHECK-NEXT: name: "arg2",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4, 4 ],
// CHECK-NEXT: buffer: 4,
// CHECK-NEXT: name: "arg3",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4, 4 ],
// CHECK-NEXT: buffer: 5,
// CHECK-NEXT: name: "arg4",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4, 4 ],
// CHECK-NEXT: buffer: 6,
// CHECK-NEXT: name: "arg5",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4, 4 ],
// CHECK-NEXT: buffer: 7,
// CHECK-NEXT: name: "arg6",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4, 4 ],
// CHECK-NEXT: buffer: 8,
// CHECK-NEXT: name: "arg7",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4, 4 ],
// CHECK-NEXT: buffer: 9,
// CHECK-NEXT: name: "arg8",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 10,
// CHECK-NEXT: name: "arg9",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 11,
// CHECK-NEXT: name: "arg10",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 12,
// CHECK-NEXT: name: "arg11",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 1, 4 ],
// CHECK-NEXT: buffer: 13,
// CHECK-NEXT: name: "arg12",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 14,
// CHECK-NEXT: name: "arg13",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 15,
// CHECK-NEXT: name: "arg14",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 16,
// CHECK-NEXT: name: "arg15",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4, 4 ],
// CHECK-NEXT: buffer: 17,
// CHECK-NEXT: name: "arg16",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 18,
// CHECK-NEXT: name: "arg17",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 19,
// CHECK-NEXT: name: "arg18",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 20,
// CHECK-NEXT: name: "arg19",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 21,
// CHECK-NEXT: name: "arg20",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 22,
// CHECK-NEXT: name: "arg21",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 1, 4 ],
// CHECK-NEXT: name: "Const",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: is_variable: true,
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 1, 4 ],
// CHECK-NEXT: name: "Const1",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: is_variable: true,
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 1, 4 ],
// CHECK-NEXT: buffer: 25,
// CHECK-NEXT: name: "tfl.lstm",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: } ],
// CHECK-NEXT: inputs: [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 ],
// CHECK-NEXT: outputs: [ 24 ],
// CHECK-NEXT: operators: [ {
// CHECK-NEXT: inputs: [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 22, 23, 18, 19, 20, 21 ],
// CHECK-NEXT: outputs: [ 24 ],
// CHECK-NEXT: builtin_options_type: LSTMOptions,
// CHECK-NEXT: builtin_options: {
// CHECK-NEXT: asymmetric_quantize_inputs: true
// CHECK-NEXT: },
// CHECK-NEXT: intermediates: [ ]
// CHECK-NEXT: } ],
// CHECK-NEXT: name: "main"
// CHECK-NEXT: } ],
// CHECK-NEXT: description: "MLIR Converted.",
// CHECK-NEXT: buffers: [ {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 49, 46, 55, 46, 48, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
// CHECK-NEXT: } ],
// CHECK-NEXT: metadata: [ {
// CHECK-NEXT: name: "min_runtime_version",
// CHECK-NEXT: buffer: 26
// CHECK-NEXT: } ]
// CHECK-NEXT: signature_defs: [ ]
// CHECK-NEXT: }
// CHECK-EMPTY:
^bb0(%arg0: tensor<1x4xf32>, %arg1: tensor<4x4xf32>, %arg2: tensor<4x4xf32>, %arg3: tensor<4x4xf32>, %arg4: tensor<4x4xf32>, %arg5: tensor<4x4xf32>, %arg6: tensor<4x4xf32>, %arg7: tensor<4x4xf32>, %arg8: tensor<4x4xf32>, %arg9: tensor<4xf32>, %arg10: tensor<4xf32>, %arg11: tensor<4xf32>, %arg12: tensor<1x4xf32>, %arg13: tensor<4xf32>, %arg14: tensor<4xf32>, %arg15: tensor<4xf32>, %arg16: tensor<4x4xf32>, %arg17: tensor<4xf32>, %arg18: tensor<4xf32>, %arg19: tensor<4xf32>, %arg20: tensor<4xf32>, %arg21: tensor<4xf32>):
%cst0 = "tfl.pseudo_const" () {value = dense<0.0> : tensor<1x4xf32>} : () -> tensor<1x4xf32> loc("Const")
%cst1 = "tfl.pseudo_const" () {value = dense<0.0> : tensor<1x4xf32>} : () -> tensor<1x4xf32> loc("Const")
%24 = "tfl.lstm"(%arg0, %arg1, %arg2, %arg3, %arg4, %arg5, %arg6, %arg7, %arg8, %arg9, %arg10, %arg11, %arg12, %arg13, %arg14, %arg15, %arg16, %arg17, %cst0, %cst1, %arg18, %arg19, %arg20, %arg21) ({}) {asymmetric_quantize_inputs = true, cell_clip = 0.000000e+00 : f32, fused_activation_function = "NONE", kernel_type = #tfl<lstm_kernel_type_attr FULL>, proj_clip = 0.000000e+00 : f32} : (tensor<1x4xf32>, tensor<4x4xf32>, tensor<4x4xf32>, tensor<4x4xf32>, tensor<4x4xf32>, tensor<4x4xf32>, tensor<4x4xf32>, tensor<4x4xf32>, tensor<4x4xf32>, tensor<4xf32>, tensor<4xf32>, tensor<4xf32>, tensor<1x4xf32>, tensor<4xf32>, tensor<4xf32>, tensor<4xf32>, tensor<4x4xf32>, tensor<4xf32>, tensor<1x4xf32>, tensor<1x4xf32>, tensor<4xf32>, tensor<4xf32>, tensor<4xf32>, tensor<4xf32>) -> tensor<1x4xf32>
func.return %24 : tensor<1x4xf32>
}
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/lstm_quantized.mlir
+366
View File
@@ -0,0 +1,366 @@
// Copyright 2026 The TensorFlow Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// ==============================================================================
// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_to_string - | FileCheck %s
func.func @main(%arg0: tensor<1x528x!quant.uniform<i8:f32, 0.037248000502586365:-19>>, %arg1: tensor<2048x528x!quant.uniform<i8<-127:127>:f32, 0.059801999479532242>>, %arg2: tensor<2048x528x!quant.uniform<i8<-127:127>:f32, 0.031925998628139496>>, %arg3: tensor<2048x528x!quant.uniform<i8<-127:127>:f32, 0.056272000074386597>>, %arg4: tensor<2048x528x!quant.uniform<i8<-127:127>:f32, 0.063763998448848724>>, %arg5: tensor<2048x640x!quant.uniform<i8<-127:127>:f32, 0.013358999975025654>>, %arg6: tensor<2048x640x!quant.uniform<i8<-127:127>:f32, 0.022830000147223473>>, %arg7: tensor<2048x640x!quant.uniform<i8<-127:127>:f32, 0.032276000827550888>>, %arg8: tensor<2048x640x!quant.uniform<i8<-127:127>:f32, 0.035427000373601913>>, %arg9: tensor<2048x!quant.uniform<i32:f32, 4.2675782196965883E-7>>, %arg10: tensor<2048x!quant.uniform<i32:f32, 1.0742187583900886E-7>>, %arg11: tensor<2048x!quant.uniform<i32:f32, 1.6406249869760359E-7>>, %arg12: tensor<2048x!quant.uniform<i32:f32, 1.523437447303877E-7>>, %arg13: tensor<640x2048x!quant.uniform<i8<-127:127>:f32, 0.021174000576138496>>, %arg14: tensor<640x!quant.uniform<i32:f32, 1.601389680352559E-4>>, %arg15: tensor<2048x!quant.uniform<i16:f32, 4.3700000969693065E-4>>, %arg16: tensor<2048x!quant.uniform<i16:f32, 1.1000000085914508E-4>>, %arg17: tensor<2048x!quant.uniform<i16:f32, 1.6799999866634607E-4>>, %arg18: tensor<2048x!quant.uniform<i16:f32, 1.55999994603917E-4>>, %arg19: tensor<1x640x!quant.uniform<i8:f32, 0.09671100229024887:10>>, %arg20: tensor<1x2048x!quant.uniform<i16:f32, 4.8799999058246613E-4>>) -> tensor<1x640x!quant.uniform<i8:f32, 0.09671100229024887:10>> {
%cst = "tfl.no_value"() {value = unit} : () -> none
%0 = "tfl.lstm"(%arg0, %arg1, %arg2, %arg3, %arg4, %arg5, %arg6, %arg7, %arg8, %cst, %cst, %cst, %arg9, %arg10, %arg11, %arg12, %arg13, %arg14, %arg19, %arg20, %arg15, %arg16, %arg17, %arg18) ({}) {cell_clip = 1.000000e+01 : f32, fused_activation_function = "TANH", input_to_input_intermediate = tensor<0x!quant.uniform<i16:f32, 0.0049890000373125076>>, input_to_forget_intermediate = tensor<0x!quant.uniform<i16:f32, 0.0078849997371435165>>, input_to_cell_intermediate = tensor<0x!quant.uniform<i16:f32, 0.0087630003690719604>>, input_to_output_intermediate = tensor<0x!quant.uniform<i16:f32, 0.0057529998011887074>>, effective_hidden_scale_intermediate = tensor<0x!quant.uniform<i8<-127:127>:f32, 0.0075630000792443752:2>>, kernel_type = #tfl<lstm_kernel_type_attr FULL>, proj_clip = 0.01 : f32} : (tensor<1x528x!quant.uniform<i8:f32, 0.037248000502586365:-19>>, tensor<2048x528x!quant.uniform<i8<-127:127>:f32, 0.059801999479532242>>, tensor<2048x528x!quant.uniform<i8<-127:127>:f32, 0.031925998628139496>>, tensor<2048x528x!quant.uniform<i8<-127:127>:f32, 0.056272000074386597>>, tensor<2048x528x!quant.uniform<i8<-127:127>:f32, 0.063763998448848724>>, tensor<2048x640x!quant.uniform<i8<-127:127>:f32, 0.013358999975025654>>, tensor<2048x640x!quant.uniform<i8<-127:127>:f32, 0.022830000147223473>>, tensor<2048x640x!quant.uniform<i8<-127:127>:f32, 0.032276000827550888>>, tensor<2048x640x!quant.uniform<i8<-127:127>:f32, 0.035427000373601913>>, none, none, none, tensor<2048x!quant.uniform<i32:f32, 4.2675782196965883E-7>>, tensor<2048x!quant.uniform<i32:f32, 1.0742187583900886E-7>>, tensor<2048x!quant.uniform<i32:f32, 1.6406249869760359E-7>>, tensor<2048x!quant.uniform<i32:f32, 1.523437447303877E-7>>, tensor<640x2048x!quant.uniform<i8<-127:127>:f32, 0.021174000576138496>>, tensor<640x!quant.uniform<i32:f32, 1.601389680352559E-4>>, tensor<1x640x!quant.uniform<i8:f32, 0.09671100229024887:10>>, tensor<1x2048x!quant.uniform<i16:f32, 4.8799999058246613E-4>>, tensor<2048x!quant.uniform<i16:f32, 4.3700000969693065E-4>>, tensor<2048x!quant.uniform<i16:f32, 1.1000000085914508E-4>>, tensor<2048x!quant.uniform<i16:f32, 1.6799999866634607E-4>>, tensor<2048x!quant.uniform<i16:f32, 1.55999994603917E-4>>) -> tensor<1x640x!quant.uniform<i8:f32, 0.09671100229024887:10>>
func.return %0 : tensor<1x640x!quant.uniform<i8:f32, 0.09671100229024887:10>>
// CHECK: {
// CHECK-NEXT: version: 3,
// CHECK-NEXT: operator_codes: [ {
// CHECK-NEXT: deprecated_builtin_code: 16,
// CHECK-NEXT: version: 1,
// CHECK-NEXT: builtin_code: LSTM
// CHECK-NEXT: } ],
// CHECK-NEXT: subgraphs: [ {
// CHECK-NEXT: tensors: [ {
// CHECK-NEXT: shape: [ 1, 528 ],
// CHECK-NEXT: type: INT8,
// CHECK-NEXT: buffer: 1,
// CHECK-NEXT: name: "arg0",
// CHECK-NEXT: quantization: {
// CHECK-NEXT: scale: [ 0.037248 ],
// CHECK-NEXT: zero_point: [ -19 ]
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 2048, 528 ],
// CHECK-NEXT: type: INT8,
// CHECK-NEXT: buffer: 2,
// CHECK-NEXT: name: "arg1",
// CHECK-NEXT: quantization: {
// CHECK-NEXT: scale: [ 0.059802 ],
// CHECK-NEXT: zero_point: [ 0 ]
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 2048, 528 ],
// CHECK-NEXT: type: INT8,
// CHECK-NEXT: buffer: 3,
// CHECK-NEXT: name: "arg2",
// CHECK-NEXT: quantization: {
// CHECK-NEXT: scale: [ 0.031926 ],
// CHECK-NEXT: zero_point: [ 0 ]
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 2048, 528 ],
// CHECK-NEXT: type: INT8,
// CHECK-NEXT: buffer: 4,
// CHECK-NEXT: name: "arg3",
// CHECK-NEXT: quantization: {
// CHECK-NEXT: scale: [ 0.056272 ],
// CHECK-NEXT: zero_point: [ 0 ]
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 2048, 528 ],
// CHECK-NEXT: type: INT8,
// CHECK-NEXT: buffer: 5,
// CHECK-NEXT: name: "arg4",
// CHECK-NEXT: quantization: {
// CHECK-NEXT: scale: [ 0.063764 ],
// CHECK-NEXT: zero_point: [ 0 ]
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 2048, 640 ],
// CHECK-NEXT: type: INT8,
// CHECK-NEXT: buffer: 6,
// CHECK-NEXT: name: "arg5",
// CHECK-NEXT: quantization: {
// CHECK-NEXT: scale: [ 0.013359 ],
// CHECK-NEXT: zero_point: [ 0 ]
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 2048, 640 ],
// CHECK-NEXT: type: INT8,
// CHECK-NEXT: buffer: 7,
// CHECK-NEXT: name: "arg6",
// CHECK-NEXT: quantization: {
// CHECK-NEXT: scale: [ 0.02283 ],
// CHECK-NEXT: zero_point: [ 0 ]
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 2048, 640 ],
// CHECK-NEXT: type: INT8,
// CHECK-NEXT: buffer: 8,
// CHECK-NEXT: name: "arg7",
// CHECK-NEXT: quantization: {
// CHECK-NEXT: scale: [ 0.032276 ],
// CHECK-NEXT: zero_point: [ 0 ]
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 2048, 640 ],
// CHECK-NEXT: type: INT8,
// CHECK-NEXT: buffer: 9,
// CHECK-NEXT: name: "arg8",
// CHECK-NEXT: quantization: {
// CHECK-NEXT: scale: [ 0.035427 ],
// CHECK-NEXT: zero_point: [ 0 ]
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 2048 ],
// CHECK-NEXT: type: INT32,
// CHECK-NEXT: buffer: 10,
// CHECK-NEXT: name: "arg9",
// CHECK-NEXT: quantization: {
// CHECK-NEXT: scale: [ 0.0 ],
// CHECK-NEXT: zero_point: [ 0 ]
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 2048 ],
// CHECK-NEXT: type: INT32,
// CHECK-NEXT: buffer: 11,
// CHECK-NEXT: name: "arg10",
// CHECK-NEXT: quantization: {
// CHECK-NEXT: scale: [ 0.0 ],
// CHECK-NEXT: zero_point: [ 0 ]
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 2048 ],
// CHECK-NEXT: type: INT32,
// CHECK-NEXT: buffer: 12,
// CHECK-NEXT: name: "arg11",
// CHECK-NEXT: quantization: {
// CHECK-NEXT: scale: [ 0.0 ],
// CHECK-NEXT: zero_point: [ 0 ]
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 2048 ],
// CHECK-NEXT: type: INT32,
// CHECK-NEXT: buffer: 13,
// CHECK-NEXT: name: "arg12",
// CHECK-NEXT: quantization: {
// CHECK-NEXT: scale: [ 0.0 ],
// CHECK-NEXT: zero_point: [ 0 ]
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 640, 2048 ],
// CHECK-NEXT: type: INT8,
// CHECK-NEXT: buffer: 14,
// CHECK-NEXT: name: "arg13",
// CHECK-NEXT: quantization: {
// CHECK-NEXT: scale: [ 0.021174 ],
// CHECK-NEXT: zero_point: [ 0 ]
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 640 ],
// CHECK-NEXT: type: INT32,
// CHECK-NEXT: buffer: 15,
// CHECK-NEXT: name: "arg14",
// CHECK-NEXT: quantization: {
// CHECK-NEXT: scale: [ 0.00016 ],
// CHECK-NEXT: zero_point: [ 0 ]
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 2048 ],
// CHECK-NEXT: type: INT16,
// CHECK-NEXT: buffer: 16,
// CHECK-NEXT: name: "arg15",
// CHECK-NEXT: quantization: {
// CHECK-NEXT: scale: [ 0.000437 ],
// CHECK-NEXT: zero_point: [ 0 ]
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 2048 ],
// CHECK-NEXT: type: INT16,
// CHECK-NEXT: buffer: 17,
// CHECK-NEXT: name: "arg16",
// CHECK-NEXT: quantization: {
// CHECK-NEXT: scale: [ 0.00011 ],
// CHECK-NEXT: zero_point: [ 0 ]
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 2048 ],
// CHECK-NEXT: type: INT16,
// CHECK-NEXT: buffer: 18,
// CHECK-NEXT: name: "arg17",
// CHECK-NEXT: quantization: {
// CHECK-NEXT: scale: [ 0.000168 ],
// CHECK-NEXT: zero_point: [ 0 ]
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 2048 ],
// CHECK-NEXT: type: INT16,
// CHECK-NEXT: buffer: 19,
// CHECK-NEXT: name: "arg18",
// CHECK-NEXT: quantization: {
// CHECK-NEXT: scale: [ 0.000156 ],
// CHECK-NEXT: zero_point: [ 0 ]
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 1, 640 ],
// CHECK-NEXT: type: INT8,
// CHECK-NEXT: name: "arg19",
// CHECK-NEXT: quantization: {
// CHECK-NEXT: scale: [ 0.096711 ],
// CHECK-NEXT: zero_point: [ 10 ]
// CHECK-NEXT: },
// CHECK-NEXT: is_variable: true,
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 1, 2048 ],
// CHECK-NEXT: type: INT16,
// CHECK-NEXT: name: "arg20",
// CHECK-NEXT: quantization: {
// CHECK-NEXT: scale: [ 0.000488 ],
// CHECK-NEXT: zero_point: [ 0 ]
// CHECK-NEXT: },
// CHECK-NEXT: is_variable: true,
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 0 ],
// CHECK-NEXT: type: INT16,
// CHECK-NEXT: name: "input_to_input_intermediate",
// CHECK-NEXT: quantization: {
// CHECK-NEXT: scale: [ 0.004989 ],
// CHECK-NEXT: zero_point: [ 0 ]
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 0 ],
// CHECK-NEXT: type: INT16,
// CHECK-NEXT: name: "input_to_forget_intermediate",
// CHECK-NEXT: quantization: {
// CHECK-NEXT: scale: [ 0.007885 ],
// CHECK-NEXT: zero_point: [ 0 ]
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 0 ],
// CHECK-NEXT: type: INT16,
// CHECK-NEXT: name: "input_to_cell_intermediate",
// CHECK-NEXT: quantization: {
// CHECK-NEXT: scale: [ 0.008763 ],
// CHECK-NEXT: zero_point: [ 0 ]
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 0 ],
// CHECK-NEXT: type: INT16,
// CHECK-NEXT: name: "input_to_output_intermediate",
// CHECK-NEXT: quantization: {
// CHECK-NEXT: scale: [ 0.005753 ],
// CHECK-NEXT: zero_point: [ 0 ]
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 0 ],
// CHECK-NEXT: type: INT8,
// CHECK-NEXT: name: "effective_hidden_scale_intermediate",
// CHECK-NEXT: quantization: {
// CHECK-NEXT: scale: [ 0.007563 ],
// CHECK-NEXT: zero_point: [ 2 ]
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 1, 640 ],
// CHECK-NEXT: type: INT8,
// CHECK-NEXT: buffer: 22,
// CHECK-NEXT: name: "tfl.lstm",
// CHECK-NEXT: quantization: {
// CHECK-NEXT: scale: [ 0.096711 ],
// CHECK-NEXT: zero_point: [ 10 ]
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: } ],
// CHECK-NEXT: inputs: [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20 ],
// CHECK-NEXT: outputs: [ 26 ],
// CHECK-NEXT: operators: [ {
// CHECK-NEXT: inputs: [ 0, 1, 2, 3, 4, 5, 6, 7, 8, -1, -1, -1, 9, 10, 11, 12, 13, 14, 19, 20, 15, 16, 17, 18 ],
// CHECK-NEXT: outputs: [ 26 ],
// CHECK-NEXT: builtin_options_type: LSTMOptions,
// CHECK-NEXT: builtin_options: {
// CHECK-NEXT: fused_activation_function: TANH,
// CHECK-NEXT: cell_clip: 10.0,
// CHECK-NEXT: proj_clip: 0.01
// CHECK-NEXT: },
// CHECK-NEXT: intermediates: [ 21, 22, 23, 24, 25 ]
// CHECK-NEXT: } ],
// CHECK-NEXT: name: "main"
// CHECK-NEXT: } ],
// CHECK-NEXT: description: "MLIR Converted.",
// CHECK-NEXT: buffers: [ {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 49, 46, 55, 46, 48, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
// CHECK-NEXT: } ],
// CHECK-NEXT: metadata: [ {
// CHECK-NEXT: name: "min_runtime_version",
// CHECK-NEXT: buffer: 23
// CHECK-NEXT: } ]
// CHECK-NEXT: signature_defs: [ ]
// CHECK-NEXT: }
}
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/math.mlir
+174
View File
@@ -0,0 +1,174 @@
// Copyright 2026 The TensorFlow Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// ==============================================================================
// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_to_string - | FileCheck %s
func.func @main(tensor<4xf32>) -> tensor<4xf32> {
^bb0(%arg0: tensor<4xf32>):
// CHECK: {
// CHECK-NEXT: version: 3,
// CHECK-NEXT: operator_codes: [ {
// CHECK-NEXT: deprecated_builtin_code: 99,
// CHECK-NEXT: version: 1,
// CHECK-NEXT: builtin_code: SQUARED_DIFFERENCE
// CHECK-NEXT: }, {
// CHECK-NEXT: deprecated_builtin_code: 18,
// CHECK-NEXT: version: 1,
// CHECK-NEXT: builtin_code: MUL
// CHECK-NEXT: }, {
// CHECK-NEXT: deprecated_builtin_code: 42,
// CHECK-NEXT: version: 1,
// CHECK-NEXT: builtin_code: DIV
// CHECK-NEXT: }, {
// CHECK-NEXT: deprecated_builtin_code: 47,
// CHECK-NEXT: version: 1,
// CHECK-NEXT: builtin_code: EXP
// CHECK-NEXT: }, {
// CHECK-NEXT: deprecated_builtin_code: 59,
// CHECK-NEXT: version: 1,
// CHECK-NEXT: builtin_code: NEG
// CHECK-NEXT: } ],
// CHECK-NEXT: subgraphs: [ {
// CHECK-NEXT: tensors: [ {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 1,
// CHECK-NEXT: name: "arg0",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 2,
// CHECK-NEXT: name: "Const",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 3,
// CHECK-NEXT: name: "squared_difference",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 4,
// CHECK-NEXT: name: "mul",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 5,
// CHECK-NEXT: name: "div",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 6,
// CHECK-NEXT: name: "exp",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 7,
// CHECK-NEXT: name: "neg",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: } ],
// CHECK-NEXT: inputs: [ 0 ],
// CHECK-NEXT: outputs: [ 6 ],
// CHECK-NEXT: operators: [ {
// CHECK-NEXT: inputs: [ 0, 1 ],
// CHECK-NEXT: outputs: [ 2 ]
// CHECK-NEXT: }, {
// CHECK-NEXT: opcode_index: 1,
// CHECK-NEXT: inputs: [ 0, 2 ],
// CHECK-NEXT: outputs: [ 3 ],
// CHECK-NEXT: builtin_options_type: MulOptions,
// CHECK-NEXT: builtin_options: {
// CHECK-EMPTY:
// CHECK-NEXT: }
// CHECK-NEXT: }, {
// CHECK-NEXT: opcode_index: 2,
// CHECK-NEXT: inputs: [ 3, 2 ],
// CHECK-NEXT: outputs: [ 4 ],
// CHECK-NEXT: builtin_options_type: DivOptions,
// CHECK-NEXT: builtin_options: {
// CHECK-EMPTY:
// CHECK-NEXT: }
// CHECK-NEXT: }, {
// CHECK-NEXT: opcode_index: 3,
// CHECK-NEXT: inputs: [ 4 ],
// CHECK-NEXT: outputs: [ 5 ],
// CHECK-NEXT: builtin_options_type: ExpOptions,
// CHECK-NEXT: builtin_options: {
// CHECK-EMPTY:
// CHECK-NEXT: }
// CHECK-NEXT: }, {
// CHECK-NEXT: opcode_index: 4,
// CHECK-NEXT: inputs: [ 5 ],
// CHECK-NEXT: outputs: [ 6 ],
// CHECK-NEXT: builtin_options_type: NegOptions,
// CHECK-NEXT: builtin_options: {
// CHECK-EMPTY:
// CHECK-NEXT: }
// CHECK-NEXT: } ]
// CHECK-NEXT: name: "main"
// CHECK-NEXT: } ],
// CHECK-NEXT: description: "MLIR Converted.",
// CHECK-NEXT: buffers: [ {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 0, 0, 128, 63, 0, 0, 128, 63, 0, 0, 128, 63, 0, 0, 128, 63 ]
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 49, 46, 49, 51, 46, 49, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
// CHECK-NEXT: } ],
// CHECK-NEXT: metadata: [ {
// CHECK-NEXT: name: "min_runtime_version",
// CHECK-NEXT: buffer: 8
// CHECK-NEXT: } ]
// CHECK-NEXT: signature_defs: [ ]
// CHECK-NEXT: }
%0 = "tfl.pseudo_const" () {value = dense<1.0> : tensor<4xf32>} : () -> tensor<4xf32> loc("Const")
%1 = "tfl.squared_difference"(%arg0, %0) {fused_activation_function = "NONE"} : (tensor<4xf32>, tensor<4xf32>) -> tensor<4xf32> loc("squared_difference")
%2 = "tfl.mul"(%arg0, %1) {fused_activation_function = "NONE"} : (tensor<4xf32>, tensor<4xf32>) -> tensor<4xf32> loc("mul")
%3 = "tfl.div"(%2, %1) {fused_activation_function = "NONE"} : (tensor<4xf32>, tensor<4xf32>) -> tensor<4xf32> loc("div")
%4 = "tfl.exp"(%3) : (tensor<4xf32>) -> tensor<4xf32> loc("exp")
%5 = "tfl.neg"(%4) : (tensor<4xf32>) -> tensor<4xf32> loc("neg")
func.return %5 : tensor<4xf32>
}
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/metadata.mlir
+51
View File
@@ -0,0 +1,51 @@
// Copyright 2026 The TensorFlow Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// ==============================================================================
// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_to_string - | FileCheck %s
module attributes {
tfl.metadata = {key1 = "value1", key2 = "value2"}
} {
func.func @main(tensor<3x2xi32>) -> tensor<3x2xi32>
attributes {tf.entry_function = {inputs = "input", outputs = "SameNameAsOutput"}} {
^bb0(%arg0: tensor<3x2xi32>):
%0 = "tfl.pseudo_const" () {value = dense<[[1, 2], [3, 4], [5, 6]]> : tensor<3x2xi32>} : () -> tensor<3x2xi32>
%1 = "tfl.sub" (%arg0, %0) {fused_activation_function = "NONE"} : (tensor<3x2xi32>, tensor<3x2xi32>) -> tensor<3x2xi32>
func.return %1 : tensor<3x2xi32>
}
}
// CHECK: buffers: [ {
// CHECK: }, {
// CHECK: }, {
// CHECK: }, {
// CHECK: }, {
// CHECK-NEXT: data: [ 118, 97, 108, 117, 101, 49 ]
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 118, 97, 108, 117, 101, 50 ]
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 49, 46, 54, 46, 48, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
// CHECK-NEXT: } ],
// CHECK-NEXT: metadata: [ {
// CHECK-NEXT: name: "key1",
// CHECK-NEXT: buffer: 4
// CHECK-NEXT: }, {
// CHECK-NEXT: name: "key2",
// CHECK-NEXT: buffer: 5
// CHECK-NEXT: }, {
// CHECK-NEXT: name: "min_runtime_version",
// CHECK-NEXT: buffer: 6
// CHECK-NEXT: } ]
// CHECK-NEXT: signature_defs: [ ]
// CHECK-NEXT: }
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/mul_v2.mlir
+92
View File
@@ -0,0 +1,92 @@
// Copyright 2026 The TensorFlow Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// ==============================================================================
// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_to_string - | FileCheck %s
func.func @main(tensor<3x!quant.uniform<i8:f32, 0.1>>) -> tensor<3x!quant.uniform<i8:f32, 0.1>> {
^bb0(%arg0: tensor<3x!quant.uniform<i8:f32, 0.1>>):
// CHECK: {
// CHECK-NEXT: version: 3,
// CHECK-NEXT: operator_codes: [ {
// CHECK-NEXT: deprecated_builtin_code: 18,
// CHECK-NEXT: version: 2,
// CHECK-NEXT: builtin_code: MUL
// CHECK-NEXT: } ],
// CHECK-NEXT: subgraphs: [ {
// CHECK-NEXT: tensors: [ {
// CHECK-NEXT: shape: [ 3 ],
// CHECK-NEXT: type: INT8,
// CHECK-NEXT: buffer: 1,
// CHECK-NEXT: name: "arg0",
// CHECK-NEXT: quantization: {
// CHECK-NEXT: scale: [ 0.1 ],
// CHECK-NEXT: zero_point: [ 0 ]
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 3 ],
// CHECK-NEXT: type: INT8,
// CHECK-NEXT: buffer: 2,
// CHECK-NEXT: name: "tfl.pseudo_qconst",
// CHECK-NEXT: quantization: {
// CHECK-NEXT: scale: [ 0.1 ],
// CHECK-NEXT: zero_point: [ 0 ]
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 3 ],
// CHECK-NEXT: type: INT8,
// CHECK-NEXT: buffer: 3,
// CHECK-NEXT: name: "mul",
// CHECK-NEXT: quantization: {
// CHECK-NEXT: scale: [ 0.1 ],
// CHECK-NEXT: zero_point: [ 0 ]
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: } ],
// CHECK-NEXT: inputs: [ 0 ],
// CHECK-NEXT: outputs: [ 2 ],
// CHECK-NEXT: operators: [ {
// CHECK-NEXT: inputs: [ 0, 1 ],
// CHECK-NEXT: outputs: [ 2 ],
// CHECK-NEXT: builtin_options_type: MulOptions,
// CHECK-NEXT: builtin_options: {
// CHECK-EMPTY:
// CHECK-NEXT: }
// CHECK-NEXT: } ],
// CHECK-NEXT: name: "main"
// CHECK-NEXT: } ],
// CHECK-NEXT: description: "MLIR Converted.",
// CHECK-NEXT: buffers: [ {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 2, 2, 2 ]
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 49, 46, 49, 52, 46, 48, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
// CHECK-NEXT: } ],
// CHECK-NEXT: metadata: [ {
// CHECK-NEXT: name: "min_runtime_version",
// CHECK-NEXT: buffer: 4
// CHECK-NEXT: } ]
// CHECK-NEXT: signature_defs: [ ]
// CHECK-NEXT:}
%0 = "tfl.pseudo_qconst"() { qtype = tensor<3x!quant.uniform<i8:f32, 0.1>>, value = dense<2> : tensor<3xi8>} : () -> tensor<3x!quant.uniform<i8:f32, 0.1>>
%1 = "tfl.mul"(%arg0, %0) {fused_activation_function = "NONE"} : (tensor<3x!quant.uniform<i8:f32, 0.1>>, tensor<3x!quant.uniform<i8:f32, 0.1>>) -> tensor<3x!quant.uniform<i8:f32, 0.1>> loc("mul")
func.return %1 : tensor<3x!quant.uniform<i8:f32, 0.1>>
}
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/mul_v3.mlir
+92
View File
@@ -0,0 +1,92 @@
// Copyright 2026 The TensorFlow Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// ==============================================================================
// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_to_string - | FileCheck %s
func.func @main(tensor<3x!quant.uniform<i8:f32, 1.0>>) -> tensor<3x!quant.uniform<i8:f32, 1.0>> {
^bb0(%arg0: tensor<3x!quant.uniform<i8:f32, 1.0>>):
// CHECK: {
// CHECK-NEXT: version: 3,
// CHECK-NEXT: operator_codes: [ {
// CHECK-NEXT: deprecated_builtin_code: 18,
// CHECK-NEXT: version: 3,
// CHECK-NEXT: builtin_code: MUL
// CHECK-NEXT: } ],
// CHECK-NEXT: subgraphs: [ {
// CHECK-NEXT: tensors: [ {
// CHECK-NEXT: shape: [ 3 ],
// CHECK-NEXT: type: INT8,
// CHECK-NEXT: buffer: 1,
// CHECK-NEXT: name: "arg0",
// CHECK-NEXT: quantization: {
// CHECK-NEXT: scale: [ 1.0 ],
// CHECK-NEXT: zero_point: [ 0 ]
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 3 ],
// CHECK-NEXT: type: INT8,
// CHECK-NEXT: buffer: 2,
// CHECK-NEXT: name: "tfl.pseudo_qconst",
// CHECK-NEXT: quantization: {
// CHECK-NEXT: scale: [ 1.0 ],
// CHECK-NEXT: zero_point: [ 0 ]
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 3 ],
// CHECK-NEXT: type: INT8,
// CHECK-NEXT: buffer: 3,
// CHECK-NEXT: name: "mul",
// CHECK-NEXT: quantization: {
// CHECK-NEXT: scale: [ 1.0 ],
// CHECK-NEXT: zero_point: [ 0 ]
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: } ],
// CHECK-NEXT: inputs: [ 0 ],
// CHECK-NEXT: outputs: [ 2 ],
// CHECK-NEXT: operators: [ {
// CHECK-NEXT: inputs: [ 0, 1 ],
// CHECK-NEXT: outputs: [ 2 ],
// CHECK-NEXT: builtin_options_type: MulOptions,
// CHECK-NEXT: builtin_options: {
// CHECK-EMPTY:
// CHECK-NEXT: }
// CHECK-NEXT: } ],
// CHECK-NEXT: name: "main"
// CHECK-NEXT: } ],
// CHECK-NEXT: description: "MLIR Converted.",
// CHECK-NEXT: buffers: [ {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 2, 2, 2 ]
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 49, 46, 49, 53, 46, 48, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
// CHECK-NEXT: } ],
// CHECK-NEXT: metadata: [ {
// CHECK-NEXT: name: "min_runtime_version",
// CHECK-NEXT: buffer: 4
// CHECK-NEXT: } ]
// CHECK-NEXT: signature_defs: [ ]
// CHECK-NEXT:}
%0 = "tfl.pseudo_qconst"() { qtype = tensor<3x!quant.uniform<i8:f32, 1.0>>, value = dense<2> : tensor<3xi8>} : () -> tensor<3x!quant.uniform<i8:f32, 1.0>>
%1 = "tfl.mul"(%arg0, %0) {fused_activation_function = "NONE"} : (tensor<3x!quant.uniform<i8:f32, 1.0>>, tensor<3x!quant.uniform<i8:f32, 1.0>>) -> tensor<3x!quant.uniform<i8:f32, 1.0>> loc("mul")
func.return %1 : tensor<3x!quant.uniform<i8:f32, 1.0>>
}
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/nn.mlir
+79
View File
@@ -0,0 +1,79 @@
// Copyright 2026 The TensorFlow Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// ==============================================================================
// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_to_string - | FileCheck %s
func.func @main(tensor<1x6x6x16xf32>) -> tensor<1x1x1x16xf32> {
^bb0(%arg0: tensor<1x6x6x16xf32>):
// CHECK: {
// CHECK-NEXT: version: 3,
// CHECK-NEXT: operator_codes: [ {
// CHECK-NEXT: deprecated_builtin_code: 1,
// CHECK-NEXT: version: 1,
// CHECK-NEXT: builtin_code: AVERAGE_POOL_2D
// CHECK-NEXT: } ],
// CHECK-NEXT: subgraphs: [ {
// CHECK-NEXT: tensors: [ {
// CHECK-NEXT: shape: [ 1, 6, 6, 16 ],
// CHECK-NEXT: buffer: 1,
// CHECK-NEXT: name: "arg0",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 1, 1, 1, 16 ],
// CHECK-NEXT: buffer: 2,
// CHECK-NEXT: name: "avgpool",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: } ],
// CHECK-NEXT: inputs: [ 0 ],
// CHECK-NEXT: outputs: [ 1 ],
// CHECK-NEXT: operators: [ {
// CHECK-NEXT: inputs: [ 0 ],
// CHECK-NEXT: outputs: [ 1 ],
// CHECK-NEXT: builtin_options_type: Pool2DOptions,
// CHECK-NEXT: builtin_options: {
// CHECK-NEXT: padding: VALID,
// CHECK-NEXT: stride_w: 1,
// CHECK-NEXT: stride_h: 3,
// CHECK-NEXT: filter_width: 6,
// CHECK-NEXT: filter_height: 3
// CHECK-NEXT: }
// CHECK-NEXT: } ]
// CHECK-NEXT: name: "main"
// CHECK-NEXT: } ],
// CHECK-NEXT: description: "MLIR Converted.",
// CHECK-NEXT: buffers: [ {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 49, 46, 53, 46, 48, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
// CHECK-NEXT: } ],
// CHECK-NEXT: metadata: [ {
// CHECK-NEXT: name: "min_runtime_version",
// CHECK-NEXT: buffer: 3
// CHECK-NEXT: } ]
// CHECK-NEXT: signature_defs: [ ]
// CHECK-NEXT: }
%0 = "tfl.average_pool_2d"(%arg0) {filter_height = 3 : i32, filter_width = 6 : i32, fused_activation_function = "NONE", padding = "VALID", stride_h = 3 : i32, stride_w = 1 : i32} : (tensor<1x6x6x16xf32>) -> tensor<1x1x1x16xf32> loc("avgpool")
func.return %0 : tensor<1x1x1x16xf32>
}
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/numeric_verify.mlir
+83
View File
@@ -0,0 +1,83 @@
// Copyright 2026 The TensorFlow Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// ==============================================================================
// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_to_string - | FileCheck %s
// CHECK: {
// CHECK-NEXT: version: 3,
// CHECK-NEXT: operator_codes: [ {
// CHECK-NEXT: deprecated_builtin_code: 32,
// CHECK-NEXT: custom_code: "NumericVerify",
// CHECK-NEXT: builtin_code: CUSTOM
// CHECK-NEXT: } ],
// CHECK-NEXT: subgraphs: [ {
// CHECK-NEXT: tensors: [ {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 1,
// CHECK-NEXT: name: "arg0",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: type: UINT8,
// CHECK-NEXT: buffer: 2,
// CHECK-NEXT: name: "arg1",
// CHECK-NEXT: quantization: {
// CHECK-NEXT: scale: [ 0.1 ],
// CHECK-NEXT: zero_point: [ 0 ]
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 3,
// CHECK-NEXT: name: "NumericVerify/arg1:1",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: } ],
// CHECK-NEXT: inputs: [ 0, 1 ],
// CHECK-NEXT: outputs: [ 0 ],
// CHECK-NEXT: operators: [ {
// CHECK-NEXT: inputs: [ 1, 0 ],
// CHECK-NEXT: outputs: [ 2 ],
// CHECK-NEXT: custom_options:
// CHECK-NEXT: } ],
// CHECK-NEXT: name: "main"
// CHECK-NEXT: } ],
// CHECK-NEXT: description: "MLIR Converted.",
// CHECK-NEXT: buffers: [ {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
// CHECK-NEXT: } ],
// CHECK-NEXT: metadata: [ {
// CHECK-NEXT: name: "min_runtime_version",
// CHECK-NEXT: buffer: 4
// CHECK-NEXT: } ]
// CHECK-NEXT: signature_defs: [ ]
// CHECK-NEXT:}
func.func @main(%arg0: tensor<4xf32>, %arg1: tensor<4x!quant.uniform<u8:f32, 0.1>>) -> tensor<4xf32> {
"tfl.NumericVerify"(%arg1, %arg0) {tolerance = 0.1 : f32} : (tensor<4x!quant.uniform<u8:f32, 0.1>>, tensor<4xf32>) -> (tensor<4xf32>)
func.return %arg0 : tensor<4xf32>
}
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/optional.mlir
+30
View File
@@ -0,0 +1,30 @@
// Copyright 2026 The TensorFlow Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// ==============================================================================
// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_to_string - | FileCheck %s
func.func @main(%arg0: tensor<40x37xf32>, %arg1: tensor<40x37xf32>) -> tensor<40x40xf32> {
%0 = "tfl.no_value"() {value = unit} : () -> none
%1:2 = "tfl.fully_connected"(%arg0, %arg1, %0) {fused_activation_function = "NONE", keep_num_dims = false, weights_format = "DEFAULT"} : (tensor<40x37xf32>, tensor<40x37xf32>, none) -> (tensor<40x40xf32>, tensor<40x40xf32>)
func.return %1 : tensor<40x40xf32>
}
// CHECK: operators: [ {
// CHECK-NEXT: inputs: [ 0, 1, -1 ],
// CHECK-NEXT: outputs: [ 2, 3 ],
// CHECK-NEXT: builtin_options_type: FullyConnectedOptions,
// CHECK-NEXT: builtin_options: {
// CHECK-EMPTY:
// CHECK-NEXT: }
// CHECK-NEXT: } ],
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/quantization.mlir
+201
View File
@@ -0,0 +1,201 @@
// Copyright 2026 The TensorFlow Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// ==============================================================================
// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_to_string - | FileCheck %s
func.func @main(%arg0: tensor<1x224x224x3xf32>) -> tensor<1x401408xf32> {
// CHECK: {
// CHECK-NEXT: version: 3,
// CHECK-NEXT: operator_codes: [ {
// CHECK-NEXT: deprecated_builtin_code: 114,
// CHECK-NEXT: version: 1,
// CHECK-NEXT: builtin_code: QUANTIZE
// CHECK-NEXT: }, {
// CHECK-NEXT: deprecated_builtin_code: 3,
// CHECK-NEXT: version: 1,
// CHECK-NEXT: builtin_code: CONV_2D
// CHECK-NEXT: }, {
// CHECK-NEXT: deprecated_builtin_code: 22,
// CHECK-NEXT: version: 1,
// CHECK-NEXT: builtin_code: RESHAPE
// CHECK-NEXT: }, {
// CHECK-NEXT: deprecated_builtin_code: 25,
// CHECK-NEXT: version: 1,
// CHECK-NEXT: builtin_code: SOFTMAX
// CHECK-NEXT: }, {
// CHECK-NEXT: deprecated_builtin_code: 6,
// CHECK-NEXT: version: 1,
// CHECK-NEXT: builtin_code: DEQUANTIZE
// CHECK-NEXT: } ],
// CHECK-NEXT: subgraphs: [ {
// CHECK-NEXT: tensors: [ {
// CHECK-NEXT: shape: [ 1, 224, 224, 3 ],
// CHECK-NEXT: buffer: 1,
// CHECK-NEXT: name: "arg0",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 2 ],
// CHECK-NEXT: type: INT32,
// CHECK-NEXT: buffer: 2,
// CHECK-NEXT: name: "Const",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 1, 224, 224, 3 ],
// CHECK-NEXT: type: UINT8,
// CHECK-NEXT: buffer: 3,
// CHECK-NEXT: name: "tfl.quantize",
// CHECK-NEXT: quantization: {
// CHECK-NEXT: scale: [ 0.007812 ],
// CHECK-NEXT: zero_point: [ 128 ]
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 32, 3, 3, 3 ],
// CHECK-NEXT: type: UINT8,
// CHECK-NEXT: buffer: 4,
// CHECK-NEXT: name: "tfl.pseudo_qconst",
// CHECK-NEXT: quantization: {
// CHECK-NEXT: scale: [ 0.021827 ],
// CHECK-NEXT: zero_point: [ 151 ]
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 32 ],
// CHECK-NEXT: type: INT32,
// CHECK-NEXT: buffer: 5,
// CHECK-NEXT: name: "tfl.pseudo_qconst1",
// CHECK-NEXT: quantization: {
// CHECK-NEXT: scale: [ 0.000171 ],
// CHECK-NEXT: zero_point: [ 0 ]
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 1, 112, 112, 32 ],
// CHECK-NEXT: type: UINT8,
// CHECK-NEXT: buffer: 6,
// CHECK-NEXT: name: "tfl.conv_2d",
// CHECK-NEXT: quantization: {
// CHECK-NEXT: scale: [ 0.023528 ],
// CHECK-NEXT: zero_point: [ 0 ]
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 1, 401408 ],
// CHECK-NEXT: type: UINT8,
// CHECK-NEXT: buffer: 7,
// CHECK-NEXT: name: "tfl.reshape",
// CHECK-NEXT: quantization: {
// CHECK-NEXT: scale: [ 0.023528 ],
// CHECK-NEXT: zero_point: [ 0 ]
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 1, 401408 ],
// CHECK-NEXT: type: UINT8,
// CHECK-NEXT: buffer: 8,
// CHECK-NEXT: name: "tfl.softmax",
// CHECK-NEXT: quantization: {
// CHECK-NEXT: scale: [ 0.003906 ],
// CHECK-NEXT: zero_point: [ 0 ]
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 1, 401408 ],
// CHECK-NEXT: buffer: 9,
// CHECK-NEXT: name: "tfl.dequantize",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: } ],
// CHECK-NEXT: inputs: [ 0 ],
// CHECK-NEXT: outputs: [ 8 ],
// CHECK-NEXT: operators: [ {
// CHECK-NEXT: inputs: [ 0 ],
// CHECK-NEXT: outputs: [ 2 ]
// CHECK-NEXT: }, {
// CHECK-NEXT: opcode_index: 1,
// CHECK-NEXT: inputs: [ 2, 3, 4 ],
// CHECK-NEXT: outputs: [ 5 ],
// CHECK-NEXT: builtin_options_type: Conv2DOptions,
// CHECK-NEXT: builtin_options: {
// CHECK-NEXT: stride_w: 2,
// CHECK-NEXT: stride_h: 2
// CHECK-NEXT: }
// CHECK-NEXT: }, {
// CHECK-NEXT: opcode_index: 2,
// CHECK-NEXT: inputs: [ 5, 1 ],
// CHECK-NEXT: outputs: [ 6 ]
// CHECK-NEXT: }, {
// CHECK-NEXT: opcode_index: 3,
// CHECK-NEXT: inputs: [ 6 ],
// CHECK-NEXT: outputs: [ 7 ],
// CHECK-NEXT: builtin_options_type: SoftmaxOptions,
// CHECK-NEXT: builtin_options: {
// CHECK-NEXT: beta: 1.0
// CHECK-NEXT: }
// CHECK-NEXT: }, {
// CHECK-NEXT: opcode_index: 4,
// CHECK-NEXT: inputs: [ 7 ],
// CHECK-NEXT: outputs: [ 8 ]
// CHECK-NEXT: } ]
// CHECK-NEXT: name: "main"
// CHECK-NEXT: } ],
// CHECK-NEXT: description: "MLIR Converted.",
// CHECK-NEXT: buffers: [ {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 1, 0, 0, 0, 0, 32, 6, 0 ]
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180, 180 ]
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 49, 46, 49, 52, 46, 48, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
// CHECK-NEXT: } ],
// CHECK-NEXT: metadata: [ {
// CHECK-NEXT: name: "min_runtime_version",
// CHECK-NEXT: buffer: 10
// CHECK-NEXT: } ]
// CHECK-NEXT: signature_defs: [ ]
// CHECK-NEXT:}
%0 = "tfl.pseudo_const" () {value = dense<[1, 401408]> : tensor<2xi32>} : () -> tensor<2xi32> loc("Const")
%1 = "tfl.quantize"(%arg0) {qtype = tensor<1x224x224x3x!quant.uniform<u8:f32, 7.812500e-03:128>>} : (tensor<1x224x224x3xf32>) -> tensor<1x224x224x3x!quant.uniform<u8:f32, 7.812500e-03:128>>
%2 = "tfl.pseudo_qconst"() {qtype = tensor<32x3x3x3x!quant.uniform<u8<1:255>:f32, 0.021826678373682216:151>>, value = dense<-76> : tensor<32x3x3x3xi8>} : () -> tensor<32x3x3x3x!quant.uniform<u8<1:255>:f32, 0.021826678373682216:151>>
%3 = "tfl.pseudo_qconst"() {qtype = tensor<32x!quant.uniform<i32:f32, 1.7052092479439231E-4>>, value = dense<0> : tensor<32xi32>} : () -> tensor<32x!quant.uniform<i32:f32, 1.7052092479439231E-4>>
%4 = "tfl.conv_2d"(%1, %2, %3) {dilation_h_factor = 1 : i32, dilation_w_factor = 1 : i32, fused_activation_function = "NONE", padding = "SAME", stride_h = 2 : i32, stride_w = 2 : i32} : (tensor<1x224x224x3x!quant.uniform<u8:f32, 7.812500e-03:128>>, tensor<32x3x3x3x!quant.uniform<u8<1:255>:f32, 0.021826678373682216:151>>, tensor<32x!quant.uniform<i32:f32, 1.7052092479439231E-4>>) -> tensor<1x112x112x32x!quant.uniform<u8:f32, 0.023528476789885875>>
%5 = "tfl.reshape"(%4, %0) : (tensor<1x112x112x32x!quant.uniform<u8:f32, 0.023528476789885875>>, tensor<2xi32>) -> tensor<1x401408x!quant.uniform<u8:f32, 0.023528476789885875>>
%6 = "tfl.softmax"(%5) {beta = 1.000000e+00 : f32} : (tensor<1x401408x!quant.uniform<u8:f32, 0.023528476789885875>>) -> tensor<1x401408x!quant.uniform<u8:f32, 3.906250e-03>>
%7 = "tfl.dequantize"(%6) : (tensor<1x401408x!quant.uniform<u8:f32, 3.906250e-03>>) -> tensor<1x401408xf32>
func.return %7 : tensor<1x401408xf32>
}
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/reshape.mlir
+85
View File
@@ -0,0 +1,85 @@
// Copyright 2026 The TensorFlow Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// ==============================================================================
// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_to_string - | FileCheck %s
func.func @main(tensor<3x2xi32>) -> tensor<6xi32> {
^bb0(%arg0: tensor<3x2xi32>):
// CHECK: {
// CHECK-NEXT: version: 3,
// CHECK-NEXT: operator_codes: [ {
// CHECK-NEXT: deprecated_builtin_code: 22,
// CHECK-NEXT: version: 1,
// CHECK-NEXT: builtin_code: RESHAPE
// CHECK-NEXT: } ],
// CHECK-NEXT: subgraphs: [ {
// CHECK-NEXT: tensors: [ {
// CHECK-NEXT: shape: [ 3, 2 ],
// CHECK-NEXT: type: INT32,
// CHECK-NEXT: buffer: 1,
// CHECK-NEXT: name: "arg0",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 1 ],
// CHECK-NEXT: type: INT32,
// CHECK-NEXT: buffer: 2,
// CHECK-NEXT: name: "Const",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 6 ],
// CHECK-NEXT: type: INT32,
// CHECK-NEXT: buffer: 3,
// CHECK-NEXT: name: "tfl.reshape",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: } ],
// CHECK-NEXT: inputs: [ 0 ],
// CHECK-NEXT: outputs: [ 2 ],
// CHECK-NEXT: operators: [ {
// CHECK-NEXT: inputs: [ 0, 1 ],
// CHECK-NEXT: outputs: [ 2 ]
// CHECK-NEXT: } ]
// CHECK-NEXT: name: "main"
// CHECK-NEXT: } ],
// CHECK-NEXT: description: "MLIR Converted.",
// CHECK-NEXT: buffers: [ {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 6, 0, 0, 0 ]
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 49, 46, 53, 46, 48, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
// CHECK-NEXT: } ],
// CHECK-NEXT: metadata: [ {
// CHECK-NEXT: name: "min_runtime_version",
// CHECK-NEXT: buffer: 4
// CHECK-NEXT: } ]
// CHECK-NEXT: signature_defs: [ ]
// CHECK-NEXT: }
%0 = "tfl.pseudo_const" () {value = dense<[6]> : tensor<1xi32>} : () -> tensor<1xi32> loc("Const")
%1 = "tfl.reshape" (%arg0, %0) : (tensor<3x2xi32>, tensor<1xi32>) -> tensor<6xi32>
func.return %1 : tensor<6xi32>
}
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/runtime_version_metadata.mlir
+24
View File
@@ -0,0 +1,24 @@
// Copyright 2026 The TensorFlow Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// ==============================================================================
// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s 2>&1 | FileCheck %s
module attributes {tfl.metadata = {min_runtime_version = ""}} {
func.func @main(%arg0: tensor<3x2xi32>) -> tensor<3x2xi32>
attributes {tf.entry_function = {inputs = "input", outputs = "SameNameAsOutput"}} {
func.return %arg0 : tensor<3x2xi32>
}
}
// CHECK: Skipping runtime version metadata in the model. This will be generated by the exporter.
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/signature_def.mlir
+137
View File
@@ -0,0 +1,137 @@
// Copyright 2026 The TensorFlow Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// ==============================================================================
// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_to_string - | FileCheck %s
// CHECK: {
// CHECK-NEXT: version: 3,
// CHECK-NEXT: operator_codes: [ {
// CHECK-NEXT: deprecated_builtin_code: 9,
// CHECK-NEXT: version: 1,
// CHECK-NEXT: builtin_code: FULLY_CONNECTED
// CHECK-NEXT: } ],
// CHECK-NEXT: subgraphs: [ {
// CHECK-NEXT: tensors: [ {
// CHECK-NEXT: shape: [ 1, 384 ],
// CHECK-NEXT: buffer: 1,
// CHECK-NEXT: name: "serving_default_input2:0",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: shape_signature: [ -1, 384 ],
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 1, 384 ],
// CHECK-NEXT: buffer: 2,
// CHECK-NEXT: name: "serving_default_input1:0",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: shape_signature: [ -1, 384 ],
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 5 ],
// CHECK-NEXT: buffer: 3,
// CHECK-NEXT: name: "arith.constant",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 5, 384 ],
// CHECK-NEXT: buffer: 4,
// CHECK-NEXT: name: "arith.constant1",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 5, 384 ],
// CHECK-NEXT: buffer: 4,
// CHECK-NEXT: name: "arith.constant2",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 1, 5 ],
// CHECK-NEXT: buffer: 6,
// CHECK-NEXT: name: "StatefulPartitionedCall:0",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: shape_signature: [ -1, 5 ],
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 1, 5 ],
// CHECK-NEXT: buffer: 7,
// CHECK-NEXT: name: "StatefulPartitionedCall:1",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: shape_signature: [ -1, 5 ],
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: } ],
// CHECK-NEXT: inputs: [ 0, 1 ],
// CHECK-NEXT: outputs: [ 6, 5 ],
// CHECK-NEXT: operators: [ {
// CHECK-NEXT: inputs: [ 0, 3, 2 ],
// CHECK-NEXT: outputs: [ 5 ],
// CHECK-NEXT: builtin_options_type: FullyConnectedOptions,
// CHECK-NEXT: builtin_options: {
// CHECK-EMPTY:
// CHECK-NEXT: }
// CHECK-NEXT: }, {
// CHECK-NEXT: inputs: [ 0, 4, 2 ],
// CHECK-NEXT: outputs: [ 6 ],
// CHECK-NEXT: builtin_options_type: FullyConnectedOptions,
// CHECK-NEXT: builtin_options: {
// CHECK-EMPTY:
// CHECK-NEXT: }
// CHECK-NEXT: } ],
// CHECK-NEXT: name: "main"
// CHECK-NEXT: } ],
// CHECK-NEXT: description: "MLIR Converted.",
// CHECK: metadata: [ {
// CHECK-NEXT: name: "min_runtime_version",
// CHECK-NEXT: buffer: 8
// CHECK-NEXT: } ],
// CHECK-NEXT: signature_defs: [ {
// CHECK-NEXT: inputs: [ {
// CHECK-NEXT: name: "input1",
// CHECK-NEXT: tensor_index: 1
// CHECK-NEXT: }, {
// CHECK-NEXT: name: "input2"
// CHECK-NEXT: } ],
// CHECK-NEXT: outputs: [ {
// CHECK-NEXT: name: "end_logits",
// CHECK-NEXT: tensor_index: 5
// CHECK-NEXT: }, {
// CHECK-NEXT: name: "start_logits",
// CHECK-NEXT: tensor_index: 6
// CHECK-NEXT: } ],
// CHECK-NEXT: signature_key: "serving_default"
// CHECK-NEXT: } ]
// CHECK-NEXT:}
module attributes {tf.versions = {bad_consumers = [], min_consumer = 12 : i32, producer = 554 : i32}, tf_saved_model.semantics} {
func.func @main(%arg0: tensor<?x384xf32> {tf_saved_model.index_path = ["input2"]}, %arg1: tensor<?x384xf32> {tf_saved_model.index_path = ["input1"]}) -> (tensor<?x5xf32> {tf_saved_model.index_path = ["start_logits"]}, tensor<?x5xf32> {tf_saved_model.index_path = ["end_logits"]}) attributes {tf.entry_function = {control_outputs = "", inputs = "serving_default_input2:0,serving_default_input1:0", outputs = "StatefulPartitionedCall:1,StatefulPartitionedCall:0"}, tf_saved_model.exported_names = ["serving_default"]} {
%cst = arith.constant dense<0.000000e+00> : tensor<5xf32>
%cst_0 = arith.constant dense<1.0> : tensor<5x384xf32>
%cst_1 = arith.constant dense<1.0> : tensor<5x384xf32>
%0 = "tfl.fully_connected"(%arg0, %cst_0, %cst) {fused_activation_function = "NONE", keep_num_dims = false, weights_format = "DEFAULT"} : (tensor<?x384xf32>, tensor<5x384xf32>, tensor<5xf32>) -> tensor<?x5xf32>
%1 = "tfl.fully_connected"(%arg0, %cst_1, %cst) {fused_activation_function = "NONE", keep_num_dims = false, weights_format = "DEFAULT"} : (tensor<?x384xf32>, tensor<5x384xf32>, tensor<5xf32>) -> tensor<?x5xf32>
func.return %1, %0 : tensor<?x5xf32>, tensor<?x5xf32>
}
}
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/signature_def_output_override.mlir
+125
View File
@@ -0,0 +1,125 @@
// Copyright 2026 The TensorFlow Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// ==============================================================================
// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_to_string - | FileCheck %s
// CHECK: {
// CHECK-NEXT: version: 3,
// CHECK-NEXT: operator_codes: [ {
// CHECK-NEXT: deprecated_builtin_code: 9,
// CHECK-NEXT: version: 1,
// CHECK-NEXT: builtin_code: FULLY_CONNECTED
// CHECK-NEXT: } ],
// CHECK-NEXT: subgraphs: [ {
// CHECK-NEXT: tensors: [ {
// CHECK-NEXT: shape: [ 1, 3 ],
// CHECK-NEXT: buffer: 1,
// CHECK-NEXT: name: "serving_default_input2:0",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: shape_signature: [ -1, 3 ],
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 1, 3 ],
// CHECK-NEXT: buffer: 2,
// CHECK-NEXT: name: "serving_default_input1:0",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: shape_signature: [ -1, 3 ],
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 5 ],
// CHECK-NEXT: buffer: 3,
// CHECK-NEXT: name: "arith.constant",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 5, 3 ],
// CHECK-NEXT: buffer: 4,
// CHECK-NEXT: name: "arith.constant1",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 1, 5 ],
// CHECK-NEXT: buffer: 5,
// CHECK-NEXT: name: "StatefulPartitionedCall:1",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: shape_signature: [ -1, 5 ],
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: } ],
// CHECK-NEXT: inputs: [ 0, 1 ],
// CHECK-NEXT: outputs: [ 4, 4 ],
// CHECK-NEXT: operators: [ {
// CHECK-NEXT: inputs: [ 0, 3, 2 ],
// CHECK-NEXT: outputs: [ 4 ],
// CHECK-NEXT: builtin_options_type: FullyConnectedOptions,
// CHECK-NEXT: builtin_options: {
// CHECK-EMPTY:
// CHECK-NEXT: }
// CHECK-NEXT: } ],
// CHECK-NEXT: name: "main"
// CHECK-NEXT: } ],
// CHECK-NEXT: description: "MLIR Converted.",
// CHECK-NEXT: buffers: [ {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 0, 0, 128, 63, 0, 0, 128, 63, 0, 0, 128, 63, 0, 0, 128, 63, 0, 0, 128, 63, 0, 0, 128, 63, 0, 0, 128, 63, 0, 0, 128, 63, 0, 0, 128, 63, 0, 0, 128, 63, 0, 0, 128, 63, 0, 0, 128, 63, 0, 0, 128, 63, 0, 0, 128, 63, 0, 0, 128, 63 ]
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 49, 46, 53, 46, 48, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
// CHECK-NEXT: } ],
// CHECK-NEXT: metadata: [ {
// CHECK-NEXT: name: "min_runtime_version",
// CHECK-NEXT: buffer: 6
// CHECK-NEXT: } ],
// CHECK-NEXT: signature_defs: [ {
// CHECK-NEXT: inputs: [ {
// CHECK-NEXT: name: "input1",
// CHECK-NEXT: tensor_index: 1
// CHECK-NEXT: }, {
// CHECK-NEXT: name: "input2"
// CHECK-NEXT: } ],
// CHECK-NEXT: outputs: [ {
// CHECK-NEXT: name: "end_logits",
// CHECK-NEXT: tensor_index: 4
// CHECK-NEXT: }, {
// CHECK-NEXT: name: "start_logits",
// CHECK-NEXT: tensor_index: 4
// CHECK-NEXT: } ],
// CHECK-NEXT: signature_key: "serving_default"
// CHECK-NEXT: } ]
// CHECK-NEXT:}
module attributes {tf.versions = {bad_consumers = [], min_consumer = 12 : i32, producer = 554 : i32}, tf_saved_model.semantics} {
func.func @main(%arg0: tensor<?x3xf32> {tf_saved_model.index_path = ["input2"]}, %arg1: tensor<?x3xf32> {tf_saved_model.index_path = ["input1"]}) -> (tensor<?x5xf32> {tf_saved_model.index_path = ["start_logits"]}, tensor<?x5xf32> {tf_saved_model.index_path = ["end_logits"]}) attributes {tf.entry_function = {control_outputs = "", inputs = "serving_default_input2:0,serving_default_input1:0", outputs = "StatefulPartitionedCall:1,StatefulPartitionedCall:0"}, tf_saved_model.exported_names = ["serving_default"]} {
%cst = arith.constant dense<0.000000e+00> : tensor<5xf32>
%cst_0 = arith.constant dense<1.0> : tensor<5x3xf32>
%0 = "tfl.fully_connected"(%arg0, %cst_0, %cst) {fused_activation_function = "NONE", keep_num_dims = false, weights_format = "DEFAULT"} : (tensor<?x3xf32>, tensor<5x3xf32>, tensor<5xf32>) -> tensor<?x5xf32>
func.return %0, %0 : tensor<?x5xf32>, tensor<?x5xf32>
}
}
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/signature_def_with_multiple_entry_points.mlir
+186
View File
@@ -0,0 +1,186 @@
// Copyright 2026 The TensorFlow Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// ==============================================================================
// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_to_string - | FileCheck %s
// CHECK: {
// CHECK-NEXT: version: 3,
// CHECK-NEXT: operator_codes: [ {
// CHECK-NEXT: version: 1
// CHECK-NEXT: }, {
// CHECK-NEXT: deprecated_builtin_code: 41,
// CHECK-NEXT: version: 1,
// CHECK-NEXT: builtin_code: SUB
// CHECK-NEXT: } ],
// CHECK-NEXT: subgraphs: [ {
// CHECK-NEXT: tensors: [ {
// CHECK-NEXT: shape: [ 1 ],
// CHECK-NEXT: buffer: 1,
// CHECK-NEXT: name: "input1:0",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: shape_signature: [ -1 ],
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 1 ],
// CHECK-NEXT: buffer: 2,
// CHECK-NEXT: name: "input2:0",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: shape_signature: [ -1 ],
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 1 ],
// CHECK-NEXT: buffer: 3,
// CHECK-NEXT: name: "tfl.add",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: shape_signature: [ -1 ],
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 1 ],
// CHECK-NEXT: buffer: 4,
// CHECK-NEXT: name: "result:0",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: shape_signature: [ -1 ],
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: } ],
// CHECK-NEXT: inputs: [ 0, 1 ],
// CHECK-NEXT: outputs: [ 3 ],
// CHECK-NEXT: operators: [ {
// CHECK-NEXT: inputs: [ 0, 1 ],
// CHECK-NEXT: outputs: [ 2 ],
// CHECK-NEXT: builtin_options_type: AddOptions,
// CHECK-NEXT: builtin_options: {
// CHECK-EMPTY:
// CHECK-NEXT: }
// CHECK-NEXT: }, {
// CHECK-NEXT: inputs: [ 2, 2 ],
// CHECK-NEXT: outputs: [ 3 ],
// CHECK-NEXT: builtin_options_type: AddOptions,
// CHECK-NEXT: builtin_options: {
// CHECK-EMPTY:
// CHECK-NEXT: }
// CHECK-NEXT: } ],
// CHECK-NEXT: name: "add"
// CHECK-NEXT: }, {
// CHECK-NEXT: tensors: [ {
// CHECK-NEXT: shape: [ 1 ],
// CHECK-NEXT: buffer: 5,
// CHECK-NEXT: name: "input2:0",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: shape_signature: [ -1 ],
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 1 ],
// CHECK-NEXT: buffer: 6,
// CHECK-NEXT: name: "input1:0",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: shape_signature: [ -1 ],
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 1 ],
// CHECK-NEXT: buffer: 7,
// CHECK-NEXT: name: "result:0",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: shape_signature: [ -1 ],
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: } ],
// CHECK-NEXT: inputs: [ 0, 1 ],
// CHECK-NEXT: outputs: [ 2 ],
// CHECK-NEXT: operators: [ {
// CHECK-NEXT: opcode_index: 1,
// CHECK-NEXT: inputs: [ 0, 1 ],
// CHECK-NEXT: outputs: [ 2 ],
// CHECK-NEXT: builtin_options_type: SubOptions,
// CHECK-NEXT: builtin_options: {
// CHECK-EMPTY:
// CHECK-NEXT: }
// CHECK-NEXT: } ],
// CHECK-NEXT: name: "sub"
// CHECK-NEXT: } ],
// CHECK-NEXT: description: "MLIR Converted.",
// CHECK-NEXT: buffers: [ {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 49, 46, 54, 46, 48, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
// CHECK-NEXT: } ],
// CHECK-NEXT: metadata: [ {
// CHECK-NEXT: name: "min_runtime_version",
// CHECK-NEXT: buffer: 8
// CHECK-NEXT: } ],
// CHECK-NEXT: signature_defs: [ {
// CHECK-NEXT: inputs: [ {
// CHECK-NEXT: name: "input1"
// CHECK-NEXT: }, {
// CHECK-NEXT: name: "input2",
// CHECK-NEXT: tensor_index: 1
// CHECK-NEXT: } ],
// CHECK-NEXT: outputs: [ {
// CHECK-NEXT: name: "result",
// CHECK-NEXT: tensor_index: 3
// CHECK-NEXT: } ],
// CHECK-NEXT: signature_key: "add"
// CHECK-NEXT: }, {
// CHECK-NEXT: inputs: [ {
// CHECK-NEXT: name: "input1",
// CHECK-NEXT: tensor_index: 1
// CHECK-NEXT: }, {
// CHECK-NEXT: name: "input2"
// CHECK-NEXT: } ],
// CHECK-NEXT: outputs: [ {
// CHECK-NEXT: name: "result",
// CHECK-NEXT: tensor_index: 2
// CHECK-NEXT: } ],
// CHECK-NEXT: signature_key: "sub",
// CHECK-NEXT: subgraph_index: 1
// CHECK-NEXT: } ]
// CHECK-NEXT: }
module attributes {tf.versions = {bad_consumers = [], min_consumer = 12 : i32, producer = 554 : i32}, tf_saved_model.semantics} {
func.func @add(%arg0: tensor<?xf32> {tf_saved_model.index_path = ["input1"]}, %arg1: tensor<?xf32> {tf_saved_model.index_path = ["input2"]}) -> (tensor<?xf32> {tf_saved_model.index_path = ["result"]}) attributes {tf.entry_function = {control_outputs = "", inputs = "input1:0,input2:0", outputs = "result:0"}, tf_saved_model.exported_names = ["add"]} {
%0 = tfl.add %arg0, %arg1 {fused_activation_function = "NONE"} : tensor<?xf32>
%1 = tfl.add %0, %0 {fused_activation_function = "NONE"} : tensor<?xf32>
func.return %1 : tensor<?xf32>
}
func.func @sub(%arg0: tensor<?xf32> {tf_saved_model.index_path = ["input2"]}, %arg1: tensor<?xf32> {tf_saved_model.index_path = ["input1"]}) -> (tensor<?xf32> {tf_saved_model.index_path = ["result"]}) attributes {tf.entry_function = {control_outputs = "", inputs = "input2:0,input1:0", outputs = "result:0"}, tf_saved_model.exported_names = ["sub"]} {
%0 = tfl.sub %arg0, %arg1 {fused_activation_function = "NONE"} : tensor<?xf32>
func.return %0 : tensor<?xf32>
}
}
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/signature_def_with_no_inputs.mlir
+61
View File
@@ -0,0 +1,61 @@
// Copyright 2026 The TensorFlow Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// ==============================================================================
// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_to_string - | FileCheck %s
// CHECK: {
// CHECK-NEXT: version: 3,
// CHECK-NEXT: operator_codes: [ ],
// CHECK-NEXT: subgraphs: [ {
// CHECK-NEXT: tensors: [ {
// CHECK-NEXT: shape: [ 5 ],
// CHECK-NEXT: buffer: 1,
// CHECK-NEXT: name: "StatefulPartitionedCall:1",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: } ],
// CHECK-NEXT: inputs: [ ],
// CHECK-NEXT: outputs: [ 0 ],
// CHECK-NEXT: operators: [ ],
// CHECK-NEXT: name: "main"
// CHECK-NEXT: } ],
// CHECK-NEXT: description: "MLIR Converted.",
// CHECK-NEXT: buffers: [ {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
// CHECK-NEXT: } ],
// CHECK-NEXT: metadata: [ {
// CHECK-NEXT: name: "min_runtime_version",
// CHECK-NEXT: buffer: 2
// CHECK-NEXT: } ],
// CHECK-NEXT: signature_defs: [ {
// CHECK-NEXT: inputs: [ ],
// CHECK-NEXT: outputs: [ {
// CHECK-NEXT: name: "start_logits"
// CHECK-NEXT: } ],
// CHECK-NEXT: signature_key: "serving_default"
// CHECK-NEXT: } ]
// CHECK-NEXT: }
module attributes {tf.versions = {bad_consumers = [], min_consumer = 12 : i32, producer = 554 : i32}, tf_saved_model.semantics} {
func.func @main() -> (tensor<5xf32> {tf_saved_model.index_path = ["start_logits"]}) attributes {tf.entry_function = {control_outputs = "", inputs = "", outputs = "StatefulPartitionedCall:1"}, tf_saved_model.exported_names = ["serving_default"]} {
%cst = arith.constant dense<0.000000e+00> : tensor<5xf32>
func.return %cst : tensor<5xf32>
}
}
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/simple.mlir
+135
View File
@@ -0,0 +1,135 @@
// Copyright 2026 The TensorFlow Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// ==============================================================================
// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_to_string - | FileCheck %s
// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - -strip-debug-info | flatbuffer_to_string - | FileCheck %s --check-prefix=STRIP
func.func @main(tensor<3x2xi32>) -> tensor<3x2xi32>
attributes {tf.entry_function = {inputs = "input", outputs = "SameNameAsOutput"}} {
^bb0(%arg0: tensor<3x2xi32>):
// CHECK: {
// CHECK-NEXT: version: 3,
// CHECK-NEXT: operator_codes: [ {
// CHECK-NEXT: deprecated_builtin_code: 41,
// CHECK-NEXT: version: 1,
// CHECK-NEXT: builtin_code: SUB
// CHECK-NEXT: }, {
// CHECK-NEXT: version: 1
// CHECK-NEXT: } ],
// CHECK-NEXT: subgraphs: [ {
// CHECK-NEXT: tensors: [ {
// CHECK-NEXT: shape: [ 3, 2 ],
// CHECK-NEXT: type: INT32,
// CHECK-NEXT: buffer: 1,
// CHECK-NEXT: name: "input",
// STRIP: buffer: 1,
// STRIP-NEXT: name: "input",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 3, 2 ],
// CHECK-NEXT: type: INT32,
// CHECK-NEXT: buffer: 2,
// CHECK-NEXT: name: "Const",
// STRIP: buffer: 2,
// STRIP-NEXT: name: "0",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 3, 2 ],
// CHECK-NEXT: type: INT32,
// CHECK-NEXT: buffer: 3,
// CHECK-NEXT: name: "sub",
// STRIP: buffer: 3,
// STRIP-NEXT: name: "1",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ ],
// CHECK-NEXT: type: INT32,
// CHECK-NEXT: buffer: 4,
// CHECK-NEXT: name: "SameNameAsOutput1",
// STRIP: buffer: 4,
// STRIP-NEXT: name: "2",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 3, 2 ],
// CHECK-NEXT: type: INT32,
// CHECK-NEXT: buffer: 5,
// CHECK-NEXT: name: "SameNameAsOutput",
// STRIP: buffer: 5,
// STRIP-NEXT: name: "SameNameAsOutput",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: } ],
// CHECK-NEXT: inputs: [ 0 ],
// CHECK-NEXT: outputs: [ 4 ],
// CHECK-NEXT: operators: [ {
// CHECK-NEXT: inputs: [ 0, 1 ],
// CHECK-NEXT: outputs: [ 2 ],
// CHECK-NEXT: builtin_options_type: SubOptions,
// CHECK-NEXT: builtin_options: {
// CHECK-NEXT: fused_activation_function: RELU6
// CHECK-NEXT: }
// CHECK-NEXT: }, {
// CHECK-NEXT: opcode_index: 1,
// CHECK-NEXT: inputs: [ 3, 2 ],
// CHECK-NEXT: outputs: [ 4 ],
// CHECK-NEXT: builtin_options_type: AddOptions,
// CHECK-NEXT: builtin_options: {
// CHECK-EMPTY:
// CHECK-NEXT: }
// CHECK-NEXT: } ]
// CHECK-NEXT: name: "main"
// CHECK-NEXT: } ],
// CHECK-NEXT: description: "MLIR Converted.",
// CHECK-NEXT: buffers: [ {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 1, 0, 0, 0, 2, 0, 0, 0, 3, 0, 0, 0, 4, 0, 0, 0, 5, 0, 0, 0, 6, 0, 0, 0 ]
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 10, 0, 0, 0 ]
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 49, 46, 54, 46, 48, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
// CHECK-NEXT: } ],
// CHECK-NEXT: metadata: [ {
// CHECK-NEXT: name: "min_runtime_version",
// CHECK-NEXT: buffer: 6
// CHECK-NEXT: } ]
// CHECK-NEXT: signature_defs: [ ]
// CHECK-NEXT: }
%0 = "tfl.pseudo_const" () {value = dense<[[1, 2], [3, 4], [5, 6]]> : tensor<3x2xi32>} : () -> tensor<3x2xi32> loc("Const")
%1 = "tfl.sub" (%arg0, %0) {fused_activation_function = "RELU6"} : (tensor<3x2xi32>, tensor<3x2xi32>) -> tensor<3x2xi32> loc("sub")
%2 = "arith.constant" () {value = dense<10> : tensor<i32>} : () -> tensor<i32> loc("SameNameAsOutput")
%3 = "tfl.add" (%2, %1) {fused_activation_function = "NONE"} : (tensor<i32>, tensor<3x2xi32>) -> tensor<3x2xi32> loc("add")
func.return %3 : tensor<3x2xi32>
}
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/simple_with_connected_control_nodes.mlir
+140
View File
@@ -0,0 +1,140 @@
// Copyright 2026 The TensorFlow Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// ==============================================================================
// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_to_string - | FileCheck %s
// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - -strip-debug-info | flatbuffer_to_string - | FileCheck %s --check-prefix=STRIP
func.func @main(tensor<3x2xi32>) -> tensor<3x2xi32>
attributes {tf.entry_function = {inputs = "input", outputs = "SameNameAsOutput"}} {
^bb0(%arg0: tensor<3x2xi32>):
// CHECK: {
// CHECK-NEXT: version: 3,
// CHECK-NEXT: operator_codes: [ {
// CHECK-NEXT: deprecated_builtin_code: 41,
// CHECK-NEXT: version: 1,
// CHECK-NEXT: builtin_code: SUB
// CHECK-NEXT: }, {
// CHECK-NEXT: version: 1
// CHECK-NEXT: } ],
// CHECK-NEXT: subgraphs: [ {
// CHECK-NEXT: tensors: [ {
// CHECK-NEXT: shape: [ 3, 2 ],
// CHECK-NEXT: type: INT32,
// CHECK-NEXT: buffer: 1,
// CHECK-NEXT: name: "input",
// STRIP: buffer: 1,
// STRIP-NEXT: name: "input",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 3, 2 ],
// CHECK-NEXT: type: INT32,
// CHECK-NEXT: buffer: 2,
// CHECK-NEXT: name: "Const",
// STRIP: buffer: 2,
// STRIP-NEXT: name: "0",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 3, 2 ],
// CHECK-NEXT: type: INT32,
// CHECK-NEXT: buffer: 3,
// CHECK-NEXT: name: "sub",
// STRIP: buffer: 3,
// STRIP-NEXT: name: "1",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ ],
// CHECK-NEXT: type: INT32,
// CHECK-NEXT: buffer: 4,
// CHECK-NEXT: name: "SameNameAsOutput1",
// STRIP: buffer: 4,
// STRIP-NEXT: name: "2",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 3, 2 ],
// CHECK-NEXT: type: INT32,
// CHECK-NEXT: buffer: 5,
// CHECK-NEXT: name: "SameNameAsOutput",
// STRIP: buffer: 5,
// STRIP-NEXT: name: "SameNameAsOutput",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: } ],
// CHECK-NEXT: inputs: [ 0 ],
// CHECK-NEXT: outputs: [ 4 ],
// CHECK-NEXT: operators: [ {
// CHECK-NEXT: inputs: [ 0, 1 ],
// CHECK-NEXT: outputs: [ 2 ],
// CHECK-NEXT: builtin_options_type: SubOptions,
// CHECK-NEXT: builtin_options: {
// CHECK-NEXT: fused_activation_function: RELU6
// CHECK-NEXT: }
// CHECK-NEXT: }, {
// CHECK-NEXT: opcode_index: 1,
// CHECK-NEXT: inputs: [ 3, 2 ],
// CHECK-NEXT: outputs: [ 4 ],
// CHECK-NEXT: builtin_options_type: AddOptions,
// CHECK-NEXT: builtin_options: {
// CHECK-EMPTY:
// CHECK-NEXT: }
// CHECK-NEXT: } ]
// CHECK-NEXT: name: "main"
// CHECK-NEXT: } ],
// CHECK-NEXT: description: "MLIR Converted.",
// CHECK-NEXT: buffers: [ {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 1, 0, 0, 0, 2, 0, 0, 0, 3, 0, 0, 0, 4, 0, 0, 0, 5, 0, 0, 0, 6, 0, 0, 0 ]
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 10, 0, 0, 0 ]
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 49, 46, 54, 46, 48, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 1, 1, 1, 0, 2 ]
// CHECK-NEXT: } ],
// CHECK-NEXT: metadata: [ {
// CHECK-NEXT: name: "min_runtime_version",
// CHECK-NEXT: buffer: 6
// CHECK-NEXT: }, {
// CHECK-NEXT: name: "model_control_dependencies",
// CHECK-NEXT: buffer: 7
// CHECK-NEXT: } ],
// CHECK-NEXT: signature_defs: [ ]
// CHECK-NEXT: }
%0 = "tfl.pseudo_const" () {value = dense<[[1, 2], [3, 4], [5, 6]]> : tensor<3x2xi32>} : () -> tensor<3x2xi32> loc("Const")
%1,%control_1 = tfl.control_node controls "tfl.sub" (%arg0, %0) {fused_activation_function = "RELU6"} : (tensor<3x2xi32>, tensor<3x2xi32>) -> tensor<3x2xi32> loc("sub")
%2 = "arith.constant" () {value = dense<10> : tensor<i32>} : () -> tensor<i32> loc("SameNameAsOutput")
%3,%control_2 = tfl.control_node(%control_1) controls "tfl.add" (%2, %1) {fused_activation_function = "NONE"} : (tensor<i32>, tensor<3x2xi32>) -> tensor<3x2xi32> loc("add")
func.return %3 : tensor<3x2xi32>
}
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/simple_with_unconnected_control_nodes.mlir
+135
View File
@@ -0,0 +1,135 @@
// Copyright 2026 The TensorFlow Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// ==============================================================================
// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_to_string - | FileCheck %s
// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - -strip-debug-info | flatbuffer_to_string - | FileCheck %s --check-prefix=STRIP
func.func @main(tensor<3x2xi32>) -> tensor<3x2xi32>
attributes {tf.entry_function = {inputs = "input", outputs = "SameNameAsOutput"}} {
^bb0(%arg0: tensor<3x2xi32>):
// CHECK: {
// CHECK-NEXT: version: 3,
// CHECK-NEXT: operator_codes: [ {
// CHECK-NEXT: deprecated_builtin_code: 41,
// CHECK-NEXT: version: 1,
// CHECK-NEXT: builtin_code: SUB
// CHECK-NEXT: }, {
// CHECK-NEXT: version: 1
// CHECK-NEXT: } ],
// CHECK-NEXT: subgraphs: [ {
// CHECK-NEXT: tensors: [ {
// CHECK-NEXT: shape: [ 3, 2 ],
// CHECK-NEXT: type: INT32,
// CHECK-NEXT: buffer: 1,
// CHECK-NEXT: name: "input",
// STRIP: buffer: 1,
// STRIP-NEXT: name: "input",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 3, 2 ],
// CHECK-NEXT: type: INT32,
// CHECK-NEXT: buffer: 2,
// CHECK-NEXT: name: "Const",
// STRIP: buffer: 2,
// STRIP-NEXT: name: "0",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 3, 2 ],
// CHECK-NEXT: type: INT32,
// CHECK-NEXT: buffer: 3,
// CHECK-NEXT: name: "sub",
// STRIP: buffer: 3,
// STRIP-NEXT: name: "1",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ ],
// CHECK-NEXT: type: INT32,
// CHECK-NEXT: buffer: 4,
// CHECK-NEXT: name: "SameNameAsOutput1",
// STRIP: buffer: 4,
// STRIP-NEXT: name: "2",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 3, 2 ],
// CHECK-NEXT: type: INT32,
// CHECK-NEXT: buffer: 5,
// CHECK-NEXT: name: "SameNameAsOutput",
// STRIP: buffer: 5,
// STRIP-NEXT: name: "SameNameAsOutput",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: } ],
// CHECK-NEXT: inputs: [ 0 ],
// CHECK-NEXT: outputs: [ 4 ],
// CHECK-NEXT: operators: [ {
// CHECK-NEXT: inputs: [ 0, 1 ],
// CHECK-NEXT: outputs: [ 2 ],
// CHECK-NEXT: builtin_options_type: SubOptions,
// CHECK-NEXT: builtin_options: {
// CHECK-NEXT: fused_activation_function: RELU6
// CHECK-NEXT: }
// CHECK-NEXT: }, {
// CHECK-NEXT: opcode_index: 1,
// CHECK-NEXT: inputs: [ 3, 2 ],
// CHECK-NEXT: outputs: [ 4 ],
// CHECK-NEXT: builtin_options_type: AddOptions,
// CHECK-NEXT: builtin_options: {
// CHECK-EMPTY:
// CHECK-NEXT: }
// CHECK-NEXT: } ]
// CHECK-NEXT: name: "main"
// CHECK-NEXT: } ],
// CHECK-NEXT: description: "MLIR Converted.",
// CHECK-NEXT: buffers: [ {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 1, 0, 0, 0, 2, 0, 0, 0, 3, 0, 0, 0, 4, 0, 0, 0, 5, 0, 0, 0, 6, 0, 0, 0 ]
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 10, 0, 0, 0 ]
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 49, 46, 54, 46, 48, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
// CHECK-NEXT: } ],
// CHECK-NEXT: metadata: [ {
// CHECK-NEXT: name: "min_runtime_version",
// CHECK-NEXT: buffer: 6
// CHECK-NEXT: } ],
// CHECK-NEXT: signature_defs: [ ]
// CHECK-NEXT: }
%0 = "tfl.pseudo_const" () {value = dense<[[1, 2], [3, 4], [5, 6]]> : tensor<3x2xi32>} : () -> tensor<3x2xi32> loc("Const")
%1,%control_1 = tfl.control_node controls "tfl.sub" (%arg0, %0) {fused_activation_function = "RELU6"} : (tensor<3x2xi32>, tensor<3x2xi32>) -> tensor<3x2xi32> loc("sub")
%2 = "arith.constant" () {value = dense<10> : tensor<i32>} : () -> tensor<i32> loc("SameNameAsOutput")
%3,%control_2 = tfl.control_node controls "tfl.add" (%2, %1) {fused_activation_function = "NONE"} : (tensor<i32>, tensor<3x2xi32>) -> tensor<3x2xi32> loc("add")
func.return %3 : tensor<3x2xi32>
}
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/svdf.mlir
+118
View File
@@ -0,0 +1,118 @@
// Copyright 2026 The TensorFlow Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// ==============================================================================
// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_to_string - | FileCheck %s
func.func @main(tensor<4 x f32>, tensor<4 x f32>, tensor<4 x f32>, tensor<4 x f32>) -> tensor<4 x f32> {
// CHECK: {
// CHECK-NEXT: version: 3,
// CHECK-NEXT: operator_codes: [ {
// CHECK-NEXT: deprecated_builtin_code: 27,
// CHECK-NEXT: version: 1,
// CHECK-NEXT: builtin_code: SVDF
// CHECK-NEXT: } ],
// CHECK-NEXT: subgraphs: [ {
// CHECK-NEXT: tensors: [ {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 1,
// CHECK-NEXT: name: "arg0",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 2,
// CHECK-NEXT: name: "arg1",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 3,
// CHECK-NEXT: name: "arg2",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 4,
// CHECK-NEXT: name: "arg3",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: name: "Const",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: is_variable: true,
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 6,
// CHECK-NEXT: name: "tfl.svdf",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: } ],
// CHECK-NEXT: inputs: [ 0, 1, 2, 3 ],
// CHECK-NEXT: outputs: [ 5 ],
// CHECK-NEXT: operators: [ {
// CHECK-NEXT: inputs: [ 0, 1, 2, 3, 4 ],
// CHECK-NEXT: outputs: [ 5 ],
// CHECK-NEXT: builtin_options_type: SVDFOptions,
// CHECK-NEXT: builtin_options: {
// CHECK-NEXT: rank: 2,
// CHECK-NEXT: fused_activation_function: RELU
// CHECK-NEXT: }
// CHECK-NEXT: } ],
// CHECK-NEXT: name: "main"
// CHECK-NEXT: } ],
// CHECK-NEXT: description: "MLIR Converted.",
// CHECK-NEXT: buffers: [ {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 49, 46, 53, 46, 48, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
// CHECK-NEXT: } ],
// CHECK-NEXT: metadata: [ {
// CHECK-NEXT: name: "min_runtime_version",
// CHECK-NEXT: buffer: 7
// CHECK-NEXT: } ]
// CHECK-NEXT: signature_defs: [ ]
// CHECK-NEXT: }
// CHECK-EMPTY:
^bb0(%arg0: tensor<4 x f32>, %arg1: tensor<4 x f32>, %arg2: tensor<4 x f32>, %arg3: tensor<4 x f32>):
%0 = "tfl.pseudo_const" () {value = dense<0.0> : tensor<4xf32>} : () -> tensor<4xf32> loc("Const")
%1 = "tfl.svdf"(%arg0, %arg1, %arg2, %arg3, %0) {fused_activation_function = "RELU", rank = 2 : i32} : (tensor<4xf32>, tensor<4xf32>, tensor<4xf32>, tensor<4xf32>, tensor<4xf32>) -> tensor<4xf32>
func.return %1 : tensor<4xf32>
}
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/svdf_v2.mlir
+119
View File
@@ -0,0 +1,119 @@
// Copyright 2026 The TensorFlow Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// ==============================================================================
// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_to_string - | FileCheck %s
func.func @main(tensor<4 x f32>, tensor<4 x i8>, tensor<4 x f32>, tensor<4 x f32>) -> tensor<4 x f32> {
// CHECK: {
// CHECK-NEXT: version: 3,
// CHECK-NEXT: operator_codes: [ {
// CHECK-NEXT: deprecated_builtin_code: 27,
// CHECK-NEXT: version: 2,
// CHECK-NEXT: builtin_code: SVDF
// CHECK-NEXT: } ],
// CHECK-NEXT: subgraphs: [ {
// CHECK-NEXT: tensors: [ {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 1,
// CHECK-NEXT: name: "arg0",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: type: INT8,
// CHECK-NEXT: buffer: 2,
// CHECK-NEXT: name: "arg1",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 3,
// CHECK-NEXT: name: "arg2",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 4,
// CHECK-NEXT: name: "arg3",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: name: "Const",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: is_variable: true,
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 6,
// CHECK-NEXT: name: "tfl.svdf",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: } ],
// CHECK-NEXT: inputs: [ 0, 1, 2, 3 ],
// CHECK-NEXT: outputs: [ 5 ],
// CHECK-NEXT: operators: [ {
// CHECK-NEXT: inputs: [ 0, 1, 2, 3, 4 ],
// CHECK-NEXT: outputs: [ 5 ],
// CHECK-NEXT: builtin_options_type: SVDFOptions,
// CHECK-NEXT: builtin_options: {
// CHECK-NEXT: rank: 2,
// CHECK-NEXT: fused_activation_function: RELU
// CHECK-NEXT: }
// CHECK-NEXT: } ],
// CHECK-NEXT: name: "main"
// CHECK-NEXT: } ],
// CHECK-NEXT: description: "MLIR Converted.",
// CHECK-NEXT: buffers: [ {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 49, 46, 49, 52, 46, 48, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
// CHECK-NEXT: } ],
// CHECK-NEXT: metadata: [ {
// CHECK-NEXT: name: "min_runtime_version",
// CHECK-NEXT: buffer: 7
// CHECK-NEXT: } ]
// CHECK-NEXT: signature_defs: [ ]
// CHECK-NEXT: }
// CHECK-EMPTY:
^bb0(%arg0: tensor<4 x f32>, %arg1: tensor<4 x i8>, %arg2: tensor<4 x f32>, %arg3: tensor<4 x f32>):
%0 = "tfl.pseudo_const" () {value = dense<0.0> : tensor<4xf32>} : () -> tensor<4xf32> loc("Const")
%1 = "tfl.svdf"(%arg0, %arg1, %arg2, %arg3, %0) {fused_activation_function = "RELU", rank = 2 : i32} : (tensor<4xf32>, tensor<4xi8>, tensor<4xf32>, tensor<4xf32>, tensor<4xf32>) -> tensor<4xf32>
func.return %1 : tensor<4xf32>
}
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/tf_entry_function.mlir
+72
View File
@@ -0,0 +1,72 @@
// Copyright 2026 The TensorFlow Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// ==============================================================================
// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_to_string - | FileCheck %s
module {
func.func @serving_default(%arg0: tensor<3x2xf32>) -> tensor<3x2xf32> attributes {tf.entry_function = {inputs = "serving_default_x", outputs = "outputs"}} {
// CHECK: {
// CHECK-LABEL: version: 3,
// CHECK-LABEL: operator_codes: [ {
// CHECK: version: 1
// CHECK: } ],
// CHECK-LABEL: subgraphs: [ {
// CHECK: tensors: [ {
// CHECK: shape: [ 3, 2 ],
// CHECK: buffer: 1,
// CHECK: name: "serving_default_x",
// CHECK: quantization: {
// CHECK: }
// CHECK: }, {
// CHECK: shape: [ 3, 2 ],
// CHECK: buffer: 2,
// CHECK: name: "tfl.pseudo_const",
// CHECK: quantization: {
// CHECK: },
// CHECK: has_rank: true
// CHECK: }, {
// CHECK: shape: [ 3, 2 ],
// CHECK: buffer: 3,
// CHECK: name: "outputs",
// CHECK: quantization: {
// CHECK: },
// CHECK: has_rank: true
// CHECK: } ],
// CHECK: inputs: [ 0 ],
// CHECK: outputs: [ 2 ],
// CHECK: operators: [ {
// CHECK: inputs: [ 1, 0 ],
// CHECK: outputs: [ 2 ],
// CHECK: builtin_options_type: AddOptions,
// CHECK: builtin_options: {
// CHECK: }
// CHECK: } ],
// CHECK: name: "main"
// CHECK: } ],
// CHECK-LABEL: description: "MLIR Converted.",
// CHECK-LABEL: buffers: [ {
// CHECK: }, {
// CHECK: }, {
// CHECK: data: [ 0, 0, 128, 63, 0, 0, 0, 64, 0, 0, 64, 64, 0, 0, 128, 64, 0, 0, 160, 64, 0, 0, 192, 64 ]
// CHECK: }, {
// CHECK: } ]
// CHECK: }
%0 = "tfl.pseudo_const" () {value = dense<[[1.0, 2.0], [3.0, 4.0], [5.0, 6.0]]> : tensor<3x2xf32>} : () -> tensor<3x2xf32>
%1 = "tfl.add" (%0, %arg0) {fused_activation_function = "NONE"} : (tensor<3x2xf32>, tensor<3x2xf32>) -> tensor<3x2xf32>
func.return %1 : tensor<3x2xf32>
}
}
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/tfl_while_op.mlir
+250
View File
@@ -0,0 +1,250 @@
// Copyright 2026 The TensorFlow Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// ==============================================================================
// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_to_string - | FileCheck %s
// CHECK: {
// CHECK-NEXT: version: 3,
// CHECK-NEXT: operator_codes: [ {
// CHECK-NEXT: deprecated_builtin_code: 119,
// CHECK-NEXT: version: 1,
// CHECK-NEXT: builtin_code: WHILE
// CHECK-NEXT: }, {
// CHECK-NEXT: deprecated_builtin_code: 61,
// CHECK-NEXT: version: 1,
// CHECK-NEXT: builtin_code: GREATER
// CHECK-NEXT: }, {
// CHECK-NEXT: deprecated_builtin_code: 41,
// CHECK-NEXT: version: 1,
// CHECK-NEXT: builtin_code: SUB
// CHECK-NEXT: }, {
// CHECK-NEXT: version: 1
// CHECK-NEXT: } ],
// CHECK-NEXT: subgraphs: [ {
// CHECK-NEXT: tensors: [ {
// CHECK-NEXT: shape: [ ],
// CHECK-NEXT: type: INT32,
// CHECK-NEXT: buffer: 1,
// CHECK-NEXT: name: "arg0",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 1 ],
// CHECK-NEXT: buffer: 2,
// CHECK-NEXT: name: "arg1",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ ],
// CHECK-NEXT: type: INT32,
// CHECK-NEXT: buffer: 3,
// CHECK-NEXT: name: "WhileOp",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 1 ],
// CHECK-NEXT: buffer: 4,
// CHECK-NEXT: name: "WhileOp1",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: } ],
// CHECK-NEXT: inputs: [ 0, 1 ],
// CHECK-NEXT: outputs: [ 3 ],
// CHECK-NEXT: operators: [ {
// CHECK-NEXT: inputs: [ 0, 1 ],
// CHECK-NEXT: outputs: [ 2, 3 ],
// CHECK-NEXT: builtin_options_type: WhileOptions,
// CHECK-NEXT: builtin_options: {
// CHECK-NEXT: cond_subgraph_index: 1,
// CHECK-NEXT: body_subgraph_index: 2
// CHECK-NEXT: }
// CHECK-NEXT: } ],
// CHECK-NEXT: name: "main"
// CHECK-NEXT: }, {
// CHECK-NEXT: tensors: [ {
// CHECK-NEXT: shape: [ ],
// CHECK-NEXT: type: INT32,
// CHECK-NEXT: buffer: 5,
// CHECK-NEXT: name: "WhileOp_cond_arg0",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: }
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ ],
// CHECK-NEXT: buffer: 6,
// CHECK-NEXT: name: "WhileOp_cond_arg1",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: }
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ ],
// CHECK-NEXT: type: INT32,
// CHECK-NEXT: buffer: 7,
// CHECK-NEXT: name: "Const",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ ],
// CHECK-NEXT: type: BOOL,
// CHECK-NEXT: buffer: 8,
// CHECK-NEXT: name: "tfl.greater",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: } ],
// CHECK-NEXT: inputs: [ 0, 1 ],
// CHECK-NEXT: outputs: [ 3 ],
// CHECK-NEXT: operators: [ {
// CHECK-NEXT: opcode_index: 1,
// CHECK-NEXT: inputs: [ 0, 2 ],
// CHECK-NEXT: outputs: [ 3 ]
// CHECK-NEXT: } ],
// CHECK-NEXT: name: "WhileOp_cond"
// CHECK-NEXT: }, {
// CHECK-NEXT: tensors: [ {
// CHECK-NEXT: shape: [ ],
// CHECK-NEXT: type: INT32,
// CHECK-NEXT: buffer: 9,
// CHECK-NEXT: name: "WhileOp_body_arg0",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: }
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ ],
// CHECK-NEXT: buffer: 10,
// CHECK-NEXT: name: "WhileOp_body_arg1",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: }
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ ],
// CHECK-NEXT: type: INT32,
// CHECK-NEXT: buffer: 11,
// CHECK-NEXT: name: "Const1",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ ],
// CHECK-NEXT: type: INT32,
// CHECK-NEXT: buffer: 12,
// CHECK-NEXT: name: "tfl.sub",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: }
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ ],
// CHECK-NEXT: buffer: 13,
// CHECK-NEXT: name: "tfl.add",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: }
// CHECK-NEXT: } ],
// CHECK-NEXT: inputs: [ 0, 1 ],
// CHECK-NEXT: outputs: [ 3, 4 ],
// CHECK-NEXT: operators: [ {
// CHECK-NEXT: opcode_index: 2,
// CHECK-NEXT: inputs: [ 0, 2 ],
// CHECK-NEXT: outputs: [ 3 ],
// CHECK-NEXT: builtin_options_type: SubOptions,
// CHECK-NEXT: builtin_options: {
// CHECK-EMPTY:
// CHECK-NEXT: }
// CHECK-NEXT: }, {
// CHECK-NEXT: opcode_index: 3,
// CHECK-NEXT: inputs: [ 1, 1 ],
// CHECK-NEXT: outputs: [ 4 ],
// CHECK-NEXT: builtin_options_type: AddOptions,
// CHECK-NEXT: builtin_options: {
// CHECK-EMPTY:
// CHECK-NEXT: }
// CHECK-NEXT: } ],
// CHECK-NEXT: name: "WhileOp_body"
// CHECK-NEXT: } ],
// CHECK-NEXT: description: "MLIR Converted.",
// CHECK-NEXT: buffers: [ {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 0, 0, 0, 0 ]
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 1, 0, 0, 0 ]
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 49, 46, 49, 53, 46, 48, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
// CHECK-NEXT: } ],
// CHECK-NEXT: metadata: [ {
// CHECK-NEXT: name: "min_runtime_version",
// CHECK-NEXT: buffer: 14
// CHECK-NEXT: } ]
// CHECK-NEXT: signature_defs: [ ]
// CHECK-NEXT: }
func.func @WhileOp_cond(%arg0: tensor<*xi32>, %arg1: tensor<*xf32>) -> tensor<i1> {
%cst = arith.constant dense<0> : tensor<i32> loc("Const")
%0 = "tfl.greater"(%arg0, %cst) : (tensor<*xi32>, tensor<i32>) -> tensor<i1>
func.return %0 : tensor<i1>
}
func.func @WhileOp_body(%arg0: tensor<*xi32>, %arg1: tensor<*xf32>) -> (tensor<*xi32>, tensor<*xf32>) {
%cst = arith.constant dense<1> : tensor<i32> loc("Const1")
%0 = "tfl.sub"(%arg0, %cst) {fused_activation_function = "NONE"} : (tensor<*xi32>, tensor<i32>) -> tensor<*xi32>
%1 = tfl.add %arg1, %arg1 {fused_activation_function = "NONE"} : tensor<*xf32>
func.return %0, %1 : tensor<*xi32>, tensor<*xf32>
}
func.func @main(%arg0: tensor<i32>, %arg1: tensor<1xf32>) -> tensor<1xf32> {
%0:2 = "tfl.while"(%arg0, %arg1) ({
^bb0(%arg2: tensor<*xi32>, %arg3: tensor<*xf32>):
%1 = func.call @WhileOp_cond(%arg2, %arg3) : (tensor<*xi32>, tensor<*xf32>) -> tensor<i1>
"tfl.yield"(%1) : (tensor<i1>) -> ()
}, {
^bb0(%arg2: tensor<*xi32>, %arg3: tensor<*xf32>):
%1:2 = func.call @WhileOp_body(%arg2, %arg3) : (tensor<*xi32>, tensor<*xf32>) -> (tensor<*xi32>, tensor<*xf32>)
"tfl.yield"(%1#0, %1#1) : (tensor<*xi32>, tensor<*xf32>) -> ()
}) : (tensor<i32>, tensor<1xf32>) -> (tensor<i32>, tensor<1xf32>) loc("WhileOp")
func.return %0#1 : tensor<1xf32>
}
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/transpose_conv_optional.mlir
+97
View File
@@ -0,0 +1,97 @@
// Copyright 2026 The TensorFlow Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// ==============================================================================
// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_to_string - | FileCheck %s
func.func @main(%arg0: tensor<4xi32>, %arg1: tensor<32x4x4x128xf32>, %arg2: tensor<1x32x42x128xf32>) -> tensor<1x64x84x32xf32> {
// CHECK: {
// CHECK-NEXT: version: 3,
// CHECK-NEXT: operator_codes: [ {
// CHECK-NEXT: deprecated_builtin_code: 67,
// CHECK-NEXT: version: 1,
// CHECK-NEXT: builtin_code: TRANSPOSE_CONV
// CHECK-NEXT: } ],
// CHECK-NEXT: subgraphs: [ {
// CHECK-NEXT: tensors: [ {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: type: INT32,
// CHECK-NEXT: buffer: 1,
// CHECK-NEXT: name: "arg0",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 32, 4, 4, 128 ],
// CHECK-NEXT: buffer: 2,
// CHECK-NEXT: name: "arg1",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 1, 32, 42, 128 ],
// CHECK-NEXT: buffer: 3,
// CHECK-NEXT: name: "arg2",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 1, 64, 84, 32 ],
// CHECK-NEXT: buffer: 4,
// CHECK-NEXT: name: "tfl.transpose_conv",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: } ],
// CHECK-NEXT: inputs: [ 0, 1, 2 ],
// CHECK-NEXT: outputs: [ 3 ],
// CHECK-NEXT: operators: [ {
// CHECK-NEXT: inputs: [ 0, 1, 2 ],
// CHECK-NEXT: outputs: [ 3 ],
// CHECK-NEXT: builtin_options_type: TransposeConvOptions,
// CHECK-NEXT: builtin_options: {
// CHECK-NEXT: stride_w: 2,
// CHECK-NEXT: stride_h: 2
// CHECK-NEXT: }
// CHECK-NEXT: } ],
// CHECK-NEXT: name: "main"
// CHECK-NEXT: } ],
// CHECK-NEXT: description: "MLIR Converted.",
// CHECK-NEXT: buffers: [ {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 49, 46, 57, 46, 48, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
// CHECK-NEXT: } ],
// CHECK-NEXT: metadata: [ {
// CHECK-NEXT: name: "min_runtime_version",
// CHECK-NEXT: buffer: 5
// CHECK-NEXT: } ]
// CHECK-NEXT: signature_defs: [ ]
// CHECK-NEXT:}
%cst = "tfl.no_value"() {value = unit} : () -> none
%0 = "tfl.transpose_conv"(%arg0, %arg1, %arg2, %cst) {padding = "SAME", stride_h = 2 : i32, stride_w = 2 : i32, fused_activation_function = "NONE"} : (tensor<4xi32>, tensor<32x4x4x128xf32>, tensor<1x32x42x128xf32>, none) -> tensor<1x64x84x32xf32>
func.return %0 : tensor<1x64x84x32xf32>
}
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/type_attr.mlir
+55
View File
@@ -0,0 +1,55 @@
// Copyright 2026 The TensorFlow Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// ==============================================================================
// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -emit-custom-ops -emit-builtin-tflite-ops=false -o - | flatbuffer_to_string - | FileCheck %s
// CHECK: {
// CHECK: version: 3,
// CHECK: operator_codes: [ {
// CHECK: deprecated_builtin_code: 32,
// CHECK: custom_code: "SomeOperation",
// CHECK: builtin_code: CUSTOM
// CHECK: } ],
// CHECK: subgraphs: [ {
// CHECK: tensors: [ {
// CHECK: shape: [ ],
// CHECK: type: INT32,
// CHECK: buffer: 1,
// CHECK: name: "tf.SomeOperation",
// CHECK: quantization: {
// CHECK-EMPTY
// CHECK: }
// CHECK: } ],
// CHECK: inputs: [ ],
// CHECK: outputs: [ 0 ],
// CHECK: operators: [ {
// CHECK: inputs: [ ],
// CHECK: outputs: [ 0 ],
// CHECK: custom_options: [ 100, 116, 121, 112, 101, 0, 1, 7, 1, 1, 1, 2, 4, 2, 36, 1 ]
// CHECK: } ],
// CHECK: name: "main"
// CHECK: } ],
// CHECK: description: "MLIR Converted.",
// CHECK: buffers: [ {
// CHECK-EMPTY
// CHECK: }, {
// CHECK-EMPTY
// CHECK: } ]
// CHECK: }
func.func @main() -> tensor<*xi32> {
// Tests that the below type attribute is convertible into the corresponding custom option in flatbuffer.
%0 = "tf.SomeOperation"() {dtype = i32 } : () -> tensor<*xi32>
func.return %0 : tensor<*xi32>
}
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/u16_quant.mlir
+33
View File
@@ -0,0 +1,33 @@
// Copyright 2026 The TensorFlow Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// ==============================================================================
// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_to_string - | FileCheck %s
func.func @main(%arg0: tensor<*x!quant.uniform<u16:f32, 2.0:37>>) -> tensor<*x!quant.uniform<u16:f32, 2.0:37>> {
// CHECK: {
// CHECK-NEXT: version: 3,
// CHECK-NEXT: operator_codes: [ ],
// CHECK-NEXT: subgraphs: [ {
// CHECK-NEXT: tensors: [ {
// CHECK-NEXT: shape: [ ],
// CHECK-NEXT: type: UINT16,
// CHECK-NEXT: buffer: 1,
// CHECK-NEXT: name: "arg0",
// CHECK-NEXT: quantization: {
// CHECK-NEXT: scale: [ 2.0 ],
// CHECK-NEXT: zero_point: [ 37 ]
// CHECK: }
// CHECK-NEXT: } ],
return %arg0 : tensor<*x!quant.uniform<u16:f32, 2.0:37>>
}
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/unidirectional_sequence_lstm.mlir
+361
View File
@@ -0,0 +1,361 @@
// Copyright 2026 The TensorFlow Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// ==============================================================================
// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_to_string - | FileCheck %s
func.func @main(tensor<4x4x4xf32>, tensor<4x4xf32>, tensor<4x4xf32>, tensor<4x4xf32>, tensor<4x4xf32>, tensor<4x4xf32>, tensor<4x4xf32>, tensor<4x4xf32>, tensor<4x4xf32>, tensor<4xf32>, tensor<4xf32>, tensor<4xf32>, tensor<4xf32>, tensor<4xf32>, tensor<4xf32>, tensor<4xf32>, tensor<4x4xf32>, tensor<4xf32>, tensor<4x4xf32>, tensor<4x4xf32>, tensor<4x4xf32>, tensor<4x4xf32>) -> tensor<4x4x4xf32> {
// CHECK: {
// CHECK-NEXT: version: 3,
// CHECK-NEXT: operator_codes: [ {
// CHECK-NEXT: deprecated_builtin_code: 44,
// CHECK-NEXT: version: 1,
// CHECK-NEXT: builtin_code: UNIDIRECTIONAL_SEQUENCE_LSTM
// CHECK-NEXT: } ],
// CHECK-NEXT: subgraphs: [ {
// CHECK-NEXT: tensors: [ {
// CHECK-NEXT: shape: [ 4, 4, 4 ],
// CHECK-NEXT: buffer: 1,
// CHECK-NEXT: name: "arg0",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4, 4 ],
// CHECK-NEXT: buffer: 2,
// CHECK-NEXT: name: "arg1",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4, 4 ],
// CHECK-NEXT: buffer: 3,
// CHECK-NEXT: name: "arg2",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4, 4 ],
// CHECK-NEXT: buffer: 4,
// CHECK-NEXT: name: "arg3",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4, 4 ],
// CHECK-NEXT: buffer: 5,
// CHECK-NEXT: name: "arg4",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4, 4 ],
// CHECK-NEXT: buffer: 6,
// CHECK-NEXT: name: "arg5",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4, 4 ],
// CHECK-NEXT: buffer: 7,
// CHECK-NEXT: name: "arg6",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4, 4 ],
// CHECK-NEXT: buffer: 8,
// CHECK-NEXT: name: "arg7",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4, 4 ],
// CHECK-NEXT: buffer: 9,
// CHECK-NEXT: name: "arg8",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 10,
// CHECK-NEXT: name: "arg9",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 11,
// CHECK-NEXT: name: "arg10",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 12,
// CHECK-NEXT: name: "arg11",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 13,
// CHECK-NEXT: name: "arg12",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 14,
// CHECK-NEXT: name: "arg13",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 15,
// CHECK-NEXT: name: "arg14",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 16,
// CHECK-NEXT: name: "arg15",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4, 4 ],
// CHECK-NEXT: buffer: 17,
// CHECK-NEXT: name: "arg16",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 18,
// CHECK-NEXT: name: "arg17",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4, 4 ],
// CHECK-NEXT: buffer: 19,
// CHECK-NEXT: name: "arg18",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4, 4 ],
// CHECK-NEXT: buffer: 20,
// CHECK-NEXT: name: "arg19",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4, 4 ],
// CHECK-NEXT: buffer: 21,
// CHECK-NEXT: name: "arg20",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4, 4 ],
// CHECK-NEXT: buffer: 22,
// CHECK-NEXT: name: "arg21",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4, 4 ],
// CHECK-NEXT: name: "Const",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: is_variable: true,
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4, 4 ],
// CHECK-NEXT: name: "Const1",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: is_variable: true,
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 0 ],
// CHECK-NEXT: name: "input_to_input_intermediate",
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 0 ],
// CHECK-NEXT: name: "input_to_forget_intermediate",
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 0 ],
// CHECK-NEXT: name: "input_to_cell_intermediate",
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 0 ],
// CHECK-NEXT: name: "input_to_output_intermediate",
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 0 ],
// CHECK-NEXT: type: INT8,
// CHECK-NEXT: name: "effective_hidden_scale_intermediate",
// CHECK-NEXT: quantization: {
// CHECK-NEXT: scale: [ 0.007788 ],
// CHECK-NEXT: zero_point: [ 0 ]
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4, 4, 4 ],
// CHECK-NEXT: buffer: 25,
// CHECK-NEXT: name: "tfl.unidirectional_sequence_lstm",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: } ],
// CHECK-NEXT: inputs: [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 ],
// CHECK-NEXT: outputs: [ 29 ],
// CHECK-NEXT: operators: [ {
// CHECK-NEXT: inputs: [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 22, 23, 18, 19, 20, 21 ],
// CHECK-NEXT: outputs: [ 29 ],
// CHECK-NEXT: builtin_options_type: UnidirectionalSequenceLSTMOptions,
// CHECK-NEXT: builtin_options: {
// CHECK-NEXT: time_major: true
// CHECK-NEXT: },
// CHECK-NEXT: intermediates: [ 24, 25, 26, 27, 28 ]
// CHECK-NEXT: } ],
// CHECK-NEXT: name: "main"
// CHECK-NEXT: } ],
// CHECK-NEXT: description: "MLIR Converted.",
// CHECK-NEXT: buffers: [ {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 49, 46, 49, 51, 46, 49, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
// CHECK-NEXT: } ],
// CHECK-NEXT: metadata: [ {
// CHECK-NEXT: name: "min_runtime_version",
// CHECK-NEXT: buffer: 26
// CHECK-NEXT: } ]
// CHECK-NEXT: signature_defs: [ ]
// CHECK-NEXT: }
// CHECK-EMPTY:
^bb0(%arg0: tensor<4x4x4xf32>,
%arg1: tensor<4x4xf32>, %arg2: tensor<4x4xf32>, %arg3: tensor<4x4xf32>, %arg4: tensor<4x4xf32>,
%arg5: tensor<4x4xf32>, %arg6: tensor<4x4xf32>, %arg7: tensor<4x4xf32>, %arg8: tensor<4x4xf32>,
%arg9: tensor<4xf32>, %arg10: tensor<4xf32>, %arg11: tensor<4xf32>,
%arg12: tensor<4xf32>, %arg13: tensor<4xf32>, %arg14: tensor<4xf32>, %arg15: tensor<4xf32>,
%arg16: tensor<4x4xf32>, %arg17: tensor<4xf32>,
%arg18: tensor<4x4xf32>, %arg19: tensor<4x4xf32>, %arg20: tensor<4x4xf32>, %arg21: tensor<4x4xf32>):
%0 = "tfl.pseudo_const" () {value = dense<0.0> : tensor<4x4xf32>} : () -> tensor<4x4xf32> loc("Const")
%1 = "tfl.pseudo_const" () {value = dense<0.0> : tensor<4x4xf32>} : () -> tensor<4x4xf32> loc("Const")
%2 = "tfl.unidirectional_sequence_lstm"(%arg0,
%arg1, %arg2, %arg3, %arg4,
%arg5, %arg6, %arg7, %arg8,
%arg9, %arg10, %arg11,
%arg12, %arg13, %arg14, %arg15,
%arg16, %arg17,
%0, %1,
%arg18, %arg19,%arg20, %arg21) {
effective_hidden_scale_intermediate = tensor<0x!quant.uniform<i8<-127:127>:f32, 0.0077881771139800549>>,
fused_activation_function = "NONE",
input_to_cell_intermediate = tensor<0xf32>,
input_to_forget_intermediate = tensor<0xf32>,
input_to_input_intermediate = tensor<0xf32>,
input_to_output_intermediate = tensor<0xf32>, time_major = true}
: (tensor<4x4x4xf32>,
tensor<4x4xf32>, tensor<4x4xf32>, tensor<4x4xf32>, tensor<4x4xf32>,
tensor<4x4xf32>, tensor<4x4xf32>, tensor<4x4xf32>, tensor<4x4xf32>,
tensor<4xf32>, tensor<4xf32>, tensor<4xf32>,
tensor<4xf32>, tensor<4xf32>, tensor<4xf32>, tensor<4xf32>,
tensor<4x4xf32>, tensor<4xf32>,
tensor<4x4xf32>, tensor<4x4xf32>,
tensor<4x4xf32>, tensor<4x4xf32>, tensor<4x4xf32>, tensor<4x4xf32>) -> tensor<4x4x4xf32>
func.return %2 : tensor<4x4x4xf32>
}
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/unidirectional_sequence_rnn.mlir
+118
View File
@@ -0,0 +1,118 @@
// Copyright 2026 The TensorFlow Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// ==============================================================================
// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_to_string - | FileCheck %s
func.func @main(tensor<4 x f32>, tensor<4 x f32>, tensor<4 x f32>, tensor<4 x f32>) -> tensor<4 x f32> {
// CHECK: {
// CHECK-NEXT: version: 3,
// CHECK-NEXT: operator_codes: [ {
// CHECK-NEXT: deprecated_builtin_code: 35,
// CHECK-NEXT: version: 1,
// CHECK-NEXT: builtin_code: UNIDIRECTIONAL_SEQUENCE_RNN
// CHECK-NEXT: } ],
// CHECK-NEXT: subgraphs: [ {
// CHECK-NEXT: tensors: [ {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 1,
// CHECK-NEXT: name: "arg0",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 2,
// CHECK-NEXT: name: "arg1",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 3,
// CHECK-NEXT: name: "arg2",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 4,
// CHECK-NEXT: name: "arg3",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4, 4 ],
// CHECK-NEXT: name: "Const",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: is_variable: true,
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 4 ],
// CHECK-NEXT: buffer: 6,
// CHECK-NEXT: name: "tfl.unidirectional_sequence_rnn",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: } ],
// CHECK-NEXT: inputs: [ 0, 1, 2, 3 ],
// CHECK-NEXT: outputs: [ 5 ],
// CHECK-NEXT: operators: [ {
// CHECK-NEXT: inputs: [ 0, 1, 2, 3, 4 ],
// CHECK-NEXT: outputs: [ 5 ],
// CHECK-NEXT: builtin_options_type: SequenceRNNOptions,
// CHECK-NEXT: builtin_options: {
// CHECK-NEXT: time_major: true,
// CHECK-NEXT: fused_activation_function: TANH
// CHECK-NEXT: }
// CHECK-NEXT: } ],
// CHECK-NEXT: name: "main"
// CHECK-NEXT: } ],
// CHECK-NEXT: description: "MLIR Converted.",
// CHECK-NEXT: buffers: [ {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 49, 46, 49, 52, 46, 48, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
// CHECK-NEXT: } ],
// CHECK-NEXT: metadata: [ {
// CHECK-NEXT: name: "min_runtime_version",
// CHECK-NEXT: buffer: 7
// CHECK-NEXT: } ]
// CHECK-NEXT: signature_defs: [ ]
// CHECK-NEXT: }
// CHECK-EMPTY:
^bb0(%arg0: tensor<4 x f32>, %arg1: tensor<4 x f32>, %arg2: tensor<4 x f32>, %arg3: tensor<4 x f32>):
%0 = "tfl.pseudo_const" () {value = dense<0.0> : tensor<4x4xf32>} : () -> tensor<4x4xf32> loc("Const")
%1 = "tfl.unidirectional_sequence_rnn"(%arg0, %arg1, %arg2, %arg3, %0) {fused_activation_function = "TANH", time_major = true} : (tensor<4xf32>, tensor<4xf32>, tensor<4xf32>, tensor<4xf32>, tensor<4x4xf32>) -> tensor<4xf32>
func.return %1 : tensor<4xf32>
}
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/unranked_tensor.mlir
+65
View File
@@ -0,0 +1,65 @@
// Copyright 2026 The TensorFlow Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// ==============================================================================
// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_to_string - | FileCheck %s
module {
func.func @serving_default(%arg0: tensor<*xf32>) -> tensor<*xf32> attributes {tf.entry_function = {inputs = "serving_default_x", outputs = "outputs"}} {
// CHECK: {
// CHECK-NEXT: version: 3,
// CHECK-NEXT: operator_codes: [ {
// CHECK-NEXT: version: 1
// CHECK-NEXT: } ],
// CHECK-NEXT: subgraphs: [ {
// CHECK-NEXT: tensors: [ {
// CHECK-NEXT: shape: [ ],
// CHECK-NEXT: buffer: 1,
// CHECK-NEXT: name: "serving_default_x",
// CHECK-NEXT: quantization: {
// CHECK: }
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ ],
// CHECK-NEXT: buffer: 2,
// CHECK-NEXT: name: "outputs",
// CHECK-NEXT: quantization: {
// CHECK: }
// CHECK-NEXT: } ],
// CHECK-NEXT: inputs: [ 0 ],
// CHECK-NEXT: outputs: [ 1 ],
// CHECK-NEXT: operators: [ {
// CHECK-NEXT: inputs: [ 0, 0 ],
// CHECK-NEXT: outputs: [ 1 ],
// CHECK-NEXT: builtin_options_type: AddOptions,
// CHECK-NEXT: builtin_options: {
// CHECK: }
// CHECK-NEXT: } ],
// CHECK-NEXT: name: "main"
// CHECK-NEXT: } ],
// CHECK-NEXT: description: "MLIR Converted.",
// CHECK-NEXT: buffers: [ {
// CHECK: }, {
// CHECK: }, {
// CHECK: }, {
// CHECK-NEXT: data: [ 49, 46, 53, 46, 48, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
// CHECK-NEXT: } ],
// CHECK-NEXT: metadata: [ {
// CHECK-NEXT: name: "min_runtime_version",
// CHECK-NEXT: buffer: 3
// CHECK-NEXT: } ],
// CHECK-NEXT: signature_defs: [ ]
// CHECK-NEXT:}
%0 = "tfl.add"(%arg0, %arg0) {fused_activation_function = "NONE"} : (tensor<*xf32>, tensor<*xf32>) -> tensor<*xf32>
return %0 : tensor<*xf32>
}
}
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/unsorted_segment_prod.mlir
+94
View File
@@ -0,0 +1,94 @@
// Copyright 2026 The TensorFlow Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// ==============================================================================
// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_to_string - | FileCheck %s
func.func @main(tensor<8xi32>, tensor<8xi32>, tensor<i32>) -> tensor<8xi32> {
^bb0(%arg0: tensor<8xi32>, %arg1: tensor<8xi32>, %arg2: tensor<i32>):
// CHECK: {
// CHECK-NEXT: version: 3,
// CHECK-NEXT: operator_codes: [ {
// CHECK-NEXT: deprecated_builtin_code: 127,
// CHECK-NEXT: version: 1,
// CHECK-NEXT: builtin_code: UNSORTED_SEGMENT_PROD
// CHECK-NEXT: } ],
// CHECK-NEXT: subgraphs: [ {
// CHECK-NEXT: tensors: [ {
// CHECK-NEXT: shape: [ 8 ],
// CHECK-NEXT: type: INT32,
// CHECK-NEXT: buffer: 1,
// CHECK-NEXT: name: "arg0",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 8 ],
// CHECK-NEXT: type: INT32,
// CHECK-NEXT: buffer: 2,
// CHECK-NEXT: name: "arg1",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ ],
// CHECK-NEXT: type: INT32,
// CHECK-NEXT: buffer: 3,
// CHECK-NEXT: name: "arg2",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 8 ],
// CHECK-NEXT: type: INT32,
// CHECK-NEXT: buffer: 4,
// CHECK-NEXT: name: "tfl.unsorted_segment_prod",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: } ],
// CHECK-NEXT: inputs: [ 0, 1, 2 ],
// CHECK-NEXT: outputs: [ 3 ],
// CHECK-NEXT: operators: [ {
// CHECK-NEXT: inputs: [ 0, 1, 2 ],
// CHECK-NEXT: outputs: [ 3 ]
// CHECK-NEXT: } ]
// CHECK-NEXT: name: "main"
// CHECK-NEXT: } ],
// CHECK-NEXT: description: "MLIR Converted.",
// CHECK-NEXT: buffers: [ {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 50, 46, 49, 48, 46, 48, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
// CHECK-NEXT: } ],
// CHECK-NEXT: metadata: [ {
// CHECK-NEXT: name: "min_runtime_version",
// CHECK-NEXT: buffer: 5
// CHECK-NEXT: } ]
// CHECK-NEXT: signature_defs: [ ]
// CHECK-NEXT: }
%0 = "tfl.unsorted_segment_prod"(%arg0, %arg1, %arg2) : (tensor<8xi32>, tensor<8xi32>, tensor<i32>) -> tensor<8xi32>
func.return %0 : tensor<8xi32>
}
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/variable.mlir
+54
View File
@@ -0,0 +1,54 @@
// Copyright 2026 The TensorFlow Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// ==============================================================================
// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_to_string - | FileCheck %s
func.func @main() -> tensor<3x2xi32> {
%0 = "tfl.pseudo_const" () {value = dense<0> : tensor<3x2xi32>, tfl.is_variable} : () -> tensor<3x2xi32> loc("variable")
func.return %0 : tensor<3x2xi32>
}
// CHECK: {
// CHECK-NEXT: version: 3,
// CHECK-NEXT: operator_codes: [ ],
// CHECK-NEXT: subgraphs: [ {
// CHECK-NEXT: tensors: [ {
// CHECK-NEXT: shape: [ 3, 2 ],
// CHECK-NEXT: type: INT32,
// CHECK-NEXT: name: "variable",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: is_variable: true
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: } ],
// CHECK-NEXT: inputs: [ ],
// CHECK-NEXT: outputs: [ 0 ],
// CHECK-NEXT: operators: [ ],
// CHECK-NEXT: name: "main"
// CHECK-NEXT: } ],
// CHECK-NEXT: description: "MLIR Converted.",
// CHECK-NEXT: buffers: [ {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ {{.*}} ]
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ {{.*}} ]
// CHECK-NEXT: } ],
// CHECK-NEXT: metadata: [ {
// CHECK-NEXT: name: "min_runtime_version",
// CHECK-NEXT: buffer: 2
// CHECK-NEXT: } ]
// CHECK-NEXT: signature_defs: [ ]
// CHECK-NEXT: }
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/variant_type_on_func.mlir
+57
View File
@@ -0,0 +1,57 @@
// Copyright 2026 The TensorFlow Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// ==============================================================================
// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_to_string - | FileCheck %s
// CHECK: {
// CHECK-NEXT: version: 3,
// CHECK-NEXT: operator_codes: [ ],
// CHECK-NEXT: subgraphs: [ {
// CHECK-NEXT: tensors: [ {
// CHECK-NEXT: shape: [ ],
// CHECK-NEXT: type: VARIANT,
// CHECK-NEXT: buffer: 1,
// CHECK-NEXT: name: "arg0",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: variant_tensors: [ {
// CHECK-NEXT: shape: [ 2 ],
// CHECK-NEXT: type: INT32,
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: } ]
// CHECK-NEXT: } ],
// CHECK-NEXT: inputs: [ 0 ],
// CHECK-NEXT: outputs: [ 0 ],
// CHECK-NEXT: operators: [ ],
// CHECK-NEXT: name: "main"
// CHECK-NEXT: } ],
// CHECK-NEXT: description: "MLIR Converted.",
// CHECK-NEXT: buffers: [ {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
// CHECK-NEXT: } ],
// CHECK-NEXT: metadata: [ {
// CHECK-NEXT: name: "min_runtime_version",
// CHECK-NEXT: buffer: 2
// CHECK-NEXT: } ],
// CHECK-NEXT: signature_defs: [ ]
// CHECK-NEXT: }
func.func @main(%arg0 : tensor<!tf_type.variant<tensor<2xi32>>>) -> tensor<!tf_type.variant<tensor<2xi32>>> {
func.return %arg0 : tensor<!tf_type.variant<tensor<2xi32>>>
}
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/variant_type_on_op.mlir
+58
View File
@@ -0,0 +1,58 @@
// Copyright 2026 The TensorFlow Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// ==============================================================================
// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_to_string - | FileCheck %s
// CHECK: {
// CHECK-NEXT: version: 3,
// CHECK-NEXT: operator_codes: [ ],
// CHECK-NEXT: subgraphs: [ {
// CHECK-NEXT: tensors: [ {
// CHECK-NEXT: shape: [ ],
// CHECK-NEXT: type: VARIANT,
// CHECK-NEXT: buffer: 1,
// CHECK-NEXT: name: "tf.Const",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: variant_tensors: [ {
// CHECK-NEXT: shape: [ 2 ],
// CHECK-NEXT: type: INT32,
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: } ]
// CHECK-NEXT: } ],
// CHECK-NEXT: inputs: [ ],
// CHECK-NEXT: outputs: [ 0 ],
// CHECK-NEXT: operators: [ ],
// CHECK-NEXT: name: "main"
// CHECK-NEXT: } ],
// CHECK-NEXT: description: "MLIR Converted.",
// CHECK-NEXT: buffers: [ {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 128, 0, 0, 0, 128, 0, 0, 0 ]
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
// CHECK-NEXT: } ],
// CHECK-NEXT: metadata: [ {
// CHECK-NEXT: name: "min_runtime_version",
// CHECK-NEXT: buffer: 2
// CHECK-NEXT: } ],
// CHECK-NEXT: signature_defs: [ ]
// CHECK-NEXT: }
func.func @main() -> tensor<!tf_type.variant<tensor<2xi32>>> {
%0 = "tf.Const"() {device = "", name = "", dtype = "tfdtype$DT_INT32", value = #tf_type<tensor_proto : "0x746674656E736F722464747970653A2044545F494E5433320A74656E736F725F7368617065207B0A202064696D207B0A2020202073697A653A20320A20207D0A7D0A74656E736F725F636F6E74656E743A20225C3230305C3030305C3030305C3030305C3230305C3030305C3030305C303030220A"> : tensor<!tf_type.variant>} : () -> tensor<!tf_type.variant<tensor<2xi32>>>
func.return %0 : tensor<!tf_type.variant<tensor<2xi32>>>
}
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/while_op.mlir
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@@ -0,0 +1,250 @@
// Copyright 2026 The TensorFlow Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// ==============================================================================
// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_to_string - | FileCheck %s
// CHECK: {
// CHECK-NEXT: version: 3,
// CHECK-NEXT: operator_codes: [ {
// CHECK-NEXT: deprecated_builtin_code: 119,
// CHECK-NEXT: version: 1,
// CHECK-NEXT: builtin_code: WHILE
// CHECK-NEXT: }, {
// CHECK-NEXT: deprecated_builtin_code: 61,
// CHECK-NEXT: version: 1,
// CHECK-NEXT: builtin_code: GREATER
// CHECK-NEXT: }, {
// CHECK-NEXT: deprecated_builtin_code: 41,
// CHECK-NEXT: version: 1,
// CHECK-NEXT: builtin_code: SUB
// CHECK-NEXT: }, {
// CHECK-NEXT: version: 1
// CHECK-NEXT: } ],
// CHECK-NEXT: subgraphs: [ {
// CHECK-NEXT: tensors: [ {
// CHECK-NEXT: shape: [ ],
// CHECK-NEXT: type: INT32,
// CHECK-NEXT: buffer: 1,
// CHECK-NEXT: name: "arg0",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 1 ],
// CHECK-NEXT: buffer: 2,
// CHECK-NEXT: name: "arg1",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ ],
// CHECK-NEXT: type: INT32,
// CHECK-NEXT: buffer: 3,
// CHECK-NEXT: name: "tfl.while",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ 1 ],
// CHECK-NEXT: buffer: 4,
// CHECK-NEXT: name: "tfl.while:1",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: } ],
// CHECK-NEXT: inputs: [ 0, 1 ],
// CHECK-NEXT: outputs: [ 3 ],
// CHECK-NEXT: operators: [ {
// CHECK-NEXT: inputs: [ 0, 1 ],
// CHECK-NEXT: outputs: [ 2, 3 ],
// CHECK-NEXT: builtin_options_type: WhileOptions,
// CHECK-NEXT: builtin_options: {
// CHECK-NEXT: cond_subgraph_index: 1,
// CHECK-NEXT: body_subgraph_index: 2
// CHECK-NEXT: }
// CHECK-NEXT: } ],
// CHECK-NEXT: name: "main"
// CHECK-NEXT: }, {
// CHECK-NEXT: tensors: [ {
// CHECK-NEXT: shape: [ ],
// CHECK-NEXT: type: INT32,
// CHECK-NEXT: buffer: 5,
// CHECK-NEXT: name: "cond_arg0",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: }
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ ],
// CHECK-NEXT: buffer: 6,
// CHECK-NEXT: name: "cond_arg1",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: }
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ ],
// CHECK-NEXT: type: INT32,
// CHECK-NEXT: buffer: 7,
// CHECK-NEXT: name: "Const",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ ],
// CHECK-NEXT: type: BOOL,
// CHECK-NEXT: buffer: 8,
// CHECK-NEXT: name: "tfl.greater",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: } ],
// CHECK-NEXT: inputs: [ 0, 1 ],
// CHECK-NEXT: outputs: [ 3 ],
// CHECK-NEXT: operators: [ {
// CHECK-NEXT: opcode_index: 1,
// CHECK-NEXT: inputs: [ 0, 2 ],
// CHECK-NEXT: outputs: [ 3 ]
// CHECK-NEXT: } ],
// CHECK-NEXT: name: "cond"
// CHECK-NEXT: }, {
// CHECK-NEXT: tensors: [ {
// CHECK-NEXT: shape: [ ],
// CHECK-NEXT: type: INT32,
// CHECK-NEXT: buffer: 9,
// CHECK-NEXT: name: "body_arg0",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: }
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ ],
// CHECK-NEXT: buffer: 10,
// CHECK-NEXT: name: "body_arg1",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: }
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ ],
// CHECK-NEXT: type: INT32,
// CHECK-NEXT: buffer: 11,
// CHECK-NEXT: name: "Const1",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: },
// CHECK-NEXT: has_rank: true
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ ],
// CHECK-NEXT: type: INT32,
// CHECK-NEXT: buffer: 12,
// CHECK-NEXT: name: "tfl.sub",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: }
// CHECK-NEXT: }, {
// CHECK-NEXT: shape: [ ],
// CHECK-NEXT: buffer: 13,
// CHECK-NEXT: name: "tfl.add",
// CHECK-NEXT: quantization: {
// CHECK-EMPTY:
// CHECK-NEXT: }
// CHECK-NEXT: } ],
// CHECK-NEXT: inputs: [ 0, 1 ],
// CHECK-NEXT: outputs: [ 3, 4 ],
// CHECK-NEXT: operators: [ {
// CHECK-NEXT: opcode_index: 2,
// CHECK-NEXT: inputs: [ 0, 2 ],
// CHECK-NEXT: outputs: [ 3 ],
// CHECK-NEXT: builtin_options_type: SubOptions,
// CHECK-NEXT: builtin_options: {
// CHECK-EMPTY:
// CHECK-NEXT: }
// CHECK-NEXT: }, {
// CHECK-NEXT: opcode_index: 3,
// CHECK-NEXT: inputs: [ 1, 1 ],
// CHECK-NEXT: outputs: [ 4 ],
// CHECK-NEXT: builtin_options_type: AddOptions,
// CHECK-NEXT: builtin_options: {
// CHECK-EMPTY:
// CHECK-NEXT: }
// CHECK-NEXT: } ],
// CHECK-NEXT: name: "body"
// CHECK-NEXT: } ],
// CHECK-NEXT: description: "MLIR Converted.",
// CHECK-NEXT: buffers: [ {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 0, 0, 0, 0 ]
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 1, 0, 0, 0 ]
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-EMPTY:
// CHECK-NEXT: }, {
// CHECK-NEXT: data: [ 49, 46, 49, 53, 46, 48, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
// CHECK-NEXT: } ],
// CHECK-NEXT: metadata: [ {
// CHECK-NEXT: name: "min_runtime_version",
// CHECK-NEXT: buffer: 14
// CHECK-NEXT: } ]
// CHECK-NEXT: signature_defs: [ ]
// CHECK-NEXT: }
func.func @main(%arg0: tensor<i32>, %arg1: tensor<1xf32>) -> tensor<1xf32> {
%0:2 = "tfl.while"(%arg0, %arg1) ({
^bb0(%arg2: tensor<*xi32>, %arg3: tensor<*xf32>):
%1 = func.call @cond(%arg2, %arg3) : (tensor<*xi32>, tensor<*xf32>) -> tensor<i1>
"tfl.yield"(%1) : (tensor<i1>) -> ()
}, {
^bb0(%arg2: tensor<*xi32>, %arg3: tensor<*xf32>):
%1:2 = func.call @body(%arg2, %arg3) : (tensor<*xi32>, tensor<*xf32>) -> (tensor<*xi32>, tensor<*xf32>)
"tfl.yield"(%1#0, %1#1) : (tensor<*xi32>, tensor<*xf32>) -> ()
}) {is_stateless = false} : (tensor<i32>, tensor<1xf32>) -> (tensor<i32>, tensor<1xf32>)
func.return %0#1 : tensor<1xf32>
}
func.func @cond(%arg0: tensor<*xi32>, %arg1: tensor<*xf32>) -> tensor<i1> {
%cst = arith.constant dense<0> : tensor<i32> loc("Const")
%0 = "tfl.greater"(%arg0, %cst) : (tensor<*xi32>, tensor<i32>) -> tensor<i1>
func.return %0 : tensor<i1>
}
func.func @body(%arg0: tensor<*xi32>, %arg1: tensor<*xf32>) -> (tensor<*xi32>, tensor<*xf32>) {
%cst = arith.constant dense<1> : tensor<i32> loc("Const")
%0 = "tfl.sub"(%arg0, %cst) {fused_activation_function = "NONE"} : (tensor<*xi32>, tensor<i32>) -> tensor<*xi32>
%1 = tfl.add %arg1, %arg1 {fused_activation_function = "NONE"} : tensor<*xf32>
func.return %0, %1 : tensor<*xi32>, tensor<*xf32>
}