wehub-resource-sync
161 lines
7.5 KiB
C++
161 lines
7.5 KiB
C++
/* Copyright 2017 The TensorFlow Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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==============================================================================*/
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#include <vector>
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#include <gtest/gtest.h>
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#include "tensorflow/lite/c/c_api_types.h"
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#include "tensorflow/lite/c/common.h"
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#include "tensorflow/lite/interpreter.h"
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#include "tensorflow/lite/kernels/subgraph_test_util.h"
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namespace tflite {
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namespace {
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TEST(ArenaPlannerSubgraphTest, TestSubgraphInputsAndOutputsNotShared) {
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Interpreter interpreter;
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subgraph_test_util::SubgraphBuilder builder;
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builder.BuildInplaceOpSubgraph(&interpreter.primary_subgraph());
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ASSERT_EQ(interpreter.ResizeInputTensor(interpreter.inputs()[0], {2}),
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kTfLiteOk);
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ASSERT_EQ(interpreter.ResizeInputTensor(interpreter.inputs()[1], {2}),
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kTfLiteOk);
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ASSERT_EQ(interpreter.AllocateTensors(), kTfLiteOk);
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const TfLiteTensor* add_input0 = interpreter.tensor(interpreter.inputs()[0]);
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const TfLiteTensor* add_input1 = interpreter.tensor(interpreter.inputs()[1]);
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const int kIntermediateTensor0 = 2;
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const int kIntermediateTensor1 = 3;
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const TfLiteTensor* add_output = interpreter.tensor(kIntermediateTensor0);
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const TfLiteTensor* reshape_output = interpreter.tensor(kIntermediateTensor1);
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const TfLiteTensor* subgraph_output =
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interpreter.tensor(interpreter.outputs()[0]);
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// Neither input to ADD may be shared since they are subgraph inputs.
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EXPECT_NE(add_input0->data.data, add_output->data.data);
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EXPECT_NE(add_input1->data.data, add_output->data.data);
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// The output of ADD may be shared with the output of RESHAPE.
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EXPECT_EQ(add_output->data.data, reshape_output->data.data);
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// RESHAPE's output can't be shared as the output of the following op is a
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// subgraph output.
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EXPECT_NE(reshape_output->data.data, subgraph_output->data.data);
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}
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TEST(ArenaPlannerSubgraphTest, TestSharingBroadcastOps) {
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Interpreter interpreter;
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subgraph_test_util::SubgraphBuilder builder;
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builder.BuildBroadcastingSubgraph(&interpreter.primary_subgraph());
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ASSERT_EQ(interpreter.ResizeInputTensor(interpreter.inputs()[0], {1}),
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kTfLiteOk);
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ASSERT_EQ(interpreter.ResizeInputTensor(interpreter.inputs()[1], {2}),
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kTfLiteOk);
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ASSERT_EQ(interpreter.AllocateTensors(), kTfLiteOk);
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TfLiteTensor* subgraph_input0 = interpreter.tensor(interpreter.inputs()[0]);
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TfLiteTensor* subgraph_input1 = interpreter.tensor(interpreter.inputs()[1]);
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const int kIntermediateTensor0 = 2;
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const int kIntermediateTensor1 = 3;
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const int kIntermediateTensor2 = 4;
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const int kIntermediateTensor3 = 5;
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const TfLiteTensor* intermediate_tensor0 =
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interpreter.tensor(kIntermediateTensor0);
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const TfLiteTensor* intermediate_tensor1 =
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interpreter.tensor(kIntermediateTensor1);
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const TfLiteTensor* intermediate_tensor2 =
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interpreter.tensor(kIntermediateTensor2);
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const TfLiteTensor* intermediate_tensor3 =
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interpreter.tensor(kIntermediateTensor3);
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subgraph_test_util::FillIntTensor(subgraph_input0, {1});
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subgraph_test_util::FillIntTensor(subgraph_input1, {2, 2});
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const TfLiteTensor* subgraph_output =
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interpreter.tensor(interpreter.outputs()[0]);
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// Neither input to ADD may be shared since they are subgraph inputs.
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EXPECT_NE(subgraph_input0->data.data, intermediate_tensor0->data.data);
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EXPECT_NE(subgraph_input1->data.data, intermediate_tensor0->data.data);
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// The 2nd ADD op consumes intermediate_tensor0 twice. Since there is more
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// than one consumer, sharing is not possible.
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EXPECT_NE(intermediate_tensor0->data.data, intermediate_tensor1->data.data);
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// intermediate_tensor1 can be shared with intermediate_tensor2.
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EXPECT_EQ(intermediate_tensor1->data.data, intermediate_tensor2->data.data);
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// intermediate_tensor3 cannot be shared with a subgraph output.
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EXPECT_NE(intermediate_tensor3->data.data, subgraph_output->data.data);
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ASSERT_EQ(interpreter.Invoke(), kTfLiteOk);
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subgraph_test_util::CheckIntTensor(subgraph_output, {2}, {9, 9});
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}
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TEST(ArenaPlannerSubgraphTest, TestOffsetAddSharing) {
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Interpreter interpreter;
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subgraph_test_util::SubgraphBuilder builder;
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builder.BuildOffsetAddSharing(&interpreter.primary_subgraph());
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ASSERT_EQ(interpreter.ResizeInputTensor(interpreter.inputs()[0], {1}),
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kTfLiteOk);
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ASSERT_EQ(interpreter.ResizeInputTensor(interpreter.inputs()[1], {3}),
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kTfLiteOk);
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ASSERT_EQ(interpreter.AllocateTensors(), kTfLiteOk);
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TfLiteTensor* subgraph_input0 = interpreter.tensor(interpreter.inputs()[0]);
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TfLiteTensor* subgraph_input1 = interpreter.tensor(interpreter.inputs()[1]);
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const int kIntermediateTensor0 = 2;
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const int kIntermediateTensor1 = 3;
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const int kIntermediateTensor2 = 4;
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const TfLiteTensor* intermediate_tensor0 =
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interpreter.tensor(kIntermediateTensor0);
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const TfLiteTensor* intermediate_tensor1 =
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interpreter.tensor(kIntermediateTensor1);
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const TfLiteTensor* intermediate_tensor2 =
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interpreter.tensor(kIntermediateTensor2);
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subgraph_test_util::FillIntTensor(subgraph_input0, {1});
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subgraph_test_util::FillIntTensor(subgraph_input1, {3, 4, 5});
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const TfLiteTensor* subgraph_output =
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interpreter.tensor(interpreter.outputs()[0]);
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// Neither input to ADD may be shared since they are subgraph inputs.
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EXPECT_NE(subgraph_input0->data.data, intermediate_tensor0->data.data);
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EXPECT_NE(subgraph_input1->data.data, intermediate_tensor1->data.data);
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// ADD_OFFSET allows sharing of input1, but not input0.
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EXPECT_EQ(intermediate_tensor1->data.data, intermediate_tensor2->data.data);
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// intermediate_tensor2 cannot be shared with a subgraph output.
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EXPECT_NE(intermediate_tensor2->data.data, subgraph_output->data.data);
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ASSERT_EQ(interpreter.Invoke(), kTfLiteOk);
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subgraph_test_util::CheckIntTensor(subgraph_output, {3}, {10, 12, 11});
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}
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TEST(ArenaPlannerSubgraphTest, HWTensor) {
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Interpreter interpreter;
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subgraph_test_util::SubgraphBuilder builder;
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builder.BuildInplaceOpSubgraph(&interpreter.primary_subgraph());
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ASSERT_EQ(interpreter.ResizeInputTensor(interpreter.inputs()[0], {2}),
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kTfLiteOk);
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ASSERT_EQ(interpreter.ResizeInputTensor(interpreter.inputs()[1], {2}),
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kTfLiteOk);
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TfLiteTensor* add_input0 = interpreter.tensor(interpreter.inputs()[0]);
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const TfLiteTensor* add_input1 = interpreter.tensor(interpreter.inputs()[1]);
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const int kIntermediateTensor0 = 2;
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const int kIntermediateTensor1 = 3;
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const TfLiteTensor* add_output = interpreter.tensor(kIntermediateTensor0);
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const TfLiteTensor* reshape_output = interpreter.tensor(kIntermediateTensor1);
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TfLiteTensor* subgraph_output = interpreter.tensor(interpreter.outputs()[0]);
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add_input0->allocation_type = kTfLiteNonCpu;
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subgraph_output->allocation_type = kTfLiteNonCpu;
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ASSERT_EQ(interpreter.AllocateTensors(), kTfLiteOk);
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// Non-CPU tensors shouldn't be allocated.
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EXPECT_EQ(add_input0->data.data, nullptr);
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EXPECT_EQ(subgraph_output->data.data, nullptr);
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// CPU tensors should be allocated.
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EXPECT_NE(add_input1->data.data, nullptr);
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EXPECT_NE(add_output->data.data, nullptr);
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EXPECT_NE(reshape_output->data.data, nullptr);
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}
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} // namespace
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} // namespace tflite
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