wehub-resource-sync
96 lines
3.3 KiB
C++
96 lines
3.3 KiB
C++
/* Copyright 2024 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 <cstdint>
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#include <vector>
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#include <gmock/gmock.h>
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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/core/subgraph.h"
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#include "tensorflow/lite/kernels/test_util.h"
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#include "tensorflow/lite/schema/schema_generated.h"
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namespace tflite {
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namespace {
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using ::testing::ElementsAre;
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class AndOpModel : public SingleOpModel {
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public:
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AndOpModel(const TensorData& input1, const TensorData& input2,
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const TensorData& output) {
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input1_ = AddInput(input1);
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input2_ = AddInput(input2);
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output_ = AddOutput(output);
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SetBuiltinOp(BuiltinOperator_STABLEHLO_AND, BuiltinOptions_NONE, 0);
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SetBypassDefaultDelegates();
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BuildInterpreter({GetShape(input1_), GetShape(input2_)});
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}
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int input1() { return input1_; }
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int input2() { return input2_; }
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template <typename T>
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std::vector<T> GetOutput() {
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return ExtractVector<T>(output_);
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}
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protected:
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int input1_;
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int input2_;
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int output_;
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};
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TEST(StablehloElementwise, AndInt32) {
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AndOpModel model({TensorType_INT32, {1, 2, 2, 1}},
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{TensorType_INT32, {1, 2, 2, 1}}, {TensorType_INT32, {}});
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model.PopulateTensor<int32_t>(model.input1(), {2, 3, 7, 8});
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model.PopulateTensor<int32_t>(model.input2(), {4, 5, 7, 1});
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ASSERT_EQ(model.Invoke(), kTfLiteOk);
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EXPECT_THAT(model.GetOutput<int32_t>(), ElementsAre(0, 1, 7, 0));
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}
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TEST(StablehloElementwise, AndInt8) {
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AndOpModel model({TensorType_INT8, {1, 3, 1}}, {TensorType_INT8, {1, 3, 1}},
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{TensorType_INT8, {}});
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model.PopulateTensor<int8_t>(model.input1(), {7, -8, -8});
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model.PopulateTensor<int8_t>(model.input2(), {0, 7, -8});
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ASSERT_EQ(model.Invoke(), kTfLiteOk);
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EXPECT_THAT(model.GetOutput<int8_t>(), ElementsAre(0, 0, -8));
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}
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TEST(StablehloElementwise, AndInt16) {
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AndOpModel model({TensorType_INT16, {1, 1, 3}}, {TensorType_INT16, {1, 1, 3}},
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{TensorType_INT16, {}});
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model.PopulateTensor<int16_t>(model.input1(), {32767, -32768, -32768});
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model.PopulateTensor<int16_t>(model.input2(), {32767, -32768, -32768});
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ASSERT_EQ(model.Invoke(), kTfLiteOk);
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EXPECT_THAT(model.GetOutput<int16_t>(), ElementsAre(32767, -32768, -32768));
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}
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TEST(StablehloElementwise, AndBool) {
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AndOpModel model({TensorType_BOOL, {2, 1, 2, 1}},
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{TensorType_BOOL, {2, 1, 2, 1}}, {TensorType_BOOL, {}});
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model.PopulateTensor<bool>(model.input1(), {false, false, true, true});
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model.PopulateTensor<bool>(model.input2(), {false, true, false, true});
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ASSERT_EQ(model.Invoke(), kTfLiteOk);
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EXPECT_THAT(model.GetOutput<bool>(), ElementsAre(false, false, false, true));
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}
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} // namespace
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} // namespace tflite
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