204 lines
7.0 KiB
C++
204 lines
7.0 KiB
C++
/****************************************************************************
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*
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* Copyright (c) 2021 Vivante Corporation
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*
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* Permission is hereby granted, free of charge, to any person obtaining a
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* copy of this software and associated documentation files (the "Software"),
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* to deal in the Software without restriction, including without limitation
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* the rights to use, copy, modify, merge, publish, distribute, sublicense,
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* and/or sell copies of the Software, and to permit persons to whom the
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* Software is furnished to do so, subject to the following conditions:
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*
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* The above copyright notice and this permission notice shall be included in
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* all copies or substantial portions of the Software.
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*
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* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
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* FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
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* DEALINGS IN THE SOFTWARE.
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*
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*****************************************************************************/
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#include "tim/vx/context.h"
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#include "tim/vx/graph.h"
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#include "tim/vx/ops/matmul.h"
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#include "gtest/gtest.h"
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namespace {
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template<typename T>
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::testing::AssertionResult ArraysMatch(const std::vector<T>& expected,
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const std::vector<T>& actual,
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T abs_error){
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for (size_t i = 0; i < expected.size(); ++i){
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EXPECT_NEAR(expected[i], actual[i], abs_error) << "at index:" << i;
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}
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return ::testing::AssertionSuccess();
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}
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}
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TEST(Matmul, shape_2_6_shape_6_2_float) {
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auto ctx = tim::vx::Context::Create();
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auto graph = ctx->CreateGraph();
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tim::vx::ShapeType a_shape({6, 2});
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tim::vx::ShapeType b_shape({2, 6});
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tim::vx::ShapeType out_shape({2, 2});
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tim::vx::TensorSpec a_spec(tim::vx::DataType::FLOAT32,
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a_shape, tim::vx::TensorAttribute::INPUT);
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tim::vx::TensorSpec b_spec(tim::vx::DataType::FLOAT32,
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b_shape, tim::vx::TensorAttribute::INPUT);
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tim::vx::TensorSpec out_spec(tim::vx::DataType::FLOAT32,
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out_shape, tim::vx::TensorAttribute::OUTPUT);
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auto a_tensor = graph->CreateTensor(a_spec);
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auto b_tensor = graph->CreateTensor(b_spec);
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auto out_tensor = graph->CreateTensor(out_spec);
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std::vector<float> a_data = {
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1, 2, 3, 4, 5, 6,
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-1, -2, -3, -4, -5, -6
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};
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std::vector<float> b_data = {
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6, 5,
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4, 3,
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2, 1,
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-6, -5,
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-4, -3,
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-2, -1
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};
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std::vector<float> golden = {
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-36, -27,
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36, 27
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};
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EXPECT_TRUE(a_tensor->CopyDataToTensor(a_data.data(), a_data.size() * sizeof(float)));
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EXPECT_TRUE(b_tensor->CopyDataToTensor(b_data.data(), b_data.size() * sizeof(float)));
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auto op = graph->CreateOperation<tim::vx::ops::Matmul>();
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(*op).BindInputs({a_tensor, b_tensor}).BindOutputs({out_tensor});
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EXPECT_TRUE(graph->Compile());
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EXPECT_TRUE(graph->Run());
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std::vector<float> output(golden.size());
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EXPECT_TRUE(out_tensor->CopyDataFromTensor(output.data()));
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EXPECT_TRUE(ArraysMatch(golden, output, 1e-5f));
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}
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TEST(Matmul, shape_2_3_2_shape_2_3_2_float_transpose_b) {
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auto ctx = tim::vx::Context::Create();
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auto graph = ctx->CreateGraph();
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tim::vx::ShapeType a_shape({2, 3, 2});
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tim::vx::ShapeType b_shape({2, 3, 2});
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tim::vx::ShapeType out_shape({3, 3, 2});
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tim::vx::TensorSpec a_spec(tim::vx::DataType::FLOAT32,
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a_shape, tim::vx::TensorAttribute::INPUT);
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tim::vx::TensorSpec b_spec(tim::vx::DataType::FLOAT32,
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b_shape, tim::vx::TensorAttribute::INPUT);
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tim::vx::TensorSpec out_spec(tim::vx::DataType::FLOAT32,
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out_shape, tim::vx::TensorAttribute::OUTPUT);
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auto a_tensor = graph->CreateTensor(a_spec);
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auto b_tensor = graph->CreateTensor(b_spec);
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auto out_tensor = graph->CreateTensor(out_spec);
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std::vector<float> a_data = {
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1, 2,
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3, 4,
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5, 6,
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-1, -2,
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-3, -4,
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-5, -6
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};
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std::vector<float> b_data = {
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6, 5,
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4, 3,
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2, 1,
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-6, -5,
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-4, -3,
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-2, -1
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};
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std::vector<float> golden = {
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16, 10, 4,
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38, 24, 10,
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60, 38, 16,
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16, 10, 4,
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38, 24, 10,
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60, 38, 16,
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};
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EXPECT_TRUE(a_tensor->CopyDataToTensor(a_data.data(), a_data.size() * sizeof(float)));
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EXPECT_TRUE(b_tensor->CopyDataToTensor(b_data.data(), b_data.size() * sizeof(float)));
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auto op = graph->CreateOperation<tim::vx::ops::Matmul>(false, true);
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(*op).BindInputs({a_tensor, b_tensor}).BindOutputs({out_tensor});
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EXPECT_TRUE(graph->Compile());
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EXPECT_TRUE(graph->Run());
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std::vector<float> output(golden.size() * sizeof(float));
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EXPECT_TRUE(out_tensor->CopyDataFromTensor(output.data()));
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EXPECT_TRUE(ArraysMatch(golden, output, 1e-5f));
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}
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TEST(Matmul, shape_2_3_2_shape_2_3_2_uint8_transpose_a) {
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auto ctx = tim::vx::Context::Create();
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auto graph = ctx->CreateGraph();
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tim::vx::ShapeType a_shape({2, 3, 2});
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tim::vx::ShapeType b_shape({2, 3, 2});
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tim::vx::ShapeType out_shape({2, 2, 2});
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tim::vx::Quantization input_quant(tim::vx::QuantType::ASYMMETRIC, 1, 6);
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tim::vx::Quantization output_quant(tim::vx::QuantType::ASYMMETRIC, 1, 0);
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tim::vx::TensorSpec a_spec(tim::vx::DataType::UINT8,
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a_shape, tim::vx::TensorAttribute::INPUT, input_quant);
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tim::vx::TensorSpec b_spec(tim::vx::DataType::UINT8,
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b_shape, tim::vx::TensorAttribute::INPUT, input_quant);
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tim::vx::TensorSpec out_spec(tim::vx::DataType::UINT8,
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out_shape, tim::vx::TensorAttribute::OUTPUT, output_quant);
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auto a_tensor = graph->CreateTensor(a_spec);
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auto b_tensor = graph->CreateTensor(b_spec);
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auto out_tensor = graph->CreateTensor(out_spec);
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std::vector<uint8_t> a_data = {
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7, 8,
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9, 10,
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11, 12,
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5, 4,
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3, 2,
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1, 0,
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};
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std::vector<uint8_t> b_data = {
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12, 11,
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10, 9,
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8, 7,
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0, 1,
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2, 3,
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4, 5,
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};
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std::vector<uint8_t> golden = {
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28, 19,
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40, 28,
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28, 19,
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40, 28,
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};
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EXPECT_TRUE(a_tensor->CopyDataToTensor(a_data.data(), a_data.size()));
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EXPECT_TRUE(b_tensor->CopyDataToTensor(b_data.data(), b_data.size()));
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auto op = graph->CreateOperation<tim::vx::ops::Matmul>(true);
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(*op).BindInputs({a_tensor, b_tensor}).BindOutputs({out_tensor});
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EXPECT_TRUE(graph->Compile());
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EXPECT_TRUE(graph->Run());
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std::vector<uint8_t> output(golden.size());
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EXPECT_TRUE(out_tensor->CopyDataFromTensor(output.data()));
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EXPECT_EQ(golden, output);
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} |