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242 lines
8.6 KiB
C++
242 lines
8.6 KiB
C++
// Copyright © Advanced Micro Devices, Inc., or its affiliates.
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// SPDX-License-Identifier: MIT
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#include <gtest/gtest.h>
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#include <hipdnn_frontend/attributes/ConvolutionFpropAttributes.hpp>
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TEST(TestConvolutionFwdAttributes, CreateConvolutionFwdAttributes)
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{
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hipdnn_frontend::graph::ConvFpropAttributes convAttributes;
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// Set tensors
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convAttributes.set_x(std::make_shared<hipdnn_frontend::graph::TensorAttributes>());
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convAttributes.set_w(std::make_shared<hipdnn_frontend::graph::TensorAttributes>());
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convAttributes.set_y(std::make_shared<hipdnn_frontend::graph::TensorAttributes>());
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// Set convolution parameters
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convAttributes.set_pre_padding({1, 1});
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convAttributes.set_post_padding({1, 1});
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convAttributes.set_stride({1, 1});
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convAttributes.set_dilation({1, 1});
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convAttributes.set_convolution_mode(hipdnn_frontend::ConvolutionMode::CROSS_CORRELATION);
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// Configure input tensor
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auto xTensor = convAttributes.get_x();
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xTensor->set_uid(1)
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.set_name("InputTensor")
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.set_data_type(hipdnn_frontend::DataType::FLOAT)
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.set_dim({1, 3, 32, 32}) // NCHW format
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.set_stride({3072, 1024, 32, 1});
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// Configure weights tensor
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auto wTensor = convAttributes.get_w();
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wTensor->set_uid(2)
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.set_name("WeightsTensor")
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.set_data_type(hipdnn_frontend::DataType::FLOAT)
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.set_dim({64, 3, 3, 3}) // KCHW format
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.set_stride({27, 9, 3, 1});
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// Configure output tensor
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auto yTensor = convAttributes.get_y();
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yTensor->set_uid(3)
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.set_name("OutputTensor")
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.set_data_type(hipdnn_frontend::DataType::FLOAT)
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.set_dim({1, 64, 32, 32}) // NCHW format
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.set_stride({65536, 1024, 32, 1});
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// Verify tensor attributes
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EXPECT_EQ(xTensor->get_uid(), 1);
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EXPECT_EQ(xTensor->get_name(), "InputTensor");
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EXPECT_EQ(xTensor->get_data_type(), hipdnn_frontend::DataType::FLOAT);
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EXPECT_EQ(xTensor->get_dim(), (std::vector<int64_t>{1, 3, 32, 32}));
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EXPECT_EQ(xTensor->get_stride(), (std::vector<int64_t>{3072, 1024, 32, 1}));
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EXPECT_EQ(wTensor->get_uid(), 2);
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EXPECT_EQ(wTensor->get_name(), "WeightsTensor");
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EXPECT_EQ(wTensor->get_data_type(), hipdnn_frontend::DataType::FLOAT);
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EXPECT_EQ(wTensor->get_dim(), (std::vector<int64_t>{64, 3, 3, 3}));
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EXPECT_EQ(wTensor->get_stride(), (std::vector<int64_t>{27, 9, 3, 1}));
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EXPECT_EQ(yTensor->get_uid(), 3);
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EXPECT_EQ(yTensor->get_name(), "OutputTensor");
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EXPECT_EQ(yTensor->get_data_type(), hipdnn_frontend::DataType::FLOAT);
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EXPECT_EQ(yTensor->get_dim(), (std::vector<int64_t>{1, 64, 32, 32}));
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EXPECT_EQ(yTensor->get_stride(), (std::vector<int64_t>{65536, 1024, 32, 1}));
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// Verify convolution parameters
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EXPECT_EQ(convAttributes.get_pre_padding(), (std::vector<int64_t>{1, 1}));
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EXPECT_EQ(convAttributes.get_post_padding(), (std::vector<int64_t>{1, 1}));
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EXPECT_EQ(convAttributes.get_stride(), (std::vector<int64_t>{1, 1}));
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EXPECT_EQ(convAttributes.get_dilation(), (std::vector<int64_t>{1, 1}));
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EXPECT_EQ(convAttributes.get_convolution_mode(),
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hipdnn_frontend::ConvolutionMode::CROSS_CORRELATION);
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}
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TEST(TestConvolutionFwdAttributes, DefaultValues)
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{
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const hipdnn_frontend::graph::ConvFpropAttributes convAttributes;
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// Check default convolution mode
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EXPECT_EQ(convAttributes.get_convolution_mode(),
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hipdnn_frontend::ConvolutionMode::CROSS_CORRELATION);
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// Check that parameters are empty by default
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EXPECT_TRUE(convAttributes.get_pre_padding().empty());
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EXPECT_TRUE(convAttributes.get_post_padding().empty());
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EXPECT_TRUE(convAttributes.get_stride().empty());
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EXPECT_TRUE(convAttributes.get_dilation().empty());
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// Check that tensors are null by default
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EXPECT_EQ(convAttributes.get_x(), nullptr);
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EXPECT_EQ(convAttributes.get_w(), nullptr);
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EXPECT_EQ(convAttributes.get_y(), nullptr);
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}
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TEST(TestConvolutionFwdAttributes, SetPrePaddingWithMove)
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{
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hipdnn_frontend::graph::ConvFpropAttributes convAttributes;
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std::vector<int64_t> prePaddingMove = {3, 3};
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convAttributes.set_pre_padding(std::move(prePaddingMove));
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EXPECT_EQ(convAttributes.get_pre_padding(), (std::vector<int64_t>{3, 3}));
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}
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TEST(TestConvolutionFwdAttributes, SetPostPaddingWithMove)
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{
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hipdnn_frontend::graph::ConvFpropAttributes convAttributes;
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std::vector<int64_t> postPaddingMove = {4, 4};
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convAttributes.set_post_padding(std::move(postPaddingMove));
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EXPECT_EQ(convAttributes.get_post_padding(), (std::vector<int64_t>{4, 4}));
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}
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TEST(TestConvolutionFwdAttributes, SetStrideWithMove)
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{
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hipdnn_frontend::graph::ConvFpropAttributes convAttributes;
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std::vector<int64_t> strideMove = {2, 2};
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convAttributes.set_stride(std::move(strideMove));
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EXPECT_EQ(convAttributes.get_stride(), (std::vector<int64_t>{2, 2}));
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}
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TEST(TestConvolutionFwdAttributes, SetDilationWithMove)
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{
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hipdnn_frontend::graph::ConvFpropAttributes convAttributes;
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std::vector<int64_t> dilationMove = {2, 2};
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convAttributes.set_dilation(std::move(dilationMove));
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EXPECT_EQ(convAttributes.get_dilation(), (std::vector<int64_t>{2, 2}));
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}
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TEST(TestConvolutionFwdAttributes, SetPaddingBothPreAndPost)
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{
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hipdnn_frontend::graph::ConvFpropAttributes convAttributes;
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const std::vector<int64_t> padding = {5, 5};
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convAttributes.set_padding(padding);
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// set_padding should set both pre and post padding to the same value
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EXPECT_EQ(convAttributes.get_pre_padding(), (std::vector<int64_t>{5, 5}));
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EXPECT_EQ(convAttributes.get_post_padding(), (std::vector<int64_t>{5, 5}));
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}
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TEST(TestConvolutionFwdAttributes, SetXMove)
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{
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hipdnn_frontend::graph::ConvFpropAttributes convAttributes;
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auto xTensor = std::make_shared<hipdnn_frontend::graph::TensorAttributes>();
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xTensor->set_uid(10)
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.set_name("MovedInputTensor")
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.set_data_type(hipdnn_frontend::DataType::FLOAT)
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.set_dim({1, 3, 224, 224})
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.set_stride({150528, 50176, 224, 1});
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// Store the raw pointer before moving
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auto rawPtr = xTensor.get();
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convAttributes.set_x(std::move(xTensor));
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// After move, xTensor should be nullptr
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EXPECT_EQ(xTensor, nullptr);
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// The moved tensor should be accessible through get_x()
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auto retrievedTensor = convAttributes.get_x();
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EXPECT_EQ(retrievedTensor.get(), rawPtr);
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}
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TEST(TestConvolutionFwdAttributes, SetWMove)
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{
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hipdnn_frontend::graph::ConvFpropAttributes convAttributes;
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auto wTensor = std::make_shared<hipdnn_frontend::graph::TensorAttributes>();
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wTensor->set_uid(20)
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.set_name("MovedWeightTensor")
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.set_data_type(hipdnn_frontend::DataType::HALF)
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.set_dim({128, 64, 5, 5})
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.set_stride({1600, 25, 5, 1});
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// Store the raw pointer before moving
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auto rawPtr = wTensor.get();
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convAttributes.set_w(std::move(wTensor));
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// After move, wTensor should be nullptr
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EXPECT_EQ(wTensor, nullptr);
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// The moved tensor should be accessible through get_w()
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auto retrievedTensor = convAttributes.get_w();
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EXPECT_EQ(retrievedTensor.get(), rawPtr);
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}
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TEST(TestConvolutionFwdAttributes, SetYWithMove)
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{
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hipdnn_frontend::graph::ConvFpropAttributes convAttributes;
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auto yTensor = std::make_shared<hipdnn_frontend::graph::TensorAttributes>();
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yTensor->set_uid(30)
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.set_name("MovedOutputTensor")
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.set_data_type(hipdnn_frontend::DataType::BFLOAT16)
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.set_dim({1, 128, 112, 112})
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.set_stride({1605632, 12544, 112, 1});
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// Store the raw pointer before moving
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auto rawPtr = yTensor.get();
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convAttributes.set_y(std::move(yTensor));
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// After move, yTensor should be nullptr
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EXPECT_EQ(yTensor, nullptr);
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// The moved tensor should be accessible through get_y()
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auto retrievedTensor = convAttributes.get_y();
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EXPECT_EQ(retrievedTensor.get(), rawPtr);
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}
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TEST(TestConvolutionFwdAttributes, SetTensorsConstRef)
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{
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hipdnn_frontend::graph::ConvFpropAttributes convAttributes;
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// Create tensors
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auto xTensor = std::make_shared<hipdnn_frontend::graph::TensorAttributes>();
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xTensor->set_uid(40).set_name("InputConstRef");
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auto wTensor = std::make_shared<hipdnn_frontend::graph::TensorAttributes>();
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wTensor->set_uid(50).set_name("WeightConstRef");
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auto yTensor = std::make_shared<hipdnn_frontend::graph::TensorAttributes>();
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yTensor->set_uid(60).set_name("OutputConstRef");
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// Set using const reference (copy)
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convAttributes.set_x(xTensor);
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convAttributes.set_w(wTensor);
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convAttributes.set_y(yTensor);
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// Original tensors should still be valid
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EXPECT_NE(xTensor, nullptr);
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EXPECT_NE(wTensor, nullptr);
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EXPECT_NE(yTensor, nullptr);
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}
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