derek.holloway
7502bf64a4
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368 lines
17 KiB
C++
368 lines
17 KiB
C++
// Copyright © Advanced Micro Devices, Inc., or its affiliates.
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// SPDX-License-Identifier: MIT
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#include "BackendTestHelpers.hpp"
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#include "hipdnn_backend.h"
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#include <gtest/gtest.h>
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#include <hipdnn_flatbuffers_sdk/data_objects/convolution_common_generated.h>
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#include <hipdnn_test_sdk/constants/ConvFpropConstants.hpp>
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#include <hipdnn_test_sdk/utilities/TestUtilities.hpp>
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#include <test_plugins/TestPluginConstants.hpp>
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#include <vector>
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using namespace backend_test;
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using namespace hipdnn_tests::constants;
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class IntegrationConvOperationDescriptorApi : public ::testing::Test
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{
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protected:
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void SetUp() override
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{
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const std::array<const char*, 1> paths
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= {hipdnn_tests::plugin_constants::testGoodPluginPath().c_str()};
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ASSERT_EQ(hipdnnSetEnginePluginPaths_ext(
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paths.size(), paths.data(), HIPDNN_PLUGIN_LOADING_ABSOLUTE),
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HIPDNN_STATUS_SUCCESS);
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}
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void TearDown() override
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{
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for(auto* desc : _descriptors)
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{
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hipdnnBackendDestroyDescriptor(desc);
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}
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}
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hipdnnBackendDescriptor_t createAndTrackTensor(int64_t uid,
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const char* name,
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const std::vector<int64_t>& dims,
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const std::vector<int64_t>& strides)
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{
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auto desc = createAndFinalizeTensorDesc(uid, name, dims, strides);
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_descriptors.push_back(desc);
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return desc;
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}
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std::vector<hipdnnBackendDescriptor_t> _descriptors;
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};
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TEST_F(IntegrationConvOperationDescriptorApi, CreateAndFinalizeConvOperation)
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{
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auto xDesc = createAndTrackTensor(
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K_FPROP_TENSOR_X_UID, "X", toVec(K_FPROP_TENSOR_X_DIMS), toVec(K_FPROP_TENSOR_X_STRIDES));
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auto wDesc = createAndTrackTensor(
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K_FPROP_TENSOR_W_UID, "W", toVec(K_FPROP_TENSOR_W_DIMS), toVec(K_FPROP_TENSOR_W_STRIDES));
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auto yDesc = createAndTrackTensor(
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K_FPROP_TENSOR_Y_UID, "Y", toVec(K_FPROP_TENSOR_Y_DIMS), toVec(K_FPROP_TENSOR_Y_STRIDES));
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hipdnnBackendDescriptor_t opDesc = nullptr;
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ASSERT_EQ(hipdnnBackendCreateDescriptor(HIPDNN_BACKEND_OPERATION_CONVOLUTION_FORWARD_DESCRIPTOR,
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&opDesc),
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HIPDNN_STATUS_SUCCESS);
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_descriptors.push_back(opDesc);
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// Set tensor references
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EXPECT_EQ(hipdnnBackendSetAttribute(opDesc,
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HIPDNN_ATTR_OPERATION_CONVOLUTION_FORWARD_X,
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HIPDNN_TYPE_BACKEND_DESCRIPTOR,
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1,
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static_cast<const void*>(&xDesc)),
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HIPDNN_STATUS_SUCCESS);
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EXPECT_EQ(hipdnnBackendSetAttribute(opDesc,
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HIPDNN_ATTR_OPERATION_CONVOLUTION_FORWARD_W,
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HIPDNN_TYPE_BACKEND_DESCRIPTOR,
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1,
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static_cast<const void*>(&wDesc)),
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HIPDNN_STATUS_SUCCESS);
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EXPECT_EQ(hipdnnBackendSetAttribute(opDesc,
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HIPDNN_ATTR_OPERATION_CONVOLUTION_FORWARD_Y,
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HIPDNN_TYPE_BACKEND_DESCRIPTOR,
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1,
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static_cast<const void*>(&yDesc)),
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HIPDNN_STATUS_SUCCESS);
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// Set convolution parameters
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auto padding = toVec(K_FPROP_CONV_PADDING);
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auto stride = toVec(K_FPROP_CONV_STRIDE);
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auto dilation = toVec(K_FPROP_CONV_DILATION);
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EXPECT_EQ(hipdnnBackendSetAttribute(opDesc,
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HIPDNN_ATTR_CONVOLUTION_PRE_PADDINGS,
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HIPDNN_TYPE_INT64,
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static_cast<int64_t>(padding.size()),
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padding.data()),
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HIPDNN_STATUS_SUCCESS);
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EXPECT_EQ(hipdnnBackendSetAttribute(opDesc,
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HIPDNN_ATTR_CONVOLUTION_POST_PADDINGS,
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HIPDNN_TYPE_INT64,
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static_cast<int64_t>(padding.size()),
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padding.data()),
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HIPDNN_STATUS_SUCCESS);
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EXPECT_EQ(hipdnnBackendSetAttribute(opDesc,
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HIPDNN_ATTR_CONVOLUTION_FILTER_STRIDES,
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HIPDNN_TYPE_INT64,
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static_cast<int64_t>(stride.size()),
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stride.data()),
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HIPDNN_STATUS_SUCCESS);
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EXPECT_EQ(hipdnnBackendSetAttribute(opDesc,
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HIPDNN_ATTR_CONVOLUTION_DILATIONS,
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HIPDNN_TYPE_INT64,
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static_cast<int64_t>(dilation.size()),
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dilation.data()),
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HIPDNN_STATUS_SUCCESS);
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hipdnnConvolutionMode_t convMode = HIPDNN_CROSS_CORRELATION;
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EXPECT_EQ(
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hipdnnBackendSetAttribute(
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opDesc, HIPDNN_ATTR_CONVOLUTION_CONV_MODE, HIPDNN_TYPE_CONVOLUTION_MODE, 1, &convMode),
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HIPDNN_STATUS_SUCCESS);
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auto computeType = HIPDNN_DATA_FLOAT;
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EXPECT_EQ(
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hipdnnBackendSetAttribute(
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opDesc, HIPDNN_ATTR_CONVOLUTION_COMP_TYPE, HIPDNN_TYPE_DATA_TYPE, 1, &computeType),
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HIPDNN_STATUS_SUCCESS);
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EXPECT_EQ(hipdnnBackendFinalize(opDesc), HIPDNN_STATUS_SUCCESS);
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}
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TEST_F(IntegrationConvOperationDescriptorApi, GetAfterSetVerifiesAllAttributes)
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{
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auto xDesc = createAndTrackTensor(
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K_FPROP_TENSOR_X_UID, "X", toVec(K_FPROP_TENSOR_X_DIMS), toVec(K_FPROP_TENSOR_X_STRIDES));
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auto wDesc = createAndTrackTensor(
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K_FPROP_TENSOR_W_UID, "W", toVec(K_FPROP_TENSOR_W_DIMS), toVec(K_FPROP_TENSOR_W_STRIDES));
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auto yDesc = createAndTrackTensor(
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K_FPROP_TENSOR_Y_UID, "Y", toVec(K_FPROP_TENSOR_Y_DIMS), toVec(K_FPROP_TENSOR_Y_STRIDES));
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hipdnnBackendDescriptor_t opDesc = nullptr;
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ASSERT_EQ(hipdnnBackendCreateDescriptor(HIPDNN_BACKEND_OPERATION_CONVOLUTION_FORWARD_DESCRIPTOR,
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&opDesc),
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HIPDNN_STATUS_SUCCESS);
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_descriptors.push_back(opDesc);
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// Set tensor references
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EXPECT_EQ(hipdnnBackendSetAttribute(opDesc,
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HIPDNN_ATTR_OPERATION_CONVOLUTION_FORWARD_X,
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HIPDNN_TYPE_BACKEND_DESCRIPTOR,
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1,
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static_cast<const void*>(&xDesc)),
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HIPDNN_STATUS_SUCCESS);
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EXPECT_EQ(hipdnnBackendSetAttribute(opDesc,
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HIPDNN_ATTR_OPERATION_CONVOLUTION_FORWARD_W,
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HIPDNN_TYPE_BACKEND_DESCRIPTOR,
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1,
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static_cast<const void*>(&wDesc)),
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HIPDNN_STATUS_SUCCESS);
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EXPECT_EQ(hipdnnBackendSetAttribute(opDesc,
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HIPDNN_ATTR_OPERATION_CONVOLUTION_FORWARD_Y,
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HIPDNN_TYPE_BACKEND_DESCRIPTOR,
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1,
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static_cast<const void*>(&yDesc)),
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HIPDNN_STATUS_SUCCESS);
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// Set convolution parameters
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auto padding = toVec(K_FPROP_CONV_PADDING);
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auto stride = toVec(K_FPROP_CONV_STRIDE);
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auto dilation = toVec(K_FPROP_CONV_DILATION);
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EXPECT_EQ(hipdnnBackendSetAttribute(opDesc,
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HIPDNN_ATTR_CONVOLUTION_PRE_PADDINGS,
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HIPDNN_TYPE_INT64,
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static_cast<int64_t>(padding.size()),
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padding.data()),
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HIPDNN_STATUS_SUCCESS);
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EXPECT_EQ(hipdnnBackendSetAttribute(opDesc,
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HIPDNN_ATTR_CONVOLUTION_POST_PADDINGS,
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HIPDNN_TYPE_INT64,
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static_cast<int64_t>(padding.size()),
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padding.data()),
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HIPDNN_STATUS_SUCCESS);
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EXPECT_EQ(hipdnnBackendSetAttribute(opDesc,
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HIPDNN_ATTR_CONVOLUTION_FILTER_STRIDES,
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HIPDNN_TYPE_INT64,
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static_cast<int64_t>(stride.size()),
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stride.data()),
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HIPDNN_STATUS_SUCCESS);
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EXPECT_EQ(hipdnnBackendSetAttribute(opDesc,
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HIPDNN_ATTR_CONVOLUTION_DILATIONS,
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HIPDNN_TYPE_INT64,
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static_cast<int64_t>(dilation.size()),
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dilation.data()),
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HIPDNN_STATUS_SUCCESS);
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hipdnnConvolutionMode_t convMode = HIPDNN_CROSS_CORRELATION;
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EXPECT_EQ(
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hipdnnBackendSetAttribute(
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opDesc, HIPDNN_ATTR_CONVOLUTION_CONV_MODE, HIPDNN_TYPE_CONVOLUTION_MODE, 1, &convMode),
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HIPDNN_STATUS_SUCCESS);
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auto computeType = HIPDNN_DATA_FLOAT;
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EXPECT_EQ(
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hipdnnBackendSetAttribute(
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opDesc, HIPDNN_ATTR_CONVOLUTION_COMP_TYPE, HIPDNN_TYPE_DATA_TYPE, 1, &computeType),
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HIPDNN_STATUS_SUCCESS);
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ASSERT_EQ(hipdnnBackendFinalize(opDesc), HIPDNN_STATUS_SUCCESS);
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// Verify tensor descriptor references via getAttribute
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int64_t elementCount = 0;
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hipdnnBackendDescriptor_t retrievedDesc = nullptr;
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EXPECT_EQ(hipdnnBackendGetAttribute(opDesc,
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HIPDNN_ATTR_OPERATION_CONVOLUTION_FORWARD_X,
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HIPDNN_TYPE_BACKEND_DESCRIPTOR,
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1,
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&elementCount,
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static_cast<void*>(&retrievedDesc)),
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HIPDNN_STATUS_SUCCESS);
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EXPECT_EQ(elementCount, 1);
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EXPECT_NE(retrievedDesc, nullptr);
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_descriptors.push_back(retrievedDesc);
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elementCount = 0;
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retrievedDesc = nullptr;
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EXPECT_EQ(hipdnnBackendGetAttribute(opDesc,
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HIPDNN_ATTR_OPERATION_CONVOLUTION_FORWARD_W,
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HIPDNN_TYPE_BACKEND_DESCRIPTOR,
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1,
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&elementCount,
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static_cast<void*>(&retrievedDesc)),
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HIPDNN_STATUS_SUCCESS);
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EXPECT_EQ(elementCount, 1);
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EXPECT_NE(retrievedDesc, nullptr);
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_descriptors.push_back(retrievedDesc);
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elementCount = 0;
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retrievedDesc = nullptr;
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EXPECT_EQ(hipdnnBackendGetAttribute(opDesc,
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HIPDNN_ATTR_OPERATION_CONVOLUTION_FORWARD_Y,
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HIPDNN_TYPE_BACKEND_DESCRIPTOR,
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1,
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&elementCount,
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static_cast<void*>(&retrievedDesc)),
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HIPDNN_STATUS_SUCCESS);
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EXPECT_EQ(elementCount, 1);
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EXPECT_NE(retrievedDesc, nullptr);
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_descriptors.push_back(retrievedDesc);
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// Verify convolution parameter arrays
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std::vector<int64_t> retrievedPadding(2, 0);
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elementCount = 0;
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EXPECT_EQ(hipdnnBackendGetAttribute(opDesc,
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HIPDNN_ATTR_CONVOLUTION_PRE_PADDINGS,
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HIPDNN_TYPE_INT64,
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2,
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&elementCount,
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retrievedPadding.data()),
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HIPDNN_STATUS_SUCCESS);
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EXPECT_EQ(elementCount, 2);
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EXPECT_EQ(retrievedPadding, padding);
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std::vector<int64_t> retrievedPostPadding(2, 0);
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elementCount = 0;
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EXPECT_EQ(hipdnnBackendGetAttribute(opDesc,
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HIPDNN_ATTR_CONVOLUTION_POST_PADDINGS,
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HIPDNN_TYPE_INT64,
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2,
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&elementCount,
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retrievedPostPadding.data()),
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HIPDNN_STATUS_SUCCESS);
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EXPECT_EQ(elementCount, 2);
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EXPECT_EQ(retrievedPostPadding, padding);
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std::vector<int64_t> retrievedStride(2, 0);
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elementCount = 0;
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EXPECT_EQ(hipdnnBackendGetAttribute(opDesc,
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HIPDNN_ATTR_CONVOLUTION_FILTER_STRIDES,
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HIPDNN_TYPE_INT64,
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2,
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&elementCount,
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retrievedStride.data()),
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HIPDNN_STATUS_SUCCESS);
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EXPECT_EQ(elementCount, 2);
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EXPECT_EQ(retrievedStride, stride);
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std::vector<int64_t> retrievedDilation(2, 0);
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elementCount = 0;
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EXPECT_EQ(hipdnnBackendGetAttribute(opDesc,
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HIPDNN_ATTR_CONVOLUTION_DILATIONS,
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HIPDNN_TYPE_INT64,
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2,
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&elementCount,
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retrievedDilation.data()),
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HIPDNN_STATUS_SUCCESS);
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EXPECT_EQ(elementCount, 2);
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EXPECT_EQ(retrievedDilation, dilation);
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// Verify conv mode
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hipdnnConvolutionMode_t retrievedConvMode = {};
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elementCount = 0;
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EXPECT_EQ(hipdnnBackendGetAttribute(opDesc,
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HIPDNN_ATTR_CONVOLUTION_CONV_MODE,
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HIPDNN_TYPE_CONVOLUTION_MODE,
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1,
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&elementCount,
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&retrievedConvMode),
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HIPDNN_STATUS_SUCCESS);
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EXPECT_EQ(elementCount, 1);
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EXPECT_EQ(retrievedConvMode, HIPDNN_CROSS_CORRELATION);
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// Verify compute type
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hipdnnDataType_t retrievedCompType = {};
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elementCount = 0;
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EXPECT_EQ(hipdnnBackendGetAttribute(opDesc,
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HIPDNN_ATTR_CONVOLUTION_COMP_TYPE,
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HIPDNN_TYPE_DATA_TYPE,
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1,
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&elementCount,
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&retrievedCompType),
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HIPDNN_STATUS_SUCCESS);
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EXPECT_EQ(elementCount, 1);
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EXPECT_EQ(retrievedCompType, HIPDNN_DATA_FLOAT);
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}
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TEST_F(IntegrationConvOperationDescriptorApi, ConvOperationFailsWithoutTensorRefs)
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{
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hipdnnBackendDescriptor_t opDesc = nullptr;
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ASSERT_EQ(hipdnnBackendCreateDescriptor(HIPDNN_BACKEND_OPERATION_CONVOLUTION_FORWARD_DESCRIPTOR,
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&opDesc),
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HIPDNN_STATUS_SUCCESS);
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_descriptors.push_back(opDesc);
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// Set conv params but omit tensor references
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auto padding = toVec(K_FPROP_CONV_PADDING);
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auto stride = toVec(K_FPROP_CONV_STRIDE);
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auto dilation = toVec(K_FPROP_CONV_DILATION);
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hipdnnBackendSetAttribute(opDesc,
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HIPDNN_ATTR_CONVOLUTION_PRE_PADDINGS,
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HIPDNN_TYPE_INT64,
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static_cast<int64_t>(padding.size()),
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padding.data());
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hipdnnBackendSetAttribute(opDesc,
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HIPDNN_ATTR_CONVOLUTION_POST_PADDINGS,
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HIPDNN_TYPE_INT64,
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static_cast<int64_t>(padding.size()),
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padding.data());
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hipdnnBackendSetAttribute(opDesc,
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HIPDNN_ATTR_CONVOLUTION_FILTER_STRIDES,
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HIPDNN_TYPE_INT64,
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static_cast<int64_t>(stride.size()),
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stride.data());
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hipdnnBackendSetAttribute(opDesc,
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HIPDNN_ATTR_CONVOLUTION_DILATIONS,
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HIPDNN_TYPE_INT64,
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static_cast<int64_t>(dilation.size()),
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dilation.data());
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hipdnnConvolutionMode_t convMode = HIPDNN_CROSS_CORRELATION;
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hipdnnBackendSetAttribute(
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opDesc, HIPDNN_ATTR_CONVOLUTION_CONV_MODE, HIPDNN_TYPE_CONVOLUTION_MODE, 1, &convMode);
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auto computeType = HIPDNN_DATA_FLOAT;
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hipdnnBackendSetAttribute(
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opDesc, HIPDNN_ATTR_CONVOLUTION_COMP_TYPE, HIPDNN_TYPE_DATA_TYPE, 1, &computeType);
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EXPECT_NE(hipdnnBackendFinalize(opDesc), HIPDNN_STATUS_SUCCESS);
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}
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