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391 lines
16 KiB
C++
391 lines
16 KiB
C++
// Copyright © Advanced Micro Devices, Inc., or its affiliates.
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// SPDX-License-Identifier: MIT
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#include "HipdnnOperationType.h"
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#include "TensorDescriptorTestUtils.hpp"
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#include "TestMacros.hpp"
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#include "descriptors/BlockScaleDequantizeOperationDescriptor.hpp"
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#include "descriptors/NodeFactory.hpp"
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#include "descriptors/ScopedDescriptor.hpp"
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#include "descriptors/TensorDescriptor.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/block_scale_dequantize_attributes_generated.h>
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#include <hipdnn_flatbuffers_sdk/data_objects/graph_generated.h>
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#include <hipdnn_flatbuffers_sdk/data_objects/tensor_attributes_generated.h>
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#include <hipdnn_test_sdk/constants/BlockScaleDequantizeConstants.hpp>
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#include <hipdnn_test_sdk/utilities/ToVec.hpp>
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#include <memory>
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#include <unordered_map>
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#include <vector>
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using namespace hipdnn_backend;
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using namespace hipdnn_flatbuffers_sdk::data_objects;
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using namespace hipdnn_tests::constants;
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using hipdnn_tests::toVec;
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// =============================================================================
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// BlockScaleDequantizeOperationDescriptor::fromNode() Tests
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// =============================================================================
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class TestBlockScaleDequantizeOperationFromNode : public ::testing::Test
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{
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protected:
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std::unordered_map<int64_t, std::shared_ptr<TensorDescriptor>> _tensorMap;
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void SetUp() override
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{
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TensorAttributesT xAttrs;
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xAttrs.uid = K_BSD_TENSOR_X_UID;
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xAttrs.data_type = DataType::FLOAT;
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xAttrs.dims = toVec(K_BSD_TENSOR_X_DIMS);
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xAttrs.strides = toVec(K_BSD_TENSOR_X_STRIDES);
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_tensorMap[K_BSD_TENSOR_X_UID] = TensorDescriptor::fromFlatBuffer(xAttrs);
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TensorAttributesT scaleAttrs;
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scaleAttrs.uid = K_BSD_TENSOR_SCALE_UID;
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scaleAttrs.data_type = DataType::FLOAT;
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scaleAttrs.dims = toVec(K_BSD_TENSOR_SCALE_DIMS);
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scaleAttrs.strides = toVec(K_BSD_TENSOR_SCALE_STRIDES);
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_tensorMap[K_BSD_TENSOR_SCALE_UID] = TensorDescriptor::fromFlatBuffer(scaleAttrs);
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TensorAttributesT yAttrs;
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yAttrs.uid = K_BSD_TENSOR_Y_UID;
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yAttrs.data_type = DataType::FLOAT;
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yAttrs.dims = toVec(K_BSD_TENSOR_Y_DIMS);
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yAttrs.strides = toVec(K_BSD_TENSOR_Y_STRIDES);
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_tensorMap[K_BSD_TENSOR_Y_UID] = TensorDescriptor::fromFlatBuffer(yAttrs);
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}
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static BlockScaleDequantizeAttributesT createStandardBlockScaleDequantizeAttrs()
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{
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BlockScaleDequantizeAttributesT attrs;
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attrs.x_tensor_uid = K_BSD_TENSOR_X_UID;
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attrs.scale_tensor_uid = K_BSD_TENSOR_SCALE_UID;
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attrs.y_tensor_uid = K_BSD_TENSOR_Y_UID;
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attrs.block_size = {K_BSD_BLOCK_SIZE};
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attrs.is_negative_scale = false;
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return attrs;
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}
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static NodeT createStandardNode(DataType computeType = DataType::FLOAT)
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{
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NodeT node;
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node.compute_data_type = computeType;
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node.attributes.Set(createStandardBlockScaleDequantizeAttrs());
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return node;
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}
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};
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TEST_F(TestBlockScaleDequantizeOperationFromNode, CreatesValidFinalizedDescriptor)
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{
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auto node = createStandardNode();
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auto desc = BlockScaleDequantizeOperationDescriptor::fromNode(node, _tensorMap);
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ASSERT_NE(desc, nullptr);
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ASSERT_TRUE(desc->isFinalized());
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ASSERT_EQ(desc->getType(), HIPDNN_BACKEND_OPERATION_BLOCK_SCALE_DEQUANTIZE_DESCRIPTOR);
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EXPECT_EQ(desc->getData().x_tensor_uid, K_BSD_TENSOR_X_UID);
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}
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TEST_F(TestBlockScaleDequantizeOperationFromNode, NodeFactoryDelegatesCorrectly)
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{
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auto node = createStandardNode();
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// NodeFactory::createOperationFromNode delegates to fromNode internally.
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// Verify the delegation produces a valid, correctly-typed descriptor.
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auto graphOp = NodeFactory::createOperationFromNode(node, _tensorMap);
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ASSERT_NE(graphOp, nullptr);
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// Verify the factory dispatched to the correct operation type, then static_cast.
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// Cannot use dynamic_pointer_cast: backend tests compile with -fno-rtti.
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auto* op = graphOp->asGraphOperation();
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ASSERT_NE(op, nullptr);
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auto rebuiltNode = op->buildNode();
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ASSERT_EQ(rebuiltNode->attributes.type, NodeAttributes::BlockScaleDequantizeAttributes);
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auto desc = std::static_pointer_cast<BlockScaleDequantizeOperationDescriptor>(graphOp);
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ASSERT_TRUE(desc->isFinalized());
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// Verify all attributes are correctly populated via the delegated path
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EXPECT_EQ(desc->getData().x_tensor_uid, K_BSD_TENSOR_X_UID);
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EXPECT_EQ(desc->getData().scale_tensor_uid, K_BSD_TENSOR_SCALE_UID);
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EXPECT_EQ(desc->getData().y_tensor_uid, K_BSD_TENSOR_Y_UID);
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EXPECT_EQ(desc->getComputeDataType(), DataType::FLOAT);
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EXPECT_EQ(desc->getXDesc()->getData().uid, K_BSD_TENSOR_X_UID);
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EXPECT_EQ(desc->getScaleDesc()->getData().uid, K_BSD_TENSOR_SCALE_UID);
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EXPECT_EQ(desc->getYDesc()->getData().uid, K_BSD_TENSOR_Y_UID);
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}
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TEST_F(TestBlockScaleDequantizeOperationFromNode, PreservesComputeDataType)
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{
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auto node = createStandardNode(DataType::HALF);
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auto desc = BlockScaleDequantizeOperationDescriptor::fromNode(node, _tensorMap);
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ASSERT_EQ(desc->getComputeDataType(), DataType::HALF);
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}
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TEST_F(TestBlockScaleDequantizeOperationFromNode, SetsTensorReferences)
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{
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auto node = createStandardNode();
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auto desc = BlockScaleDequantizeOperationDescriptor::fromNode(node, _tensorMap);
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ASSERT_NE(desc->getXDesc(), nullptr);
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EXPECT_EQ(desc->getXDesc()->getData().uid, K_BSD_TENSOR_X_UID);
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ASSERT_NE(desc->getScaleDesc(), nullptr);
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EXPECT_EQ(desc->getScaleDesc()->getData().uid, K_BSD_TENSOR_SCALE_UID);
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ASSERT_NE(desc->getYDesc(), nullptr);
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EXPECT_EQ(desc->getYDesc()->getData().uid, K_BSD_TENSOR_Y_UID);
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}
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TEST_F(TestBlockScaleDequantizeOperationFromNode, TensorReferencesMatchTensorMap)
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{
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auto node = createStandardNode();
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auto desc = BlockScaleDequantizeOperationDescriptor::fromNode(node, _tensorMap);
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EXPECT_EQ(desc->getXDesc(), _tensorMap[K_BSD_TENSOR_X_UID]);
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EXPECT_EQ(desc->getScaleDesc(), _tensorMap[K_BSD_TENSOR_SCALE_UID]);
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EXPECT_EQ(desc->getYDesc(), _tensorMap[K_BSD_TENSOR_Y_UID]);
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}
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TEST_F(TestBlockScaleDequantizeOperationFromNode, SetsTensorReferencesWithFullValues)
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{
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auto node = createStandardNode();
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auto desc = BlockScaleDequantizeOperationDescriptor::fromNode(node, _tensorMap);
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ASSERT_NE(desc->getXDesc(), nullptr);
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EXPECT_EQ(desc->getXDesc()->getData().uid, K_BSD_TENSOR_X_UID);
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EXPECT_EQ(desc->getXDesc()->getData().data_type, DataType::FLOAT);
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EXPECT_EQ(desc->getXDesc()->getData().dims, toVec(K_BSD_TENSOR_X_DIMS));
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EXPECT_EQ(desc->getXDesc()->getData().strides, toVec(K_BSD_TENSOR_X_STRIDES));
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ASSERT_NE(desc->getScaleDesc(), nullptr);
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EXPECT_EQ(desc->getScaleDesc()->getData().uid, K_BSD_TENSOR_SCALE_UID);
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EXPECT_EQ(desc->getScaleDesc()->getData().data_type, DataType::FLOAT);
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EXPECT_EQ(desc->getScaleDesc()->getData().dims, toVec(K_BSD_TENSOR_SCALE_DIMS));
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EXPECT_EQ(desc->getScaleDesc()->getData().strides, toVec(K_BSD_TENSOR_SCALE_STRIDES));
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ASSERT_NE(desc->getYDesc(), nullptr);
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EXPECT_EQ(desc->getYDesc()->getData().uid, K_BSD_TENSOR_Y_UID);
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EXPECT_EQ(desc->getYDesc()->getData().data_type, DataType::FLOAT);
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EXPECT_EQ(desc->getYDesc()->getData().dims, toVec(K_BSD_TENSOR_Y_DIMS));
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EXPECT_EQ(desc->getYDesc()->getData().strides, toVec(K_BSD_TENSOR_Y_STRIDES));
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}
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TEST_F(TestBlockScaleDequantizeOperationFromNode, FailsWithMissingXTensor)
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{
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_tensorMap.erase(K_BSD_TENSOR_X_UID);
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auto node = createStandardNode();
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ASSERT_THROW_HIPDNN_STATUS(BlockScaleDequantizeOperationDescriptor::fromNode(node, _tensorMap),
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HIPDNN_STATUS_INTERNAL_ERROR);
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}
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TEST_F(TestBlockScaleDequantizeOperationFromNode, FailsWithMissingScaleTensor)
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{
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_tensorMap.erase(K_BSD_TENSOR_SCALE_UID);
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auto node = createStandardNode();
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ASSERT_THROW_HIPDNN_STATUS(BlockScaleDequantizeOperationDescriptor::fromNode(node, _tensorMap),
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HIPDNN_STATUS_INTERNAL_ERROR);
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}
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TEST_F(TestBlockScaleDequantizeOperationFromNode, FailsWithMissingYTensor)
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{
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_tensorMap.erase(K_BSD_TENSOR_Y_UID);
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auto node = createStandardNode();
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ASSERT_THROW_HIPDNN_STATUS(BlockScaleDequantizeOperationDescriptor::fromNode(node, _tensorMap),
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HIPDNN_STATUS_INTERNAL_ERROR);
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}
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TEST_F(TestBlockScaleDequantizeOperationFromNode, GetTensorDescriptorsReturnsAllTensors)
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{
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auto node = createStandardNode();
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auto desc = BlockScaleDequantizeOperationDescriptor::fromNode(node, _tensorMap);
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auto tensors = desc->getTensorDescriptors();
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ASSERT_EQ(tensors.size(), 3);
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EXPECT_EQ(tensors[0]->getData().uid, K_BSD_TENSOR_X_UID);
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EXPECT_EQ(tensors[1]->getData().uid, K_BSD_TENSOR_SCALE_UID);
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EXPECT_EQ(tensors[2]->getData().uid, K_BSD_TENSOR_Y_UID);
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}
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TEST_F(TestBlockScaleDequantizeOperationFromNode, BuildNodeRoundTrip)
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{
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auto node = createStandardNode();
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auto desc = BlockScaleDequantizeOperationDescriptor::fromNode(node, _tensorMap);
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auto rebuiltNode = desc->buildNode();
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ASSERT_NE(rebuiltNode, nullptr);
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ASSERT_EQ(rebuiltNode->compute_data_type, DataType::FLOAT);
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ASSERT_EQ(rebuiltNode->attributes.type, NodeAttributes::BlockScaleDequantizeAttributes);
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const auto* rebuiltAttrs = rebuiltNode->attributes.AsBlockScaleDequantizeAttributes();
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ASSERT_NE(rebuiltAttrs, nullptr);
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EXPECT_EQ(rebuiltAttrs->x_tensor_uid, K_BSD_TENSOR_X_UID);
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EXPECT_EQ(rebuiltAttrs->scale_tensor_uid, K_BSD_TENSOR_SCALE_UID);
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EXPECT_EQ(rebuiltAttrs->y_tensor_uid, K_BSD_TENSOR_Y_UID);
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EXPECT_EQ(rebuiltAttrs->block_size, (std::vector<int32_t>{K_BSD_BLOCK_SIZE}));
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}
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TEST_F(TestBlockScaleDequantizeOperationFromNode, FromNodePreservesIsNegativeScale)
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{
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auto attrs = createStandardBlockScaleDequantizeAttrs();
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attrs.is_negative_scale = true;
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NodeT node;
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node.compute_data_type = DataType::FLOAT;
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node.attributes.Set(attrs);
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auto desc = BlockScaleDequantizeOperationDescriptor::fromNode(node, _tensorMap);
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ASSERT_NE(desc, nullptr);
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EXPECT_EQ(desc->getData().is_negative_scale, true);
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auto rebuiltNode = desc->buildNode();
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const auto* rebuiltAttrs = rebuiltNode->attributes.AsBlockScaleDequantizeAttributes();
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ASSERT_NE(rebuiltAttrs, nullptr);
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EXPECT_EQ(rebuiltAttrs->is_negative_scale, true);
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}
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TEST_F(TestBlockScaleDequantizeOperationFromNode, GetAttributeWorksAfterFromNode)
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{
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auto node = createStandardNode();
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auto desc = BlockScaleDequantizeOperationDescriptor::fromNode(node, _tensorMap);
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// Verify compute type
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hipdnnDataType_t computeType = {};
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int64_t dtCount = 0;
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desc->getAttribute(HIPDNN_ATTR_OPERATION_BLOCK_SCALE_DEQUANTIZE_MATH_PREC,
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HIPDNN_TYPE_DATA_TYPE,
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1,
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&dtCount,
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&computeType);
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ASSERT_EQ(computeType, HIPDNN_DATA_FLOAT);
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// Verify x tensor
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hipdnn_backend::ScopedDescriptor xScoped;
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int64_t xCount = 0;
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desc->getAttribute(HIPDNN_ATTR_OPERATION_BLOCK_SCALE_DEQUANTIZE_XDESC,
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HIPDNN_TYPE_BACKEND_DESCRIPTOR,
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1,
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&xCount,
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static_cast<void*>(xScoped.getPtr()));
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ASSERT_EQ(xCount, 1);
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ASSERT_NE(xScoped.get(), nullptr);
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hipdnn_backend::test_utilities::verifyTensorDescriptor(xScoped.get(),
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K_BSD_TENSOR_X_UID,
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HIPDNN_DATA_FLOAT,
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toVec(K_BSD_TENSOR_X_DIMS),
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toVec(K_BSD_TENSOR_X_STRIDES));
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// Verify scale tensor
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hipdnn_backend::ScopedDescriptor scaleScoped;
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int64_t scaleCount = 0;
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desc->getAttribute(HIPDNN_ATTR_OPERATION_BLOCK_SCALE_DEQUANTIZE_SCALE_DESC,
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HIPDNN_TYPE_BACKEND_DESCRIPTOR,
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1,
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&scaleCount,
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static_cast<void*>(scaleScoped.getPtr()));
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ASSERT_EQ(scaleCount, 1);
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ASSERT_NE(scaleScoped.get(), nullptr);
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hipdnn_backend::test_utilities::verifyTensorDescriptor(scaleScoped.get(),
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K_BSD_TENSOR_SCALE_UID,
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HIPDNN_DATA_FLOAT,
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toVec(K_BSD_TENSOR_SCALE_DIMS),
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toVec(K_BSD_TENSOR_SCALE_STRIDES));
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// Verify y tensor
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hipdnn_backend::ScopedDescriptor yScoped;
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int64_t yCount = 0;
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desc->getAttribute(HIPDNN_ATTR_OPERATION_BLOCK_SCALE_DEQUANTIZE_YDESC,
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HIPDNN_TYPE_BACKEND_DESCRIPTOR,
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1,
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&yCount,
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static_cast<void*>(yScoped.getPtr()));
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ASSERT_EQ(yCount, 1);
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ASSERT_NE(yScoped.get(), nullptr);
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hipdnn_backend::test_utilities::verifyTensorDescriptor(yScoped.get(),
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K_BSD_TENSOR_Y_UID,
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HIPDNN_DATA_FLOAT,
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toVec(K_BSD_TENSOR_Y_DIMS),
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toVec(K_BSD_TENSOR_Y_STRIDES));
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// Verify operation type
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hipdnnOperationType_ext_t opType = HIPDNN_OPERATION_TYPE_NOT_SET_EXT;
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int64_t opTypeCount = 0;
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desc->getAttribute(
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HIPDNN_ATTR_OPERATION_TYPE_EXT, HIPDNN_TYPE_OPERATION_TYPE_EXT, 1, &opTypeCount, &opType);
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ASSERT_EQ(opTypeCount, 1);
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EXPECT_EQ(opType, HIPDNN_OPERATION_TYPE_BLOCK_SCALE_DEQUANTIZE_EXT);
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// Verify block_size
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int64_t blockSizeCount = 0;
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desc->getAttribute(HIPDNN_ATTR_OPERATION_BLOCK_SCALE_DEQUANTIZE_BLOCK_SIZE,
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HIPDNN_TYPE_INT32,
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0,
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&blockSizeCount,
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nullptr);
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ASSERT_EQ(blockSizeCount, 1);
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int32_t blockSizeVal = 0;
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int64_t actualBlockSizeCount = 0;
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desc->getAttribute(HIPDNN_ATTR_OPERATION_BLOCK_SCALE_DEQUANTIZE_BLOCK_SIZE,
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HIPDNN_TYPE_INT32,
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1,
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&actualBlockSizeCount,
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&blockSizeVal);
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EXPECT_EQ(blockSizeVal, K_BSD_BLOCK_SIZE);
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// Verify is_negative_scale
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bool isNegativeScale = true;
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int64_t isNegCount = 0;
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desc->getAttribute(HIPDNN_ATTR_OPERATION_BLOCK_SCALE_DEQUANTIZE_NEG_SCALE,
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HIPDNN_TYPE_BOOLEAN,
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1,
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&isNegCount,
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&isNegativeScale);
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EXPECT_EQ(isNegativeScale, false);
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}
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TEST_F(TestBlockScaleDequantizeOperationFromNode, NamePreservedFromNode)
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{
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auto node = createStandardNode();
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node.name = "test_blockscaledequantize_1";
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auto desc = BlockScaleDequantizeOperationDescriptor::fromNode(node, _tensorMap);
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int64_t count = 0;
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desc->getAttribute(HIPDNN_ATTR_OPERATION_NAME_EXT, HIPDNN_TYPE_CHAR, 0, &count, nullptr);
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ASSERT_EQ(count, static_cast<int64_t>(std::string("test_blockscaledequantize_1").size() + 1));
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std::vector<char> buffer(static_cast<size_t>(count));
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int64_t actualCount = 0;
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desc->getAttribute(
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HIPDNN_ATTR_OPERATION_NAME_EXT, HIPDNN_TYPE_CHAR, count, &actualCount, buffer.data());
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EXPECT_STREQ(buffer.data(), "test_blockscaledequantize_1");
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}
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TEST_F(TestBlockScaleDequantizeOperationFromNode, EmptyNamePreservedFromNode)
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{
|
|
auto node = createStandardNode();
|
|
auto desc = BlockScaleDequantizeOperationDescriptor::fromNode(node, _tensorMap);
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|
|
|
int64_t count = 0;
|
|
desc->getAttribute(HIPDNN_ATTR_OPERATION_NAME_EXT, HIPDNN_TYPE_CHAR, 0, &count, nullptr);
|
|
EXPECT_EQ(count, 1);
|
|
}
|
|
|
|
TEST_F(TestBlockScaleDequantizeOperationFromNode, BuildNodePreservesName)
|
|
{
|
|
auto node = createStandardNode();
|
|
node.name = "test_build_name";
|
|
|
|
auto desc = BlockScaleDequantizeOperationDescriptor::fromNode(node, _tensorMap);
|
|
auto rebuiltNode = desc->buildNode();
|
|
|
|
ASSERT_NE(rebuiltNode, nullptr);
|
|
EXPECT_EQ(rebuiltNode->name, "test_build_name");
|
|
}
|