// Copyright © Advanced Micro Devices, Inc., or its affiliates. // SPDX-License-Identifier: MIT #include "HipdnnOperationType.h" #include "TensorDescriptorTestUtils.hpp" #include "TestMacros.hpp" #include "descriptors/LayernormBackwardOperationDescriptor.hpp" #include "descriptors/NodeFactory.hpp" #include "descriptors/ScopedDescriptor.hpp" #include "descriptors/TensorDescriptor.hpp" #include #include #include #include #include #include #include #include #include #include using namespace hipdnn_backend; using namespace hipdnn_flatbuffers_sdk::data_objects; using namespace hipdnn_tests::constants; using hipdnn_backend::test_utilities::verifyTensorDescriptor; using hipdnn_tests::toVec; // ============================================================================= // LayernormBackwardOperationDescriptor::fromNode() Tests // ============================================================================= class TestLayernormBackwardOperationFromNode : public ::testing::Test { protected: std::unordered_map> _tensorMap; void SetUp() override { TensorAttributesT dyAttrs; dyAttrs.uid = K_LAYERNORMBACKWARD_TENSOR_DY_UID; dyAttrs.data_type = DataType::FLOAT; dyAttrs.dims = toVec(K_LAYERNORMBACKWARD_TENSOR_DY_DIMS); dyAttrs.strides = toVec(K_LAYERNORMBACKWARD_TENSOR_DY_STRIDES); _tensorMap[K_LAYERNORMBACKWARD_TENSOR_DY_UID] = TensorDescriptor::fromFlatBuffer(dyAttrs); TensorAttributesT xAttrs; xAttrs.uid = K_LAYERNORMBACKWARD_TENSOR_X_UID; xAttrs.data_type = DataType::FLOAT; xAttrs.dims = toVec(K_LAYERNORMBACKWARD_TENSOR_X_DIMS); xAttrs.strides = toVec(K_LAYERNORMBACKWARD_TENSOR_X_STRIDES); _tensorMap[K_LAYERNORMBACKWARD_TENSOR_X_UID] = TensorDescriptor::fromFlatBuffer(xAttrs); TensorAttributesT scaleAttrs; scaleAttrs.uid = K_LAYERNORMBACKWARD_TENSOR_SCALE_UID; scaleAttrs.data_type = DataType::FLOAT; scaleAttrs.dims = toVec(K_LAYERNORMBACKWARD_TENSOR_SCALE_DIMS); scaleAttrs.strides = toVec(K_LAYERNORMBACKWARD_TENSOR_SCALE_STRIDES); _tensorMap[K_LAYERNORMBACKWARD_TENSOR_SCALE_UID] = TensorDescriptor::fromFlatBuffer(scaleAttrs); TensorAttributesT meanAttrs; meanAttrs.uid = K_LAYERNORMBACKWARD_TENSOR_MEAN_UID; meanAttrs.data_type = DataType::FLOAT; meanAttrs.dims = toVec(K_LAYERNORMBACKWARD_TENSOR_MEAN_DIMS); meanAttrs.strides = toVec(K_LAYERNORMBACKWARD_TENSOR_MEAN_STRIDES); _tensorMap[K_LAYERNORMBACKWARD_TENSOR_MEAN_UID] = TensorDescriptor::fromFlatBuffer(meanAttrs); TensorAttributesT invVarianceAttrs; invVarianceAttrs.uid = K_LAYERNORMBACKWARD_TENSOR_INV_VARIANCE_UID; invVarianceAttrs.data_type = DataType::FLOAT; invVarianceAttrs.dims = toVec(K_LAYERNORMBACKWARD_TENSOR_INV_VARIANCE_DIMS); invVarianceAttrs.strides = toVec(K_LAYERNORMBACKWARD_TENSOR_INV_VARIANCE_STRIDES); _tensorMap[K_LAYERNORMBACKWARD_TENSOR_INV_VARIANCE_UID] = TensorDescriptor::fromFlatBuffer(invVarianceAttrs); TensorAttributesT epsilonAttrs; epsilonAttrs.uid = K_LAYERNORMBACKWARD_TENSOR_EPSILON_UID; epsilonAttrs.data_type = DataType::FLOAT; epsilonAttrs.dims = toVec(K_LAYERNORMBACKWARD_TENSOR_EPSILON_DIMS); epsilonAttrs.strides = toVec(K_LAYERNORMBACKWARD_TENSOR_EPSILON_STRIDES); _tensorMap[K_LAYERNORMBACKWARD_TENSOR_EPSILON_UID] = TensorDescriptor::fromFlatBuffer(epsilonAttrs); TensorAttributesT dxAttrs; dxAttrs.uid = K_LAYERNORMBACKWARD_TENSOR_DX_UID; dxAttrs.data_type = DataType::FLOAT; dxAttrs.dims = toVec(K_LAYERNORMBACKWARD_TENSOR_DX_DIMS); dxAttrs.strides = toVec(K_LAYERNORMBACKWARD_TENSOR_DX_STRIDES); _tensorMap[K_LAYERNORMBACKWARD_TENSOR_DX_UID] = TensorDescriptor::fromFlatBuffer(dxAttrs); TensorAttributesT dscaleAttrs; dscaleAttrs.uid = K_LAYERNORMBACKWARD_TENSOR_DSCALE_UID; dscaleAttrs.data_type = DataType::FLOAT; dscaleAttrs.dims = toVec(K_LAYERNORMBACKWARD_TENSOR_DSCALE_DIMS); dscaleAttrs.strides = toVec(K_LAYERNORMBACKWARD_TENSOR_DSCALE_STRIDES); _tensorMap[K_LAYERNORMBACKWARD_TENSOR_DSCALE_UID] = TensorDescriptor::fromFlatBuffer(dscaleAttrs); TensorAttributesT dbiasAttrs; dbiasAttrs.uid = K_LAYERNORMBACKWARD_TENSOR_DBIAS_UID; dbiasAttrs.data_type = DataType::FLOAT; dbiasAttrs.dims = toVec(K_LAYERNORMBACKWARD_TENSOR_DBIAS_DIMS); dbiasAttrs.strides = toVec(K_LAYERNORMBACKWARD_TENSOR_DBIAS_STRIDES); _tensorMap[K_LAYERNORMBACKWARD_TENSOR_DBIAS_UID] = TensorDescriptor::fromFlatBuffer(dbiasAttrs); } static hipdnn_flatbuffers_sdk::data_objects::LayernormBackwardAttributesT createStandardLayernormBackwardAttrs() { hipdnn_flatbuffers_sdk::data_objects::LayernormBackwardAttributesT attrs; attrs.dy_tensor_uid = K_LAYERNORMBACKWARD_TENSOR_DY_UID; attrs.x_tensor_uid = K_LAYERNORMBACKWARD_TENSOR_X_UID; attrs.scale_tensor_uid = K_LAYERNORMBACKWARD_TENSOR_SCALE_UID; attrs.mean_tensor_uid = K_LAYERNORMBACKWARD_TENSOR_MEAN_UID; attrs.inv_variance_tensor_uid = K_LAYERNORMBACKWARD_TENSOR_INV_VARIANCE_UID; attrs.epsilon_tensor_uid = K_LAYERNORMBACKWARD_TENSOR_EPSILON_UID; attrs.dx_tensor_uid = K_LAYERNORMBACKWARD_TENSOR_DX_UID; attrs.dscale_tensor_uid = K_LAYERNORMBACKWARD_TENSOR_DSCALE_UID; attrs.dbias_tensor_uid = K_LAYERNORMBACKWARD_TENSOR_DBIAS_UID; attrs.normalized_dim_count = 3; return attrs; } static NodeT createStandardNode(DataType computeType = DataType::FLOAT) { NodeT node; node.compute_data_type = computeType; node.attributes.Set(createStandardLayernormBackwardAttrs()); return node; } }; TEST_F(TestLayernormBackwardOperationFromNode, CreatesValidFinalizedDescriptor) { auto node = createStandardNode(); auto desc = LayernormBackwardOperationDescriptor::fromNode(node, _tensorMap); ASSERT_NE(desc, nullptr); ASSERT_TRUE(desc->isFinalized()); ASSERT_EQ(desc->getType(), HIPDNN_BACKEND_OPERATION_LAYERNORM_BACKWARD_DESCRIPTOR_EXT); EXPECT_EQ(desc->getData().dy_tensor_uid, K_LAYERNORMBACKWARD_TENSOR_DY_UID); } TEST_F(TestLayernormBackwardOperationFromNode, NodeFactoryDelegatesCorrectly) { auto node = createStandardNode(); // NodeFactory::createOperationFromNode delegates to fromNode internally. // Verify the delegation produces a valid, correctly-typed descriptor. auto graphOp = NodeFactory::createOperationFromNode(node, _tensorMap); ASSERT_NE(graphOp, nullptr); // Verify the factory dispatched to the correct operation type, then static_cast. // Cannot use dynamic_pointer_cast: backend tests compile with -fno-rtti. auto* op = graphOp->asGraphOperation(); ASSERT_NE(op, nullptr); const auto rebuiltNode = op->buildNode(); ASSERT_EQ(rebuiltNode->attributes.type, NodeAttributes::LayernormBackwardAttributes); auto desc = std::static_pointer_cast(graphOp); ASSERT_TRUE(desc->isFinalized()); // Verify all attributes are correctly populated via the delegated path EXPECT_EQ(desc->getData().dy_tensor_uid, K_LAYERNORMBACKWARD_TENSOR_DY_UID); EXPECT_EQ(desc->getData().x_tensor_uid, K_LAYERNORMBACKWARD_TENSOR_X_UID); EXPECT_EQ(desc->getData().scale_tensor_uid, K_LAYERNORMBACKWARD_TENSOR_SCALE_UID); EXPECT_EQ(desc->getData().mean_tensor_uid, K_LAYERNORMBACKWARD_TENSOR_MEAN_UID); EXPECT_EQ(desc->getData().inv_variance_tensor_uid, K_LAYERNORMBACKWARD_TENSOR_INV_VARIANCE_UID); EXPECT_EQ(desc->getData().epsilon_tensor_uid, K_LAYERNORMBACKWARD_TENSOR_EPSILON_UID); EXPECT_EQ(desc->getData().dx_tensor_uid, K_LAYERNORMBACKWARD_TENSOR_DX_UID); EXPECT_EQ(desc->getData().dscale_tensor_uid, K_LAYERNORMBACKWARD_TENSOR_DSCALE_UID); EXPECT_EQ(desc->getData().dbias_tensor_uid, K_LAYERNORMBACKWARD_TENSOR_DBIAS_UID); EXPECT_EQ(desc->getComputeDataType(), DataType::FLOAT); EXPECT_EQ(desc->getDyDesc()->getData().uid, K_LAYERNORMBACKWARD_TENSOR_DY_UID); EXPECT_EQ(desc->getXDesc()->getData().uid, K_LAYERNORMBACKWARD_TENSOR_X_UID); EXPECT_EQ(desc->getScaleDesc()->getData().uid, K_LAYERNORMBACKWARD_TENSOR_SCALE_UID); EXPECT_EQ(desc->getDxDesc()->getData().uid, K_LAYERNORMBACKWARD_TENSOR_DX_UID); EXPECT_EQ(desc->getDscaleDesc()->getData().uid, K_LAYERNORMBACKWARD_TENSOR_DSCALE_UID); EXPECT_EQ(desc->getDbiasDesc()->getData().uid, K_LAYERNORMBACKWARD_TENSOR_DBIAS_UID); EXPECT_EQ(desc->getMeanDesc()->getData().uid, K_LAYERNORMBACKWARD_TENSOR_MEAN_UID); EXPECT_EQ(desc->getInvVarianceDesc()->getData().uid, K_LAYERNORMBACKWARD_TENSOR_INV_VARIANCE_UID); EXPECT_EQ(desc->getEpsilonDesc()->getData().uid, K_LAYERNORMBACKWARD_TENSOR_EPSILON_UID); } TEST_F(TestLayernormBackwardOperationFromNode, PreservesComputeDataType) { auto node = createStandardNode(DataType::HALF); auto desc = LayernormBackwardOperationDescriptor::fromNode(node, _tensorMap); ASSERT_EQ(desc->getComputeDataType(), DataType::HALF); } TEST_F(TestLayernormBackwardOperationFromNode, SetsTensorReferences) { auto node = createStandardNode(); auto desc = LayernormBackwardOperationDescriptor::fromNode(node, _tensorMap); ASSERT_NE(desc->getDyDesc(), nullptr); EXPECT_EQ(desc->getDyDesc()->getData().uid, K_LAYERNORMBACKWARD_TENSOR_DY_UID); ASSERT_NE(desc->getXDesc(), nullptr); EXPECT_EQ(desc->getXDesc()->getData().uid, K_LAYERNORMBACKWARD_TENSOR_X_UID); ASSERT_NE(desc->getScaleDesc(), nullptr); EXPECT_EQ(desc->getScaleDesc()->getData().uid, K_LAYERNORMBACKWARD_TENSOR_SCALE_UID); ASSERT_NE(desc->getDxDesc(), nullptr); EXPECT_EQ(desc->getDxDesc()->getData().uid, K_LAYERNORMBACKWARD_TENSOR_DX_UID); ASSERT_NE(desc->getDscaleDesc(), nullptr); EXPECT_EQ(desc->getDscaleDesc()->getData().uid, K_LAYERNORMBACKWARD_TENSOR_DSCALE_UID); ASSERT_NE(desc->getDbiasDesc(), nullptr); EXPECT_EQ(desc->getDbiasDesc()->getData().uid, K_LAYERNORMBACKWARD_TENSOR_DBIAS_UID); ASSERT_NE(desc->getMeanDesc(), nullptr); EXPECT_EQ(desc->getMeanDesc()->getData().uid, K_LAYERNORMBACKWARD_TENSOR_MEAN_UID); ASSERT_NE(desc->getInvVarianceDesc(), nullptr); EXPECT_EQ(desc->getInvVarianceDesc()->getData().uid, K_LAYERNORMBACKWARD_TENSOR_INV_VARIANCE_UID); ASSERT_NE(desc->getEpsilonDesc(), nullptr); EXPECT_EQ(desc->getEpsilonDesc()->getData().uid, K_LAYERNORMBACKWARD_TENSOR_EPSILON_UID); } TEST_F(TestLayernormBackwardOperationFromNode, TensorReferencesMatchTensorMap) { auto node = createStandardNode(); auto desc = LayernormBackwardOperationDescriptor::fromNode(node, _tensorMap); EXPECT_EQ(desc->getDyDesc(), _tensorMap[K_LAYERNORMBACKWARD_TENSOR_DY_UID]); EXPECT_EQ(desc->getXDesc(), _tensorMap[K_LAYERNORMBACKWARD_TENSOR_X_UID]); EXPECT_EQ(desc->getScaleDesc(), _tensorMap[K_LAYERNORMBACKWARD_TENSOR_SCALE_UID]); EXPECT_EQ(desc->getDxDesc(), _tensorMap[K_LAYERNORMBACKWARD_TENSOR_DX_UID]); EXPECT_EQ(desc->getDscaleDesc(), _tensorMap[K_LAYERNORMBACKWARD_TENSOR_DSCALE_UID]); EXPECT_EQ(desc->getDbiasDesc(), _tensorMap[K_LAYERNORMBACKWARD_TENSOR_DBIAS_UID]); EXPECT_EQ(desc->getMeanDesc(), _tensorMap[K_LAYERNORMBACKWARD_TENSOR_MEAN_UID]); EXPECT_EQ(desc->getInvVarianceDesc(), _tensorMap[K_LAYERNORMBACKWARD_TENSOR_INV_VARIANCE_UID]); EXPECT_EQ(desc->getEpsilonDesc(), _tensorMap[K_LAYERNORMBACKWARD_TENSOR_EPSILON_UID]); } TEST_F(TestLayernormBackwardOperationFromNode, SetsTensorReferencesWithFullValues) { auto node = createStandardNode(); auto desc = LayernormBackwardOperationDescriptor::fromNode(node, _tensorMap); ASSERT_NE(desc->getDyDesc(), nullptr); EXPECT_EQ(desc->getDyDesc()->getData().uid, K_LAYERNORMBACKWARD_TENSOR_DY_UID); EXPECT_EQ(desc->getDyDesc()->getData().data_type, DataType::FLOAT); EXPECT_EQ(desc->getDyDesc()->getData().dims, (std::vector{16, 64, 32, 32})); EXPECT_EQ(desc->getDyDesc()->getData().strides, (std::vector{65536, 1024, 32, 1})); ASSERT_NE(desc->getXDesc(), nullptr); EXPECT_EQ(desc->getXDesc()->getData().uid, K_LAYERNORMBACKWARD_TENSOR_X_UID); EXPECT_EQ(desc->getXDesc()->getData().data_type, DataType::FLOAT); EXPECT_EQ(desc->getXDesc()->getData().dims, (std::vector{16, 64, 32, 32})); EXPECT_EQ(desc->getXDesc()->getData().strides, (std::vector{65536, 1024, 32, 1})); ASSERT_NE(desc->getScaleDesc(), nullptr); EXPECT_EQ(desc->getScaleDesc()->getData().uid, K_LAYERNORMBACKWARD_TENSOR_SCALE_UID); EXPECT_EQ(desc->getScaleDesc()->getData().data_type, DataType::FLOAT); EXPECT_EQ(desc->getScaleDesc()->getData().dims, (std::vector{1, 64, 32, 32})); EXPECT_EQ(desc->getScaleDesc()->getData().strides, (std::vector{65536, 1024, 32, 1})); ASSERT_NE(desc->getDxDesc(), nullptr); EXPECT_EQ(desc->getDxDesc()->getData().uid, K_LAYERNORMBACKWARD_TENSOR_DX_UID); EXPECT_EQ(desc->getDxDesc()->getData().data_type, DataType::FLOAT); EXPECT_EQ(desc->getDxDesc()->getData().dims, (std::vector{16, 64, 32, 32})); EXPECT_EQ(desc->getDxDesc()->getData().strides, (std::vector{65536, 1024, 32, 1})); ASSERT_NE(desc->getDscaleDesc(), nullptr); EXPECT_EQ(desc->getDscaleDesc()->getData().uid, K_LAYERNORMBACKWARD_TENSOR_DSCALE_UID); EXPECT_EQ(desc->getDscaleDesc()->getData().data_type, DataType::FLOAT); EXPECT_EQ(desc->getDscaleDesc()->getData().dims, (std::vector{1, 64, 32, 32})); EXPECT_EQ(desc->getDscaleDesc()->getData().strides, (std::vector{65536, 1024, 32, 1})); ASSERT_NE(desc->getDbiasDesc(), nullptr); EXPECT_EQ(desc->getDbiasDesc()->getData().uid, K_LAYERNORMBACKWARD_TENSOR_DBIAS_UID); EXPECT_EQ(desc->getDbiasDesc()->getData().data_type, DataType::FLOAT); EXPECT_EQ(desc->getDbiasDesc()->getData().dims, (std::vector{1, 64, 32, 32})); EXPECT_EQ(desc->getDbiasDesc()->getData().strides, (std::vector{65536, 1024, 32, 1})); ASSERT_NE(desc->getMeanDesc(), nullptr); EXPECT_EQ(desc->getMeanDesc()->getData().uid, K_LAYERNORMBACKWARD_TENSOR_MEAN_UID); EXPECT_EQ(desc->getMeanDesc()->getData().data_type, DataType::FLOAT); EXPECT_EQ(desc->getMeanDesc()->getData().dims, (std::vector{16, 1, 1, 1})); EXPECT_EQ(desc->getMeanDesc()->getData().strides, (std::vector{1, 1, 1, 1})); ASSERT_NE(desc->getInvVarianceDesc(), nullptr); EXPECT_EQ(desc->getInvVarianceDesc()->getData().uid, K_LAYERNORMBACKWARD_TENSOR_INV_VARIANCE_UID); EXPECT_EQ(desc->getInvVarianceDesc()->getData().data_type, DataType::FLOAT); EXPECT_EQ(desc->getInvVarianceDesc()->getData().dims, (std::vector{16, 1, 1, 1})); EXPECT_EQ(desc->getInvVarianceDesc()->getData().strides, (std::vector{1, 1, 1, 1})); ASSERT_NE(desc->getEpsilonDesc(), nullptr); EXPECT_EQ(desc->getEpsilonDesc()->getData().uid, K_LAYERNORMBACKWARD_TENSOR_EPSILON_UID); EXPECT_EQ(desc->getEpsilonDesc()->getData().data_type, DataType::FLOAT); EXPECT_EQ(desc->getEpsilonDesc()->getData().dims, (std::vector{1})); EXPECT_EQ(desc->getEpsilonDesc()->getData().strides, (std::vector{1})); } TEST_F(TestLayernormBackwardOperationFromNode, FailsWithMissingDyTensor) { _tensorMap.erase(K_LAYERNORMBACKWARD_TENSOR_DY_UID); auto node = createStandardNode(); ASSERT_THROW_HIPDNN_STATUS(LayernormBackwardOperationDescriptor::fromNode(node, _tensorMap), HIPDNN_STATUS_INTERNAL_ERROR); } TEST_F(TestLayernormBackwardOperationFromNode, FailsWithMissingXTensor) { _tensorMap.erase(K_LAYERNORMBACKWARD_TENSOR_X_UID); auto node = createStandardNode(); ASSERT_THROW_HIPDNN_STATUS(LayernormBackwardOperationDescriptor::fromNode(node, _tensorMap), HIPDNN_STATUS_INTERNAL_ERROR); } TEST_F(TestLayernormBackwardOperationFromNode, FailsWithMissingScaleTensor) { _tensorMap.erase(K_LAYERNORMBACKWARD_TENSOR_SCALE_UID); auto node = createStandardNode(); ASSERT_THROW_HIPDNN_STATUS(LayernormBackwardOperationDescriptor::fromNode(node, _tensorMap), HIPDNN_STATUS_INTERNAL_ERROR); } TEST_F(TestLayernormBackwardOperationFromNode, FailsWithMissingDxTensor) { _tensorMap.erase(K_LAYERNORMBACKWARD_TENSOR_DX_UID); auto node = createStandardNode(); ASSERT_THROW_HIPDNN_STATUS(LayernormBackwardOperationDescriptor::fromNode(node, _tensorMap), HIPDNN_STATUS_INTERNAL_ERROR); } TEST_F(TestLayernormBackwardOperationFromNode, FailsWithMissingDscaleTensor) { _tensorMap.erase(K_LAYERNORMBACKWARD_TENSOR_DSCALE_UID); auto node = createStandardNode(); ASSERT_THROW_HIPDNN_STATUS(LayernormBackwardOperationDescriptor::fromNode(node, _tensorMap), HIPDNN_STATUS_INTERNAL_ERROR); } TEST_F(TestLayernormBackwardOperationFromNode, FailsWithMissingDbiasTensor) { _tensorMap.erase(K_LAYERNORMBACKWARD_TENSOR_DBIAS_UID); auto node = createStandardNode(); ASSERT_THROW_HIPDNN_STATUS(LayernormBackwardOperationDescriptor::fromNode(node, _tensorMap), HIPDNN_STATUS_INTERNAL_ERROR); } TEST_F(TestLayernormBackwardOperationFromNode, SucceedsWithOnlyRequiredTensors) { auto attrs = createStandardLayernormBackwardAttrs(); attrs.mean_tensor_uid = flatbuffers::nullopt; attrs.inv_variance_tensor_uid = flatbuffers::nullopt; attrs.epsilon_tensor_uid = flatbuffers::nullopt; NodeT node; node.compute_data_type = DataType::FLOAT; node.attributes.Set(attrs); auto desc = LayernormBackwardOperationDescriptor::fromNode(node, _tensorMap); ASSERT_NE(desc, nullptr); ASSERT_TRUE(desc->isFinalized()); // Required tensor getters are non-null EXPECT_NE(desc->getDyDesc(), nullptr); EXPECT_NE(desc->getXDesc(), nullptr); EXPECT_NE(desc->getScaleDesc(), nullptr); EXPECT_NE(desc->getDxDesc(), nullptr); EXPECT_NE(desc->getDscaleDesc(), nullptr); EXPECT_NE(desc->getDbiasDesc(), nullptr); // Optional tensor getters are null EXPECT_EQ(desc->getMeanDesc(), nullptr); EXPECT_EQ(desc->getInvVarianceDesc(), nullptr); EXPECT_EQ(desc->getEpsilonDesc(), nullptr); } TEST_F(TestLayernormBackwardOperationFromNode, FailsWhenOptionalMeanUidSetButTensorMissing) { _tensorMap.erase(K_LAYERNORMBACKWARD_TENSOR_MEAN_UID); auto node = createStandardNode(); ASSERT_THROW_HIPDNN_STATUS(LayernormBackwardOperationDescriptor::fromNode(node, _tensorMap), HIPDNN_STATUS_INTERNAL_ERROR); } TEST_F(TestLayernormBackwardOperationFromNode, FailsWhenOptionalInvVarianceUidSetButTensorMissing) { _tensorMap.erase(K_LAYERNORMBACKWARD_TENSOR_INV_VARIANCE_UID); auto node = createStandardNode(); ASSERT_THROW_HIPDNN_STATUS(LayernormBackwardOperationDescriptor::fromNode(node, _tensorMap), HIPDNN_STATUS_INTERNAL_ERROR); } TEST_F(TestLayernormBackwardOperationFromNode, FailsWhenOptionalEpsilonUidSetButTensorMissing) { _tensorMap.erase(K_LAYERNORMBACKWARD_TENSOR_EPSILON_UID); auto node = createStandardNode(); ASSERT_THROW_HIPDNN_STATUS(LayernormBackwardOperationDescriptor::fromNode(node, _tensorMap), HIPDNN_STATUS_INTERNAL_ERROR); } TEST_F(TestLayernormBackwardOperationFromNode, GetTensorDescriptorsReturnsAllTensors) { auto node = createStandardNode(); auto desc = LayernormBackwardOperationDescriptor::fromNode(node, _tensorMap); auto tensors = desc->getTensorDescriptors(); ASSERT_EQ(tensors.size(), 9); EXPECT_EQ(tensors[0]->getData().uid, K_LAYERNORMBACKWARD_TENSOR_DY_UID); EXPECT_EQ(tensors[1]->getData().uid, K_LAYERNORMBACKWARD_TENSOR_X_UID); EXPECT_EQ(tensors[2]->getData().uid, K_LAYERNORMBACKWARD_TENSOR_SCALE_UID); EXPECT_EQ(tensors[3]->getData().uid, K_LAYERNORMBACKWARD_TENSOR_MEAN_UID); EXPECT_EQ(tensors[4]->getData().uid, K_LAYERNORMBACKWARD_TENSOR_INV_VARIANCE_UID); EXPECT_EQ(tensors[5]->getData().uid, K_LAYERNORMBACKWARD_TENSOR_EPSILON_UID); EXPECT_EQ(tensors[6]->getData().uid, K_LAYERNORMBACKWARD_TENSOR_DX_UID); EXPECT_EQ(tensors[7]->getData().uid, K_LAYERNORMBACKWARD_TENSOR_DSCALE_UID); EXPECT_EQ(tensors[8]->getData().uid, K_LAYERNORMBACKWARD_TENSOR_DBIAS_UID); } TEST_F(TestLayernormBackwardOperationFromNode, BuildNodeRoundTrip) { auto node = createStandardNode(); auto desc = LayernormBackwardOperationDescriptor::fromNode(node, _tensorMap); const auto rebuiltNode = desc->buildNode(); ASSERT_NE(rebuiltNode, nullptr); ASSERT_EQ(rebuiltNode->compute_data_type, DataType::FLOAT); ASSERT_EQ(rebuiltNode->attributes.type, NodeAttributes::LayernormBackwardAttributes); const auto* rebuiltAttrs = rebuiltNode->attributes.AsLayernormBackwardAttributes(); ASSERT_NE(rebuiltAttrs, nullptr); EXPECT_EQ(rebuiltAttrs->dy_tensor_uid, K_LAYERNORMBACKWARD_TENSOR_DY_UID); EXPECT_EQ(rebuiltAttrs->x_tensor_uid, K_LAYERNORMBACKWARD_TENSOR_X_UID); EXPECT_EQ(rebuiltAttrs->scale_tensor_uid, K_LAYERNORMBACKWARD_TENSOR_SCALE_UID); EXPECT_EQ(rebuiltAttrs->mean_tensor_uid, K_LAYERNORMBACKWARD_TENSOR_MEAN_UID); EXPECT_EQ(rebuiltAttrs->inv_variance_tensor_uid, K_LAYERNORMBACKWARD_TENSOR_INV_VARIANCE_UID); EXPECT_EQ(rebuiltAttrs->epsilon_tensor_uid, K_LAYERNORMBACKWARD_TENSOR_EPSILON_UID); EXPECT_EQ(rebuiltAttrs->dx_tensor_uid, K_LAYERNORMBACKWARD_TENSOR_DX_UID); EXPECT_EQ(rebuiltAttrs->dscale_tensor_uid, K_LAYERNORMBACKWARD_TENSOR_DSCALE_UID); EXPECT_EQ(rebuiltAttrs->dbias_tensor_uid, K_LAYERNORMBACKWARD_TENSOR_DBIAS_UID); } TEST_F(TestLayernormBackwardOperationFromNode, GetAttributeWorksAfterFromNode) { auto node = createStandardNode(); auto desc = LayernormBackwardOperationDescriptor::fromNode(node, _tensorMap); // Verify compute type hipdnnDataType_t computeType = {}; int64_t dtCount = 0; desc->getAttribute(HIPDNN_ATTR_LAYERNORM_BACKWARD_COMP_TYPE_EXT, HIPDNN_TYPE_DATA_TYPE, 1, &dtCount, &computeType); ASSERT_EQ(computeType, HIPDNN_DATA_FLOAT); // Verify dy tensor hipdnn_backend::ScopedDescriptor dyScoped; int64_t dyCount = 0; desc->getAttribute(HIPDNN_ATTR_OPERATION_LAYERNORM_BACKWARD_DY_EXT, HIPDNN_TYPE_BACKEND_DESCRIPTOR, 1, &dyCount, static_cast(dyScoped.getPtr())); ASSERT_EQ(dyCount, 1); ASSERT_NE(dyScoped.get(), nullptr); verifyTensorDescriptor(dyScoped.get(), K_LAYERNORMBACKWARD_TENSOR_DY_UID, HIPDNN_DATA_FLOAT, {16, 64, 32, 32}, {65536, 1024, 32, 1}); // Verify x tensor hipdnn_backend::ScopedDescriptor xScoped; int64_t xCount = 0; desc->getAttribute(HIPDNN_ATTR_OPERATION_LAYERNORM_BACKWARD_X_EXT, HIPDNN_TYPE_BACKEND_DESCRIPTOR, 1, &xCount, static_cast(xScoped.getPtr())); ASSERT_EQ(xCount, 1); ASSERT_NE(xScoped.get(), nullptr); verifyTensorDescriptor(xScoped.get(), K_LAYERNORMBACKWARD_TENSOR_X_UID, HIPDNN_DATA_FLOAT, {16, 64, 32, 32}, {65536, 1024, 32, 1}); // Verify scale tensor hipdnn_backend::ScopedDescriptor scaleScoped; int64_t scaleCount = 0; desc->getAttribute(HIPDNN_ATTR_OPERATION_LAYERNORM_BACKWARD_SCALE_EXT, HIPDNN_TYPE_BACKEND_DESCRIPTOR, 1, &scaleCount, static_cast(scaleScoped.getPtr())); ASSERT_EQ(scaleCount, 1); ASSERT_NE(scaleScoped.get(), nullptr); verifyTensorDescriptor(scaleScoped.get(), K_LAYERNORMBACKWARD_TENSOR_SCALE_UID, HIPDNN_DATA_FLOAT, {1, 64, 32, 32}, {65536, 1024, 32, 1}); // Verify dx tensor hipdnn_backend::ScopedDescriptor dxScoped; int64_t dxCount = 0; desc->getAttribute(HIPDNN_ATTR_OPERATION_LAYERNORM_BACKWARD_DX_EXT, HIPDNN_TYPE_BACKEND_DESCRIPTOR, 1, &dxCount, static_cast(dxScoped.getPtr())); ASSERT_EQ(dxCount, 1); ASSERT_NE(dxScoped.get(), nullptr); verifyTensorDescriptor(dxScoped.get(), K_LAYERNORMBACKWARD_TENSOR_DX_UID, HIPDNN_DATA_FLOAT, {16, 64, 32, 32}, {65536, 1024, 32, 1}); // Verify dscale tensor hipdnn_backend::ScopedDescriptor dscaleScoped; int64_t dscaleCount = 0; desc->getAttribute(HIPDNN_ATTR_OPERATION_LAYERNORM_BACKWARD_DSCALE_EXT, HIPDNN_TYPE_BACKEND_DESCRIPTOR, 1, &dscaleCount, static_cast(dscaleScoped.getPtr())); ASSERT_EQ(dscaleCount, 1); ASSERT_NE(dscaleScoped.get(), nullptr); verifyTensorDescriptor(dscaleScoped.get(), K_LAYERNORMBACKWARD_TENSOR_DSCALE_UID, HIPDNN_DATA_FLOAT, {1, 64, 32, 32}, {65536, 1024, 32, 1}); // Verify dbias tensor hipdnn_backend::ScopedDescriptor dbiasScoped; int64_t dbiasCount = 0; desc->getAttribute(HIPDNN_ATTR_OPERATION_LAYERNORM_BACKWARD_DBIAS_EXT, HIPDNN_TYPE_BACKEND_DESCRIPTOR, 1, &dbiasCount, static_cast(dbiasScoped.getPtr())); ASSERT_EQ(dbiasCount, 1); ASSERT_NE(dbiasScoped.get(), nullptr); verifyTensorDescriptor(dbiasScoped.get(), K_LAYERNORMBACKWARD_TENSOR_DBIAS_UID, HIPDNN_DATA_FLOAT, {1, 64, 32, 32}, {65536, 1024, 32, 1}); // Verify mean tensor (optional) hipdnn_backend::ScopedDescriptor meanScoped; int64_t meanCount = 0; desc->getAttribute(HIPDNN_ATTR_OPERATION_LAYERNORM_BACKWARD_MEAN_EXT, HIPDNN_TYPE_BACKEND_DESCRIPTOR, 1, &meanCount, static_cast(meanScoped.getPtr())); ASSERT_EQ(meanCount, 1); ASSERT_NE(meanScoped.get(), nullptr); verifyTensorDescriptor(meanScoped.get(), K_LAYERNORMBACKWARD_TENSOR_MEAN_UID, HIPDNN_DATA_FLOAT, {16, 1, 1, 1}, {1, 1, 1, 1}); // Verify inv_variance tensor (optional) hipdnn_backend::ScopedDescriptor invVarianceScoped; int64_t invVarianceCount = 0; desc->getAttribute(HIPDNN_ATTR_OPERATION_LAYERNORM_BACKWARD_INV_VARIANCE_EXT, HIPDNN_TYPE_BACKEND_DESCRIPTOR, 1, &invVarianceCount, static_cast(invVarianceScoped.getPtr())); ASSERT_EQ(invVarianceCount, 1); ASSERT_NE(invVarianceScoped.get(), nullptr); verifyTensorDescriptor(invVarianceScoped.get(), K_LAYERNORMBACKWARD_TENSOR_INV_VARIANCE_UID, HIPDNN_DATA_FLOAT, {16, 1, 1, 1}, {1, 1, 1, 1}); // Verify epsilon tensor (optional) hipdnn_backend::ScopedDescriptor epsilonScoped; int64_t epsilonCount = 0; desc->getAttribute(HIPDNN_ATTR_OPERATION_LAYERNORM_BACKWARD_EPSILON_EXT, HIPDNN_TYPE_BACKEND_DESCRIPTOR, 1, &epsilonCount, static_cast(epsilonScoped.getPtr())); ASSERT_EQ(epsilonCount, 1); ASSERT_NE(epsilonScoped.get(), nullptr); verifyTensorDescriptor( epsilonScoped.get(), K_LAYERNORMBACKWARD_TENSOR_EPSILON_UID, HIPDNN_DATA_FLOAT, {1}, {1}); // Verify operation type hipdnnOperationType_ext_t opType = HIPDNN_OPERATION_TYPE_NOT_SET_EXT; int64_t opTypeCount = 0; desc->getAttribute( HIPDNN_ATTR_OPERATION_TYPE_EXT, HIPDNN_TYPE_OPERATION_TYPE_EXT, 1, &opTypeCount, &opType); ASSERT_EQ(opTypeCount, 1); EXPECT_EQ(opType, HIPDNN_OPERATION_TYPE_LAYERNORM_BACKWARD_EXT); } TEST_F(TestLayernormBackwardOperationFromNode, NamePreservedFromNode) { auto node = createStandardNode(); node.name = "test_layernormbackward_1"; auto desc = LayernormBackwardOperationDescriptor::fromNode(node, _tensorMap); int64_t count = 0; desc->getAttribute(HIPDNN_ATTR_OPERATION_NAME_EXT, HIPDNN_TYPE_CHAR, 0, &count, nullptr); ASSERT_EQ(count, static_cast(std::string("test_layernormbackward_1").size() + 1)); std::vector buffer(static_cast(count)); int64_t actualCount = 0; desc->getAttribute( HIPDNN_ATTR_OPERATION_NAME_EXT, HIPDNN_TYPE_CHAR, count, &actualCount, buffer.data()); EXPECT_STREQ(buffer.data(), "test_layernormbackward_1"); } TEST_F(TestLayernormBackwardOperationFromNode, EmptyNamePreservedFromNode) { auto node = createStandardNode(); auto desc = LayernormBackwardOperationDescriptor::fromNode(node, _tensorMap); int64_t count = 0; desc->getAttribute(HIPDNN_ATTR_OPERATION_NAME_EXT, HIPDNN_TYPE_CHAR, 0, &count, nullptr); EXPECT_EQ(count, 1); } TEST_F(TestLayernormBackwardOperationFromNode, BuildNodePreservesName) { auto node = createStandardNode(); node.name = "test_build_name"; auto desc = LayernormBackwardOperationDescriptor::fromNode(node, _tensorMap); const auto rebuiltNode = desc->buildNode(); ASSERT_NE(rebuiltNode, nullptr); EXPECT_EQ(rebuiltNode->name, "test_build_name"); }