/* Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */ #include "paddle/fluid/operators/bmm_op.h" #include namespace paddle { namespace operators { class BmmOp : public framework::OperatorWithKernel { public: using framework::OperatorWithKernel::OperatorWithKernel; protected: void InferShape(framework::InferShapeContext* ctx) const override { PADDLE_ENFORCE_EQ( ctx->HasInput("X"), true, platform::errors::NotFound("Input(X) of BmmOp should not be null")); PADDLE_ENFORCE_EQ( ctx->HasInput("Y"), true, platform::errors::NotFound("Input(Y) of BmmOp should not be null")); PADDLE_ENFORCE_EQ( ctx->HasOutput("Out"), true, platform::errors::NotFound("Output(Out) of BmmOp should not be null.")); auto x_dims = ctx->GetInputDim("X"); auto y_dims = ctx->GetInputDim("Y"); PADDLE_ENFORCE_EQ(x_dims.size(), 3, platform::errors::InvalidArgument( "Input(X) of BmmOp must be 3-dimensional in BmmOp, " "but received X's shape: [%s].", x_dims)); PADDLE_ENFORCE_EQ(y_dims.size(), 3, platform::errors::InvalidArgument( "Input(Y) of BmmOp must be 3-dimensional in BmmOp, " "but received Y's shape: [%s].", y_dims)); PADDLE_ENFORCE_EQ( x_dims[0], y_dims[0], platform::errors::InvalidArgument( "Input(X) and Input(Y) must have the same batch size in BmmOp, " "but received X's batch size: [%s]," "Y's batch size [%s]", x_dims[0], y_dims[0])); PADDLE_ENFORCE_EQ( x_dims[2], y_dims[1], platform::errors::InvalidArgument( "Input(X)'s width must be equal with Input(Y)'s height in BmmOp," "but receive X's width: [%s]," "Y's height: [%s].", x_dims[2], y_dims[1])); std::vector dim_out; dim_out.push_back(x_dims[0]); dim_out.push_back(x_dims[1]); dim_out.push_back(y_dims[2]); ctx->SetOutputDim("Out", pten::make_ddim(dim_out)); ctx->ShareLoD("X", /*->*/ "Out"); } framework::OpKernelType GetExpectedKernelType( const framework::ExecutionContext& ctx) const override { auto data_type = OperatorWithKernel::IndicateVarDataType(ctx, "X"); return framework::OpKernelType(data_type, ctx.device_context()); } }; class BmmOpMaker : public framework::OpProtoAndCheckerMaker { public: void Make() override { AddInput("X", "(Tensor), The first input tensor of Bmm op."); AddInput("Y", "(Tensor), The second input tensor of Bmm op."); AddOutput("Out", "(Tensor), The output tensor of Bmm op."); AddComment(R"DOC( The Bmm operator is used to perform batched matrix multiplication over the last two dimensions of the input tensors `X` and `Y` which are both 3-dimentionsal. Examples: - X: [B, M, K], Y: [B, K, N] => Out: [B, M, N] )DOC"); } }; class BmmOpGrad : public framework::OperatorWithKernel { public: using framework::OperatorWithKernel::OperatorWithKernel; protected: void InferShape(framework::InferShapeContext* ctx) const override { PADDLE_ENFORCE_EQ( ctx->HasInput("X"), true, platform::errors::NotFound("Input(X) of BmmOp should not be null")); PADDLE_ENFORCE_EQ( ctx->HasInput("Y"), true, platform::errors::NotFound("Input(Y) of BmmOp should not be null")); PADDLE_ENFORCE_EQ(ctx->HasInput(framework::GradVarName("Out")), true, platform::errors::NotFound( "Output(Out@GRAD) of BmmOp should not be null.")); auto x_dims = ctx->GetInputDim("X"); auto y_dims = ctx->GetInputDim("Y"); auto x_grad_name = framework::GradVarName("X"); auto y_grad_name = framework::GradVarName("Y"); if (ctx->HasOutput(x_grad_name)) { ctx->SetOutputDim(x_grad_name, x_dims); } if (ctx->HasOutput(y_grad_name)) { ctx->SetOutputDim(y_grad_name, y_dims); } } framework::OpKernelType GetExpectedKernelType( const framework::ExecutionContext& ctx) const override { return framework::OpKernelType(OperatorWithKernel::IndicateVarDataType( ctx, framework::GradVarName("Out")), ctx.device_context()); } }; template class BmmOpGradMaker : public framework::SingleGradOpMaker { public: using framework::SingleGradOpMaker::SingleGradOpMaker; protected: void Apply(GradOpPtr retv) const override { retv->SetType("bmm_grad"); retv->SetInput("X", this->Input("X")); retv->SetInput("Y", this->Input("Y")); retv->SetInput(framework::GradVarName("Out"), this->OutputGrad("Out")); retv->SetOutput(framework::GradVarName("X"), this->InputGrad("X")); retv->SetOutput(framework::GradVarName("Y"), this->InputGrad("Y")); } }; } // namespace operators } // namespace paddle namespace ops = paddle::operators; REGISTER_OPERATOR(bmm, ops::BmmOp, ops::BmmOpMaker, ops::BmmOpGradMaker, ops::BmmOpGradMaker); REGISTER_OPERATOR(bmm_grad, ops::BmmOpGrad); REGISTER_OP_CPU_KERNEL( bmm, ops::BmmKernel, ops::BmmKernel); REGISTER_OP_CPU_KERNEL( bmm_grad, ops::BmmGradKernel, ops::BmmGradKernel);