// 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/trace_op.h" #include "paddle/fluid/framework/op_version_registry.h" namespace paddle { namespace operators { class TraceOp : public framework::OperatorWithKernel { public: using framework::OperatorWithKernel::OperatorWithKernel; void InferShape(framework::InferShapeContext *ctx) const override { PADDLE_ENFORCE_EQ( ctx->HasInput("Input"), true, platform::errors::NotFound("Input of TraceOp is not found.")); PADDLE_ENFORCE_EQ( ctx->HasOutput("Out"), true, platform::errors::NotFound("Output of TraceOp is not found.")); int dim1 = ctx->Attrs().Get("axis1"); int dim2 = ctx->Attrs().Get("axis2"); auto x_dims = ctx->GetInputDim("Input"); int dim1_ = dim1 < 0 ? x_dims.size() + dim1 : dim1; int dim2_ = dim2 < 0 ? x_dims.size() + dim2 : dim2; PADDLE_ENFORCE_GE( x_dims.size(), 2, platform::errors::OutOfRange( "Input's dim is out of range (expected at least 2, but got %ld).", x_dims.size())); PADDLE_ENFORCE_LT( dim1_, x_dims.size(), platform::errors::OutOfRange( "Attr(dim1) is out of range (expected to be in range of [%ld, " "%ld], but got %ld).", -(x_dims.size()), (x_dims.size() - 1), dim1)); PADDLE_ENFORCE_LT( dim2_, x_dims.size(), platform::errors::OutOfRange( "Attr(dim2) is out of range (expected to be in range of [%ld, " "%ld], but got %ld).", -(x_dims.size()), (x_dims.size() - 1), dim2)); PADDLE_ENFORCE_NE(dim1_, dim2_, platform::errors::InvalidArgument( "The dimensions should not be identical " "%ld vs %ld.", dim1, dim2)); auto sizes = vectorize(x_dims); if (x_dims.size() == 2) { sizes.clear(); sizes.push_back(1); } else { sizes.erase(sizes.begin() + std::max(dim1_, dim2_)); sizes.erase(sizes.begin() + std::min(dim1_, dim2_)); } ctx->SetOutputDim("Out", framework::make_ddim(sizes)); } }; class TraceOpMaker : public framework::OpProtoAndCheckerMaker { public: void Make() override { AddInput("Input", "(Tensor) The input tensor, from which the diagonals are taken."); AddOutput("Out", "(Tensor) the sum along diagonals of the input tensor"); AddAttr( "offset", R"DOC((int, default 0), offset of the diagonal from the main diagonal. Can be both positive and negative. Defaults to 0. )DOC") .SetDefault(0); AddAttr( "axis1", R"DOC((int, default 0), the first axis of the 2-D planes from which the diagonals should be taken. Can be either positive or negative. Default: 0. )DOC") .SetDefault(0); AddAttr( "axis2", R"DOC((int, default 1), the second axis of the 2-D planes from which the diagonals should be taken. Can be either positive or negative. Default: 1. )DOC") .SetDefault(1); AddComment(R"DOC( Trace Operator. Return the sum along diagonals of the input tensor. The behavior of this operator is similar to how `numpy.trace` works. If Input is 2-D, returns the sum of diagonal. If Input has larger dimensions, then returns an tensor of diagonals sum, diagonals be taken from the 2-D planes specified by dim1 and dim2. )DOC"); } }; class TraceOpGrad : public framework::OperatorWithKernel { public: using framework::OperatorWithKernel::OperatorWithKernel; void InferShape(framework::InferShapeContext *ctx) const override { PADDLE_ENFORCE_EQ( ctx->HasInput("Input"), true, platform::errors::NotFound("Input(Input) of TraceOp is not found.")); PADDLE_ENFORCE_EQ(ctx->HasOutput(framework::GradVarName("Input")), true, platform::errors::NotFound( "Output(Input@GRAD) of TraceGradOp is not found.")); ctx->SetOutputDim(framework::GradVarName("Input"), ctx->GetInputDim("Input")); } protected: framework::OpKernelType GetExpectedKernelType( const framework::ExecutionContext &ctx) const override { return framework::OpKernelType(OperatorWithKernel::IndicateVarDataType( ctx, framework::GradVarName("Out")), ctx.GetPlace()); } }; template class TraceGradOpMaker : public framework::SingleGradOpMaker { public: using framework::SingleGradOpMaker::SingleGradOpMaker; protected: void Apply(GradOpPtr grad_op) const override { grad_op->SetType("trace_grad"); grad_op->SetInput("Input", this->Input("Input")); grad_op->SetInput(framework::GradVarName("Out"), this->OutputGrad("Out")); grad_op->SetOutput(framework::GradVarName("Input"), this->InputGrad("Input")); grad_op->SetAttrMap(this->Attrs()); } }; DECLARE_NO_NEED_BUFFER_VARS_INFERER(TraceGradNoNeedBufferVarsInferer, "Input"); } // namespace operators } // namespace paddle namespace ops = paddle::operators; REGISTER_OPERATOR(trace, ops::TraceOp, ops::TraceOpMaker, ops::TraceGradOpMaker, ops::TraceGradOpMaker); REGISTER_OPERATOR(trace_grad, ops::TraceOpGrad, ops::TraceGradNoNeedBufferVarsInferer); REGISTER_OP_CPU_KERNEL( trace, ops::TraceKernel, ops::TraceKernel, ops::TraceKernel, ops::TraceKernel, ops::TraceKernel>, ops::TraceKernel>); REGISTER_OP_CPU_KERNEL( trace_grad, ops::TraceGradKernel, ops::TraceGradKernel, ops::TraceGradKernel, ops::TraceGradKernel, ops::TraceGradKernel>, ops::TraceGradKernel>); /* ========================== register checkpoint ===========================*/ REGISTER_OP_VERSION(trace) .AddCheckpoint( R"ROC(Upgrade trace add a new attribute [axis2])ROC", paddle::framework::compatible::OpVersionDesc() .NewAttr("axis1", "The added attribute 'axis1' is not yet registered.", std::vector{0.0f}) .NewAttr("axis2", "The added attribute 'axis2' is not yet registered.", std::vector{1.0f}) .DeleteAttr("dim1", "The attribute 'dim1' is not recommend according to " "the specification 2.0.") .DeleteAttr("dim2", "The attribute 'dim2' is not recommend according to " "the specification 2.0."));