// Copyright (c) 2018 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 #include #include "paddle/fluid/framework/op_registry.h" #include "paddle/fluid/framework/op_version_registry.h" #include "paddle/fluid/framework/operator.h" #include "paddle/fluid/platform/enforce.h" namespace paddle { namespace operators { class AllcloseOpMaker : public framework::OpProtoAndCheckerMaker { public: void Make() override { AddInput("Input", "The input tensor, it's data type should be float32, float64."); AddInput("Other", "The input tensor, it's data type should be float32, float64."); AddInput("Rtol", "The relative tolerance.").AsDispensable(); AddInput("Atol", "The absolute tolerance.").AsDispensable(); AddOutput("Out", "The output tensor, it's data type is bool."); AddAttr("rtol", "The relative tolerance. Default: :math:`1e-5` .") .SetDefault("1e-5"); AddAttr("atol", "The absolute tolerance. Default: :math:`1e-8` .") .SetDefault("1e-8"); AddAttr("equal_nan", "If :math:`True` , then two :math:`NaNs` will be " "compared as equal. Default: :math:`False` .") .SetDefault(false); AddComment(R"DOC( This operator checks if all :math:`x` and :math:`y` satisfy the condition: .. math:: \left| x - y \right| \leq atol + rtol \times \left| y \right| elementwise, for all elements of :math:`x` and :math:`y`. The behaviour of this operator is analogous to :math:`numpy.allclose`, namely that it returns :math:`True` if two tensors are elementwise equal within a tolerance. )DOC"); } }; class AllcloseOp : public framework::OperatorWithKernel { public: using framework::OperatorWithKernel::OperatorWithKernel; void InferShape(framework::InferShapeContext* ctx) const override { OP_INOUT_CHECK(ctx->HasInput("Input"), "Input", "Input", "Allclose"); OP_INOUT_CHECK(ctx->HasInput("Other"), "Input", "Other", "Allclose"); OP_INOUT_CHECK(ctx->HasOutput("Out"), "Output", "Out", "Allclose"); auto input_dim = ctx->GetInputDim("Input"); auto other_dim = ctx->GetInputDim("Other"); PADDLE_ENFORCE_EQ(input_dim.size(), other_dim.size(), platform::errors::PreconditionNotMet( "Input(Input) and Input(Other) must have the same " "dimension size.")); int n = input_dim.size(); bool is_runtime = ctx->IsRuntime(); for (int i = 0; i < n; i++) { if (is_runtime) { PADDLE_ENFORCE_EQ(input_dim[i], other_dim[i], platform::errors::PreconditionNotMet( "The value at dim %d of Input(Input) is not " "equal to the Input(Other): %ld != %ld.", i, input_dim[i], other_dim[i])); } else { if (!(input_dim[i] < 0 || other_dim[i] < 0)) { PADDLE_ENFORCE_EQ(input_dim[i], other_dim[i], platform::errors::PreconditionNotMet( "The value at dim %d of Input(Input) is not " "equal to the Input(Other): %ld != %ld.", i, input_dim[i], other_dim[i])); } } } ctx->SetOutputDim("Out", phi::make_ddim({1})); } protected: framework::OpKernelType GetExpectedKernelType( const framework::ExecutionContext& ctx) const override { return framework::OpKernelType( OperatorWithKernel::IndicateVarDataType(ctx, "Input"), ctx.device_context()); } }; class AllcloseOpVarTypeInference : public framework::VarTypeInference { public: void operator()(framework::InferVarTypeContext* ctx) const override { ctx->SetOutputDataType("Out", framework::proto::VarType::BOOL); } }; } // namespace operators } // namespace paddle namespace ops = paddle::operators; using CPU = paddle::platform::CPUDeviceContext; REGISTER_OPERATOR( allclose, ops::AllcloseOp, ops::AllcloseOpMaker, paddle::framework::EmptyGradOpMaker, paddle::framework::EmptyGradOpMaker, ops::AllcloseOpVarTypeInference); /* ========================== register checkpoint ===========================*/ REGISTER_OP_VERSION(allclose) .AddCheckpoint( R"ROC(Upgrade allclose, add two new inputs [Rtol] and [Atol].)ROC", paddle::framework::compatible::OpVersionDesc() .NewInput("Rtol", "The added input 'Rtol' is not" "dispensable.") .NewInput("Atol", "The added input 'Atol' is not" "dispensable.")) .AddCheckpoint( R"ROC(Delete two float attributes [rtol] and [atol], then add 2 string attributes [atol, rtol]. Don't be surprised. This is because float cannot represent hight-precision floating-point values, and our framework doesn't support the use of double attributes. As a result, string instead of double is used here to represent high-precision floating-point values. )ROC", paddle::framework::compatible::OpVersionDesc() .DeleteAttr("rtol", "The attribute 'rtol' is deleted." "The reason why it is deleted is that" "attributes do not support a float64 value" "and it is changed to a tensor.") .DeleteAttr("atol", "The attribute 'atol' is deleted." "The reason why it is deleted is that" "attributes do not support a float64 value" "and it is changed to a tensor.") .NewAttr("rtol", "(string) The relative tolerance. Default: :math:`1e-5` .", std::string("1e-5")) .NewAttr("atol", "(string) The absolute tolerance. Default: :math:`1e-8` .", std::string("1e-8")));