wehub-resource-sync
95 lines
3.4 KiB
C++
95 lines
3.4 KiB
C++
// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#include "paddle/fluid/framework/infershape_utils.h"
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#include "paddle/fluid/framework/op_registry.h"
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#include "paddle/phi/core/infermeta_utils.h"
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#include "paddle/phi/infermeta/binary.h"
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namespace paddle {
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namespace operators {
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class SequenceMaskOp : public framework::OperatorWithKernel {
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public:
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using framework::OperatorWithKernel::OperatorWithKernel;
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protected:
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phi::KernelKey GetExpectedKernelType(
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const framework::ExecutionContext& ctx) const override {
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return phi::KernelKey(OperatorWithKernel::IndicateVarDataType(ctx, "X"),
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ctx.GetPlace());
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}
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phi::KernelKey GetKernelTypeForVar(
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const std::string& var_name,
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const phi::DenseTensor& tensor,
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const phi::KernelKey& expected_kernel_type) const override {
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if (var_name == "depth_tensor") {
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return phi::KernelKey(phi::Backend::ALL_BACKEND,
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expected_kernel_type.layout(),
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expected_kernel_type.dtype());
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}
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return phi::KernelKey(
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tensor.place(), tensor.layout(), expected_kernel_type.dtype());
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}
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};
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class SequenceMaskOpMaker : public framework::OpProtoAndCheckerMaker {
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public:
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void Make() override {
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AddInput("X", "The input tensor of sequence_mask op.");
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AddOutput("Y", "The output mask of sequence_mask op.");
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AddInput("MaxLenTensor",
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"Max length tensor "
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"have higher priority than maxlen attribute")
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.AsDispensable();
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AddAttr<int>("maxlen",
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"The maximum length of the sequence. If maxlen < 0, maxlen "
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"= max(Input(X)).")
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.SetDefault(-1)
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.AddCustomChecker([](const int& v) {
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PADDLE_ENFORCE_EQ(
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v < 0 || v >= 1,
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true,
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common::errors::InvalidArgument(
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"Attr(maxlen) must be less than 0 or larger than 1"));
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});
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AddAttr<int>("out_dtype", "Output data type");
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AddComment(R"DOC(
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SequenceMask Operator
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This operator outputs a Mask according to Input(X) and Attr(maxlen).
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Supposing Input(X) is a DenseTensor with shape [d_1, d_2, ..., d_n], the
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Output(Y) is a mask with shape [d_1, d_2, ..., d_n, maxlen], where:
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Y(i_1, i_2, ..., i_n, j) = (j < X(i_1, i_2, ..., i_n))
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If maxlen < 0, maxlen = max(X)
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)DOC");
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}
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};
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} // namespace operators
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} // namespace paddle
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DECLARE_INFER_SHAPE_FUNCTOR(sequence_mask,
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SequenceMaskInferShapeFunctor,
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PD_INFER_META(phi::SequenceMaskInferMeta));
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REGISTER_OPERATOR(
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sequence_mask,
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paddle::operators::SequenceMaskOp,
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paddle::operators::SequenceMaskOpMaker,
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paddle::framework::EmptyGradOpMaker<paddle::framework::OpDesc>,
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paddle::framework::EmptyGradOpMaker<paddle::imperative::OpBase>,
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SequenceMaskInferShapeFunctor);
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