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75 lines
2.6 KiB
75 lines
2.6 KiB
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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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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http://www.apache.org/licenses/LICENSE-2.0
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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/operators/clip_by_norm_op.h"
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namespace paddle {
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namespace operators {
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class ClipByNormOp : 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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void InferShape(framework::InferShapeContext* ctx) const override {
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PADDLE_ENFORCE(ctx->HasInput("X"),
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"Input(X) of ClipByNormOp should not be null.");
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PADDLE_ENFORCE(ctx->HasOutput("Out"),
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"Output(Out) of ClipByNormOp should not be null.");
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auto max_norm = ctx->Attrs().Get<float>("max_norm");
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PADDLE_ENFORCE_GT(max_norm, 0, "max_norm should be greater than 0.");
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auto x_dims = ctx->GetInputDim("X");
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ctx->SetOutputDim("Out", x_dims);
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ctx->ShareLoD("X", /*->*/ "Out");
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}
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};
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class ClipByNormOpMaker : public framework::OpProtoAndCheckerMaker {
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public:
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ClipByNormOpMaker(framework::OpProto* proto,
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framework::OpAttrChecker* op_checker)
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: OpProtoAndCheckerMaker(proto, op_checker) {
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AddInput("X",
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"(Tensor) The input of clip_by_norm op."
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"The number of dimensions must be between [1, 9].");
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AddOutput("Out",
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"(Tensor) The output of clip_by_norm op with shape as input(X)");
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AddAttr<float>("max_norm", "(float) The maximum norm value.");
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AddComment(R"DOC(
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ClipByNorm Operator.
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This operator limits the L2 norm of the input $X$ within $max\_norm$.
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If the L2 norm of $X$ is less than or equal to $max\_norm$, $Out$ will be
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the same as $X$. If the L2 norm of $X$ is greater than $max\_norm$, $X$ will
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be linearly scaled to make the L2 norm of $Out$ equal to $max\_norm$, as
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shown in the following formula:
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$$
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Out = \frac{max\_norm * X}{norm(X)},
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$$
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where $norm(X)$ represents the L2 norm of $X$.
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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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namespace ops = paddle::operators;
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REGISTER_OP_WITHOUT_GRADIENT(clip_by_norm, ops::ClipByNormOp,
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ops::ClipByNormOpMaker);
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REGISTER_OP_CPU_KERNEL(
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clip_by_norm, ops::ClipByNormKernel<paddle::platform::CPUPlace, float>);
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