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64 lines
2.1 KiB
64 lines
2.1 KiB
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved.
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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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#pragma once
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#include <chrono> // NOLINT
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#include <vector>
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#include "paddle/fluid/framework/op_registry.h"
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#include "paddle/fluid/operators/strided_memcpy.h"
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namespace paddle {
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namespace operators {
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template <typename DeviceContext, typename T>
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class SplitOpKernel : public framework::OpKernel<T> {
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public:
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void Compute(const framework::ExecutionContext& ctx) const override {
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auto* in = ctx.Input<framework::Tensor>("X");
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auto outs = ctx.MultiOutput<framework::Tensor>("Out");
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auto in_stride = framework::stride_numel(in->dims());
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int64_t axis = static_cast<int64_t>(ctx.Attr<int>("axis"));
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auto place = ctx.GetPlace();
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size_t input_offset = 0;
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for (auto& out : outs) {
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out->mutable_data<T>(ctx.GetPlace());
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auto out_stride = framework::stride_numel(out->dims());
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StridedNumelCopyWithAxis<T>(ctx.device_context(), axis, out->data<T>(),
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out_stride, in->data<T>() + input_offset,
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in_stride, out_stride[axis]);
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input_offset += out_stride[axis];
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}
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}
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};
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class SplitGradMaker : public framework::SingleGradOpDescMaker {
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public:
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using framework::SingleGradOpDescMaker::SingleGradOpDescMaker;
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protected:
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std::unique_ptr<framework::OpDesc> Apply() const override {
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auto op = new framework::OpDesc();
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op->SetType("concat");
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op->SetInput("X", OutputGrad("Out"));
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op->SetOutput("Out", InputGrad("X"));
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op->SetAttrMap(Attrs());
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return std::unique_ptr<framework::OpDesc>(op);
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}
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};
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} // namespace operators
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} // namespace paddle
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