sequence_reshape_op.h 3.1 KB
Newer Older
Y
yangyaming 已提交
1
/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
Y
yangyaming 已提交
2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28

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. */

#pragma once
#include "paddle/framework/op_registry.h"
#include "paddle/operators/math/math_function.h"

namespace paddle {
namespace operators {

using LoDTensor = framework::LoDTensor;
template <typename DeviceContext, typename T>
class SequenceReshapeKernel : public framework::OpKernel<T> {
 public:
  void Compute(const framework::ExecutionContext& context) const override {
    auto* in = context.Input<LoDTensor>("X");
    auto* out = context.Output<LoDTensor>("Out");
29
    int out_width = context.Attr<int>("new_dim");
Y
yangyaming 已提交
30 31 32 33 34 35 36

    auto in_dims = in->dims();
    int64_t in_width = in_dims[1];
    auto& in_lod = in->lod();

    PADDLE_ENFORCE_EQ(in_lod.size(), 1UL,
                      "Only support one level sequence now.");
37 38 39
    PADDLE_ENFORCE_EQ(
        in_dims[0], in_lod[0].back(),
        "Inconsistent size between X.shape[0] and X.lod()[0].back().");
Y
yangyaming 已提交
40 41 42 43

    auto in_lod_l0 = in_lod[0];
    int seq_num = in_lod_l0.size() - 1;

Y
yangyaming 已提交
44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61
    if (in_width == out_width) {
      out->set_lod(in->lod());
    } else {
      auto& out_lod = *out->mutable_lod();
      out_lod.resize(1);
      out_lod[0].clear();
      out_lod[0].push_back(0);
      for (int i = 0; i < seq_num; ++i) {
        size_t seq_len = in_lod_l0[i + 1] - in_lod_l0[i];
        size_t offset = 0;
        offset = (seq_len * in_width) / out_width;
        PADDLE_ENFORCE_EQ(offset * out_width, seq_len * in_width,
                          "Please make sure (sequence_length * dimension) can "
                          "be divided by new_dim with no remainder for each "
                          "sequence. The %dth sequence is invalid.",
                          i + 1);
        out_lod[0].push_back(out_lod[0].back() + offset);
      }
Y
yangyaming 已提交
62 63
    }

64
    out->mutable_data<T>(context.GetPlace());
Y
yangyaming 已提交
65 66
    framework::Copy(*in, context.GetPlace(), out);
    out->Resize({static_cast<int64_t>(out->lod()[0].back()), out_width});
Y
yangyaming 已提交
67 68 69 70 71 72 73 74
  }
};

template <typename DeviceContext, typename T>
class SequenceReshapeGradKernel : public framework::OpKernel<T> {
 public:
  void Compute(const framework::ExecutionContext& context) const override {
    auto* x_tensor_ptr = context.Input<LoDTensor>("X");
Y
yangyaming 已提交
75
    auto* outg_tensor_ptr =
Y
yangyaming 已提交
76
        context.Input<LoDTensor>(framework::GradVarName("Out"));
Y
yangyaming 已提交
77
    auto* xg_tensor_ptr =
Y
yangyaming 已提交
78 79
        context.Output<LoDTensor>(framework::GradVarName("X"));

Y
yangyaming 已提交
80 81 82
    xg_tensor_ptr->mutable_data<T>(context.GetPlace());
    framework::Copy(*outg_tensor_ptr, context.GetPlace(), xg_tensor_ptr);
    xg_tensor_ptr->Resize(x_tensor_ptr->dims());
Y
yangyaming 已提交
83 84 85 86 87
  }
};

}  // namespace operators
}  // namespace paddle