grad_tensor_holder.cc 3.9 KB
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// Copyright (c) 2021 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 "paddle/fluid/eager/grad_tensor_holder.h"
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#include "paddle/fluid/imperative/gradient_accumulator.h"
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#include "paddle/fluid/framework/convert_utils.h"
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#include "paddle/fluid/framework/var_type.h"
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#include "paddle/phi/kernels/funcs/math_function.h"
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namespace egr {

void GradTensorHolder::add(size_t slot_id, size_t rank,
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                           const paddle::experimental::Tensor& t,
                           bool fill_one) {
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  // TODO(jiabin): We need to deal with empty input_buffer with slot size not
  // empty;
  PADDLE_ENFORCE(slot_id < buffer_.size(),
                 paddle::platform::errors::Fatal(
                     "Invalid slot_id for GradTensorHolder::add() "
                     "which exceeds size of buffer"));
  VLOG(6) << "Add Tensor for buffer_ slot: " << slot_id
          << ", size: " << buffer_[slot_id].size();
  if (buffer_[slot_id].empty()) {
    VLOG(6) << "Pass add Tensor for buffer_ slot: " << slot_id
            << " since its buffer_ is empty ";
    return;
  }
  PADDLE_ENFORCE(
      rank < buffer_[slot_id].size(),
      paddle::platform::errors::Fatal(
          "Invalid rank for GradTensorHolder::add() which exceeds size "
          "of buffer slot %d, got slot size is: %d rank is: %d",
          slot_id, buffer_[slot_id].size(), rank));
  if (!fill_one) {
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    paddle::experimental::Tensor& buffer_tensor = buffer_[slot_id][rank];
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    // TODO(jiabin): Code bellow is ugly to divide which inner var we used,
    // remove framework::Variable
    // related code later.
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    // This if statement is trying to test neither phi::Tensor nor
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    // framework::Variable is initialized.
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    if ((!buffer_tensor.defined() || !buffer_tensor.initialized())) {
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      // Simply copy tensor->impl
      buffer_tensor = t;
    } else {
      // Accumulation
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      PADDLE_ENFORCE_EQ(t.initialized(), true,
                        paddle::platform::errors::Fatal(
                            "We can only accumulate initialized tensor, but we "
                            "got tensor: %s is empty please check you network "
                            "and make sure it creates grads.",
                            t.name()));
      if (t.is_dense_tensor()) {
        if (buffer_tensor.is_dense_tensor()) {
          paddle::imperative::TensorAdd<paddle::experimental::Tensor>(
              t, &buffer_tensor);
        } else {
          // TODO(jiabin): Support Other TensorBase later
          paddle::experimental::Tensor new_buffer(
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              std::make_shared<phi::DenseTensor>(), "tmp_accumulator");
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          paddle::imperative::SelectedRowsAddTensor(buffer_tensor, t,
                                                    &new_buffer);
          buffer_tensor.set_impl(new_buffer.impl());
        }
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      } else {
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        // TODO(jiabin): Support Other TensorBase later
        if (buffer_tensor.is_dense_tensor()) {
          paddle::imperative::SelectedRowsAddToTensor(t, &buffer_tensor);
        } else {
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          buffer_tensor =
              std::move(*paddle::imperative::SelectedRowsMerge<
                        paddle::experimental::Tensor>(t, buffer_tensor));
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        }
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      }
    }
  } else {
    // Create new tensor->impl and fill it with 1.0
    if (t.defined()) {
      // Fill 1.0
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      buffer_[slot_id][rank] = paddle::experimental::ones_like(t);
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    }
  }
}

}  // namespace egr