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125 lines
4.1 KiB
125 lines
4.1 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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#include "paddle/fluid/framework/tensor.h"
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#include "paddle/fluid/framework/var_type.h"
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namespace paddle {
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namespace framework {
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extern size_t SizeOfType(proto::VarType::Type type);
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void Tensor::check_memory_size() const {
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PADDLE_ENFORCE_NOT_NULL(
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holder_, "Tensor holds no memory. Call Tensor::mutable_data first.");
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PADDLE_ENFORCE_LE(
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numel() * SizeOfType(type()), memory_size(),
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"Tensor's dims_ is out of bound. Call Tensor::mutable_data "
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"first to re-allocate memory.\n"
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"or maybe the required data-type mismatches the data already stored.");
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}
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Tensor::Tensor(const proto::VarType::Type& dtype) : type_(dtype), offset_(0) {}
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size_t Tensor::memory_size() const {
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return holder_ == nullptr ? 0UL : holder_->size() - offset_;
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}
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void* Tensor::mutable_data(const platform::Place& place,
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proto::VarType::Type type, size_t requested_size) {
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type_ = type;
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PADDLE_ENFORCE_GE(numel(), 0,
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"When calling this method, the Tensor's numel must be "
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"equal or larger than zero. "
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"Please check Tensor::dims, or Tensor::Resize has been "
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"called first. The Tensor's shape is [",
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dims(), "] now");
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size_t size = numel() * SizeOfType(type);
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if (requested_size) {
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PADDLE_ENFORCE_GE(requested_size, size);
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size = requested_size;
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}
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/* some versions of boost::variant don't have operator!= */
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if (holder_ == nullptr || !(holder_->place() == place) ||
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holder_->size() < size + offset_) {
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// Reset holder first before re-allocate to save memory
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holder_.reset();
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holder_ = memory::AllocShared(place, size);
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offset_ = 0;
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}
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return reinterpret_cast<void*>(reinterpret_cast<uintptr_t>(holder_->ptr()) +
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offset_);
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}
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void* Tensor::mutable_data(const platform::Place& place,
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size_t requested_size) {
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PADDLE_ENFORCE_NOT_NULL(
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this->holder_, "Cannot invoke mutable data if current hold nothing.");
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return mutable_data(place, type_, requested_size);
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}
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Tensor& Tensor::ShareDataWith(const Tensor& src) {
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src.check_memory_size();
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*this = src;
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return *this;
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}
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Tensor Tensor::Slice(int64_t begin_idx, int64_t end_idx) const {
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check_memory_size();
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PADDLE_ENFORCE_GE(begin_idx, 0,
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"The start row index must be greater than 0.");
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PADDLE_ENFORCE_LE(end_idx, dims_[0], "The end row index is out of bound.");
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PADDLE_ENFORCE_LT(
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begin_idx, end_idx,
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"The start row index must be lesser than the end row index.");
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if (dims_[0] == 1) {
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return *this;
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} else {
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size_t base = numel() / dims_[0];
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Tensor dst;
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dst.holder_ = holder_;
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dst.set_layout(layout_);
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dst.type_ = type_;
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DDim dst_dims = dims_;
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dst_dims[0] = end_idx - begin_idx;
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dst.Resize(dst_dims);
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dst.offset_ = offset_ + begin_idx * base * SizeOfType(type());
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return dst;
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}
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}
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Tensor& Tensor::Resize(const DDim& dims) {
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dims_ = dims;
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return *this;
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}
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const DDim& Tensor::dims() const { return dims_; }
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int64_t Tensor::numel() const { return product(dims_); }
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void Tensor::ResetHolder(std::shared_ptr<memory::Allocation> holder) {
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if (holder_) {
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PADDLE_ENFORCE_EQ(numel() * SizeOfType(type()), holder->size());
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}
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holder_ = holder;
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}
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void Tensor::ResetHolderWithType(std::shared_ptr<memory::Allocation> holder,
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const proto::VarType::Type type) {
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ResetHolder(holder);
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type_ = type;
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}
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} // namespace framework
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} // namespace paddle
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