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123 lines
4.1 KiB
123 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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namespace paddle {
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namespace framework {
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extern size_t SizeOfType(std::type_index 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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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(platform::Place place, std::type_index type,
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size_t requested_size) {
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if (holder_ != nullptr) {
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holder_->set_type(type);
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}
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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::Resize has been called first.");
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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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if (platform::is_cpu_place(place)) {
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holder_.reset(new PlaceholderImpl<platform::CPUPlace>(
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boost::get<platform::CPUPlace>(place), size, type));
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} else if (platform::is_gpu_place(place) ||
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platform::is_cuda_pinned_place(place)) {
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#ifndef PADDLE_WITH_CUDA
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PADDLE_THROW(
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"CUDAPlace or CUDAPinnedPlace is not supported in CPU-only mode.");
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}
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#else
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if (platform::is_gpu_place(place)) {
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holder_.reset(new PlaceholderImpl<platform::CUDAPlace>(
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boost::get<platform::CUDAPlace>(place), size, type));
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} else if (platform::is_cuda_pinned_place(place)) {
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holder_.reset(new PlaceholderImpl<platform::CUDAPinnedPlace>(
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boost::get<platform::CUDAPinnedPlace>(place), size, type));
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}
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}
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#endif
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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(platform::Place place, size_t requested_size) {
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PADDLE_ENFORCE(this->holder_ != nullptr,
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"Cannot invoke mutable data if current hold nothing.");
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return mutable_data(place, holder_->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(int begin_idx, int 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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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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} // namespace framework
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} // namespace paddle
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