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Merge branch 'op2func_refactor' of https://github.com/chenwhql/Paddle …
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| cc_library(pten_dense_tensor SRCS dense_tensor.cc DEPS tensor_base) |
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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. */ | ||
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| #include "paddle/pten/core/candidate/dense_tensor.h" | ||
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| namespace pten { | ||
| namespace candidate { | ||
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| DenseTensorMeta::DenseTensorMeta(DataType type, const DDim& dims) | ||
| : dims(dims), type(type) {} | ||
| DenseTensorMeta::DenseTensorMeta(DataType type, | ||
| const DDim& dims, | ||
| DataLayout layout) | ||
| : dims(dims), type(type), layout(layout) {} | ||
| DenseTensorMeta::DenseTensorMeta(DataType type, | ||
| const DDim& dims, | ||
| DataLayout layout, | ||
| const std::vector<std::vector<size_t>>& lod) | ||
| : dims(dims), type(type), layout(layout), lod(lod) {} | ||
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| bool DenseTensorMeta::valid() const noexcept { | ||
| bool valid{true}; | ||
| valid = valid && (type != DataType::UNDEFINED); | ||
| valid = valid && (layout != DataLayout::UNDEFINED); | ||
| valid = valid && (is_scalar || product(dims)); | ||
| return valid; | ||
| } | ||
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| DenseTensor::DenseTensor(const std::shared_ptr<Allocator>& a, | ||
| const DenseTensorMeta& meta) | ||
| : meta_(meta), | ||
| storage_( | ||
| make_intrusive<TensorStorage>(a, SizeOf(data_type()) * numel())) {} | ||
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| DenseTensor::DenseTensor(const std::shared_ptr<Allocator>& a, | ||
| DenseTensorMeta&& meta) | ||
| : meta_(std::move(meta)), | ||
| storage_( | ||
| make_intrusive<TensorStorage>(a, SizeOf(data_type()) * numel())) {} | ||
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| DenseTensor::DenseTensor(intrusive_ptr<Storage> storage, | ||
| const DenseTensorMeta& meta) | ||
| : meta_(meta), storage_(std::move(storage)) {} | ||
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| DenseTensor::DenseTensor(intrusive_ptr<Storage> storage, DenseTensorMeta&& meta) | ||
| : meta_(std::move(meta)), storage_(std::move(storage)) {} | ||
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| int64_t DenseTensor::numel() const { | ||
| if (meta_.is_scalar) { | ||
| return 1; | ||
| } | ||
| return product(meta_.dims); | ||
| } | ||
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| bool DenseTensor::SharesStorageWith(const DenseTensor& b) const { | ||
| return storage_.get() == b.storage_.get() && storage_.get() != nullptr; | ||
| } | ||
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| template <typename T> | ||
| T* DenseTensor::mutable_data(size_t request_bytes) { | ||
| PADDLE_ENFORCE( | ||
| valid(), | ||
| paddle::platform::errors::PreconditionNotMet( | ||
| "The meta data must be valid when call the mutable data function.")); | ||
| PADDLE_ENFORCE_NOT_NULL( | ||
| storage_, | ||
| paddle::platform::errors::PreconditionNotMet( | ||
| "The storage must be valid when call the mutable data function.")); | ||
| PADDLE_ENFORCE( | ||
| (data_type() == paddle::experimental::CppTypeToDataType<T>::Type()), | ||
| paddle::platform::errors::PreconditionNotMet( | ||
| "The type of data we are trying to retrieve does not match the " | ||
| "type of data currently contained in the container.")); | ||
| size_t bytes = numel() * SizeOf(data_type()); | ||
| if (request_bytes) { | ||
| PADDLE_ENFORCE_GE(request_bytes, | ||
| bytes, | ||
| paddle::platform::errors::InvalidArgument( | ||
| "The reserved size %d should be enough to meet the " | ||
| "volume required by metadata %d.", | ||
| request_bytes, | ||
| bytes)); | ||
| bytes = request_bytes; | ||
| } | ||
| if (storage_->size() < bytes) { | ||
| storage_->Realloc(bytes); | ||
| } | ||
| return static_cast<T*>(storage_->data()); | ||
| } | ||
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| template <typename T> | ||
| const T* DenseTensor::data() const { | ||
| PADDLE_ENFORCE_NOT_NULL( | ||
| storage_, | ||
| paddle::platform::errors::PreconditionNotMet( | ||
| "The storage must be valid when call the mutable data function.")); | ||
| PADDLE_ENFORCE( | ||
| (data_type() == paddle::experimental::CppTypeToDataType<T>::Type()), | ||
| paddle::platform::errors::PreconditionNotMet( | ||
| "The type of data we are trying to retrieve does not match the " | ||
| "type of data currently contained in the container.")); | ||
| return static_cast<const T*>(storage_->data()); | ||
| } | ||
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| void DenseTensor::check_memory_size() const { | ||
| size_t bytes = numel() * SizeOf(data_type()); | ||
| PADDLE_ENFORCE_GE(memory_size(), | ||
| bytes, | ||
| paddle::platform::errors::InvalidArgument( | ||
| "The memory size %d should be enough to meet the " | ||
| "volume required by metadata %d.", | ||
| memory_size(), | ||
| bytes)); | ||
| } | ||
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| #define DATA_MEMBER_FUNC_INSTANTIATION(dtype) \ | ||
| template dtype* DenseTensor::mutable_data(size_t request_bytes); \ | ||
| template const dtype* DenseTensor::data() const; | ||
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| DATA_MEMBER_FUNC_INSTANTIATION(int8_t); | ||
| DATA_MEMBER_FUNC_INSTANTIATION(uint8_t); | ||
| DATA_MEMBER_FUNC_INSTANTIATION(int16_t); | ||
| DATA_MEMBER_FUNC_INSTANTIATION(uint16_t); | ||
| DATA_MEMBER_FUNC_INSTANTIATION(int32_t); | ||
| DATA_MEMBER_FUNC_INSTANTIATION(uint32_t); | ||
| DATA_MEMBER_FUNC_INSTANTIATION(int64_t); | ||
| DATA_MEMBER_FUNC_INSTANTIATION(uint64_t); | ||
| DATA_MEMBER_FUNC_INSTANTIATION(float); | ||
| DATA_MEMBER_FUNC_INSTANTIATION(double); | ||
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| #undef DATA_MEMBER_FUNC_INSTANTIATION | ||
|
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| } // namespace candidate | ||
| } // namespace pten |
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