// Copyright (c) 2018 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/framework/dlpack_tensor.h" #include "paddle/fluid/framework/data_type.h" namespace paddle { namespace platform { struct bfloat16; struct float16; } // namespace platform } // namespace paddle namespace paddle { namespace framework { namespace internal { template static ::DLDataType GetDLDataTypeCode() { ::DLDataType dtype; if (std::is_same>::value || std::is_same>::value) { dtype.code = kDLComplex; } else if (std::is_same::value) { dtype.code = kDLBfloat; } else if (std::is_same::value || std::is_floating_point::value) { dtype.code = kDLFloat; } else if (std::is_unsigned::value) { dtype.code = kDLUInt; } else if (std::is_integral::value) { dtype.code = kDLInt; } else { PADDLE_THROW(platform::errors::Unavailable( "Unsupported data type (%s), only supports float16, float, unsigned " "int and int.", platform::demangle(typeid(T).name()))); } dtype.bits = 8 * sizeof(T); dtype.lanes = 1; return dtype; } static std::unordered_map CreateDLDataTypeMap() { static std::unordered_map result; #define REG_DL_DATA_TYPE(cpp_type, proto_type) \ result[static_cast(proto_type)] = GetDLDataTypeCode() _ForEachDataType_(REG_DL_DATA_TYPE); #undef REG_DL_DATA_TYPE return result; } static DLDataType GetDLDataTypeFromTypeIndex(proto::VarType::Type type) { static auto type_to_dtype_map = CreateDLDataTypeMap(); static auto type_to_dtype_map_end_it = type_to_dtype_map.end(); auto it = type_to_dtype_map.find(static_cast(type)); PADDLE_ENFORCE_NE(it, type_to_dtype_map_end_it, platform::errors::InvalidArgument( "Unsupported data type (%s).", DataTypeToString(type))); return it->second; #undef REG_DL_DATA_TYPE } struct DLDeviceVisitor : public boost::static_visitor<::DLDevice> { inline ::DLDevice operator()(const platform::CPUPlace &place) const { ::DLDevice device; device.device_type = kDLCPU; device.device_id = 0; return device; } inline ::DLDevice operator()(const platform::IPUPlace &place) const { PADDLE_THROW( platform::errors::Unimplemented("platform::IPUPlace is not supported")); } inline ::DLDevice operator()(const platform::XPUPlace &place) const { PADDLE_THROW( platform::errors::Unimplemented("platform::XPUPlace is not supported")); } inline ::DLDevice operator()(const platform::NPUPlace &place) const { PADDLE_THROW( platform::errors::Unimplemented("platform::NPUPlace is not supported")); } inline ::DLDevice operator()(const platform::NPUPinnedPlace &place) const { PADDLE_THROW(platform::errors::Unimplemented( "platform::NPUPinnedPlace is not supported")); } inline ::DLDevice operator()(const platform::MLUPlace &place) const { PADDLE_THROW( platform::errors::Unimplemented("platform::MLUPlace is not supported")); } inline ::DLDevice operator()(const platform::CUDAPlace &place) const { #if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP) ::DLDevice device; device.device_type = kDLGPU; device.device_id = place.device; return device; #else PADDLE_THROW(platform::errors::Unavailable( "platform::CUDAPlace is not supported in CPU only version.")); #endif } inline ::DLDevice operator()(const platform::CUDAPinnedPlace &place) const { #if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP) ::DLDevice device; device.device_type = kDLCPUPinned; device.device_id = 0; return device; #else PADDLE_THROW(platform::errors::Unavailable( "platform::CUDAPinnedPlace is not supported in CPU only version.")); #endif } }; } // namespace internal DLPackTensor::DLPackTensor(const Tensor &tensor, LaneType lanes) { // init data, data buffer t_.data = const_cast(tensor.data()); // init device, DLDevice type with device_type and device_id auto place = tensor.place(); t_.device = boost::apply_visitor(internal::DLDeviceVisitor(), place); // init dtype t_.dtype = internal::GetDLDataTypeFromTypeIndex(tensor.type()); t_.dtype.lanes = lanes; // init ndim, tensor rank auto &dims = tensor.dims(); using DimType = decltype(t_.ndim); // int t_.ndim = static_cast(dims.size()); // init shape, tensor dims t_.shape = shape_; for (DimType i = 0; i < t_.ndim; ++i) { t_.shape[i] = dims[i]; } // init strides, nullptr means the tensor is compact t_.strides = nullptr; // init byte_offset t_.byte_offset = 0; } ::DLManagedTensor *DLPackTensor::ToDLManagedTensor() { // init shape auto shape = new int64_t[t_.ndim]; using DimType = decltype(t_.ndim); // int for (DimType i = 0; i < t_.ndim; ++i) { shape[i] = t_.shape[i]; } t_.shape = shape; // init strides auto strides = new int64_t[t_.ndim]; for (DimType i = 0; i < t_.ndim; ++i) { strides[i] = 1; } for (DimType i = t_.ndim - 2; i >= 0; --i) { strides[i] = t_.shape[i + 1] * strides[i + 1]; } t_.strides = strides; auto tensor = new DLManagedTensor; tensor->dl_tensor = t_; tensor->deleter = [](DLManagedTensor *arg) { delete[] arg->dl_tensor.shape; delete[] arg->dl_tensor.strides; delete arg; }; tensor->manager_ctx = nullptr; return tensor; } } // namespace framework } // namespace paddle