// 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/phi/core/kernel_factory.h" // See Note [ Why still include the fluid headers? ] #include "paddle/phi/core/enforce.h" namespace phi { uint32_t KernelKey::Hash::operator()(const KernelKey& key) const { uint32_t hash_value = 0; // |----31-20------|---19-12---|---11-8----|---7-0---| // | For extension | DataType | DataLayout | Backend | hash_value |= static_cast(key.backend()); hash_value |= (static_cast(key.layout()) << KernelKey::kBackendBitLength); hash_value |= (static_cast(key.dtype()) << (KernelKey::kBackendBitLength + KernelKey::kDataLayoutBitLength)); return hash_value; } KernelFactory& KernelFactory::Instance() { static KernelFactory g_op_kernel_factory; return g_op_kernel_factory; } Kernel KernelFactory::SelectKernel(const std::string& kernel_name, const KernelKey& kernel_key) const { auto iter = kernels_.find(kernel_name); if (iter == kernels_.end()) { return Kernel(); } auto kernel_iter = iter->second.find(kernel_key); if (kernel_iter == iter->second.end()) { return Kernel(); } return kernel_iter->second; } KernelKeyMap KernelFactory::SelectKernelMap( const std::string& kernel_name) const { auto iter = kernels_.find(kernel_name); if (iter == kernels_.end()) { return KernelKeyMap(); } return iter->second; } bool KernelFactory::IsSelectKernelValid(const std::string& kernel_name, const KernelKey& kernel_key) const { auto iter = kernels_.find(kernel_name); PADDLE_ENFORCE_NE( iter, kernels_.end(), phi::errors::NotFound("The kernel `%s` is not registered.", kernel_name)); auto kernel_iter = iter->second.find(kernel_key); if (kernel_iter == iter->second.end()) { return false; } return true; } const Kernel& KernelFactory::SelectKernelOrThrowError( const std::string& kernel_name, const KernelKey& kernel_key, bool use_cudnn) const { auto iter = kernels_.find(kernel_name); PADDLE_ENFORCE_NE( iter, kernels_.end(), phi::errors::NotFound("The kernel `%s` is not registered.", kernel_name)); #if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP) if (use_cudnn && kernel_key.backend() == Backend::GPU) { auto kernel_iter = iter->second.find( {Backend::GPUDNN, kernel_key.layout(), kernel_key.dtype()}); if (kernel_iter == iter->second.end() && kernel_key.layout() != phi::DataLayout::ALL_LAYOUT) { kernel_iter = iter->second.find( {Backend::GPUDNN, DataLayout::ALL_LAYOUT, kernel_key.dtype()}); } if (kernel_iter != iter->second.end()) { return kernel_iter->second; } LOG(WARNING) << "The cudnn kernel for [" << kernel_name << "] is not registered."; } #endif auto kernel_iter = iter->second.find(kernel_key); // TODO(chenweihang): polish refind impl here if (kernel_iter == iter->second.end() && kernel_key.layout() != phi::DataLayout::ALL_LAYOUT) { phi::KernelKey any_layout_kernel_key( kernel_key.backend(), phi::DataLayout::ALL_LAYOUT, kernel_key.dtype()); kernel_iter = iter->second.find(any_layout_kernel_key); } PADDLE_ENFORCE_NE( kernel_iter, iter->second.end(), phi::errors::NotFound( "The kernel with key %s of kernel `%s` is not registered.", kernel_key, kernel_name)); return kernel_iter->second; } const Kernel& KernelFactory::SelectKernelOrThrowError( const std::string& kernel_name, Backend backend, DataLayout layout, DataType dtype) const { return SelectKernelOrThrowError(kernel_name, KernelKey(backend, layout, dtype)); } // print kernel info with json format: // { // "(CPU, Undefined(AnyLayout), complex64)": { // "input": ["CPU, NCHW, complex64", "CPU, NCHW, complex64"], // "output": ["CPU, NCHW, complex64"], // "attribute": ["i"] // } std::ostream& operator<<(std::ostream& os, const Kernel& kernel) { // input os << "{\"input\":["; bool need_comma = false; for (auto& in_def : kernel.args_def().input_defs()) { if (need_comma) os << ","; os << "\"" << in_def.backend << ", " << in_def.layout << ", " << in_def.dtype << "\""; need_comma = true; } os << "],"; // output os << "\"output\":["; need_comma = false; for (auto& out_def : kernel.args_def().output_defs()) { if (need_comma) os << ","; os << "\"" << out_def.backend << ", " << out_def.layout << ", " << out_def.dtype << "\""; need_comma = true; } os << "],"; // attr os << "\"attribute\":["; need_comma = false; for (auto& arg_def : kernel.args_def().attribute_defs()) { if (need_comma) os << ","; os << "\"" << arg_def.type_index.name() << "\""; need_comma = true; } os << "]}"; return os; } // print all kernels info with json format: // { // "kernel_name1": // [ // { // "(CPU, Undefined(AnyLayout), complex64)": { // "input": ["CPU, NCHW, complex64", "CPU, NCHW, complex64"], // "output": ["CPU, NCHW, complex64"], // "attribute": ["i"] // }, // ... // ], // "kernel_name2": [] // ... // } std::ostream& operator<<(std::ostream& os, KernelFactory& kernel_factory) { os << "{"; bool need_comma_kernels = false; for (const auto& op_kernel_pair : kernel_factory.kernels()) { if (need_comma_kernels) os << ","; os << "\"" << op_kernel_pair.first << "\":["; bool need_comma_per_kernel = false; for (const auto& kernel_pair : op_kernel_pair.second) { if (need_comma_per_kernel) os << ","; os << "{\"" << kernel_pair.first << "\":" << kernel_pair.second << "}"; need_comma_per_kernel = true; } os << "]"; need_comma_kernels = true; } os << "}"; return os; } } // namespace phi