// 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" #include "glog/logging.h" #include "paddle/phi/core/enforce.h" #if defined(PADDLE_WITH_XPU) && !defined(PADDLE_WITH_XPU_KP) #include "paddle/phi/backends/xpu/xpu_op_list.h" #include "paddle/phi/core/compat/convert_utils.h" #endif #include "paddle/phi/core/compat/op_utils.h" #include "paddle/utils/string/string_helper.h" DECLARE_int32(low_precision_op_list); DECLARE_bool(enable_api_kernel_fallback); namespace phi { const static Kernel empty_kernel; // NOLINT std::string KernelSelectionErrorMessage(const std::string& kernel_name, const KernelKey& target_key); 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; } bool KernelFactory::HasCompatiblePhiKernel(const std::string& op_type) const { if (deprecated_op_names.find(op_type) == deprecated_op_names.end()) { if (phi::OpUtilsMap::Instance().Contains(op_type)) { return true; } else if (kernels_.find(op_type) != kernels_.end()) { return true; } } return false; } bool KernelFactory::HasStructuredKernel(const std::string& op_type) const { auto phi_kernel_name = phi::OpUtilsMap::Instance().GetBaseKernelName(op_type); auto kernel_iter = kernels_.find(phi_kernel_name); if (deprecated_op_names.find(op_type) == deprecated_op_names.end() && kernel_iter != kernels_.end()) { return std::any_of(kernel_iter->second.begin(), kernel_iter->second.end(), [](phi::KernelKeyMap::const_reference kernel_pair) { return kernel_pair.second.GetKernelRegisteredType() == KernelRegisteredType::STRUCTURE; }); } return false; } const Kernel& KernelFactory::SelectKernel(const std::string& kernel_name, const KernelKey& kernel_key) const { auto iter = kernels_.find(kernel_name); if (iter == kernels_.end()) { return empty_kernel; } auto kernel_iter = iter->second.find(kernel_key); 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); } if (kernel_iter == iter->second.end()) { return empty_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::HasKernel(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; } void KernelFactory::AddToLowPrecisionKernelList( const std::string& name, const paddle::experimental::DataType& kernel_key_type) { if (FLAGS_low_precision_op_list >= 1) { auto op_name = phi::TransToFluidOpName(name); if (op_name.find("_grad") != std::string::npos) { return; // only record forward api } if (low_precision_kernels_.find(op_name) == low_precision_kernels_.end()) { auto count = OpCount(); low_precision_kernels_[op_name] = count; } if (kernel_key_type == paddle::experimental::DataType::FLOAT16) { low_precision_kernels_[op_name].fp16_called_ += 1; } else if (kernel_key_type == paddle::experimental::DataType::BFLOAT16) { low_precision_kernels_[op_name].bf16_called_ += 1; } else if (kernel_key_type == paddle::experimental::DataType::FLOAT32) { low_precision_kernels_[op_name].fp32_called_ += 1; } else { low_precision_kernels_[op_name].other_called_ += 1; } } } std::map KernelFactory::GetLowPrecisionKernelList() { return low_precision_kernels_; } KernelResult KernelFactory::SelectKernelOrThrowError( const std::string& kernel_name, const KernelKey& const_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)); KernelKey kernel_key = KernelKey(const_kernel_key.backend(), phi::DataLayout::ALL_LAYOUT, const_kernel_key.dtype()); #if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP) if (kernel_key.backend() == Backend::GPUDNN) { auto kernel_iter = iter->second.find( {Backend::GPUDNN, phi::DataLayout::ALL_LAYOUT, kernel_key.dtype()}); if (kernel_iter != iter->second.end()) { return {kernel_iter->second, false}; } kernel_key = KernelKey(Backend::GPU, kernel_key.layout(), kernel_key.dtype()); } #endif auto kernel_iter = iter->second.find(kernel_key); PADDLE_ENFORCE_NE( kernel_iter == iter->second.end() && kernel_key.backend() == Backend::CPU, true, phi::errors::NotFound( "The kernel with key %s of kernel `%s` is not registered. %s", kernel_key, kernel_name, KernelSelectionErrorMessage(kernel_name, kernel_key))); #if defined(PADDLE_WITH_XPU) && !defined(PADDLE_WITH_XPU_KP) VLOG(6) << "fluid_op_name: " << TransToFluidOpName(kernel_name); if ((FLAGS_enable_api_kernel_fallback && kernel_iter == iter->second.end()) || !phi::backends::xpu::is_xpu_support_op(TransToFluidOpName(kernel_name), kernel_key.dtype()) #else if ((FLAGS_enable_api_kernel_fallback && kernel_iter == iter->second.end()) #endif ) { // Fallback CPU backend phi::KernelKey cpu_kernel_key( phi::Backend::CPU, kernel_key.layout(), kernel_key.dtype()); kernel_iter = iter->second.find(cpu_kernel_key); PADDLE_ENFORCE_NE( kernel_iter, iter->second.end(), phi::errors::NotFound( "The kernel with key %s of kernel `%s` is not registered and " "fail to fallback to CPU one. %s", kernel_key, kernel_name, KernelSelectionErrorMessage(kernel_name, kernel_key))); VLOG(3) << "missing " << kernel_key.backend() << " kernel: " << kernel_name << ", expected_kernel_key:" << kernel_key << ", fallbacking to CPU one!"; return {kernel_iter->second, true}; } PADDLE_ENFORCE_NE( kernel_iter, iter->second.end(), phi::errors::NotFound( "The kernel with key %s of kernel `%s` is not registered. %s " "The current value of FLAGS_enable_api_kernel_fallback(bool," " default true) is false. If you want to fallback this kernel" " to CPU one, please set the flag true before run again.", kernel_key, kernel_name, KernelSelectionErrorMessage(kernel_name, kernel_key))); return {kernel_iter->second, false}; } const KernelArgsDef& KernelFactory::GetFirstKernelArgsDef( const std::string& kernel_name) const { auto iter = kernels_.find(kernel_name); PADDLE_ENFORCE_NE( iter, kernels_.end(), phi::errors::NotFound("The kernel `%s` is not registered.", kernel_name)); return iter->second.cbegin()->second.args_def(); } std::ostream& operator<<(std::ostream& os, AttributeType attr_type) { switch (attr_type) { case AttributeType::BOOL: os << "bool"; break; case AttributeType::INT32: os << "int"; break; case AttributeType::INT64: os << "int64_t"; break; case AttributeType::FLOAT32: os << "float"; break; case AttributeType::FLOAT64: os << "double"; break; case AttributeType::STRING: os << "string"; break; case AttributeType::BOOLS: os << "vector"; break; case AttributeType::INT32S: os << "vector"; break; case AttributeType::INT64S: os << "vector"; break; case AttributeType::FLOAT32S: os << "vector"; break; case AttributeType::FLOAT64S: os << "vector"; break; case AttributeType::STRINGS: os << "vector"; break; case AttributeType::SCALAR: os << "Scalar"; break; case AttributeType::SCALARS: os << "vector"; break; case AttributeType::INT_ARRAY: os << "IntArray"; break; case AttributeType::DATA_TYPE: os << "DataType"; break; case AttributeType::DATA_LAYOUT: os << "DataLayout"; break; case AttributeType::PLACE: os << "Place"; break; default: os << "Undefined"; } return os; } // 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 << "\""; 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 << std::endl; } os << "\"" << op_kernel_pair.first << " \":[" << std::endl; bool need_comma_per_kernel = false; for (const auto& kernel_pair : op_kernel_pair.second) { if (need_comma_per_kernel) { os << ","; os << std::endl; } os << "{\"" << kernel_pair.first << "\":" << kernel_pair.second << "}"; need_comma_per_kernel = true; } os << "]"; need_comma_kernels = true; } os << "}"; return os; } // return all kernel selection error message of specific kernel_name: // 1. If target_key not supports target backend, output "Selected wrong Backend // ..." // 2. If target_key not supports target datatype, output "Selected wrong // DataType ..." // 3. `target_key` is still not supported, output all kernel keys of // corresponding kernel_name: // { // (CPU, NCHW, [int8, int16, ...]); // (GPU, Undefined(AnyLayout), [float32, float64, ...]); // ... // } std::string KernelSelectionErrorMessage(const std::string& kernel_name, const KernelKey& target_key) { PADDLE_ENFORCE_NE( KernelFactory::Instance().kernels().find(kernel_name), KernelFactory::Instance().kernels().end(), phi::errors::NotFound("The kernel `%s` is not registered.", kernel_name)); // Init data structure bool support_backend = false; bool support_dtype = false; std::unordered_map> all_kernel_key; std::unordered_set backend_set; std::unordered_set dtype_set; // Record all kernel information of kernel_name for (auto iter : KernelFactory::Instance().kernels()[kernel_name]) { KernelKey kernel_key = iter.first; if (kernel_key.backend() == target_key.backend()) { support_backend = true; if (kernel_key.dtype() == target_key.dtype()) { support_dtype = true; } dtype_set.insert( paddle::experimental::DataTypeToString(kernel_key.dtype())); } backend_set.insert( paddle::experimental::BackendToString(kernel_key.backend())); all_kernel_key[paddle::experimental::BackendToString(kernel_key.backend()) + ", " + phi::DataLayoutToString(kernel_key.layout())] .push_back(paddle::experimental::DataTypeToString(kernel_key.dtype())); } // 1. If target_key not supports target backend, output "Selected wrong // Backend ..." if (!support_backend) { std::string error_message = paddle::string::join_strings(backend_set, ", "); return "Selected wrong Backend `" + paddle::experimental::BackendToString(target_key.backend()) + "`. Paddle support following Backends: " + error_message + "."; } // 2. If target_key not supports target datatype, output "Selected wrong // DataType ..." if (!support_dtype) { std::string error_message = paddle::string::join_strings(dtype_set, ", "); return "Selected wrong DataType `" + paddle::experimental::DataTypeToString(target_key.dtype()) + "`. Paddle support following DataTypes: " + error_message + "."; } // 3. `target_key` is still not supported, output all kernel keys of // corresponding kernel_name std::string message = "Currently, paddle support following kernel keys of `" + kernel_name + "`: { "; for (auto iter = all_kernel_key.begin(); iter != all_kernel_key.end(); ++iter) { std::vector& dtype_vec = iter->second; message += "(" + iter->first + ", ["; message += paddle::string::join_strings(dtype_vec, ", "); message += "]); "; } message += "}."; return message; } } // namespace phi