// 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/inference/api/paddle_pass_builder.h" #ifdef PADDLE_WITH_CUDA #include #endif #include namespace paddle { void PaddlePassBuilder::AppendPass(const std::string &pass_type) { passes_.push_back(pass_type); } void PaddlePassBuilder::TurnOnDebug() { std::vector passes; auto it = std::begin(passes_); while (it != std::end(passes_)) { if (*it != "graph_viz_pass") { it = passes_.insert(it + 1, "graph_viz_pass"); } else { ++it; } } } std::string PaddlePassBuilder::DebugString() { std::stringstream ss; ss << "Passes to apply:\n"; for (auto &pass : passes_) { ss << " - " << pass << '\n'; } return ss.str(); } void PaddlePassBuilder::DeletePass(const std::string &pass_type) { auto it = std::begin(passes_); while (it != std::end(passes_)) { if (*it == pass_type) { it = passes_.erase(it); } else { ++it; } } } void PaddlePassBuilder::InsertPass(size_t idx, const std::string &pass_type) { passes_.insert(std::begin(passes_) + idx, pass_type); } void PaddlePassBuilder::DeletePass(size_t idx) { passes_.erase(std::begin(passes_) + idx); } void PaddlePassBuilder::AppendAnalysisPass(const std::string &pass) { analysis_passes_.push_back(pass); } void PaddlePassBuilder::ClearPasses() { passes_.clear(); } const std::vector kTRTSubgraphPasses({ "conv_affine_channel_fuse_pass", // "adaptive_pool2d_convert_global_pass", "conv_eltwiseadd_affine_channel_fuse_pass", // "shuffle_channel_detect_pass", // "quant_conv2d_dequant_fuse_pass", // "delete_quant_dequant_op_pass", // "delete_quant_dequant_filter_op_pass", // // "fc_fuse_pass", // "simplify_with_basic_ops_pass", // "embedding_eltwise_layernorm_fuse_pass", // "multihead_matmul_fuse_pass_v2", // "skip_layernorm_fuse_pass", // "unsqueeze2_eltwise_fuse_pass", // "conv_bn_fuse_pass", // "squeeze2_matmul_fuse_pass", // "reshape2_matmul_fuse_pass", // "flatten2_matmul_fuse_pass", // "map_matmul_to_mul_pass", // "fc_fuse_pass", // "conv_elementwise_add_fuse_pass", // "tensorrt_subgraph_pass", // "conv_bn_fuse_pass", // #if CUDNN_VERSION >= 7100 // To run conv_fusion, the version of cudnn must be // guaranteed at least v7 "conv_elementwise_add_act_fuse_pass", // "conv_elementwise_add2_act_fuse_pass", // #endif // "transpose_flatten_concat_fuse_pass", }); const std::vector kLiteSubgraphPasses({ #ifdef PADDLE_WITH_LITE "lite_subgraph_pass", #endif }); GpuPassStrategy::GpuPassStrategy() : PassStrategy({}) { passes_.assign({ // "identity_scale_op_clean_pass", // "is_test_pass", // "simplify_with_basic_ops_pass", // "conv_affine_channel_fuse_pass", // "conv_eltwiseadd_affine_channel_fuse_pass", // "conv_bn_fuse_pass", // "conv_eltwiseadd_bn_fuse_pass", // "embedding_eltwise_layernorm_fuse_pass", // "multihead_matmul_fuse_pass_v2", // "squeeze2_matmul_fuse_pass", // "reshape2_matmul_fuse_pass", // "flatten2_matmul_fuse_pass", // "map_matmul_to_mul_pass", // "fc_fuse_pass", // "fc_elementwise_layernorm_fuse_pass", // #if CUDNN_VERSION >= 7100 // To run conv_fusion, the version of cudnn must be // guaranteed at least v7 "conv_elementwise_add_act_fuse_pass", // "conv_elementwise_add2_act_fuse_pass", // "conv_elementwise_add_fuse_pass", // #endif // "transpose_flatten_concat_fuse_pass", // // following pass should be located in the last, since it will // work on all fused ops. "runtime_context_cache_pass" }); use_gpu_ = true; } void GpuPassStrategy::EnableCUDNN() { if (!use_cudnn_) { passes_.insert(passes_.begin(), "cudnn_placement_pass"); } use_cudnn_ = true; } void GpuPassStrategy::EnableMKLDNN() { LOG(ERROR) << "GPU not support MKLDNN yet"; } void GpuPassStrategy::EnableMkldnnQuantizer() { LOG(ERROR) << "GPU not support MKL-DNN quantization"; } void GpuPassStrategy::EnableMkldnnBfloat16() { LOG(ERROR) << "GPU not support MKL-DNN bfloat16"; } CpuPassStrategy::CpuPassStrategy() : PassStrategy({}) { // NOTE the large fusions should be located in the front, so that they will // not be damaged by smaller ones. passes_.assign({"simplify_with_basic_ops_pass", // "attention_lstm_fuse_pass", // "seqconv_eltadd_relu_fuse_pass", // // "seqpool_concat_fuse_pass", // "seqpool_cvm_concat_fuse_pass", // // "embedding_fc_lstm_fuse_pass", // // TODO(wilber): fix correctness problem. // "fc_lstm_fuse_pass", // "mul_lstm_fuse_pass", // "fc_gru_fuse_pass", // "mul_gru_fuse_pass", // "seq_concat_fc_fuse_pass", // "squeeze2_matmul_fuse_pass", // "reshape2_matmul_fuse_pass", // "flatten2_matmul_fuse_pass", // "map_matmul_to_mul_pass", // "fc_fuse_pass", // "repeated_fc_relu_fuse_pass", // "squared_mat_sub_fuse_pass", // "conv_bn_fuse_pass", // "conv_eltwiseadd_bn_fuse_pass", // "conv_transpose_bn_fuse_pass", // "conv_transpose_eltwiseadd_bn_fuse_pass", // "is_test_pass", // // following pass should be located in the last, since // it will work on all fused ops. "runtime_context_cache_pass"}); use_gpu_ = false; } void CpuPassStrategy::EnableCUDNN() { LOG(ERROR) << "CPU not support cuDNN"; } void CpuPassStrategy::EnableMKLDNN() { // TODO(Superjomn) Consider the way to mix CPU with GPU. #ifdef PADDLE_WITH_MKLDNN if (!use_mkldnn_) { passes_.insert(passes_.begin(), "mkldnn_placement_pass"); for (auto &pass : std::vector({ "depthwise_conv_mkldnn_pass", // "conv_bn_fuse_pass", // Execute BN passes again to "conv_eltwiseadd_bn_fuse_pass", // preserve correct pass order "conv_affine_channel_fuse_pass", // "conv_eltwiseadd_affine_channel_fuse_pass", // "conv_transpose_bn_fuse_pass", // "conv_transpose_eltwiseadd_bn_fuse_pass", // "conv_bias_mkldnn_fuse_pass", // "conv_transpose_bias_mkldnn_fuse_pass", "conv3d_bias_mkldnn_fuse_pass", // "conv_elementwise_add_mkldnn_fuse_pass", "conv_concat_relu_mkldnn_fuse_pass", "conv_relu_mkldnn_fuse_pass", // "conv_leaky_relu_mkldnn_fuse_pass", // "conv_relu6_mkldnn_fuse_pass", // "conv_swish_mkldnn_fuse_pass", // "scale_matmul_fuse_pass", // "reshape_transpose_matmul_mkldnn_fuse_pass", // "matmul_transpose_reshape_fuse_pass", // // Disabled due to topology-dependent speed-up // "fc_mkldnn_pass", // "fc_act_mkldnn_fuse_pass", "batch_norm_act_fuse_pass", // TODO(intel): Please fix the bug on windows. // https://github.com/PaddlePaddle/Paddle/issues/29710 // "mkldnn_inplace_pass", // This pass should be activated after // fuses. Disabled by default due to // little gain and lots of problems })) { passes_.push_back(pass); } } use_mkldnn_ = true; #else use_mkldnn_ = false; #endif } void CpuPassStrategy::EnableMkldnnQuantizer() { #ifdef PADDLE_WITH_MKLDNN if (!use_mkldnn_quantizer_) { passes_.push_back("cpu_quantize_placement_pass"); } use_mkldnn_quantizer_ = true; #else use_mkldnn_quantizer_ = false; #endif } void CpuPassStrategy::EnableMkldnnBfloat16() { #ifdef PADDLE_WITH_MKLDNN if (!use_mkldnn_bfloat16_) { passes_.push_back("cpu_bfloat16_placement_pass"); passes_.push_back("cpu_bfloat16_pass"); } use_mkldnn_bfloat16_ = true; #else use_mkldnn_bfloat16_ = false; #endif } } // namespace paddle