// 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/ir/fc_fuse_pass.h" #include #include #include #include #include "paddle/fluid/framework/ir/graph_helper.h" #include "paddle/fluid/platform/enforce.h" namespace paddle { namespace framework { namespace ir { void FCFusePass::ApplyImpl(ir::Graph* graph) const { PADDLE_ENFORCE_NOT_NULL(graph); FusePassBase::Init("fc_fuse", graph); int found_fc_count = 0; for (bool with_relu : {true, false}) { found_fc_count += ApplyFCPattern(graph, with_relu); } AddStatis(found_fc_count); } int FCFusePass::ApplyFCPattern(Graph* graph, bool with_relu) const { GraphPatternDetector gpd; auto* x = gpd.mutable_pattern() ->NewNode("fc_fuse/x") ->AsInput() ->assert_is_op_input("mul", "X"); patterns::FC fc_pattern(gpd.mutable_pattern(), "fc_fuse"); fc_pattern(x, true /*with bias*/, with_relu); int found_fc_count = 0; auto handler = [&](const GraphPatternDetector::subgraph_t& subgraph, Graph* g) { if (subgraph.count(x) <= 0) { LOG(WARNING) << "The subgraph is empty."; return; } VLOG(4) << "handle FC fuse"; GET_IR_NODE_FROM_SUBGRAPH(w, w, fc_pattern); GET_IR_NODE_FROM_SUBGRAPH(bias, bias, fc_pattern); GET_IR_NODE_FROM_SUBGRAPH(elementwise_add_out, elementwise_add_out, fc_pattern); GET_IR_NODE_FROM_SUBGRAPH(mul, mul, fc_pattern); GET_IR_NODE_FROM_SUBGRAPH(elementwise_add, elementwise_add, fc_pattern); GET_IR_NODE_FROM_SUBGRAPH(mul_out, mul_out, fc_pattern); Node* relu = nullptr; Node* relu_out = nullptr; if (with_relu) { GET_IR_NODE_FROM_SUBGRAPH(tmp_relu, relu, fc_pattern); GET_IR_NODE_FROM_SUBGRAPH(tmp_relu_out, relu_out, fc_pattern); relu = tmp_relu; relu_out = tmp_relu_out; } // Create an FC Node. OpDesc desc; desc.SetType("fc"); // Set inputs of fc desc.SetInput("Input", {subgraph.at(x)->Name()}); desc.SetInput("W", {w->Name()}); desc.SetInput("Bias", {bias->Name()}); // Set output of fc std::string fc_out_name = with_relu ? relu_out->Name() : elementwise_add_out->Name(); desc.SetOutput("Out", std::vector({fc_out_name})); // Set attrs of fc desc.SetAttr("in_num_col_dims", mul->Op()->GetAttr("x_num_col_dims")); std::string activation_type = with_relu ? "relu" : ""; desc.SetAttr("activation_type", activation_type); // This is to add padding for dimension 128 on concern of MKL performance bool use_gpu = Has("use_gpu") ? Get("use_gpu") : false; bool use_fc_padding = Has("use_fc_padding") ? Get("use_fc_padding") : true; if (!use_gpu && use_fc_padding) { auto* scope = param_scope(); auto* weight = scope->FindVar(w->Name())->GetMutable(); auto* weight_data = weight->data(); auto weight_dims = weight->dims(); int weight_num = product(weight_dims); int w_h = weight_dims[0]; int w_w = weight_dims[1]; if (w_h % 128 == 0 && w_w % 128 == 0) { auto* weight_data_tmp = new float[weight_num]; for (int i = 0; i < w_h; i++) { memcpy(weight_data_tmp + i * w_w, weight_data + i * w_w, w_w * sizeof(float)); } weight->Resize(DDim{weight_dims[0] + 4, weight_dims[1] + 4}); auto* weight_data_new = weight->mutable_data(platform::CPUPlace()); for (int i = 0; i < w_h; i++) { memcpy(weight_data_new + i * (w_w + 4), weight_data_tmp + i * w_w, w_w * sizeof(float)); } delete[] weight_data_tmp; desc.SetAttr("padding_weights", true); } } // For anakin subgraph int8 // When in anakin subgraph int8 mode, the pattern like "fake_quant + mul + // fake_dequant" can be detected by the quant_dequant_fuse_pass. This pass // will add "input_scale", "weight_scale" which are extracted from // fake_quant op and fake_dequant op to mul op, and then delete the // fake_quant op and fake_dequant op in the graph. If the mul op has the // scale info, we should add those to the fused fc. auto* mul_op_desc = mul->Op(); if (mul_op_desc->HasAttr("enable_int8")) { desc.SetAttr("enable_int8", mul_op_desc->GetAttr("enable_int8")); desc.SetAttr("Input_scale", mul_op_desc->GetAttr("X_scale")); desc.SetAttr("weight_scale", mul_op_desc->GetAttr("weight_scale")); if (mul_op_desc->HasAttr("out_scale")) desc.SetAttr("out_scale", mul_op_desc->GetAttr("out_scale")); auto elementwise_desc = elementwise_add->Op(); if (elementwise_desc->HasAttr("out_scale")) desc.SetAttr("out_scale", elementwise_desc->GetAttr("out_scale")); } auto fc_node = g->CreateOpNode(&desc); // OpDesc will be copied. if (with_relu) { GraphSafeRemoveNodes( graph, {mul, elementwise_add, mul_out, elementwise_add_out, relu}); } else { GraphSafeRemoveNodes(graph, {mul, elementwise_add, mul_out}); } IR_NODE_LINK_TO(subgraph.at(x), fc_node); IR_NODE_LINK_TO(w, fc_node); IR_NODE_LINK_TO(bias, fc_node); if (with_relu) { IR_NODE_LINK_TO(fc_node, relu_out); } else { IR_NODE_LINK_TO(fc_node, elementwise_add_out); } found_fc_count++; }; gpd(graph, handler); return found_fc_count; } } // namespace ir } // namespace framework } // namespace paddle REGISTER_PASS(fc_fuse_pass, paddle::framework::ir::FCFusePass) .RequirePassAttr("use_gpu");