/* Copyright (c) 2016 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 #include #include #include #include #include "paddle/fluid/framework/operator.h" #include "paddle/fluid/framework/unused_var_check.h" #include "paddle/fluid/platform/enforce.h" DEFINE_bool(enable_unused_var_check, false, "Checking whether operator contains unused inputs, " "especially for grad operator. It should be in unittest."); const std::unordered_set op_has_unsed_vars_white_list = { "auc", "batch_norm", "batch_norm_grad", "fused_batch_norm_act", "fused_batch_norm_act_grad", "sync_batch_norm_grad", "center_loss_grad", "crop", "cvm", "cos_sim_grad", "dgc_momentum", "fake_quantize_range_abs_max", "fill_zeros_like", "fusion_seqpool_cvm_concat", "reshape2_grad_grad", "reshape2_grad", "gru_grad", "hierarchical_sigmoid_grad", "nce_grad", "roi_perspective_transform_grad", "sequence_conv_grad", "gru_unit_grad", "affine_grid_grad", "fill_any_like", "precision_recall", "unsqueeze_grad", "kldiv_loss_grad", "cvm_grad", "stack_grad", "warpctc_grad", "sync_batch_norm", "match_matrix_tensor_grad", "ngraph_engine", "rmsprop"}; namespace paddle { namespace framework { std::unordered_set *GetThreadLocalUsedVarNameSet() { thread_local std::unordered_set used_var_name_set; return &used_var_name_set; } void LogVarUsageIfUnusedVarCheckEnabled(const std::string &name) { if (FLAGS_enable_unused_var_check) { VLOG(6) << "Variable used:" << name; GetThreadLocalUsedVarNameSet()->insert(name); } } void CheckUnusedVar(const OperatorBase &op, const Scope &scope) { // skip op in white list and it should be fixed in the future. if (op_has_unsed_vars_white_list.count(op.Type()) != 0) { return; } auto *used_set = GetThreadLocalUsedVarNameSet(); std::vector unsed_input_var_names; auto &inferer = op.Info().NoNeedBufferVarsInferer(); std::unordered_set no_need_buffer_ins = {}; if (inferer) { no_need_buffer_ins = inferer(op.Inputs(), op.Outputs(), op.Attrs()); } for (auto &pair : op.Inputs()) { // skip no need buffer vars declared if (no_need_buffer_ins.count(pair.first) != 0) { VLOG(6) << op.Type() << " " << pair.first; continue; } if (used_set->count(pair.first) == 0) { for (auto &in_var_name : pair.second) { auto *in_var = scope.FindVar(in_var_name); if (in_var != nullptr && in_var->IsInitialized()) { auto *tensor = &in_var->Get(); if (tensor != nullptr && tensor->IsInitialized()) { unsed_input_var_names.emplace_back(pair.first); break; } } } } } if (!unsed_input_var_names.empty()) { std::string err_msg = "Operator " + op.Type() + " has input(s) not uesed: "; for (auto &in_var_name : unsed_input_var_names) { err_msg += in_var_name; err_msg += ", "; } err_msg += "please make sure it(they) is(are) needed. If not, remove it(them) " "from inputs of the operator; if yes, register " "NoNeedBufferVarsInference or add " "the operator to " "white list in unused_var_check.cc. See more details at " "[https://github.com/PaddlePaddle/Paddle/wiki/" "OP-Should-Not-Have-Unused-Input]"; PADDLE_ENFORCE_EQ(unsed_input_var_names.size(), 0, platform::errors::PermissionDenied( "Unused input variables check failed: %s", err_msg)); } } } // namespace framework } // namespace paddle