diff --git a/paddle/fluid/distributed/ps/service/ps_client.h b/paddle/fluid/distributed/ps/service/ps_client.h index 0d3d23be4e8d137d241adfaaadcd985c7d272708..926bb7e7c9fd31bccea82b343237d691f3698bdb 100644 --- a/paddle/fluid/distributed/ps/service/ps_client.h +++ b/paddle/fluid/distributed/ps/service/ps_client.h @@ -109,7 +109,7 @@ class PSClient { size_t table_id) = 0; // 保留 // firstly push dense param for parameter server - // this is neccessary because dense weight initialized in trainer on cold + // this is necessary because dense weight initialized in trainer on cold // start virtual std::future PushDenseParam(const Region *regions, size_t region_num, diff --git a/paddle/fluid/framework/data_set.h b/paddle/fluid/framework/data_set.h index 1947c669e9bb0df1b2dc16080f815e66f61060ef..3f10cd7765bc1fe4e168b77b820b08366463d5de 100644 --- a/paddle/fluid/framework/data_set.h +++ b/paddle/fluid/framework/data_set.h @@ -152,7 +152,7 @@ class Dataset { virtual void DestroyPreLoadReaders() = 0; // set preload thread num virtual void SetPreLoadThreadNum(int thread_num) = 0; - // seperate train thread and dataset thread + // separate train thread and dataset thread virtual void DynamicAdjustChannelNum(int channel_num, bool discard_remaining_ins = false) = 0; virtual void DynamicAdjustReadersNum(int thread_num) = 0; diff --git a/paddle/fluid/framework/details/sparse_all_reduce_op_handle.cc b/paddle/fluid/framework/details/sparse_all_reduce_op_handle.cc index d198eb1459288f269fe1728f630f293ef4b9b596..7e63c5ffb9a44d36fc3a7a84545db4cda25a4d19 100644 --- a/paddle/fluid/framework/details/sparse_all_reduce_op_handle.cc +++ b/paddle/fluid/framework/details/sparse_all_reduce_op_handle.cc @@ -75,7 +75,7 @@ void SparseAllReduceOpHandle::RunImplEncoded() { in_var_handles.size(), places_.size(), platform::errors::PreconditionNotMet( "The number of input variables should be equal to the number of " - "places, but got the number of input variables is %zu and the the " + "places, but got the number of input variables is %zu and the " "number of places is %zu.", in_var_handles.size(), places_.size())); PADDLE_ENFORCE_EQ( @@ -83,7 +83,7 @@ void SparseAllReduceOpHandle::RunImplEncoded() { platform::errors::PreconditionNotMet( "The number of input variables should be equal to the number of " "output variables, but got the number of input variables is %zu and " - "the the number of output variables is %zu.", + "the number of output variables is %zu.", in_var_handles.size(), out_var_handles.size())); std::vector ins; diff --git a/paddle/fluid/framework/heter_pipeline_trainer.cc b/paddle/fluid/framework/heter_pipeline_trainer.cc index 13eb78874c395e8ff2baa01d2fd0bd9f2df5c42c..d0d3c2fea3b568c2ad93ae6f2ac5896ddf5d46e6 100644 --- a/paddle/fluid/framework/heter_pipeline_trainer.cc +++ b/paddle/fluid/framework/heter_pipeline_trainer.cc @@ -282,7 +282,7 @@ void HeterPipelineTrainer::Run() { if (threads_.size() > 0) { threads_.clear(); } - VLOG(3) << "Epoch Trainging done"; + VLOG(3) << "Epoch Training done"; } void HeterPipelineTrainer::Finalize() { diff --git a/paddle/fluid/framework/ir/fuse_optimizer_ops_pass/fuse_optimizer_op_pass.cc b/paddle/fluid/framework/ir/fuse_optimizer_ops_pass/fuse_optimizer_op_pass.cc index 48df5869a7a1f5afe222e71c9aae724850aac612..40e1de8a523aa3883b740bcedbae2512296071ef 100644 --- a/paddle/fluid/framework/ir/fuse_optimizer_ops_pass/fuse_optimizer_op_pass.cc +++ b/paddle/fluid/framework/ir/fuse_optimizer_ops_pass/fuse_optimizer_op_pass.cc @@ -172,7 +172,7 @@ void FuseOptimizerOpPass::ApplyImpl(ir::Graph *graph) const { VLOG(6) << "The number of new gradients is " << new_grad_idx.size(); if (new_grad_idx.size() == 1) return; // NOTE(zcd): If the gradients of backward stage and optimization stage - // have diff, Only take care of the the gradient of optimization stage. + // have diff, Only take care of the gradient of optimization stage. GradientsFilter(new_grad_idx, &opt_nodes, &aux_var_map); } } diff --git a/paddle/fluid/framework/ir/fusion_group/operation.cc b/paddle/fluid/framework/ir/fusion_group/operation.cc index 921cf0904f632936862b18b2f083f18a33c760be..2b7a3e1899c76b6a2ec02dbe66781a2130947519 100644 --- a/paddle/fluid/framework/ir/fusion_group/operation.cc +++ b/paddle/fluid/framework/ir/fusion_group/operation.cc @@ -127,7 +127,7 @@ void OperationMap::InsertUnaryElementwiseOperations() { // scale // out = (bias_after_scale) ? scale * X + bias : scale(X + bias) - // here we use '=' operator to seperate th default value + // here we use '=' operator to separate th default value // TODO(wangchaochaohu): Later we need to support Tensor input for scale and // bias. insert_handler( diff --git a/paddle/fluid/framework/ir/graph_pattern_detector.cc b/paddle/fluid/framework/ir/graph_pattern_detector.cc index fbd8fda131b6d1d755ca3afdfd18578d0d8c7af9..8c8d9fdddec851c9854ebb0c784d2b56d6dd8526 100644 --- a/paddle/fluid/framework/ir/graph_pattern_detector.cc +++ b/paddle/fluid/framework/ir/graph_pattern_detector.cc @@ -720,7 +720,7 @@ bool HasOutput(Node *op, const std::string &argument) { PADDLE_ENFORCE_EQ( op->IsOp(), true, platform::errors::InvalidArgument( - "First parameter of function HasOuput must be Node::Op")); + "First parameter of function HasOutput must be Node::Op")); auto const &names = op->Op()->OutputNames(); if (std::find(names.begin(), names.end(), argument) == names.end()) return false; diff --git a/paddle/fluid/framework/ir/graph_pattern_detector.h b/paddle/fluid/framework/ir/graph_pattern_detector.h index c9fea057d444d7946a404f31746f9e73086ba30d..9e5a82fc4458603da8b2b51587cad39047bc75e9 100644 --- a/paddle/fluid/framework/ir/graph_pattern_detector.h +++ b/paddle/fluid/framework/ir/graph_pattern_detector.h @@ -1432,7 +1432,7 @@ struct PriorBox : public PatternBase { }; // Conv + ElementwiseAdd + an activation -// This pattern can futher fuse the conv related ops after the conv+bn fusion. +// This pattern can further fuse the conv related ops after the conv+bn fusion. struct ConvElementwiseaddAct : public PatternBase { ConvElementwiseaddAct(PDPattern* pattern, const std::string& name_scope) : PatternBase(pattern, name_scope, "conv_elementwiseadd_act") {} diff --git a/paddle/fluid/framework/new_executor/interpretercore.cc b/paddle/fluid/framework/new_executor/interpretercore.cc index 6735406aacde75b908e7ac8bfdb58e28206d33f5..da2fd0c8c6114017fc72e4718ff4c4231517ceeb 100644 --- a/paddle/fluid/framework/new_executor/interpretercore.cc +++ b/paddle/fluid/framework/new_executor/interpretercore.cc @@ -277,7 +277,7 @@ void InterpreterCore::Convert( } for (size_t i = 0; i < vec_instruction_.size(); ++i) { - // checkout ouput + // checkout output for (auto& item : vec_instruction_[i].Outputs()) { for (auto var_id : item.second) { if (input_var2op_info_.at(var_id).size() == 0) { diff --git a/paddle/fluid/framework/new_executor/interpretercore_util.cc b/paddle/fluid/framework/new_executor/interpretercore_util.cc index d6de37a72c7722960c97e92d251721ebd0959a75..f601a4ad28bd7a19cd20fd34153fa702e0b68ed5 100644 --- a/paddle/fluid/framework/new_executor/interpretercore_util.cc +++ b/paddle/fluid/framework/new_executor/interpretercore_util.cc @@ -666,7 +666,7 @@ std::map> get_downstream_map( VLOG(6) << "downstream count: " << downstream_map_count(); VLOG(6) << "downstream_map: " << std::endl << downstream_map_to_str(); - // step2: remove unneccessary downstream ops + // step2: remove unnecessary downstream ops // for example, a->b->c // a: b, c // b: c diff --git a/paddle/fluid/framework/new_executor/workqueue/workqueue.h b/paddle/fluid/framework/new_executor/workqueue/workqueue.h index e9c658e3b9dc6a660b60720ad8b115f447972375..2c2576528fe0ef5331d6d7e93a83be0752a3e359 100644 --- a/paddle/fluid/framework/new_executor/workqueue/workqueue.h +++ b/paddle/fluid/framework/new_executor/workqueue/workqueue.h @@ -89,7 +89,7 @@ struct WorkQueueOptions { // If you need to blocking the calling thread to wait "queue empty", set // track_task = true and set events_waiter. EventsWaiter::WaitEvent will // block the calling thread until any of events (including "queue empty") - // occured. + // occurred. bool track_task; // If you need to be noticed when a WorkQueue Destruct() , set detached = // false and set events_waiter. diff --git a/paddle/fluid/framework/paddle2cinn/build_cinn_pass.cc b/paddle/fluid/framework/paddle2cinn/build_cinn_pass.cc index 0de89aaad3b0dafbff6e7004de734912adfeffeb..3de702027bb6c89cdb7e34af34ba023cc78983ed 100644 --- a/paddle/fluid/framework/paddle2cinn/build_cinn_pass.cc +++ b/paddle/fluid/framework/paddle2cinn/build_cinn_pass.cc @@ -511,7 +511,7 @@ void AddCinnOpToGraph(const GraphNodeSet& cluster, ExtractOpRole(cluster)); cinn_op_desc.Flush(); auto* cinn_op_node = graph->CreateOpNode(&cinn_op_desc); - // Add new links from or to the the cinn launch op node + // Add new links from or to the cinn launch op node AddLinkToCinnOp(cluster_inputs, cluster_outputs, cinn_op_node); VLOG(4) << "Add op [" << kCinnLaunchOp << "] into graph."; diff --git a/paddle/fluid/framework/prune.cc b/paddle/fluid/framework/prune.cc index efbab83f7d0e81a7b9098381b61dd730404fdfd9..4c95f01ae569f952c87a5b24a2e43fe0204554d1 100644 --- a/paddle/fluid/framework/prune.cc +++ b/paddle/fluid/framework/prune.cc @@ -421,7 +421,7 @@ void PruneBackwardImpl(proto::BlockDesc* origin, proto::BlockDesc* pruned) { for (const auto& name : var_names) { if (var_map.count(name)) { // NOTE(zhiqiu): For operator in a conditional block, the related vars - // may not exist in current block, but in its futher block. + // may not exist in current block, but in its further block. *pruned_vars->Add() = var_map[name]; } } diff --git a/paddle/fluid/imperative/layer.cc b/paddle/fluid/imperative/layer.cc index e928cbb6548397d9a784ec95785e07ac6f239d7d..76f64ab73a64bd6672b036bc6f197a1f4a965a13 100644 --- a/paddle/fluid/imperative/layer.cc +++ b/paddle/fluid/imperative/layer.cc @@ -186,7 +186,7 @@ template static void SetForwardDataTypeOfGradVars(const NameVarMap& outs) { for (auto& var_pair : outs) { for (auto& var : var_pair.second) { - // NOTE(zhiqu): The ouput may be NULL because of pruning. + // NOTE(zhiqu): The output may be NULL because of pruning. if (var) { SetForwardDataTypeOfGradVar(var); } diff --git a/paddle/fluid/imperative/reducer.cc b/paddle/fluid/imperative/reducer.cc index 03fa46eab53678e5464f478a2dc0e42f0ea5210b..c7fd2215eb42a49579e1edb396380b66f03bafb5 100644 --- a/paddle/fluid/imperative/reducer.cc +++ b/paddle/fluid/imperative/reducer.cc @@ -879,7 +879,7 @@ void Reducer::MarkVarReady(const size_t var_index, const bool is_used_var) { } // TODO(liuyuhui): If BKCL support non-blocking communication, it should be -// fixed as same as multi gpus card trainging. +// fixed as same as multi gpus card training. void Reducer::MarkGroupReady(size_t group_index) { PADDLE_ENFORCE_GE( group_index, next_group_, @@ -957,7 +957,7 @@ void Reducer::FusedAllReduceSchedule(const int run_order, Group &group, // default stream for communicating, so there exist some problems in // synchronization. And need to add a WaitComm there. // TODO(liuyuhui): If BKCL support non-blocking communication, it should be -// fixed as multi gpus card trainging. +// fixed as multi gpus card training. #ifdef PADDLE_WITH_XPU_BKCL if (platform::is_xpu_place(group.dense_tensors_[0].place())) { parallel_ctx_->WaitComm(run_order); diff --git a/paddle/fluid/inference/analysis/CMakeLists.txt b/paddle/fluid/inference/analysis/CMakeLists.txt index dab1b9f7b113523b12f468886b56d5038fe3f165..3d1a467565c841964bfbc5ffe579739d45dfcd50 100644 --- a/paddle/fluid/inference/analysis/CMakeLists.txt +++ b/paddle/fluid/inference/analysis/CMakeLists.txt @@ -1,5 +1,5 @@ unset(analysis_deps CACHE) -set(analysis_deps # analysis_deps can be extended accross the project +set(analysis_deps # analysis_deps can be extended across the project framework_proto proto_desc graph pass paddle_inference_io executor pretty_log ir_pass_manager CACHE INTERNAL "") diff --git a/paddle/fluid/inference/analysis/ir_passes/subgraph_util.cc b/paddle/fluid/inference/analysis/ir_passes/subgraph_util.cc index 09494a360270b0173b66b4cf894c910789ca827d..0c9f8d7e1655840c7eacfc2f7067e27da9c475cb 100644 --- a/paddle/fluid/inference/analysis/ir_passes/subgraph_util.cc +++ b/paddle/fluid/inference/analysis/ir_passes/subgraph_util.cc @@ -13,7 +13,7 @@ See the License for the specific language governing permissions and limitations under the License. */ /* - * This file defines the the class to partition a graph. + * This file defines the class to partition a graph. */ #include "paddle/fluid/inference/analysis/ir_passes/subgraph_util.h" diff --git a/paddle/fluid/inference/analysis/ir_passes/subgraph_util.h b/paddle/fluid/inference/analysis/ir_passes/subgraph_util.h index 621c631b8539beb9b35dcd33f3d14ef5e5745396..21bfe7582061a2ea144c26e700e8c46a8888ee0a 100644 --- a/paddle/fluid/inference/analysis/ir_passes/subgraph_util.h +++ b/paddle/fluid/inference/analysis/ir_passes/subgraph_util.h @@ -13,7 +13,7 @@ See the License for the specific language governing permissions and limitations under the License. */ /* - * This file defines the the class to partition a graph. + * This file defines the class to partition a graph. */ #pragma once diff --git a/paddle/fluid/inference/analysis/ir_passes/tensorrt_subgraph_pass.cc b/paddle/fluid/inference/analysis/ir_passes/tensorrt_subgraph_pass.cc index 059a9cb21e1d5e0b6925e85e41c963b91292ec53..bc7dc9704ac5e95476e00bfa7aff5c7103d138c7 100644 --- a/paddle/fluid/inference/analysis/ir_passes/tensorrt_subgraph_pass.cc +++ b/paddle/fluid/inference/analysis/ir_passes/tensorrt_subgraph_pass.cc @@ -286,7 +286,7 @@ void TensorRtSubgraphPass::CreateTensorRTOp( // There are models with the same structure but the different parameters, // when running in the 'use_serialize' mode, there is a bug. // serialization is affected by max_batch_size, but calibration is not. - // So we use seperate engine keys in serialization and calibration. + // So we use separate engine keys in serialization and calibration. auto engine_key = GenerateEngineKey( input_names_with_id, output_names_with_id, std::to_string(0), std::to_string(max_batch_size), diff --git a/paddle/fluid/inference/api/paddle_analysis_config.h b/paddle/fluid/inference/api/paddle_analysis_config.h index 8edbc494ab8865cfcd206539f035d9ae78dc26a8..af6cf88a3224fa91954697b8b005bfb176d89576 100644 --- a/paddle/fluid/inference/api/paddle_analysis_config.h +++ b/paddle/fluid/inference/api/paddle_analysis_config.h @@ -410,7 +410,7 @@ struct PD_INFER_DECL AnalysisConfig { /// \return int The NPU device id. /// int npu_device_id() const { return npu_device_id_; } - /// \brief Get the the number of IPU device . + /// \brief Get the number of IPU device . /// /// \return int The number of IPU device. /// diff --git a/paddle/fluid/inference/tensorrt/convert/swish_op.cc b/paddle/fluid/inference/tensorrt/convert/swish_op.cc index 0df5c013d34d4206e4d286a981841992241b2b0c..0b9a6917dd972bbe0d61dbc10a84556ba4c61abd 100644 --- a/paddle/fluid/inference/tensorrt/convert/swish_op.cc +++ b/paddle/fluid/inference/tensorrt/convert/swish_op.cc @@ -52,7 +52,7 @@ class SwishOpConverter : public OpConverter { PADDLE_ENFORCE_EQ( output_num, 1UL, platform::errors::InvalidArgument( - "The ouput Out's size must equal to 1 in TRT swish op. " + "The output Out's size must equal to 1 in TRT swish op. " "But received Out's size %u.", output_num)); // Get attrs diff --git a/paddle/fluid/inference/tests/api/analyzer_lexical_analysis_gru_tester.cc b/paddle/fluid/inference/tests/api/analyzer_lexical_analysis_gru_tester.cc index cca8ac2634c6cce278c0148bf76ccb5df985b67f..141e60513eb955e581e2d343cbbcafdb62a88ac4 100644 --- a/paddle/fluid/inference/tests/api/analyzer_lexical_analysis_gru_tester.cc +++ b/paddle/fluid/inference/tests/api/analyzer_lexical_analysis_gru_tester.cc @@ -147,10 +147,10 @@ void SetInput(std::vector> *inputs, file.read(reinterpret_cast(&total_words_num), sizeof(int64_t)); LOG(INFO) << "Total words in file: " << total_words_num; size_t lods_beginning_offset = static_cast(file.tellg()); - auto words_begining_offset = + auto words_beginning_offset = lods_beginning_offset + sizeof(size_t) * total_sentences_num; auto targets_beginning_offset = - words_begining_offset + sizeof(int64_t) * total_words_num; + words_beginning_offset + sizeof(int64_t) * total_words_num; std::vector lod_full = ReadSentenceLod(file, lods_beginning_offset, total_sentences_num); @@ -158,7 +158,7 @@ void SetInput(std::vector> *inputs, size_t lods_sum = std::accumulate(lod_full.begin(), lod_full.end(), 0UL); EXPECT_EQ(lods_sum, static_cast(total_words_num)); - TensorReader words_reader(file, words_begining_offset, "words"); + TensorReader words_reader(file, words_beginning_offset, "words"); TensorReader targets_reader(file, targets_beginning_offset, "targets"); // If FLAGS_iterations is set to 0, run all batches diff --git a/paddle/fluid/operators/activation_op.h b/paddle/fluid/operators/activation_op.h index 5448ed2a4bdad6ea027c5483721c79562954ecab..8214b733f86da5240545c5effdc132b0d50c3144 100644 --- a/paddle/fluid/operators/activation_op.h +++ b/paddle/fluid/operators/activation_op.h @@ -634,7 +634,7 @@ struct SquareGradGradFunctor : public BaseActivationFunctor { // TODO(dengkaipeng): double gradient calculation for Square/Sqrt need // DOut(dy) as input(not output), tensor extraction is different from -// others. Impliment extraction kernel seperately here. +// others. Impliment extraction kernel separately here. inline void ExtractDoubleGradTensorWithInputDOut( const framework::ExecutionContext& ctx, const framework::Tensor** X, const framework::Tensor** ddX, framework::Tensor** dX, diff --git a/paddle/fluid/operators/affine_grid_op.cc b/paddle/fluid/operators/affine_grid_op.cc index efaea94f26e8d285b7747ca2c8b0691ce8c38a75..e311d21bb54d3f6b5457c6dcfdc0a82a4ff8c35e 100644 --- a/paddle/fluid/operators/affine_grid_op.cc +++ b/paddle/fluid/operators/affine_grid_op.cc @@ -136,7 +136,7 @@ class AffineGridOpMaker : public framework::OpProtoAndCheckerMaker { .AsExtra(); AddAttr("align_corners", "(bool, default false) Whether to align the corners of input" - "and ouput.") + "and output.") .SetDefault(true); AddAttr>( "output_shape", diff --git a/paddle/fluid/operators/batch_norm_op.cc b/paddle/fluid/operators/batch_norm_op.cc index 36a0d53e052453f97a4d510cad5587614c9796c7..2663a081011573063f671269e6ec1ba17969e9a1 100644 --- a/paddle/fluid/operators/batch_norm_op.cc +++ b/paddle/fluid/operators/batch_norm_op.cc @@ -64,7 +64,7 @@ void BatchNormOp::InferShape(framework::InferShapeContext *ctx) const { (x_dims[i] == -1) || (x_dims[i] > 0), true, platform::errors::InvalidArgument( "Each dimension of input tensor is expected to be -1 or a " - "positive number, but recieved %d. Input's shape is [%s].", + "positive number, but received %d. Input's shape is [%s].", x_dims[i], x_dims)); } diff --git a/paddle/fluid/operators/collective/c_broadcast_op.cu.cc b/paddle/fluid/operators/collective/c_broadcast_op.cu.cc index 4bed282ace8d1572d2defcfa7cfd9a6d56d9b434..eeae16a0d71f3881cf9e8447bf96c1508c219d7f 100644 --- a/paddle/fluid/operators/collective/c_broadcast_op.cu.cc +++ b/paddle/fluid/operators/collective/c_broadcast_op.cu.cc @@ -77,7 +77,7 @@ class CBroadcastOpCUDAKernel : public framework::OpKernel { PADDLE_ENFORCE_GPU_SUCCESS( platform::dynload::ncclBcast(out->mutable_data(place), numel, dtype, root, comm->comm(), stream)); - VLOG(3) << "rank " << comm->rank() << " invoke Bcast. recieved " + VLOG(3) << "rank " << comm->rank() << " invoke Bcast. received " << phi::product(out->dims()); } diff --git a/paddle/fluid/operators/collective/c_broadcast_op_mlu.cc b/paddle/fluid/operators/collective/c_broadcast_op_mlu.cc index d1e269fb5a4fe9505acf7043bc7a2cea36823ffa..8f07480aaab14b442bb8be1469797f3c9819661d 100644 --- a/paddle/fluid/operators/collective/c_broadcast_op_mlu.cc +++ b/paddle/fluid/operators/collective/c_broadcast_op_mlu.cc @@ -62,7 +62,7 @@ class CBroadcastOPMLUKernel : public framework::OpKernel { } else { PADDLE_ENFORCE_MLU_SUCCESS(cnclBcast(out->mutable_data(place), numel, dtype, root, comm->comm(), stream)); - VLOG(3) << "rank " << comm->rank() << " invoke Bcast. recieved " + VLOG(3) << "rank " << comm->rank() << " invoke Bcast. received " << phi::product(out->dims()); } diff --git a/paddle/fluid/operators/collective/c_broadcast_op_npu.cc b/paddle/fluid/operators/collective/c_broadcast_op_npu.cc index 31961d8a246a9da727c3593d4ff558fa56983b54..a065e49ff72be84c393eb3e662d00d646ac712c8 100644 --- a/paddle/fluid/operators/collective/c_broadcast_op_npu.cc +++ b/paddle/fluid/operators/collective/c_broadcast_op_npu.cc @@ -59,7 +59,7 @@ class CBroadcastOpASCENDKernel : public framework::OpKernel { PADDLE_ENFORCE_NPU_SUCCESS(platform::dynload::HcclBroadcast( ptr, numel, dtype, (uint32_t)root, comm->comm(), stream)); - VLOG(3) << "rank " << comm->rank() << " invoke Bcast. recieved " + VLOG(3) << "rank " << comm->rank() << " invoke Bcast. received " << phi::product(out->dims()); dev_ctx->Wait(); diff --git a/paddle/fluid/operators/conv_op.h b/paddle/fluid/operators/conv_op.h index a5d888765bf37d45d501a3dbe5437f7c2ab5fc51..58f2eeee256db07c1d0bd35b883217919236fd70 100644 --- a/paddle/fluid/operators/conv_op.h +++ b/paddle/fluid/operators/conv_op.h @@ -43,7 +43,7 @@ inline int ConvOutputSize(int input_size, int filter_size, int dilation, output_size, 0, platform::errors::InvalidArgument( "The output's size is expected to be greater than 0. " - "But recieved: output's size is %d. The output's size is computed by " + "But received: output's size is %d. The output's size is computed by " "((input_size + 2 * padding - (dilation * (filter_size - 1) + 1)) / " "stride + 1), where input_size is %d, padding is %d, " "filter_size is %d, dilation is %d, stride is %d.", @@ -60,7 +60,7 @@ inline int ConvOutputSize(int input_size, int filter_size, int dilation, output_size, 0, platform::errors::InvalidArgument( "The output's size is expected to be greater than 0. " - "But recieved: output's size is %d. The output's size is computed by " + "But received: output's size is %d. The output's size is computed by " "((input_size + padding_1 + padding_2 - (dilation * (filter_size - " "1) + 1)) / stride + 1), where input_size is %d, padding is " "(%d, %d), filter_size is %d, dilation is %d, stride is %d.", @@ -90,7 +90,7 @@ inline void UpdatePaddingAndDilation(std::vector* paddings, platform::errors::InvalidArgument( "Attribute padding's size should be the same or twice as the " "input's dimension. " - "But recieved: padding's size is %d, padding is [%s]; input's " + "But received: padding's size is %d, padding is [%s]; input's " "dimension is %d, input's shape is [%s].", paddings->size(), phi::make_ddim(*paddings), data_dims.size(), data_dims)); diff --git a/paddle/fluid/operators/conv_op_mlu.cc b/paddle/fluid/operators/conv_op_mlu.cc index 1ee772ec72950196a3805422d38ded1325cc8d40..c1517dbe16f84c9933ac40300fc65bed8ed8fbcb 100644 --- a/paddle/fluid/operators/conv_op_mlu.cc +++ b/paddle/fluid/operators/conv_op_mlu.cc @@ -98,7 +98,7 @@ class MLUConvOpKernel : public framework::OpKernel { output_desc.get(), GetBasePtr(&output_tensor)); if (!channel_last) { - // transpose ouput from NHWC to NCHW + // transpose output from NHWC to NCHW const std::vector perm_to_nchw = {0, 3, 1, 2}; TransposeFromMLUTensor(ctx, perm_to_nchw, &output_tensor, output, false /*need_reshape_or_alloc*/); diff --git a/paddle/fluid/operators/ctc_align_op.cu b/paddle/fluid/operators/ctc_align_op.cu index b1f2e61ef3930d81aa56794c0d232930452b03d9..ba90c677570c503868dff382e9479555c032a8eb 100644 --- a/paddle/fluid/operators/ctc_align_op.cu +++ b/paddle/fluid/operators/ctc_align_op.cu @@ -26,19 +26,19 @@ __global__ void MergeAndDelCudaKernel(const int64_t num_token, const T* tokens, const size_t num_seq, size_t* lod0, const int blank, const int merge_repeated, size_t* out_lod0, T* output) { - int ouput_idx = 0; + int output_idx = 0; out_lod0[0] = 0; for (int i = 0; i < num_seq; ++i) { T pre_token = -1; for (int j = lod0[i]; j < lod0[i + 1]; ++j) { if (tokens[j] != blank && !(merge_repeated && tokens[j] == pre_token)) { - output[ouput_idx] = tokens[j]; - ++ouput_idx; + output[output_idx] = tokens[j]; + ++output_idx; } pre_token = tokens[j]; } - out_lod0[i + 1] = ouput_idx; + out_lod0[i + 1] = output_idx; } } diff --git a/paddle/fluid/operators/deformable_psroi_pooling_op.cu b/paddle/fluid/operators/deformable_psroi_pooling_op.cu index 448f67a4bad7a57a97bfa1dcc75248f552902006..873950b2d2f65bd982681d5209d4dbff4c586345 100644 --- a/paddle/fluid/operators/deformable_psroi_pooling_op.cu +++ b/paddle/fluid/operators/deformable_psroi_pooling_op.cu @@ -200,7 +200,7 @@ class DeformablePSROIPoolCUDAKernel : public framework::OpKernel { num_rois, out->dims()[0], platform::errors::InvalidArgument( "The number of Input(ROIs) should be same with the number of " - "Ouput(Output), but received ROIs number is:%d, Output number " + "Output(Output), but received ROIs number is:%d, Output number " "is:%d.", num_rois, out->dims()[0])); const int count = num_rois * output_dim * pooled_height * pooled_width; diff --git a/paddle/fluid/operators/deformable_psroi_pooling_op.h b/paddle/fluid/operators/deformable_psroi_pooling_op.h index 51a0fe4172ca2e46f6a6615e413295fb6210cf8b..3deabce54ed0bdb00a5901edf667e61a86d5567b 100644 --- a/paddle/fluid/operators/deformable_psroi_pooling_op.h +++ b/paddle/fluid/operators/deformable_psroi_pooling_op.h @@ -175,7 +175,7 @@ class DeformablePSROIPoolCPUKernel : public framework::OpKernel { num_rois, out->dims()[0], platform::errors::InvalidArgument( "The number of Input(ROIs) should be same with the number of " - "Ouput(Output), but received ROIs number is:%d, Output number " + "Output(Output), but received ROIs number is:%d, Output number " "is:%d.", num_rois, out->dims()[0])); framework::Tensor roi_batch_id_list; diff --git a/paddle/fluid/operators/detection/matrix_nms_op.cc b/paddle/fluid/operators/detection/matrix_nms_op.cc index 713c2dc7fe9c15916fba15dcfffe6c5f7e2a3958..3353739b01bf674c43fac813f390fc76ab2e87a9 100644 --- a/paddle/fluid/operators/detection/matrix_nms_op.cc +++ b/paddle/fluid/operators/detection/matrix_nms_op.cc @@ -385,7 +385,7 @@ independently for each class. The outputs is a 2-D LoDTenosr, for each image, the offsets in first dimension of LoDTensor are called LoD, the number of offset is N + 1, where N is the batch size. If LoD[i + 1] - LoD[i] == 0, means there is no detected bbox for this image. Now this operator has one more -ouput, which is RoisNum. The size of RoisNum is N, RoisNum[i] means the number of +output, which is RoisNum. The size of RoisNum is N, RoisNum[i] means the number of detected bbox for this image. For more information on Matrix NMS, please refer to: diff --git a/paddle/fluid/operators/dropout_op_npu.cc b/paddle/fluid/operators/dropout_op_npu.cc index 07b3b5381162575cbfc03dd8cc10d0c88a2d21e8..104ab1b5046402be134ac15e980e642c2c7ecda7 100644 --- a/paddle/fluid/operators/dropout_op_npu.cc +++ b/paddle/fluid/operators/dropout_op_npu.cc @@ -54,7 +54,7 @@ class DropoutNPUKernel : public framework::OpKernel { return; } - // only achive the default `upscale_in_train` method + // only achieve the default `upscale_in_train` method if (!is_test) { Tensor tmp_x(x->dtype()); Tensor tmp_out(out->dtype()); diff --git a/paddle/fluid/operators/elementwise/elementwise_mlu.h b/paddle/fluid/operators/elementwise/elementwise_mlu.h index 156cea81c0f63009823628764b09fef5833b0f77..ff1e12103be9194e971a4ad262fa984d0d7c6ca9 100644 --- a/paddle/fluid/operators/elementwise/elementwise_mlu.h +++ b/paddle/fluid/operators/elementwise/elementwise_mlu.h @@ -165,7 +165,7 @@ template void MLUUnary(const framework::ExecutionContext& ctx, cnnlComputationPreference_t prefer, const cnnlTensorDescriptor_t input_desc, const void* input, - const cnnlTensorDescriptor_t ouput_desc, void* output); + const cnnlTensorDescriptor_t output_desc, void* output); template <> inline void MLUUnary(const framework::ExecutionContext& ctx, diff --git a/paddle/fluid/operators/fc_op.cc b/paddle/fluid/operators/fc_op.cc index 33518953004aecd666f386d9cf48f58e19695e82..6e646f0d4bf264b3b4aebdb56dceaef063a404c3 100644 --- a/paddle/fluid/operators/fc_op.cc +++ b/paddle/fluid/operators/fc_op.cc @@ -75,7 +75,7 @@ class FCOp : public framework::OperatorWithKernel { platform::errors::InvalidArgument( "The attribute in_num_col_dims used to flatten Input to " "a 2-D tensor, is expected to be less than the number of " - "Input's dimensions. But recieved in_num_col_dims is %d, " + "Input's dimensions. But received in_num_col_dims is %d, " "the number of Input's dimensions is %d, Input's shape is %s.", in_num_col_dims, in_dims.size(), in_dims)); @@ -93,7 +93,7 @@ class FCOp : public framework::OperatorWithKernel { in_dims.size() >= 2 && in_dims.size() <= 4, true, platform::errors::Unimplemented( "The Input of fc is expected to be a 2-D, 3-D or 4-D tensor when " - "use_mkldnn is set. But recieved the number of Input's " + "use_mkldnn is set. But received the number of Input's " "dimensions is %d, Input's shape is %s.", in_dims.size(), in_dims)); } diff --git a/paddle/fluid/operators/fc_op.h b/paddle/fluid/operators/fc_op.h index 6d3b531ce0aa63188f489e5f5179540315352b6d..47c7128603587d4d786b13f1ca5764bca188f09d 100644 --- a/paddle/fluid/operators/fc_op.h +++ b/paddle/fluid/operators/fc_op.h @@ -36,7 +36,7 @@ inline void FCOutputSize(const framework::DDim& in_dims, in_mat_dims[1], w_dims0, platform::errors::InvalidArgument( "The input's second dimension and weight's first dimension is " - "expected to be the same. But recieved input's second dimension is " + "expected to be the same. But received input's second dimension is " "%d, input's shape is %s; weight's first dimension is %d, weight's " "shape is %s.", in_mat_dims[1], in_mat_dims, w_dims0, diff --git a/paddle/fluid/operators/fill_constant_op.cc b/paddle/fluid/operators/fill_constant_op.cc index 2e924da283ab3f8c2a551565aae78550c04adc38..07593a70f05b7c46cf7da92942c02e815fbd1cc0 100644 --- a/paddle/fluid/operators/fill_constant_op.cc +++ b/paddle/fluid/operators/fill_constant_op.cc @@ -32,7 +32,7 @@ class FillConstantOp : public framework::OperatorWithKernel { shape[i], 0, platform::errors::InvalidArgument( "Each value of attribute 'shape' is expected to be no less " - "than 0. But recieved: shape[%u] = %d; shape = [%s].", + "than 0. But received: shape[%u] = %d; shape = [%s].", i, shape[i], phi::make_ddim(shape))); } } diff --git a/paddle/fluid/operators/fold_op.cc b/paddle/fluid/operators/fold_op.cc index 92f59e118c3b7bb66a2c5c76d66109ddf04ee076..9c9183c8fafa42a6a1ab479fcfae49b770d8e060 100644 --- a/paddle/fluid/operators/fold_op.cc +++ b/paddle/fluid/operators/fold_op.cc @@ -76,47 +76,47 @@ class FoldOp : public framework::OperatorWithKernel { PADDLE_ENFORCE_GT(kernel_height, 0, platform::errors::InvalidArgument( "The `kernel_sizes` should be greater than zero, " - "but recieved kernel_height: %d kernel_width: %d.", + "but received kernel_height: %d kernel_width: %d.", kernel_sizes[0], kernel_sizes[1])); PADDLE_ENFORCE_GT(kernel_width, 0, platform::errors::InvalidArgument( "The `kernel_sizes` should be greater than zero, " - "but recieved kernel_height: %d kernel_width: %d.", + "but received kernel_height: %d kernel_width: %d.", kernel_sizes[0], kernel_sizes[1])); // check strides PADDLE_ENFORCE_GT(stride_height, 0, platform::errors::InvalidArgument( "The `strides` should be greater than zero, " - "but recieved strides_height: %d strides_width: %d.", + "but received strides_height: %d strides_width: %d.", strides[0], strides[1])); PADDLE_ENFORCE_GT(stride_width, 0, platform::errors::InvalidArgument( "The `strides` should be greater than zero, " - "but recieved strides_height: %d strides_width: %d.", + "but received strides_height: %d strides_width: %d.", strides[0], strides[1])); // check dilations PADDLE_ENFORCE_GT(output_height, 1, platform::errors::InvalidArgument( "The `output_height` should be greater than one, " - "but recieved output_height: %d .", + "but received output_height: %d .", output_height)); PADDLE_ENFORCE_GT(output_width, 1, platform::errors::InvalidArgument( "The `output_width` should be greater than one, " - "but recieved output_width: %d .", + "but received output_width: %d .", output_width)); // check output size PADDLE_ENFORCE_GT( dilation_height, 0, platform::errors::InvalidArgument( "The `dilations` should be greater than zero, " - "but recieved dilations_height: %d dilations_width: %d.", + "but received dilations_height: %d dilations_width: %d.", dilations[0], dilations[1])); PADDLE_ENFORCE_GT( dilation_width, 0, platform::errors::InvalidArgument( "The `dilations` should be greater than zero, " - "but recieved dilations_height: %d dilations_width: %d.", + "but received dilations_height: %d dilations_width: %d.", dilations[0], dilations[1])); std::vector out_dims; diff --git a/paddle/fluid/operators/fused/conv_fusion_op.cc b/paddle/fluid/operators/fused/conv_fusion_op.cc index e60fc44e9a6ffc106a9c6957c2365e7b44c467b9..671e94061cb5c2e31820a8045c598b7298b54d4d 100644 --- a/paddle/fluid/operators/fused/conv_fusion_op.cc +++ b/paddle/fluid/operators/fused/conv_fusion_op.cc @@ -80,7 +80,7 @@ class Conv2DFusionOp : public operators::ConvOp { data_format, "NHWC", platform::errors::PermissionDenied( "Operator(Conv2DFusion) only supports data format of " - "channel first (NCHW) now. But recieved: data_format = '%s'.", + "channel first (NCHW) now. But received: data_format = '%s'.", data_format)); std::vector output_shape = ComputeOutputShape(ctx); @@ -113,7 +113,7 @@ class Conv2DFusionOp : public operators::ConvOp { split_channels_sum, output_shape[1], platform::errors::InvalidArgument( "The sum of Attr(split_channels) is expected to be equal to the " - "total output channels. But recieved: the sum of " + "total output channels. But received: the sum of " "Attr(split_channels) = %d, the total output channels = %d.", split_channels_sum, output_shape[1])); diff --git a/paddle/fluid/operators/fused/conv_fusion_op.cu b/paddle/fluid/operators/fused/conv_fusion_op.cu index 5dbf4fb88b2a78838ce0fe95be653f68f4805416..8191c85f2a1205fe01cbeba72360ff13b26834eb 100644 --- a/paddle/fluid/operators/fused/conv_fusion_op.cu +++ b/paddle/fluid/operators/fused/conv_fusion_op.cu @@ -130,7 +130,7 @@ class CUDNNConvFusionOpKernel : public framework::OpKernel { default: PADDLE_THROW(platform::errors::PermissionDenied( "Operator Conv2DFusion expects Input to be a 4-D or 5-D Tensor. " - "But recieved the actual dimension = %d, shape = [%s].", + "But received the actual dimension = %d, shape = [%s].", rank, transformed_input_channel.dims())); } @@ -355,7 +355,7 @@ class CUDNNConvFusionOpKernel : public framework::OpKernel { workspace_size_in_bytes, workspace_size_limit, platform::errors::InvalidArgument( "The actual workspace size to be allocated for cuDNN is expected " - "to be less than the limit. But recieved: the actual workspace " + "to be less than the limit. But received: the actual workspace " "size = %d, limit = %d.", workspace_size_in_bytes, workspace_size_limit)); @@ -414,7 +414,7 @@ class CUDNNConvFusionOpKernel : public framework::OpKernel { } else { // TODO(qingiqng): do copy when batch size large than 1 PADDLE_THROW(platform::errors::Unimplemented( - "Input with batch size greater than 1 is unsupported. The recieved " + "Input with batch size greater than 1 is unsupported. The received " "batch size is %d, Input's shape is [%s].", x_dims[0], phi::make_ddim(x_dims))); } diff --git a/paddle/fluid/operators/fused/cudnn_bn_stats_finalize.cu.h b/paddle/fluid/operators/fused/cudnn_bn_stats_finalize.cu.h index 74cc92eb8ab6273cd39f35d9236d72490c9f07a9..4b3ed56890e187480c968ad41168419b81f36706 100644 --- a/paddle/fluid/operators/fused/cudnn_bn_stats_finalize.cu.h +++ b/paddle/fluid/operators/fused/cudnn_bn_stats_finalize.cu.h @@ -40,7 +40,7 @@ struct BNStatsFinalizeArgs { PADDLE_ENFORCE_EQ( param_shape.size(), 4U, platform::errors::InvalidArgument( - "The size of param_shape is expected to 4. But recieved " + "The size of param_shape is expected to 4. But received " "param_shape's size is %d, param_shape is [%s].", param_shape.size(), phi::make_ddim(param_shape))); diff --git a/paddle/fluid/operators/fused/cudnn_norm_conv.cu.h b/paddle/fluid/operators/fused/cudnn_norm_conv.cu.h index f63fe4b96cbebba1732b03a436917d91b1572ecc..b32f2e40933ac10b804cbff0f7a5377bff0f482a 100644 --- a/paddle/fluid/operators/fused/cudnn_norm_conv.cu.h +++ b/paddle/fluid/operators/fused/cudnn_norm_conv.cu.h @@ -45,13 +45,13 @@ struct NormConvolutionArgs { PADDLE_ENFORCE_EQ( input_shape.size(), 4U, platform::errors::InvalidArgument( - "The size of input_shape is expected to 4. But recieved " + "The size of input_shape is expected to 4. But received " "input_shape's size is %d, input_shape is [%s].", input_shape.size(), phi::make_ddim(input_shape))); PADDLE_ENFORCE_EQ( filter_shape.size(), 4U, platform::errors::InvalidArgument( - "The size of filter_shape is expected to 4. But recieved " + "The size of filter_shape is expected to 4. But received " "filter_shape's size is %d, filter_shape is [%s].", filter_shape.size(), phi::make_ddim(filter_shape))); PADDLE_ENFORCE_EQ(filter_shape[1] == filter_shape[2] && @@ -59,20 +59,20 @@ struct NormConvolutionArgs { true, platform::errors::InvalidArgument( "The filter_shape is expected to store as nhwc, and " - "h = w = 1 or 3. But recieved filter_shape is [%s].", + "h = w = 1 or 3. But received filter_shape is [%s].", phi::make_ddim(filter_shape))); PADDLE_ENFORCE_EQ((filter_shape[0] % 32 == 0 && filter_shape[3] % 8 == 0), true, platform::errors::InvalidArgument( "The input channel is expected to be multiple of 8, " "and the output channel is expected to be multiple " - "of 32. But recieved input channel is %d, output " + "of 32. But received input channel is %d, output " "channel is %d.", filter_shape[3], filter_shape[0])); PADDLE_ENFORCE_EQ( output_shape.size(), 4U, platform::errors::InvalidArgument( - "The size of output_shape is expected to 4. But recieved " + "The size of output_shape is expected to 4. But received " "filter_shape's size is %d, filter_shape is [%s].", output_shape.size(), phi::make_ddim(output_shape))); is_support = IsSupport(ctx, filter_shape, stride, dilation, group); @@ -83,7 +83,7 @@ struct NormConvolutionArgs { "compatiblity greater than or equal to 70 and the kernel size " "must be equal to 1 or 3. When the kernel size is 1, " "the stride must be 1 if the compatiblity is equal to 70. " - "Besides, the dilation and group must be equal to 1. But recieved " + "Besides, the dilation and group must be equal to 1. But received " "compatiblity is %d, kernel size is %d, stride is %d, " "dilation is %d, group is %d", ctx.GetComputeCapability(), filter_shape[1], stride, dilation, diff --git a/paddle/fluid/operators/fused/cudnn_scale_bias_add_relu.cu.h b/paddle/fluid/operators/fused/cudnn_scale_bias_add_relu.cu.h index 9d3090a7179f0a7a878d2dc8192c274b27f9fcc2..c8588b0c02e9d846eca6c1344054c7d4d217a347 100644 --- a/paddle/fluid/operators/fused/cudnn_scale_bias_add_relu.cu.h +++ b/paddle/fluid/operators/fused/cudnn_scale_bias_add_relu.cu.h @@ -43,19 +43,19 @@ struct ScaleBiasAddReluArgs { PADDLE_ENFORCE_EQ( data_shape.size(), 4U, platform::errors::InvalidArgument( - "The size of data_shape is expected to 4. But recieved " + "The size of data_shape is expected to 4. But received " "data_shape's size is %d, data_shape is [%s].", data_shape.size(), phi::make_ddim(data_shape))); PADDLE_ENFORCE_EQ( param_shape.size(), 4U, platform::errors::InvalidArgument( - "The size of param_shape is expected to 4. But recieved " + "The size of param_shape is expected to 4. But received " "param_shape's size is %d, param_shape is [%s].", param_shape.size(), phi::make_ddim(param_shape))); PADDLE_ENFORCE_EQ( bitmask_shape.size(), 3U, platform::errors::InvalidArgument( - "The size of bitmask_shape is expected to 3. But recieved " + "The size of bitmask_shape is expected to 3. But received " "bitmask_shape's size is %d, bitmask_shape is [%s].", bitmask_shape.size(), phi::make_ddim(bitmask_shape))); diff --git a/paddle/fluid/operators/fused/fused_fc_elementwise_layernorm_op.cc b/paddle/fluid/operators/fused/fused_fc_elementwise_layernorm_op.cc index 27dae277516816332110b33b19ec86cfe21d68ed..1b5b074ef1c7169e64ef3a5c58757f8ca3e4c8a2 100644 --- a/paddle/fluid/operators/fused/fused_fc_elementwise_layernorm_op.cc +++ b/paddle/fluid/operators/fused/fused_fc_elementwise_layernorm_op.cc @@ -76,7 +76,7 @@ class FusedFCElementwiseLayerNormOp : public framework::OperatorWithKernel { platform::errors::InvalidArgument( "The attribute x_num_col_dims used to flatten input X to " "a 2-D tensor, is expected to be less than the number of " - "input X's dimensions. But recieved x_num_col_dims is %d, " + "input X's dimensions. But received x_num_col_dims is %d, " "the number of input X's dimensions is %d, input X's shape is %s.", x_num_col_dims, x_dims.size(), x_dims)); @@ -85,7 +85,7 @@ class FusedFCElementwiseLayerNormOp : public framework::OperatorWithKernel { x_mat_dims[1], w_dims[0], platform::errors::InvalidArgument( "The input's second dimension and weight's first dimension is " - "expected to be the same. But recieved input's second dimension is " + "expected to be the same. But received input's second dimension is " "%d, input's shape is %s; weight's first dimension is %d, weight's " "shape is %s.", x_mat_dims[1], x_mat_dims, w_dims[0], w_dims)); @@ -100,7 +100,7 @@ class FusedFCElementwiseLayerNormOp : public framework::OperatorWithKernel { PADDLE_ENFORCE_EQ(phi::make_ddim(fc_out_dims), y_dims, platform::errors::InvalidArgument( "The output's shape of fc is expected to be equal to " - "that of input Y. But recieved output's shape of fc " + "that of input Y. But received output's shape of fc " "is %s, input Y's shape is %s.", phi::make_ddim(fc_out_dims), y_dims)); @@ -110,7 +110,7 @@ class FusedFCElementwiseLayerNormOp : public framework::OperatorWithKernel { platform::errors::InvalidArgument( "The attribute begin_norm_axis used to flatten input Y to a 2-D " "tensor, is expected to be less than the number of input Y's " - "dimensions. But recieved begin_norm_axis is %d, the number of " + "dimensions. But received begin_norm_axis is %d, the number of " "input Y's dimensions is %d, input Y's shape is %s.", begin_norm_axis, y_dims.size(), y_dims)); @@ -122,7 +122,7 @@ class FusedFCElementwiseLayerNormOp : public framework::OperatorWithKernel { PADDLE_ENFORCE_EQ(scale_dims.size(), 1, platform::errors::InvalidArgument( "The input Scale is expected to be an 1-D tensor. " - "But recieved the number of input Scale's " + "But received the number of input Scale's " "dimensions is %d, input Scale's shape is %s.", scale_dims.size(), scale_dims)); @@ -132,7 +132,7 @@ class FusedFCElementwiseLayerNormOp : public framework::OperatorWithKernel { platform::errors::InvalidArgument( "The first dimension of input Scale is expected to be equal to " "the second dimension of input Y after flattened. " - "But recieved the first dimension of input Scale is %d, input " + "But received the first dimension of input Scale is %d, input " "Scale's shape is %s; the second dimension of flattened input " "Y is %d, input Y's shape is %s, flattened axis is %d.", scale_dims[0], scale_dims, dim_1, y_dims, begin_norm_axis)); @@ -144,7 +144,7 @@ class FusedFCElementwiseLayerNormOp : public framework::OperatorWithKernel { bias1_dims.size(), 1, platform::errors::InvalidArgument( "The input Bias1 is expected to be an 1-D tensor. " - "But recieved the number of input Bias1's dimension is %d, " + "But received the number of input Bias1's dimension is %d, " "input Bias1's shape is %s.", bias1_dims.size(), bias1_dims)); @@ -154,7 +154,7 @@ class FusedFCElementwiseLayerNormOp : public framework::OperatorWithKernel { platform::errors::InvalidArgument( "The first dimension of input Bias1 is expected to be equal to " "the second dimension of input Y after flattened. " - "But recieved the first dimension of input Bias1 is %d, input " + "But received the first dimension of input Bias1 is %d, input " "Bias1's shape is %s; the second dimension of flatten input " "Y is %d, input Y's shape is %s, flattened axis is %d.", bias1_dims[0], bias1_dims, dim_1, y_dims, begin_norm_axis)); diff --git a/paddle/fluid/operators/fused/fusion_group_op.cc b/paddle/fluid/operators/fused/fusion_group_op.cc index 738e069081511ed2e6df56633971f0db21211ac1..1ebbdf792df85c1ab7626fe4917ee40e1e47ad95 100644 --- a/paddle/fluid/operators/fused/fusion_group_op.cc +++ b/paddle/fluid/operators/fused/fusion_group_op.cc @@ -52,7 +52,7 @@ class FusionGroupOp : public framework::OperatorWithKernel { x_dims[0], x_dims[i], platform::errors::InvalidArgument( "All the inputs' dims is expected to be the same. " - "But recieved [%s] (name: %s) vs [%s] (name: %s).", + "But received [%s] (name: %s) vs [%s] (name: %s).", x_dims[0], input_names[0], x_dims[i], input_names[i])); } std::vector out_dims; diff --git a/paddle/fluid/operators/inverse_op.cc b/paddle/fluid/operators/inverse_op.cc index 8c1fd34ae87d2e27498d876649671901c0b0a4fb..f5b817a0e11faa85ef4b1288d639b9f3b45d7638 100644 --- a/paddle/fluid/operators/inverse_op.cc +++ b/paddle/fluid/operators/inverse_op.cc @@ -33,21 +33,21 @@ class InverseOp : public framework::OperatorWithKernel { input_rank, 2, platform::errors::InvalidArgument( "The dimension of Input(Input) is expected to be no less than 2. " - "But recieved: Input(Input)'s dimension = %d, shape = [%s].", + "But received: Input(Input)'s dimension = %d, shape = [%s].", input_rank, input_dims)); for (int64_t i = 0; i < input_rank; ++i) { PADDLE_ENFORCE_EQ( (input_dims[i] == -1) || (input_dims[i] > 0), true, platform::errors::InvalidArgument( "Each dimension of input tensor is expected to be -1 or a " - "positive number, but recieved %d. Input's shape is [%s].", + "positive number, but received %d. Input's shape is [%s].", input_dims[i], input_dims)); } if (input_dims[input_rank - 2] > 0 && input_dims[input_rank - 1] > 0) { PADDLE_ENFORCE_EQ(input_dims[input_rank - 2], input_dims[input_rank - 1], platform::errors::InvalidArgument( "The last two dimensions are expected to be equal. " - "But recieved: %d and %d; " + "But received: %d and %d; " "Input(Input)'s shape = [%s].", input_dims[input_rank - 2], input_dims[input_rank - 1], input_dims)); diff --git a/paddle/fluid/operators/lod_reset_op.h b/paddle/fluid/operators/lod_reset_op.h index 86327a4f2c13a2c8a9db94ae97e44b3c8be03c27..642c8bcd9ae496d78f1894d2e80ffac9f5581f4b 100644 --- a/paddle/fluid/operators/lod_reset_op.h +++ b/paddle/fluid/operators/lod_reset_op.h @@ -77,7 +77,7 @@ class LoDResetKernel : public framework::OpKernel { platform::errors::InvalidArgument( "The last value of 'Target LoD''s last level LoD should be equal " "to the first dimension of Input(X). But received the 'Target LoD' " - "is %s, Input(X)'s shape is is %s.", + "is %s, Input(X)'s shape is %s.", phi::make_ddim(level0), in->dims())); for (size_t i = 0; i < level0.size() - 1; ++i) { PADDLE_ENFORCE_GE(level0[i + 1], level0[i], diff --git a/paddle/fluid/operators/math/cross_entropy.h b/paddle/fluid/operators/math/cross_entropy.h index e339be06d69ed2a24459919e20966314e80ffae2..da7340e4eb0b363877b61b49fe6204fb9c046b1f 100644 --- a/paddle/fluid/operators/math/cross_entropy.h +++ b/paddle/fluid/operators/math/cross_entropy.h @@ -38,7 +38,7 @@ struct TolerableValue { // NOTE(dzh): float16 value clip behave different. // 1. Our ValueClipping has a hardcore threshold 1e20 // for float number. 1e20 will resulting in overflow in float16. -// 2. float16 should expose the the real number overflow to python. +// 2. float16 should expose the real number overflow to python. // because mixed-training depends the inf/nan value to determine // if the scale value will be adjusted. // Also. In standard implementation of cross entropy, other diff --git a/paddle/fluid/operators/math/selected_rows_functor.cc b/paddle/fluid/operators/math/selected_rows_functor.cc index f77287826ffb3572de3e1ce7fd35e99c981c474f..a880afb0e9be34f7a29f794c8596fdbef8190ca6 100644 --- a/paddle/fluid/operators/math/selected_rows_functor.cc +++ b/paddle/fluid/operators/math/selected_rows_functor.cc @@ -32,7 +32,7 @@ struct SelectedRowsAdd { PADDLE_ENFORCE_EQ( in1_height, input2.height(), platform::errors::InvalidArgument("The two inputs height must be equal." - "But recieved first input height = " + "But received first input height = " "[%d], second input height = [%d]", in1_height, input2.height())); output->set_height(in1_height); @@ -56,27 +56,27 @@ struct SelectedRowsAdd { in1_row_numel, in2_value.numel() / in2_rows.size(), platform::errors::InvalidArgument( "The two inputs width must be equal." - "But recieved first input width = [%d], second input width = [%d]", + "But received first input width = [%d], second input width = [%d]", in1_row_numel, in2_value.numel() / in2_rows.size())); PADDLE_ENFORCE_EQ( in1_row_numel, out_value->numel() / out_rows.size(), platform::errors::InvalidArgument( "The input and oupput width must be equal." - "But recieved input width = [%d], output width = [%d]", + "But received input width = [%d], output width = [%d]", in1_row_numel, out_value->numel() / out_rows.size())); auto in1_place = input1.place(); PADDLE_ENFORCE_EQ(platform::is_cpu_place(in1_place), true, platform::errors::InvalidArgument( - "The running enviroment is not on the CPU place.")); + "The running environment is not on the CPU place.")); auto in2_place = input2.place(); PADDLE_ENFORCE_EQ(platform::is_cpu_place(in2_place), true, platform::errors::InvalidArgument( - "The running enviroment is not on the CPU place.")); + "The running environment is not on the CPU place.")); auto out_place = context.GetPlace(); PADDLE_ENFORCE_EQ(platform::is_cpu_place(out_place), true, platform::errors::InvalidArgument( - "The running enviroment is not on the CPU place.")); + "The running environment is not on the CPU place.")); auto* out_data = out_value->data(); auto* in1_data = in1_value.data(); @@ -103,14 +103,14 @@ struct SelectedRowsAddTensor { PADDLE_ENFORCE_EQ( in1_height, in2_dims[0], platform::errors::InvalidArgument("The two inputs height must be equal." - "But recieved first input height = " + "But received first input height = " "[%d], second input height = [%d]", in1_height, in2_dims[0])); PADDLE_ENFORCE_EQ( in1_height, out_dims[0], platform::errors::InvalidArgument( "The input and output height must be equal." - "But recieved input height = [%d], output height = [%d]", + "But received input height = [%d], output height = [%d]", in1_height, out_dims[0])); auto& in1_value = input1.value(); @@ -121,13 +121,13 @@ struct SelectedRowsAddTensor { in1_row_numel, input2.numel() / in1_height, platform::errors::InvalidArgument( "The two inputs width must be equal." - "But recieved first input width = [%d], second input width = [%d]", + "But received first input width = [%d], second input width = [%d]", in1_row_numel, input2.numel() / in1_height)); PADDLE_ENFORCE_EQ( in1_row_numel, output->numel() / in1_height, platform::errors::InvalidArgument( "The input and output width must be equal." - "But recieved input width = [%d], output width = [%d]", + "But received input width = [%d], output width = [%d]", in1_row_numel, output->numel() / in1_height)); phi::funcs::SetConstant functor; @@ -161,7 +161,7 @@ struct SelectedRowsAddTo { PADDLE_ENFORCE_EQ( in1_height, input2->height(), platform::errors::InvalidArgument("The two inputs height must be equal." - "But recieved first input height = " + "But received first input height = " "[%d], second input height = [%d]", in1_height, input2->height())); @@ -178,11 +178,11 @@ struct SelectedRowsAddTo { auto in1_place = input1.place(); PADDLE_ENFORCE_EQ(platform::is_cpu_place(in1_place), true, platform::errors::InvalidArgument( - "The running enviroment is not on the CPU place.")); + "The running environment is not on the CPU place.")); auto in2_place = input2->place(); PADDLE_ENFORCE_EQ(platform::is_cpu_place(in2_place), true, platform::errors::InvalidArgument( - "The running enviroment is not on the CPU place.")); + "The running environment is not on the CPU place.")); auto* in1_data = in1_value.data(); auto* in2_data = in2_value->data(); @@ -211,7 +211,7 @@ struct SelectedRowsSumTo { PADDLE_ENFORCE_EQ(in1_height, input2->height(), platform::errors::InvalidArgument( "The two inputs height must be equal." - "But recieved first input height = [%d], second " + "But received first input height = [%d], second " "input height = [%d]", in1_height, input2->height())); } @@ -253,7 +253,7 @@ struct SelectedRowsAddToTensor { PADDLE_ENFORCE_EQ( in1_height, in2_dims[0], platform::errors::InvalidArgument("The two inputs height must be equal." - "But recieved first input height = " + "But received first input height = " "[%d], second input height = [%d]", in1_height, in2_dims[0])); @@ -265,7 +265,7 @@ struct SelectedRowsAddToTensor { in1_row_numel, input2->numel() / in1_height, platform::errors::InvalidArgument( "The two inputs width must be equal." - "But recieved first input width = [%d], second input width = [%d]", + "But received first input width = [%d], second input width = [%d]", in1_row_numel, input2->numel() / in1_height)); auto* in1_data = in1_value.data(); @@ -293,7 +293,7 @@ struct SelectedRowsAddToTensor { PADDLE_ENFORCE_EQ( in1_height, in2_dims[0], platform::errors::InvalidArgument("The two inputs height must be equal." - "But recieved first input height = " + "But received first input height = " "[%d], second input height = [%d]", in1_height, in2_dims[0])); @@ -305,7 +305,7 @@ struct SelectedRowsAddToTensor { in1_row_numel, input2->numel() / in1_height, platform::errors::InvalidArgument( "The two inputs width must be equal." - "But recieved first input width = [%d], second input width = [%d]", + "But received first input width = [%d], second input width = [%d]", in1_row_numel, input2->numel() / in1_height)); auto* in1_data = in1_value.data(); @@ -842,7 +842,7 @@ struct UpdateToTensor { PADDLE_ENFORCE_EQ( in1_height, in2_dims[0], platform::errors::InvalidArgument("The two inputs height must be equal." - "But recieved first input height = " + "But received first input height = " "[%d], second input height = [%d]", in1_height, in2_dims[0])); @@ -854,7 +854,7 @@ struct UpdateToTensor { in1_row_numel, input2->numel() / in1_height, platform::errors::InvalidArgument( "The two inputs width must be equal." - "But recieved first input width = [%d], second input width = [%d]", + "But received first input width = [%d], second input width = [%d]", in1_row_numel, input2->numel() / in1_height)); auto* in1_data = in1_value.data(); diff --git a/paddle/fluid/operators/math/selected_rows_functor.cu b/paddle/fluid/operators/math/selected_rows_functor.cu index 542d4c9784352e98d0c033fd4a25d8b7af58d4ab..db5c66d319701ba587f194fc43cb2832eb031569 100644 --- a/paddle/fluid/operators/math/selected_rows_functor.cu +++ b/paddle/fluid/operators/math/selected_rows_functor.cu @@ -33,7 +33,7 @@ struct SelectedRowsAdd { PADDLE_ENFORCE_EQ( in1_height, input2.height(), platform::errors::InvalidArgument("The two inputs height must be equal." - "But recieved first input height = " + "But received first input height = " "[%d], second input height = [%d]", in1_height, input2.height())); output->set_height(in1_height); @@ -57,13 +57,13 @@ struct SelectedRowsAdd { in1_row_numel, in2_value.numel() / in2_rows.size(), platform::errors::InvalidArgument( "The two inputs width must be equal." - "But recieved first input width = [%d], second input width = [%d]", + "But received first input width = [%d], second input width = [%d]", in1_row_numel, in2_value.numel() / in2_rows.size())); PADDLE_ENFORCE_EQ( in1_row_numel, out_value->numel() / out_rows.size(), platform::errors::InvalidArgument( "The input and oupput width must be equal." - "But recieved input width = [%d], output width = [%d]", + "But received input width = [%d], output width = [%d]", in1_row_numel, out_value->numel() / out_rows.size())); auto* out_data = out_value->data(); @@ -72,15 +72,15 @@ struct SelectedRowsAdd { auto in1_place = input1.place(); PADDLE_ENFORCE_EQ(platform::is_gpu_place(in1_place), true, platform::errors::InvalidArgument( - "The running enviroment is not on the GPU place.")); + "The running environment is not on the GPU place.")); auto in2_place = input2.place(); PADDLE_ENFORCE_EQ(platform::is_gpu_place(in2_place), true, platform::errors::InvalidArgument( - "The running enviroment is not on the GPU place.")); + "The running environment is not on the GPU place.")); auto out_place = context.GetPlace(); PADDLE_ENFORCE_EQ(platform::is_gpu_place(out_place), true, platform::errors::InvalidArgument( - "The running enviroment is not on the GPU place.")); + "The running environment is not on the GPU place.")); memory::Copy(out_place, out_data, in1_place, in1_data, in1_value.numel() * sizeof(T), context.stream()); @@ -126,13 +126,13 @@ struct SelectedRowsAddTensor { in1_height, in2_dims[0], platform::errors::InvalidArgument( "The two inputs height must be equal." - "But recieved first input height = [%d], first input height = [%d]", + "But received first input height = [%d], first input height = [%d]", in1_height, in2_dims[0])); PADDLE_ENFORCE_EQ( in1_height, out_dims[0], platform::errors::InvalidArgument( "The input and output height must be equal." - "But recieved input height = [%d], output height = [%d]", + "But received input height = [%d], output height = [%d]", in1_height, out_dims[0])); auto& in1_value = input1.value(); @@ -143,13 +143,13 @@ struct SelectedRowsAddTensor { in1_row_numel, input2.numel() / in1_height, platform::errors::InvalidArgument( "The two inputs width must be equal." - "But recieved first input width = [%d], second input width = [%d]", + "But received first input width = [%d], second input width = [%d]", in1_row_numel, input2.numel() / in1_height)); PADDLE_ENFORCE_EQ( in1_row_numel, output->numel() / in1_height, platform::errors::InvalidArgument( "The input and output width must be equal." - "But recieved input width = [%d], output width = [%d]", + "But received input width = [%d], output width = [%d]", in1_row_numel, output->numel() / in1_height)); auto* in1_data = in1_value.data(); @@ -186,13 +186,13 @@ struct SelectedRowsAddTensor { in1_height, in2_dims[0], platform::errors::InvalidArgument( "The two inputs height must be equal." - "But recieved first input height = [%d], first input height = [%d]", + "But received first input height = [%d], first input height = [%d]", in1_height, in2_dims[0])); PADDLE_ENFORCE_EQ( in1_height, out_dims[0], platform::errors::InvalidArgument( "The input and output height must be equal." - "But recieved input height = [%d], output height = [%d]", + "But received input height = [%d], output height = [%d]", in1_height, out_dims[0])); auto& in1_value = input1.value(); @@ -203,13 +203,13 @@ struct SelectedRowsAddTensor { in1_row_numel, input2.numel() / in1_height, platform::errors::InvalidArgument( "The two inputs width must be equal." - "But recieved first input width = [%d], second input width = [%d]", + "But received first input width = [%d], second input width = [%d]", in1_row_numel, input2.numel() / in1_height)); PADDLE_ENFORCE_EQ( in1_row_numel, output->numel() / in1_height, platform::errors::InvalidArgument( "The input and output width must be equal." - "But recieved input width = [%d], output width = [%d]", + "But received input width = [%d], output width = [%d]", in1_row_numel, output->numel() / in1_height)); auto* in1_data = in1_value.data(); @@ -254,7 +254,7 @@ struct SelectedRowsAddTo { PADDLE_ENFORCE_EQ( in1_height, input2->height(), platform::errors::InvalidArgument("The two inputs height must be equal." - "But recieved first input height = " + "But received first input height = " "[%d], second input height = [%d]", in1_height, input2->height())); @@ -273,11 +273,11 @@ struct SelectedRowsAddTo { auto in1_place = input1.place(); PADDLE_ENFORCE_EQ(platform::is_gpu_place(in1_place), true, platform::errors::InvalidArgument( - "The running enviroment is not on the GPU place.")); + "The running environment is not on the GPU place.")); auto in2_place = input2->place(); PADDLE_ENFORCE_EQ(platform::is_gpu_place(in1_place), true, platform::errors::InvalidArgument( - "The running enviroment is not on the GPU place.")); + "The running environment is not on the GPU place.")); auto* in1_data = in1_value.data(); auto* in2_data = in2_value->data(); @@ -322,7 +322,7 @@ struct SelectedRowsAddToTensor { PADDLE_ENFORCE_EQ( in1_height, in2_dims[0], platform::errors::InvalidArgument("The two inputs height must be equal." - "But recieved first input height = " + "But received first input height = " "[%d], second input height = [%d]", in1_height, in2_dims[0])); @@ -334,7 +334,7 @@ struct SelectedRowsAddToTensor { in1_row_numel, input2->numel() / in1_height, platform::errors::InvalidArgument( "The two inputs width must be equal." - "But recieved first input width = [%d], second input width = [%d]", + "But received first input width = [%d], second input width = [%d]", in1_row_numel, input2->numel() / in1_height)); auto* in1_data = in1_value.data(); @@ -359,7 +359,7 @@ struct SelectedRowsAddToTensor { PADDLE_ENFORCE_EQ( in1_height, in2_dims[0], platform::errors::InvalidArgument("The two inputs height must be equal." - "But recieved first input height = " + "But received first input height = " "[%d], second input height = [%d]", in1_height, in2_dims[0])); @@ -371,7 +371,7 @@ struct SelectedRowsAddToTensor { in1_row_numel, input2->numel() / in1_height, platform::errors::InvalidArgument( "The two inputs width must be equal." - "But recieved first input width = [%d], second input width = [%d]", + "But received first input width = [%d], second input width = [%d]", in1_row_numel, input2->numel() / in1_height)); auto* in1_data = in1_value.data(); @@ -675,7 +675,7 @@ struct UpdateToTensor { PADDLE_ENFORCE_EQ( in1_height, in2_dims[0], platform::errors::InvalidArgument("The two inputs height must be equal." - "But recieved first input height = " + "But received first input height = " "[%d], second input height = [%d]", in1_height, in2_dims[0])); @@ -687,7 +687,7 @@ struct UpdateToTensor { in1_row_numel, input2->numel() / in1_height, platform::errors::InvalidArgument( "The two inputs width must be equal." - "But recieved first input width = [%d], second input width = [%d]", + "But received first input width = [%d], second input width = [%d]", in1_row_numel, input2->numel() / in1_height)); auto* in1_data = in1_value.template data(); diff --git a/paddle/fluid/operators/metrics/accuracy_op.cc b/paddle/fluid/operators/metrics/accuracy_op.cc index 32ef052119883944abc1876f8bf3a8c028ddc57a..ed58c90e17022e4c177470453d305e2231f0722d 100644 --- a/paddle/fluid/operators/metrics/accuracy_op.cc +++ b/paddle/fluid/operators/metrics/accuracy_op.cc @@ -36,7 +36,7 @@ class AccuracyOpMaker : public framework::OpProtoAndCheckerMaker { void Make() override { // TODO(typhoonzero): support both inference value and indices. AddInput("Out", "The network output of topk (inferences)"); - AddInput("Indices", "The the network output of topk (indices)"); + AddInput("Indices", "The network output of topk (indices)"); AddInput("Label", "Label of the training data"); // TODO(typhoonzero): AddInput("Weight", ... AddOutput("Accuracy", "The accuracy of current batch"); diff --git a/paddle/fluid/operators/mlu/mlu_baseop.cc b/paddle/fluid/operators/mlu/mlu_baseop.cc index 6b801924446ca54b3959baf655be7765c3834de7..867c5f212ba6c17514b65f83d40fe356b5d04146 100644 --- a/paddle/fluid/operators/mlu/mlu_baseop.cc +++ b/paddle/fluid/operators/mlu/mlu_baseop.cc @@ -698,14 +698,14 @@ MLUCnnlTrigonDesc::~MLUCnnlTrigonDesc() { const bool exclusive, const bool reverse, const cnnlTensorDescriptor_t input_desc, const void* input, - const cnnlTensorDescriptor_t ouput_desc, + const cnnlTensorDescriptor_t output_desc, void* output) { cnnlHandle_t handle = GetHandleFromCTX(ctx); // NAN propagation mode: Only support CNNL_NOT_PROPAGATE_NAN now. cnnlNanPropagation_t mode = CNNL_NOT_PROPAGATE_NAN; PADDLE_ENFORCE_MLU_SUCCESS(cnnlCumsum(handle, input_desc, input, axis, - exclusive, reverse, mode, ouput_desc, + exclusive, reverse, mode, output_desc, output)); } diff --git a/paddle/fluid/operators/positive_negative_pair_op.cc b/paddle/fluid/operators/positive_negative_pair_op.cc index a9646b2e8acb5201f95d2bdf7207483f04528712..cbe58644f53810ed04329dc53e0a5eb83491f70b 100644 --- a/paddle/fluid/operators/positive_negative_pair_op.cc +++ b/paddle/fluid/operators/positive_negative_pair_op.cc @@ -123,7 +123,7 @@ class PositiveNegativePairOp : public framework::OperatorWithKernel { column, depth, platform::errors::OutOfRange( "Attr(column) should be less than depth(the second " - "dimension of Input(Score)). Recieved Attr(column): %d, while " + "dimension of Input(Score)). Received Attr(column): %d, while " "depth is %d.", column, depth)); PADDLE_ENFORCE_GE( @@ -131,7 +131,7 @@ class PositiveNegativePairOp : public framework::OperatorWithKernel { platform::errors::OutOfRange( "Attr(column) should be greater than equal to negative " "depth, i.e. the second dimension of Input(Score). " - "Recieved Attr(column): %d, while negative depth is %d.", + "Received Attr(column): %d, while negative depth is %d.", column, -depth)); } diff --git a/paddle/fluid/operators/prune_gate_by_capacity_op.cu b/paddle/fluid/operators/prune_gate_by_capacity_op.cu index 7228bdbf3805a30869c9dd9e3ca0e38f5349865c..6a2ed6592e7fef0ac9e436842d052820ff97d722 100644 --- a/paddle/fluid/operators/prune_gate_by_capacity_op.cu +++ b/paddle/fluid/operators/prune_gate_by_capacity_op.cu @@ -98,7 +98,7 @@ static void VisitDataType(paddle::experimental::DataType type, visitor.template apply(); } else { PADDLE_THROW(platform::errors::InvalidArgument( - "The recieved values gate_id type %s can not meet input requirements. " + "The received values gate_id type %s can not meet input requirements. " "Because the given gate_id data type of operators must be " "int64. Please input appropriate gate_id again! ", "framework::DataTypeToString(type)")); diff --git a/paddle/fluid/operators/pscore/heter_listen_and_serv_op.cc b/paddle/fluid/operators/pscore/heter_listen_and_serv_op.cc index 2df0d7526a3d3c2105f9a0a7ecaa21cec173cc00..457e37744d3163a74c8ecf73d2bf2a37e138a4fb 100644 --- a/paddle/fluid/operators/pscore/heter_listen_and_serv_op.cc +++ b/paddle/fluid/operators/pscore/heter_listen_and_serv_op.cc @@ -63,7 +63,7 @@ void HeterListenAndServOp::RunAsyncLoop(framework::ProgramDesc *program) const { PADDLE_ENFORCE_EQ(pieces.size(), 2, platform::errors::PreconditionNotMet( "Invalid format of message_and_id argument. " - "Expected \"message:block_id\". Recieved %s", + "Expected \"message:block_id\". Received %s", grad_and_id.c_str())); PADDLE_ENFORCE_EQ(out_map->count(pieces[0]), 0, platform::errors::AlreadyExists( @@ -82,7 +82,7 @@ void HeterListenAndServOp::RunAsyncLoop(framework::ProgramDesc *program) const { PADDLE_ENFORCE_GE(num_blocks, 1, platform::errors::PreconditionNotMet( "Invalid number of blocks in server program. Expected " - "equal or greater than 1. Recieved %zu", + "equal or greater than 1. Received %zu", num_blocks)); std::vector block_list; for (size_t blkid = 1; blkid < num_blocks; ++blkid) { diff --git a/paddle/fluid/operators/rnn_op_xpu.cc b/paddle/fluid/operators/rnn_op_xpu.cc index 220d91bf4faab6931063bbeed7944f4067ab3557..941e463f63cdcc64b60c454ccfa9c3c210cf14f9 100644 --- a/paddle/fluid/operators/rnn_op_xpu.cc +++ b/paddle/fluid/operators/rnn_op_xpu.cc @@ -65,7 +65,7 @@ class RnnXPUKernel : public framework::OpKernel { auto* output = ctx.Output("Out"); auto* dropout_mask = ctx.Output("DropoutState"); auto* reserve_data = ctx.Output("Reserve"); - // Attrbutes + // Attributes const int& num_layers = ctx.Attr("num_layers"); const bool& is_bidirec = ctx.Attr("is_bidirec"); const int& hidden_size = ctx.Attr("hidden_size"); diff --git a/paddle/fluid/operators/sample_logits_op.cc b/paddle/fluid/operators/sample_logits_op.cc index 420c4c5f257caa4f3a170b5623cea1421bd21f85..e02c7ade9a11a2b8e9175b5bc52f44e9fff3e598 100644 --- a/paddle/fluid/operators/sample_logits_op.cc +++ b/paddle/fluid/operators/sample_logits_op.cc @@ -58,7 +58,7 @@ class SampleLogitsOpMaker : public framework::OpProtoAndCheckerMaker { AddOutput( "Probabilities", "(Tensor, default: Tensor), A 2-D tensor with shape [N, NT + S]." - "The probabilites of sampled positive and negtive labels.") + "The probabilities of sampled positive and negtive labels.") .AsIntermediate(); AddOutput("LogitsDim", "Store dim information of Logits for gradient op") .AsIntermediate(); diff --git a/paddle/fluid/operators/sigmoid_cross_entropy_with_logits_op_npu.cc b/paddle/fluid/operators/sigmoid_cross_entropy_with_logits_op_npu.cc index f186f95a2b96117fa56fc17f70d4d0884214af87..ed173bb3ebfa9b7294bbbfeb95bedb9606658c3c 100644 --- a/paddle/fluid/operators/sigmoid_cross_entropy_with_logits_op_npu.cc +++ b/paddle/fluid/operators/sigmoid_cross_entropy_with_logits_op_npu.cc @@ -22,7 +22,7 @@ using Tensor = framework::Tensor; const int kIgnoreIndex = -100; void CheckAttrs(const framework::ExecutionContext& ctx) { - // Add this check is is due to Ascend SigmoidCrossEntropyWithLogits + // Add this check is due to Ascend SigmoidCrossEntropyWithLogits // and SigmoidCrossEntropyWithLogitsGrad does't supoort // attr normalize and ignore_index bool normalize = ctx.Attr("normalize"); diff --git a/paddle/fluid/operators/sum_op.cu b/paddle/fluid/operators/sum_op.cu index 33590c1d7cca04e215e55abb26fb2aa3c3b61bec..8c6c083cde880e1e913b1d75446896fce668afb5 100644 --- a/paddle/fluid/operators/sum_op.cu +++ b/paddle/fluid/operators/sum_op.cu @@ -156,7 +156,7 @@ void SumToLoDTensor(const framework::ExecutionContext &context) { } } - // compute select rows seperately. + // compute select rows separately. if (!selectrow_index.empty()) { std::vector sr_in_out_data; size_t rows = 0; @@ -241,7 +241,7 @@ class SumKernel LodTensorArrayCompute(context); } else { PADDLE_THROW(platform::errors::InvalidArgument( - "Expected type of Ouput(out) must be Tensor, SelectedRows or " + "Expected type of Output(out) must be Tensor, SelectedRows or " "LodTensorArray. But got " "unsupport type: %s.", framework::ToTypeName(out_var->Type()))); diff --git a/paddle/fluid/operators/tdm_child_op.h b/paddle/fluid/operators/tdm_child_op.h index 963dfd3bf772090640b88076efdda7cebd0262f9..e437975320cc5e1ad51c8d06adac5168cb3b328e 100644 --- a/paddle/fluid/operators/tdm_child_op.h +++ b/paddle/fluid/operators/tdm_child_op.h @@ -149,7 +149,7 @@ class TDMChildKernel : public framework::OpKernel { output_type == framework::proto::VarType::INT64; PADDLE_ENFORCE_EQ(out_type_match, true, platform::errors::InvalidArgument( - "Ouput(Child) & Output(LeafMask) holds the wrong " + "Output(Child) & Output(LeafMask) holds the wrong " "type, it holds %s, but " "desires to be %s or %s", paddle::framework::DataTypeToString(output_type), diff --git a/paddle/fluid/operators/warpctc_op.cc b/paddle/fluid/operators/warpctc_op.cc index 5cd9feee82895d032b91333d27e65401b6edf0ad..1583e5d84b233e118b20a79e4adda1e5155464fd 100644 --- a/paddle/fluid/operators/warpctc_op.cc +++ b/paddle/fluid/operators/warpctc_op.cc @@ -95,7 +95,7 @@ An operator integrating the open-source https://arxiv.org/pdf/1512.02595v1.pdf), to compute Connectionist Temporal Classification (CTC) loss. It can be aliased as softmax with ctc, since a native softmax activation is -interated to the warp-ctc library, to to normalize values for each row of the +interated to the warp-ctc library, to normalize values for each row of the input tensor. More detail of CTC loss can be found by referring to diff --git a/paddle/fluid/platform/CMakeLists.txt b/paddle/fluid/platform/CMakeLists.txt index 356b5ab2cd23ce511b17c3a267cceed423d7a347..24d39c25cf335a9f04d3f8110cc75b96f962d865 100644 --- a/paddle/fluid/platform/CMakeLists.txt +++ b/paddle/fluid/platform/CMakeLists.txt @@ -116,7 +116,7 @@ endif() cc_library(cudnn_workspace_helper SRCS cudnn_workspace_helper.cc DEPS boost) -# seperate init from device_context to avoid cycle dependencies +# separate init from device_context to avoid cycle dependencies cc_library(init SRCS init.cc DEPS device_context custom_kernel context_pool) # memcpy depends on device_context, here add deps individually for diff --git a/paddle/fluid/platform/device/npu/npu_op_runner.h b/paddle/fluid/platform/device/npu/npu_op_runner.h index 2409c14b760fd8f86d2275bd3c6d58db0c6e4899..739a3ef41e4222c46e5752c640c74e56a5d5d0ca 100644 --- a/paddle/fluid/platform/device/npu/npu_op_runner.h +++ b/paddle/fluid/platform/device/npu/npu_op_runner.h @@ -70,7 +70,7 @@ class NpuOpRunner { NpuOpRunner &AddInput(const Tensor &tensor); // NOTE(zhiqiu): CANN-5.0.2 support input tensors on host. - // Specifically, the tensor of shape, tensor of dims, etc, which are are small + // Specifically, the tensor of shape, tensor of dims, etc, which are small // vector/list. NpuOpRunner &AddInput(const Tensor &tensor, aclMemType mem_type); diff --git a/paddle/fluid/platform/profiler/event_node.cc b/paddle/fluid/platform/profiler/event_node.cc index 6c8be1811d715da60fc4437da7f946ae5cdb7034..b909fb5f25aa7b4098d809af8993a85e51e73f84 100644 --- a/paddle/fluid/platform/profiler/event_node.cc +++ b/paddle/fluid/platform/profiler/event_node.cc @@ -51,7 +51,7 @@ void NodeTrees::BuildTrees( const std::vector& host_event_nodes, std::vector& runtime_event_nodes, const std::vector& device_event_nodes) { - // seperate Host Event Nodes into different threads + // separate Host Event Nodes into different threads std::map> thread2host_event_nodes; // used to store HostTraceEventNodes per thread std::map> diff --git a/paddle/infrt/common/object.h b/paddle/infrt/common/object.h index ab2d00cce985c1a4a7e916a566539b47978989b8..797595cc7c58b050ecae2d9272185e6baed7677a 100644 --- a/paddle/infrt/common/object.h +++ b/paddle/infrt/common/object.h @@ -25,7 +25,7 @@ template class Shared; /** * Object is the basic element in the INFRT, with `Shared` wrapper, the object - * can be shared accross the system. + * can be shared across the system. */ struct Object { //! Get the type representation of this object. diff --git a/paddle/phi/infermeta/binary.cc b/paddle/phi/infermeta/binary.cc index 2139605fb204861fb8e20372ce844dbe20436665..837a43905e7239cb879f5120635002aaebfce7d7 100644 --- a/paddle/phi/infermeta/binary.cc +++ b/paddle/phi/infermeta/binary.cc @@ -1534,7 +1534,7 @@ void MvInferMeta(const MetaTensor& x, const MetaTensor& vec, MetaTensor* out) { phi::errors::InvalidArgument( "X's second dimension is expected to be equal to " "Vec's first dimension" - "but recieved X'shape = [%s], Vec's shape = [%s]", + "but received X'shape = [%s], Vec's shape = [%s]", dim_x, dim_vec)); diff --git a/paddle/phi/infermeta/multiary.cc b/paddle/phi/infermeta/multiary.cc index e793eb8e6687205f095ede9e90dd3aae4ccb4ced..48c40673ab8197eceb4b8f0bd3aad63855a821ff 100644 --- a/paddle/phi/infermeta/multiary.cc +++ b/paddle/phi/infermeta/multiary.cc @@ -458,7 +458,7 @@ void BatchNormInferMeta(const MetaTensor& x, true, phi::errors::InvalidArgument( "Each dimension of input tensor is expected to be -1 or a " - "positive number, but recieved %d. Input's shape is [%s].", + "positive number, but received %d. Input's shape is [%s].", x_dims[i], x_dims)); } @@ -755,7 +755,7 @@ inline int ConvOutputSize( 0, phi::errors::InvalidArgument( "The output's size is expected to be greater than 0. " - "But recieved: output's size is %d. The output's size is computed by " + "But received: output's size is %d. The output's size is computed by " "((input_size + 2 * padding - (dilation * (filter_size - 1) + 1)) / " "stride + 1), where input_size is %d, padding is %d, " "filter_size is %d, dilation is %d, stride is %d.", diff --git a/paddle/phi/infermeta/unary.cc b/paddle/phi/infermeta/unary.cc index 6d37a31f5456208070a3a3e6f77a1efbd3510ebc..6c2956417a3a363b508b66356f5ab90a956c9c0d 100644 --- a/paddle/phi/infermeta/unary.cc +++ b/paddle/phi/infermeta/unary.cc @@ -2746,7 +2746,7 @@ void UnfoldInferMeta(const MetaTensor& x, phi::errors::InvalidArgument( "The dims of X should be larger than that of kernel_sizes " "by a number of 2, due to the batch size and input channel dim. " - "But recieved dims(X:%u) - dims(kernel_sizes:%u) != 2", + "But received dims(X:%u) - dims(kernel_sizes:%u) != 2", in_dims.size(), kernel_sizes.size())); PADDLE_ENFORCE_EQ( @@ -2754,7 +2754,7 @@ void UnfoldInferMeta(const MetaTensor& x, kernel_sizes.size(), phi::errors::InvalidArgument( "The dims of strides should be the same with that of kernel_sizes. " - "But recieved dims(strides: %u) != dims(kernel_sizes: %u).", + "But received dims(strides: %u) != dims(kernel_sizes: %u).", strides.size(), kernel_sizes.size())); PADDLE_ENFORCE_EQ( @@ -2762,7 +2762,7 @@ void UnfoldInferMeta(const MetaTensor& x, 2 * strides.size(), phi::errors::InvalidArgument( "The dims of paddings should be 2 times of that of strides. " - "But recieved dims(paddings: %u) != 2*dims(strides: %u).", + "But received dims(paddings: %u) != 2*dims(strides: %u).", paddings.size(), strides.size())); PADDLE_ENFORCE_EQ( @@ -2770,7 +2770,7 @@ void UnfoldInferMeta(const MetaTensor& x, dilations.size(), phi::errors::InvalidArgument( "The dims of strides should be the same with that of dilations. " - "But recieved dims(strides: %u) != dims(dilations: %u).", + "But received dims(strides: %u) != dims(dilations: %u).", strides.size(), dilations.size())); @@ -2779,14 +2779,14 @@ void UnfoldInferMeta(const MetaTensor& x, 0, phi::errors::InvalidArgument( "The `kernel_sizes` should be greater than zero, " - "but recieved kernel_height: %d kernel_width: %d.", + "but received kernel_height: %d kernel_width: %d.", kernel_sizes[0], kernel_sizes[1])); PADDLE_ENFORCE_GT(kernel_sizes[1], 0, phi::errors::InvalidArgument( "The `kernel_sizes` should be greater than zero, " - "but recieved kernel_height: %d kernel_width: %d.", + "but received kernel_height: %d kernel_width: %d.", kernel_sizes[0], kernel_sizes[1])); // check strides @@ -2794,14 +2794,14 @@ void UnfoldInferMeta(const MetaTensor& x, 0, phi::errors::InvalidArgument( "The `strides` should be greater than zero, " - "but recieved strides_height: %d strides_width: %d.", + "but received strides_height: %d strides_width: %d.", strides[0], strides[1])); PADDLE_ENFORCE_GT(strides[1], 0, phi::errors::InvalidArgument( "The `strides` should be greater than zero, " - "but recieved strides_height: %d strides_width: %d.", + "but received strides_height: %d strides_width: %d.", strides[0], strides[1])); // check dilations @@ -2810,7 +2810,7 @@ void UnfoldInferMeta(const MetaTensor& x, 0, phi::errors::InvalidArgument( "The `dilations` should be greater than zero, " - "but recieved dilations_height: %d dilations_width: %d.", + "but received dilations_height: %d dilations_width: %d.", dilations[0], dilations[1])); PADDLE_ENFORCE_GT( @@ -2818,7 +2818,7 @@ void UnfoldInferMeta(const MetaTensor& x, 0, phi::errors::InvalidArgument( "The `dilations` should be greater than zero, " - "but recieved dilations_height: %d dilations_width: %d.", + "but received dilations_height: %d dilations_width: %d.", dilations[0], dilations[1])); diff --git a/paddle/phi/kernels/cpu/conv_util.h b/paddle/phi/kernels/cpu/conv_util.h index d26d89086b27e3db8ccfcf339c51c6a2fdf1988a..159a5cfbeb6b4164e700c6a428c1fffae12b0c8b 100644 --- a/paddle/phi/kernels/cpu/conv_util.h +++ b/paddle/phi/kernels/cpu/conv_util.h @@ -38,7 +38,7 @@ inline void UpdatePaddingAndDilation(std::vector* paddings, phi::errors::InvalidArgument( "Attribute padding's size should be the same or twice as the " "input's dimension. " - "But recieved: padding's size is %d, padding is [%s]; input's " + "But received: padding's size is %d, padding is [%s]; input's " "dimension is %d, input's shape is [%s].", paddings->size(), make_ddim(*paddings), diff --git a/paddle/phi/kernels/cpu/rnn_kernel.cc b/paddle/phi/kernels/cpu/rnn_kernel.cc index cae97eb0764533c903aef9b098b8857f55e0a470..ae2c7a72635f7ff7948720708cb23516c80e9c65 100644 --- a/paddle/phi/kernels/cpu/rnn_kernel.cc +++ b/paddle/phi/kernels/cpu/rnn_kernel.cc @@ -808,7 +808,7 @@ struct BidirLayer : public Layer { mode, is_test); - // concat the the output result + // concat the output result funcs::ConcatFunctor concat_functor; concat_functor(dev_ctx, output_vec, static_cast(2), output); } diff --git a/paddle/phi/kernels/funcs/broadcast_function.h b/paddle/phi/kernels/funcs/broadcast_function.h index 38cd41d3b61303a053be228633f4fff53b28905c..17735c05ada52d15677bafe8cd03d3fbc58e2504 100644 --- a/paddle/phi/kernels/funcs/broadcast_function.h +++ b/paddle/phi/kernels/funcs/broadcast_function.h @@ -53,7 +53,7 @@ struct DimensionsTransform { PADDLE_THROW(phi::errors::InvalidArgument( "The %d-th dimension of input tensor is expected to be equal " "with the %d-th dimension of output tensor %d or 1, but " - "recieved %d.", + "received %d.", in_idx + 1, axis + 1, out_dims[axis], @@ -70,7 +70,7 @@ struct DimensionsTransform { PADDLE_THROW(phi::errors::InvalidArgument( "The %d-th dimension of input tensor is expected to be equal " "with the %d-th dimension of output tensor %d or 1, but " - "recieved %d.", + "received %d.", in_idx + 1, in_idx + 1, out_dims[in_idx], @@ -552,7 +552,7 @@ void BroadcastKernelForDifferentDimSize( default: { PADDLE_THROW(phi::errors::InvalidArgument( "The maximum dimension of input tensor is expected to be less than " - "%d, but recieved %d.", + "%d, but received %d.", merge_dims.dim_size, phi::DDim::kMaxRank)); } @@ -578,7 +578,7 @@ void BroadcastKernelForDifferentVecSize( kArity, phi::errors::InvalidArgument( "The number of inputs is expected to be equal to the " - "arity of functor. But recieved: the number of inputs " + "arity of functor. But received: the number of inputs " "is %d, the arity of functor is %d.", ins.size(), kArity)); diff --git a/paddle/phi/kernels/funcs/elementwise_base.h b/paddle/phi/kernels/funcs/elementwise_base.h index 4ee46facc7913b7cc31dc3a8b13a0647b7815ecd..1093bdfa726c83ba095a433662b46530b0b30b4e 100644 --- a/paddle/phi/kernels/funcs/elementwise_base.h +++ b/paddle/phi/kernels/funcs/elementwise_base.h @@ -849,7 +849,7 @@ void ElementwiseKernel(const KPDevice &ctx, kArity, phi::errors::InvalidArgument( "The number of inputs is expected to be equal to the " - "arity of functor. But recieved: the number of inputs " + "arity of functor. But received: the number of inputs " "is %d, the arity of functor is %d.", ins.size(), kArity)); diff --git a/paddle/phi/kernels/gpu/bce_loss_kernel.cu b/paddle/phi/kernels/gpu/bce_loss_kernel.cu index adbcd3b2b62077ac1d3117c98c94db3e31b781dc..b190bce4742805bbfe18991e8b20c04a2339b719 100644 --- a/paddle/phi/kernels/gpu/bce_loss_kernel.cu +++ b/paddle/phi/kernels/gpu/bce_loss_kernel.cu @@ -38,7 +38,7 @@ struct BCELossFunctor { HOSTDEVICE inline T operator()(const T x, const T label) const { PADDLE_ENFORCE( (x >= static_cast(0)) && (x <= one), - "Input is expected to be within the interval [0, 1], but recieved %f.", + "Input is expected to be within the interval [0, 1], but received %f.", x); T term1 = max(phi::kps::details::Log(x), neg_100); T term2 = max(phi::kps::details::Log(one - x), neg_100); diff --git a/paddle/phi/kernels/impl/searchsorted_kernel_impl.h b/paddle/phi/kernels/impl/searchsorted_kernel_impl.h index 82bd9fba2a66d7a4601b5aab360b9bbf80ff04d9..e3cd6f5828d04849729bde72dbb044b31f488c57 100644 --- a/paddle/phi/kernels/impl/searchsorted_kernel_impl.h +++ b/paddle/phi/kernels/impl/searchsorted_kernel_impl.h @@ -158,7 +158,7 @@ static void VisitDataType(DataType type, Visitor visitor) { visitor.template apply(); } else { PADDLE_THROW(errors::InvalidArgument( - "The recieved values data type %s can not meet input requirements. " + "The received values data type %s can not meet input requirements. " "Because the given values data type of searchsorted operators must be " "float32, float64, int32 or int64. Please input appropriate " "sorted_sequence again! ", diff --git a/paddle/phi/ops/compat/scale_sig.cc b/paddle/phi/ops/compat/scale_sig.cc index 95deb007d99d9c42bbc2cc22faed2a44fa58b0f5..8061a1fbd610a4f8681dc6f8214194f41c979240 100644 --- a/paddle/phi/ops/compat/scale_sig.cc +++ b/paddle/phi/ops/compat/scale_sig.cc @@ -30,7 +30,7 @@ namespace phi { * The infrt declare like: * * def PDKEL_Reshape_to_CPU : Pat< - * (PD_ReshapeOp $x, $shape_tensor， $shape_attr), // OpMaker arguements + * (PD_ReshapeOp $x, $shape_tensor， $shape_attr), // OpMaker arguments * (PDKEL_ReshapeKernelAttr $x, fn($shape_attr)>; // Kernel arguments * def PDKEL_Reshape_to_CPU : Pat< * (PD_ReshapeOp $x, $shape_tensor， $shape_attr), diff --git a/python/paddle/README.rst b/python/paddle/README.rst index e779f1264c4516b3e6a814a42d2ff1ce2d0d7013..2d48ee4b26cafb9a07024ae77bbac6a2321b9b48 100644 --- a/python/paddle/README.rst +++ b/python/paddle/README.rst @@ -88,7 +88,7 @@ If you want to install paddlepaddle-gpu with cuda version of 9.0 ,10.0 ,10.1 ,or After the installation is complete, you can use `python` or `python3` to enter the Python interpreter and then use `import paddle.fluid` and `fluid.install_check.run_check()` -If `Your Paddle Fluid is installed succesfully!` appears, to verify that the installation was successful. +If `Your Paddle Fluid is installed successfully!` appears, to verify that the installation was successful. diff --git a/python/paddle/distributed/auto_parallel/process_group.py b/python/paddle/distributed/auto_parallel/process_group.py index 471448b031dded54762ba8b9f3c8190b04e2fd09..d1b6e57ddc123d9af08d27471760fd14acaefef6 100644 --- a/python/paddle/distributed/auto_parallel/process_group.py +++ b/python/paddle/distributed/auto_parallel/process_group.py @@ -156,6 +156,6 @@ class ProcessGroup: # Note that Process group 0 is reserved for representing all ranks. -# At the begining, group 0 is empty and new ranks will be added automatically. +# At the beginning, group 0 is empty and new ranks will be added automatically. _g_process_group_map = {} _g_process_group_map[0] = ProcessGroup(0, []) diff --git a/python/paddle/distributed/fleet/base/distributed_strategy.py b/python/paddle/distributed/fleet/base/distributed_strategy.py index 9d20e432d8961af3e65adb8ece02411464cdfa2e..986d8e401e87208391a0f494c753fddf6ff85bb1 100644 --- a/python/paddle/distributed/fleet/base/distributed_strategy.py +++ b/python/paddle/distributed/fleet/base/distributed_strategy.py @@ -1168,9 +1168,9 @@ class DistributedStrategy(object): dp_degree(int, optional): specific the number of data parallelism group; when dp_degree >= 2, it will introduce dp_degree ways data parallelism as the outer parallelsim for the inner parallelsim. User is responsible to ensure global_world_size = mp_degree * sharding_degree * pp_degree * dp_degree. Default is 1. - mp_degree(int, optional): [Hybrid parallelism ONLY] specific the the number of gpus within each megatron parallelism group; and megatron parallelism will turn be off if mp_degree=1. Default is 1. + mp_degree(int, optional): [Hybrid parallelism ONLY] specific the number of gpus within each megatron parallelism group; and megatron parallelism will turn be off if mp_degree=1. Default is 1. - pp_degree(int, optional): [Hybrid parallelism ONLY] specific the the number of gpus within each pipeline parallelism group; and pipeline parallelism will turn be off if pp_degree=1. Default is 1. + pp_degree(int, optional): [Hybrid parallelism ONLY] specific the number of gpus within each pipeline parallelism group; and pipeline parallelism will turn be off if pp_degree=1. Default is 1. pp_allreduce_in_optimize(bool, optional): [Hybrid parallelism ONLY] move the allreduce operations from backward stage to update(optimize) stage when pipeline parallelsim is on. This configuration will affect the communication speed of Hybrid parallelism training depeneded on network topology. this strategy is experimental by now.. Default is False. @@ -1485,7 +1485,7 @@ class DistributedStrategy(object): **Notes**: k_steps(int) The local steps for training before parameter synchronization. Default 1. - begin_step(int) The step of begining training by localsgd. Default 1. + begin_step(int) The step of beginning training by localsgd. Default 1. Examples: @@ -1544,7 +1544,7 @@ class DistributedStrategy(object): init_k_steps(int) The initial steps for training before adaptive localsgd. Then, the adaptive localsgd method will modify init_k_steps automatically. Default 1. - begin_step(int) The step of begining training by adaptive localsgd. Default 1. + begin_step(int) The step of beginning training by adaptive localsgd. Default 1. Examples: diff --git a/python/paddle/distributed/fleet/launch.py b/python/paddle/distributed/fleet/launch.py index c5a9df50589ccd36bbd228822da7c29094ad9b1e..343cca7f4f0d3bd56a6df1e639c3f2f3a8c28816 100644 --- a/python/paddle/distributed/fleet/launch.py +++ b/python/paddle/distributed/fleet/launch.py @@ -556,7 +556,7 @@ def launch(): - ``--selected_mlus``: mlus aliases, recommend to use ``--mlus``. - - ``training_script``: The full path to the single GPU training program/script to be launched in parallel, followed by all the arguments for the training script. e.g., ``traing.py`` + - ``training_script``: The full path to the single GPU training program/script to be launched in parallel, followed by all the arguments for the training script. e.g., ``training.py`` - ``training_script_args``: The args of training_script. e.g., ``--lr=0.1`` diff --git a/python/paddle/distributed/fleet/meta_optimizers/ascend/ascend_parser.py b/python/paddle/distributed/fleet/meta_optimizers/ascend/ascend_parser.py index 8f1a4de86de0d9c4d053c0f3d203d174d3a63d4f..3a52041dc7e2c57b2403b1f6e9bb58a366cc66cb 100644 --- a/python/paddle/distributed/fleet/meta_optimizers/ascend/ascend_parser.py +++ b/python/paddle/distributed/fleet/meta_optimizers/ascend/ascend_parser.py @@ -1372,7 +1372,7 @@ class UniformRandomParser(AscendParserBase): max_v = self.op.attr("max") seed = self.op.attr("seed") dtype = self.op.attr("dtype") - assert max_v > min_v, "assert max_v > min_v, but recieved " + \ + assert max_v > min_v, "assert max_v > min_v, but received " + \ "as max_v={}, min_v={} ".format(max_v, min_v) tensor1 = self._create_ge_tensor([len(shape)], 2, shape) diff --git a/python/paddle/distributed/fleet/meta_optimizers/dygraph_optimizer/dygraph_sharding_optimizer.py b/python/paddle/distributed/fleet/meta_optimizers/dygraph_optimizer/dygraph_sharding_optimizer.py index b7edf5830025d13cf8a5f2271e3ac105f77b546f..d487f35324df923f62c339abaab9b49f1d63efeb 100755 --- a/python/paddle/distributed/fleet/meta_optimizers/dygraph_optimizer/dygraph_sharding_optimizer.py +++ b/python/paddle/distributed/fleet/meta_optimizers/dygraph_optimizer/dygraph_sharding_optimizer.py @@ -170,7 +170,7 @@ class DygraphShardingOptimizer(object): result = self._inner_optimizer.minimize(loss, startup_program, parameters, no_grad_set) - # sync parameters accross sharding ranks + # sync parameters across sharding ranks self._sharding_sync_parameters() return result @@ -181,7 +181,7 @@ class DygraphShardingOptimizer(object): # actually updating self._inner_optimizer.step() - # sync parameters accross sharding ranks + # sync parameters across sharding ranks self._sharding_sync_parameters() # TODO is it a good way to make _grad_clip a property diff --git a/python/paddle/distributed/launch/main.py b/python/paddle/distributed/launch/main.py index 400a4472602522af27efe507f66f626ca35f4bd2..b2c87e737c82dbf5cf237e5992a2f26b5a904fc0 100644 --- a/python/paddle/distributed/launch/main.py +++ b/python/paddle/distributed/launch/main.py @@ -54,7 +54,7 @@ def launch(): - ``--devices``: The selected accelerate devices on nodes, can be gpu/xpu/npu/mlu etc.. e.g., ``--devices=0,1,2,3`` will launch four training processes each bound to one device. - - ``training_script``: The full path to the single GPU training program/script to be launched in parallel, followed by all the arguments for the training script. e.g., ``traing.py`` + - ``training_script``: The full path to the single GPU training program/script to be launched in parallel, followed by all the arguments for the training script. e.g., ``training.py`` - ``training_script_args``: The args of training_script. e.g., ``--lr=0.1`` diff --git a/python/paddle/distributed/passes/auto_parallel_fp16.py b/python/paddle/distributed/passes/auto_parallel_fp16.py index 69c3eef7e3771b991821559e1c1052c34b4533a1..9dda310e5c022221c882521c0e81d3a5eb6eea92 100644 --- a/python/paddle/distributed/passes/auto_parallel_fp16.py +++ b/python/paddle/distributed/passes/auto_parallel_fp16.py @@ -306,7 +306,7 @@ class FP16State(object): in_var_dist_attr = consume_op_attr.get_input_dist_attr( in_var.name) assert in_var_dist_attr is not None - # truely insert cast op + # truly insert cast op if cast_var is None or cast_var.dtype != dst_dtype: # NOTE we make the cast op and var's dist attr as the op that consume the # cast var instead of the op which generates the var diff --git a/python/paddle/distributed/ps/utils/public.py b/python/paddle/distributed/ps/utils/public.py index e7edc6fd859a6338eb35da073aa850d076920aa8..7acfd6cfe19f57524ea50bf40100a1e43b73476f 100755 --- a/python/paddle/distributed/ps/utils/public.py +++ b/python/paddle/distributed/ps/utils/public.py @@ -748,7 +748,7 @@ def find_heter_ops(program, default_device="cpu"): def union_forward_gradient_op(program_block_ops_list): """ before analyzing the input & output of each block in program_block_list, we should - union the forward op and corresponding gradient op to elimincate the uneccessary variable + union the forward op and corresponding gradient op to elimincate the unnecessary variable transmit """ """ diff --git a/python/paddle/fluid/contrib/slim/tests/test_post_training_quantization_mobilenetv1.py b/python/paddle/fluid/contrib/slim/tests/test_post_training_quantization_mobilenetv1.py index 629529ff1b96555cc8ac9f54badf99d92974a27e..56d77f77b50839c994bc895716887a03e6a0a3ab 100644 --- a/python/paddle/fluid/contrib/slim/tests/test_post_training_quantization_mobilenetv1.py +++ b/python/paddle/fluid/contrib/slim/tests/test_post_training_quantization_mobilenetv1.py @@ -405,7 +405,7 @@ class TestPostTrainingAbsMaxForMobilenetv1(TestPostTrainingQuantization): is_full_quantize = False is_use_cache_file = False is_optimize_model = False - # The accuracy diff of post-traing quantization (abs_max) maybe bigger + # The accuracy diff of post-training quantization (abs_max) maybe bigger diff_threshold = 0.05 self.run_test(model, algo, round_type, data_urls, data_md5s, quantizable_op_type, is_full_quantize, is_use_cache_file, diff --git a/python/paddle/fluid/dygraph/checkpoint.py b/python/paddle/fluid/dygraph/checkpoint.py index 1ae57bcb303108bed2654b90f1aa659cba0b4362..ba5c709b1d877f8b3792118193b96bfc912ffc4d 100644 --- a/python/paddle/fluid/dygraph/checkpoint.py +++ b/python/paddle/fluid/dygraph/checkpoint.py @@ -257,7 +257,7 @@ def load_dygraph(model_path, **configs): para_dict = structured_para_dict else: # load state dict by `io.save_params/persistables` save format - # TODO(chenweihang): [ Now only supports loading parameters seperately ] + # TODO(chenweihang): [ Now only supports loading parameters separately ] # If users save all parameters as one file, the [ variable.name -> variable ] # mapping info will lost, so users need to give variable list, but users build # variable list in dygraph mode is difficult, we recommend users to use diff --git a/python/paddle/fluid/dygraph/dygraph_to_static/convert_operators.py b/python/paddle/fluid/dygraph/dygraph_to_static/convert_operators.py index 3a7b012b02bee530d2340e8969f96db404168745..576baf6cc299a996c494f2be54bee2c4da13a868 100644 --- a/python/paddle/fluid/dygraph/dygraph_to_static/convert_operators.py +++ b/python/paddle/fluid/dygraph/dygraph_to_static/convert_operators.py @@ -167,7 +167,7 @@ def convert_logical_not(x): A function representation of a Python ``not`` statement. Args: - x(bool|Tensor): Operand of of ``not`` operator. + x(bool|Tensor): Operand of ``not`` operator. Returns: A python bool variable or a bool Tensor. diff --git a/python/paddle/fluid/executor.py b/python/paddle/fluid/executor.py index c6ff3a583d6a3873f6a32255daf1ba09b8fcba86..164545d0a0595bea78a999b594964c264a4882cf 100644 --- a/python/paddle/fluid/executor.py +++ b/python/paddle/fluid/executor.py @@ -873,7 +873,7 @@ class Executor(object): _fetch_list.append(item) else: raise TypeError( - "The item in fetch_list should be str, variable or optimize_op, but recieved %s.", + "The item in fetch_list should be str, variable or optimize_op, but received %s.", type(item)) for index, item in enumerate(fetch_list): diff --git a/python/paddle/fluid/incubate/fleet/parameter_server/ir/trainer_pass.py b/python/paddle/fluid/incubate/fleet/parameter_server/ir/trainer_pass.py index 46f26e8e52cd5c24d368f9ee242c809336304664..2c09abac9e7ba8e66bf3799619c933eab45446dd 100644 --- a/python/paddle/fluid/incubate/fleet/parameter_server/ir/trainer_pass.py +++ b/python/paddle/fluid/incubate/fleet/parameter_server/ir/trainer_pass.py @@ -1407,7 +1407,7 @@ def get_communicate_var_info(program, def union_forward_gradient_op(program_block_ops_list): """ before analyzing the input & output of each block in program_block_list, we should - union the forward op and corresponding gradient op to elimincate the uneccessary variable + union the forward op and corresponding gradient op to elimincate the unnecessary variable transmit """ """ diff --git a/python/paddle/fluid/layer_helper_base.py b/python/paddle/fluid/layer_helper_base.py index ce6fe6918b56ba97ebb49ffe725a00e478ef7871..47f0c02d287250fd025628c5fbee7bd8666b6b80 100644 --- a/python/paddle/fluid/layer_helper_base.py +++ b/python/paddle/fluid/layer_helper_base.py @@ -234,7 +234,7 @@ class LayerHelperBase(object): x=g, y=norm) # The shapes of g and norm are the same. # Currently, elementwise_mul only support broadcast when the shape # of y is a subset of the shape of x. Thus, we reshape y to squeeze - # to achive the subset. + # to achieve the subset. w = elementwise_mul( x=v, y=scale if dim is None else reshape( diff --git a/python/paddle/fluid/layers/nn.py b/python/paddle/fluid/layers/nn.py index 200e8feec1e6a17559fbb24b09967cd78de9e760..8be719758ef981c946f7251b89705aa3aa12422a 100755 --- a/python/paddle/fluid/layers/nn.py +++ b/python/paddle/fluid/layers/nn.py @@ -13744,7 +13744,7 @@ def get_tensor_from_selected_rows(x, name=None): x.height = 20 x.value = [[1, 1] [2, 2] [2, 2] [3, 3] [6, 6]] - Ouput is LoDTensor: + Output is LoDTensor: out.shape = [5, 2] out.data = [[1, 1], [2, 2], diff --git a/python/paddle/fluid/layers/rnn.py b/python/paddle/fluid/layers/rnn.py index 707a1dc2cbc2f914411fb111612696b3ddff1614..b04cf90e1d8f996c1c823cc57073c169c443ddf4 100644 --- a/python/paddle/fluid/layers/rnn.py +++ b/python/paddle/fluid/layers/rnn.py @@ -673,7 +673,7 @@ def birnn(cell_fw, birnn creates a bidirectional recurrent neural network specified by RNNCell `cell_fw` and `cell_bw`, which performs :code:`cell.call()` (for dygraph mode :code:`cell.forward`) repeatedly until reaches to - the maximum length of `inputs` and then concat the ouputs for both RNNs + the maximum length of `inputs` and then concat the outputs for both RNNs along the last axis. Arguments: diff --git a/python/paddle/fluid/tests/unittests/ir/inference/auto_scan_test.py b/python/paddle/fluid/tests/unittests/ir/inference/auto_scan_test.py index bb8c6e73fdefada768b2297470db1c9b4ffa32fc..161c785ef85656b14fdd3471b9196adda5d45d4b 100755 --- a/python/paddle/fluid/tests/unittests/ir/inference/auto_scan_test.py +++ b/python/paddle/fluid/tests/unittests/ir/inference/auto_scan_test.py @@ -388,7 +388,7 @@ class PassAutoScanTest(AutoScanTest): used_time = time.time() - start_time if max_duration > 0 and used_time > max_duration: logging.error( - "The duration exceeds {} seconds, if this is neccessary, try to set a larger number for parameter `max_duration`.". + "The duration exceeds {} seconds, if this is necessary, try to set a larger number for parameter `max_duration`.". format(max_duration)) assert False diff --git a/python/paddle/fluid/tests/unittests/ir/inference/test_shuffle_channel_detect_pass.py b/python/paddle/fluid/tests/unittests/ir/inference/test_shuffle_channel_detect_pass.py index a864e2fe5a1c822b37aeff6b1535a08c58d46e6a..1781eb50483479da280a21b97324c08e046f846e 100644 --- a/python/paddle/fluid/tests/unittests/ir/inference/test_shuffle_channel_detect_pass.py +++ b/python/paddle/fluid/tests/unittests/ir/inference/test_shuffle_channel_detect_pass.py @@ -62,13 +62,13 @@ class TestShuffleChannelDetectPass(PassAutoScanTest): "transpose2", inputs={"X": ["reshape2_output1"], }, outputs={ - "Out": ["transpose2_ouput"], + "Out": ["transpose2_output"], "XShape": ["transpose2_xshape"] }, axis=axis_v) reshape2_op2 = OpConfig( "reshape2", - inputs={"X": ["transpose2_ouput"], }, + inputs={"X": ["transpose2_output"], }, outputs={ "Out": ["reshape2_output2"], "XShape": ["reshape2_xshape2"] diff --git a/python/paddle/fluid/tests/unittests/ir/pass_test.py b/python/paddle/fluid/tests/unittests/ir/pass_test.py index aae1cc65c9220c712655c632de56d2b13244cf86..e92821387aed4307b13fd66f267975dbe84fd6bb 100644 --- a/python/paddle/fluid/tests/unittests/ir/pass_test.py +++ b/python/paddle/fluid/tests/unittests/ir/pass_test.py @@ -167,7 +167,7 @@ class PassTest(unittest.TestCase): def _check_fused_ops(self, program): ''' - Check the number of specified fused op is equal to the the expected + Check the number of specified fused op is equal to the expected number. ''' if self.fused_op_type is None or self.num_fused_ops < 0: diff --git a/python/paddle/fluid/tests/unittests/op_test.py b/python/paddle/fluid/tests/unittests/op_test.py index 13c72bedefa8edbca2e9555624c795405e9d6f20..f7a3dfa1102b295096662f71d965e6aa48406a5a 100644 --- a/python/paddle/fluid/tests/unittests/op_test.py +++ b/python/paddle/fluid/tests/unittests/op_test.py @@ -872,7 +872,7 @@ class OpTest(unittest.TestCase): eager_tensor_outputs = egr_oups if egr_oups else self.append_input_output_for_dygraph( op_proto, self.outputs, False, False, block) - # prepare attrbutes + # prepare attributes attrs_outputs = {} if hasattr(self, "attrs"): for attrs_name in self.attrs: @@ -906,7 +906,7 @@ class OpTest(unittest.TestCase): outputs = self.append_input_output_for_dygraph( op_proto, self.outputs, False, False, block) - # prepare attrbutes + # prepare attributes attrs_outputs = {} if hasattr(self, "attrs"): for attrs_name in self.attrs: @@ -2016,7 +2016,7 @@ class OpTest(unittest.TestCase): outputs = self.append_input_output_for_dygraph( op_proto, self.outputs, False, False, block) - # prepare attrbutes + # prepare attributes attrs_outputs = {} if hasattr(self, "attrs"): for attrs_name in self.attrs: diff --git a/python/paddle/fluid/tests/unittests/seresnext_test_base.py b/python/paddle/fluid/tests/unittests/seresnext_test_base.py index cc40b89b585cbf8795a06ee4c5c557b162b0651f..bf33adcf48655c28b81f35b6a00fa340779e9d00 100644 --- a/python/paddle/fluid/tests/unittests/seresnext_test_base.py +++ b/python/paddle/fluid/tests/unittests/seresnext_test_base.py @@ -25,7 +25,7 @@ class TestResnetBase(TestParallelExecutorBase): check_func, use_device, delta2=1e-5, - compare_seperately=True): + compare_separately=True): if use_device == DeviceType.CUDA and not core.is_compiled_with_cuda(): return @@ -45,7 +45,7 @@ class TestResnetBase(TestParallelExecutorBase): batch_size=seresnext_net.batch_size(use_device), use_device=use_device) - if compare_seperately: + if compare_separately: for loss in zip(func_1_first_loss, func_2_first_loss): self.assertAlmostEquals(loss[0], loss[1], delta=1e-5) for loss in zip(func_1_last_loss, func_2_last_loss): diff --git a/python/paddle/fluid/tests/unittests/static_model_parallel_fused_attention.py b/python/paddle/fluid/tests/unittests/static_model_parallel_fused_attention.py index b57f26776234eb65a57cc65df2ccd5a6a38a2144..4dc3fe6eab6be6661c0a98e1d1accd3eed62382c 100644 --- a/python/paddle/fluid/tests/unittests/static_model_parallel_fused_attention.py +++ b/python/paddle/fluid/tests/unittests/static_model_parallel_fused_attention.py @@ -69,9 +69,9 @@ class ParallelFusedMultiHeadAttention(Layer): super(ParallelFusedMultiHeadAttention, self).__init__() assert embed_dim > 0, ("Expected embed_dim to be greater than 0, " - "but recieved {}".format(embed_dim)) + "but received {}".format(embed_dim)) assert num_heads > 0, ("Expected nhead to be greater than 0, " - "but recieved {}".format(num_heads)) + "but received {}".format(num_heads)) self.normalize_before = normalize_before self._dtype = self._helper.get_default_dtype() diff --git a/python/paddle/fluid/tests/unittests/static_model_parallel_fused_feedforward.py b/python/paddle/fluid/tests/unittests/static_model_parallel_fused_feedforward.py index 5f467da6a6465467dbf0c64122b6933df92a4cbc..ad570fc0acfb386d8551a6308ae6fe1bc061634e 100644 --- a/python/paddle/fluid/tests/unittests/static_model_parallel_fused_feedforward.py +++ b/python/paddle/fluid/tests/unittests/static_model_parallel_fused_feedforward.py @@ -172,10 +172,10 @@ class ParallelFusedFeedForward(Layer): name=None): super(ParallelFusedFeedForward, self).__init__() assert d_model > 0, ( - "Expected d_model to be greater than 0, but recieved {}".format( + "Expected d_model to be greater than 0, but received {}".format( d_model)) assert dim_feedforward > 0, ( - "Expected dim_feedforward to be greater than 0, but recieved {}". + "Expected dim_feedforward to be greater than 0, but received {}". format(dim_feedforward)) self._dtype = self._helper.get_default_dtype() diff --git a/python/paddle/fluid/tests/unittests/test_fleet_rolemaker.py b/python/paddle/fluid/tests/unittests/test_fleet_rolemaker.py index 4655b628dab4d5315073f2006329dc3976f42b76..f382d61c637431c7307d8febd68ec480e08c8b1c 100644 --- a/python/paddle/fluid/tests/unittests/test_fleet_rolemaker.py +++ b/python/paddle/fluid/tests/unittests/test_fleet_rolemaker.py @@ -52,7 +52,7 @@ class TestCloudRoleMaker(unittest.TestCase): self.assertTrue(ro.is_server()) self.assertEqual(ro.worker_num(), 2) - def test_traing_role(self): + def test_training_role(self): """Test training role.""" os.environ["TRAINING_ROLE"] = "TEST" ro = role_maker.PaddleCloudRoleMaker(is_collective=False) diff --git a/python/paddle/fluid/tests/unittests/test_fleet_rolemaker_new.py b/python/paddle/fluid/tests/unittests/test_fleet_rolemaker_new.py index 5e8be9a852273e4c463987762a67d3c7977aab0d..86ee0db30ef8c7e0a994b42777d4e1308f5c9bb0 100644 --- a/python/paddle/fluid/tests/unittests/test_fleet_rolemaker_new.py +++ b/python/paddle/fluid/tests/unittests/test_fleet_rolemaker_new.py @@ -116,7 +116,7 @@ class TestCloudRoleMaker(unittest.TestCase): self.assertEqual(ro._all_gather(1, "worker"), 1) self.assertEqual(ro._all_reduce(1, "sum", "worker"), 1) - def test_traing_role(self): + def test_training_role(self): """Test training role.""" os.environ["TRAINING_ROLE"] = "TEST" diff --git a/python/paddle/fluid/tests/unittests/test_gradient_clip.py b/python/paddle/fluid/tests/unittests/test_gradient_clip.py index 7984ca5571658c96b24acaf49fe6de853bc345b3..20a55af15c441efb1f638cbba4424bbbcb7d39d1 100644 --- a/python/paddle/fluid/tests/unittests/test_gradient_clip.py +++ b/python/paddle/fluid/tests/unittests/test_gradient_clip.py @@ -162,7 +162,7 @@ class TestGradientClipByGlobalNorm(TestGradientClip): "gradient clip by global norm has wrong results!, \nu={}\nv={}\ndiff={}". format(u, v, u - v)) - # test whether the ouput is right when use 'set_gradient_clip' + # test whether the output is right when use 'set_gradient_clip' def test_old_gradient_clip(self): def func(params_grads): clip = fluid.clip.GradientClipByGlobalNorm(clip_norm=self.clip_norm) @@ -172,7 +172,7 @@ class TestGradientClipByGlobalNorm(TestGradientClip): self.clip_gradient = func self.check_gradient_clip(fluid.CPUPlace()) - # test whether the ouput is right when use grad_clip + # test whether the output is right when use grad_clip def test_new_gradient_clip(self): def func(params_grads): clip = fluid.clip.GradientClipByGlobalNorm(clip_norm=self.clip_norm) @@ -181,7 +181,7 @@ class TestGradientClipByGlobalNorm(TestGradientClip): self.clip_gradient = func self.check_gradient_clip(fluid.CPUPlace()) - # test whether the ouput is right when use grad_clip under float64 + # test whether the output is right when use grad_clip under float64 def test_new_gradient_clip_fp64(self): def func(params_grads): clip = fluid.clip.GradientClipByGlobalNorm(clip_norm=self.clip_norm) @@ -267,7 +267,7 @@ class TestGradientClipByNorm(TestGradientClip): a=u, b=v, rtol=1e-5, atol=1e-8), "gradient clip by norm has wrong results!") - # test whether the ouput is right when use grad_clip + # test whether the output is right when use grad_clip def test_gradient_clip(self): def func(params_grads): clip = fluid.clip.GradientClipByNorm(clip_norm=self.clip_norm) @@ -311,7 +311,7 @@ class TestGradientClipByValue(TestGradientClip): a=u, b=v, rtol=1e-6, atol=1e-8), "gradient clip by value has wrong results!") - # test whether the ouput is right when use grad_clip + # test whether the output is right when use grad_clip def test_gradient_clip(self): def func(params_grads): clip = fluid.clip.GradientClipByValue(max=self.max, min=self.min) @@ -397,7 +397,7 @@ class TestDygraphGradientClipByGlobalNorm(TestDygraphGradientClip): self.assertTrue( np.isclose( a=a, b=b, rtol=1e-6, atol=1e-8), - "gradient clip by global norm has wrong results, expetcd:%f, but recieved:%f" + "gradient clip by global norm has wrong results, expetcd:%f, but received:%f" % (a, b)) @@ -426,7 +426,7 @@ class TestDygraphGradientClipByNorm(TestDygraphGradientClip): self.assertTrue( np.isclose( a=a, b=b, rtol=1e-6, atol=1e-8), - "gradient clip by norm has wrong results, expetcd:%f, but recieved:%f" + "gradient clip by norm has wrong results, expetcd:%f, but received:%f" % (a, b)) @@ -517,7 +517,7 @@ class TestDygraphGradientClipFP16(unittest.TestCase): self.assertTrue( np.isclose( a=a, b=b, rtol=1e-3, atol=1e-8), - "gradient clip by global norm has wrong results, expetcd:%f, but recieved:%f" + "gradient clip by global norm has wrong results, expetcd:%f, but received:%f" % (a, b)) @@ -563,7 +563,7 @@ class TestDygraphGradientClipFP64(unittest.TestCase): self.assertTrue( np.isclose( a=a, b=b, rtol=1e-6, atol=1e-8), - "gradient clip by global norm has wrong results, expetcd:%f, but recieved:%f" + "gradient clip by global norm has wrong results, expetcd:%f, but received:%f" % (a, b)) diff --git a/python/paddle/fluid/tests/unittests/test_hsigmoid_op.py b/python/paddle/fluid/tests/unittests/test_hsigmoid_op.py index 965ae65614a40a229c3f79442e173995989b887f..51ff8ec943d0137ed4c993db340a9ecc51bd3149 100644 --- a/python/paddle/fluid/tests/unittests/test_hsigmoid_op.py +++ b/python/paddle/fluid/tests/unittests/test_hsigmoid_op.py @@ -198,7 +198,7 @@ class TestHSigmoidOp(OpTest): @skip_check_grad_ci( - reason="For 'TestHSigmoidOpSparse', check_grad is is separately calculated by 'TestHSigmoidOpWithSparseGrad'." + reason="For 'TestHSigmoidOpSparse', check_grad is separately calculated by 'TestHSigmoidOpWithSparseGrad'." ) class TestHSigmoidOpSparse(OpTest): def setUp(self): diff --git a/python/paddle/fluid/tests/unittests/test_optimizer.py b/python/paddle/fluid/tests/unittests/test_optimizer.py index ba1e9be815de65855ce971bfe83988fc91ee0d25..a0c5ce77f1d25c9530ccc49ba901d0ff648233ae 100644 --- a/python/paddle/fluid/tests/unittests/test_optimizer.py +++ b/python/paddle/fluid/tests/unittests/test_optimizer.py @@ -1123,7 +1123,7 @@ class TestOptimizerDtype(unittest.TestCase): class TestMasterWeightSaveForFP16(unittest.TestCase): ''' - For Amp-O2, some optimizer(Momentum, Adam ...) will create master weights for parameters to to improve the accuracy. + For Amp-O2, some optimizer(Momentum, Adam ...) will create master weights for parameters to improve the accuracy. Master weights will be saved by optimizer::state_dict. ''' diff --git a/python/paddle/fluid/tests/unittests/test_parallel_executor_seresnext_base_cpu.py b/python/paddle/fluid/tests/unittests/test_parallel_executor_seresnext_base_cpu.py index 20a5fcb7af3b1f883984234c849bbbc8a67f5a27..9b48a87bff7b953b272707069a380c5796cef3dc 100644 --- a/python/paddle/fluid/tests/unittests/test_parallel_executor_seresnext_base_cpu.py +++ b/python/paddle/fluid/tests/unittests/test_parallel_executor_seresnext_base_cpu.py @@ -32,7 +32,7 @@ class TestResnetCPU(TestResnetBase): self._compare_result_with_origin_model( check_func, use_device=DeviceType.CPU, - compare_seperately=False, + compare_separately=False, delta2=1e-3) diff --git a/python/paddle/fluid/tests/unittests/test_parallel_executor_seresnext_base_gpu.py b/python/paddle/fluid/tests/unittests/test_parallel_executor_seresnext_base_gpu.py index 9d1364cc592fe20b9510da6c6f4b903b13cd6f23..ff529ce94bd25194aeb7924da4284360d6ceacec 100644 --- a/python/paddle/fluid/tests/unittests/test_parallel_executor_seresnext_base_gpu.py +++ b/python/paddle/fluid/tests/unittests/test_parallel_executor_seresnext_base_gpu.py @@ -30,7 +30,7 @@ class TestResnetGPU(TestResnetBase): optimizer=seresnext_net.optimizer, use_parallel_executor=False) self._compare_result_with_origin_model( - check_func, use_device=DeviceType.CUDA, compare_seperately=False) + check_func, use_device=DeviceType.CUDA, compare_separately=False) if __name__ == '__main__': diff --git a/python/paddle/fluid/tests/unittests/test_unpool_op.py b/python/paddle/fluid/tests/unittests/test_unpool_op.py index f6dc3fba6a2143878795e9b14ff9f4cda3a806f5..95ad254a6dfb0d03595e1291b736b3e79f8096ac 100644 --- a/python/paddle/fluid/tests/unittests/test_unpool_op.py +++ b/python/paddle/fluid/tests/unittests/test_unpool_op.py @@ -116,7 +116,7 @@ class TestUnpoolOpcase1(TestUnpoolOp): self.output_size = None -class TestUnpoolOpOuputsize(TestUnpoolOp): +class TestUnpoolOpOutputsize(TestUnpoolOp): def init_test_case(self): self.unpool2d_forward_naive = unpool2dmax_forward_naive self.unpooling_type = "max" @@ -127,7 +127,7 @@ class TestUnpoolOpOuputsize(TestUnpoolOp): self.output_size = [9, 9] -class TestUnpoolOpOuput(TestUnpoolOp): +class TestUnpoolOpOutput(TestUnpoolOp): def init_test_case(self): self.unpool2d_forward_naive = unpool2dmax_forward_naive self.unpooling_type = "max" diff --git a/python/paddle/framework/io.py b/python/paddle/framework/io.py index c1891d24b88c9de46629caacc55454dcf8c8dbf7..8e8dd7855113b1f97abb0d73c965fb623732f7b8 100644 --- a/python/paddle/framework/io.py +++ b/python/paddle/framework/io.py @@ -1039,7 +1039,7 @@ def _legacy_load(path, **configs): config) else: # load state dict by `io.save_params/persistables` save format - # TODO(chenweihang): [ Now only supports loading parameters seperately ] + # TODO(chenweihang): [ Now only supports loading parameters separately ] # If users save all parameters as one file, the [ variable.name -> variable ] # mapping info will lost, so users need to give variable list, but users build # variable list in dygraph mode is difficult, we recommend users to use diff --git a/python/paddle/hapi/model.py b/python/paddle/hapi/model.py index c17a56fc28d88dd50cdf89693ce91a262023517d..4b349a1957731b1249e98dd499ebbd6c70b2b5b6 100644 --- a/python/paddle/hapi/model.py +++ b/python/paddle/hapi/model.py @@ -915,7 +915,7 @@ class Model(object): When training on GPU, auto mixed precision (AMP O1) and pure float16 (AMP O2) training are both supported in static mode and dynamic mode. - In static graph mode, before traing with pure float16 (AMP O2), + In static graph mode, before training with pure float16 (AMP O2), `multi_precision` could be set to True when creating optimizer, which can avoid poor accuracy or slow convergence in a way, and inputs of dtype float should be cast to float16 by users. `paddle.static.amp.fp16_guard` API @@ -2075,7 +2075,7 @@ class Model(object): # [input1, input2, ..., label1, lable2, ...] # 3. custumed iterator yield concated inputs and labels: # [input1, input2, ..., label1, lable2, ...] - # 4. custumed iterator yield seperated inputs and labels: + # 4. custumed iterator yield separated inputs and labels: # ([input1, input2, ...], [label1, lable2, ...]) # To handle all of these, flatten (nested) list to list. data = flatten(data) diff --git a/python/paddle/incubate/autotune.py b/python/paddle/incubate/autotune.py index e98a23bc52d650b933556461c5266950b50a707b..7ac555e2520ea7f37d01ee65382bf99452cb65e1 100644 --- a/python/paddle/incubate/autotune.py +++ b/python/paddle/incubate/autotune.py @@ -49,7 +49,7 @@ def set_config(config=None): dictionary, the key is the tuning type, and the value is a dictionary of the corresponding tuning parameters. If it is a string, the path of a json file will be specified and the tuning configuration will be set - by the the json file. Default: None, auto-tuning for kernel, layout and + by the json file. Default: None, auto-tuning for kernel, layout and dataloader will be enabled. Examples: diff --git a/python/paddle/incubate/distributed/models/moe/grad_clip.py b/python/paddle/incubate/distributed/models/moe/grad_clip.py index b620253b9f26f4f067c716adf2080f2fc41c4da8..cf56f74d1f12d4ccf84c97b636f78d510ce4328d 100644 --- a/python/paddle/incubate/distributed/models/moe/grad_clip.py +++ b/python/paddle/incubate/distributed/models/moe/grad_clip.py @@ -158,7 +158,7 @@ class ClipGradForMOEByGlobalNorm(ClipGradBase): normal_params_grads = [] moe_params_grads = [] - # seperate moe params from normal params + # separate moe params from normal params if self.moe_group is not None and self.moe_group.nranks > 1: for p, g in params_grads: if self.is_expert_param_func(p): diff --git a/python/paddle/incubate/nn/layer/fused_transformer.py b/python/paddle/incubate/nn/layer/fused_transformer.py index d76b990958c9450603763b038cdc189a7104c126..072c7d9fccade2fd6caffa27a67a4d1ba5160f5d 100644 --- a/python/paddle/incubate/nn/layer/fused_transformer.py +++ b/python/paddle/incubate/nn/layer/fused_transformer.py @@ -101,9 +101,9 @@ class FusedMultiHeadAttention(Layer): super(FusedMultiHeadAttention, self).__init__() assert embed_dim > 0, ("Expected embed_dim to be greater than 0, " - "but recieved {}".format(embed_dim)) + "but received {}".format(embed_dim)) assert num_heads > 0, ("Expected nhead to be greater than 0, " - "but recieved {}".format(num_heads)) + "but received {}".format(num_heads)) self.normalize_before = normalize_before self._dtype = self._helper.get_default_dtype() @@ -278,10 +278,10 @@ class FusedFeedForward(Layer): super(FusedFeedForward, self).__init__() assert d_model > 0, ( - "Expected d_model to be greater than 0, but recieved {}".format( + "Expected d_model to be greater than 0, but received {}".format( d_model)) assert dim_feedforward > 0, ( - "Expected dim_feedforward to be greater than 0, but recieved {}". + "Expected dim_feedforward to be greater than 0, but received {}". format(dim_feedforward)) self._dtype = self._helper.get_default_dtype() @@ -434,12 +434,12 @@ class FusedTransformerEncoderLayer(Layer): super(FusedTransformerEncoderLayer, self).__init__() assert d_model > 0, ("Expected d_model to be greater than 0, " - "but recieved {}".format(d_model)) + "but received {}".format(d_model)) assert nhead > 0, ("Expected nhead to be greater than 0, " - "but recieved {}".format(nhead)) + "but received {}".format(nhead)) assert dim_feedforward > 0, ( "Expected dim_feedforward to be greater than 0, " - "but recieved {}".format(dim_feedforward)) + "but received {}".format(dim_feedforward)) attn_dropout_rate = dropout_rate if attn_dropout_rate is None else attn_dropout_rate act_dropout_rate = dropout_rate if act_dropout_rate is None else act_dropout_rate self.normalize_before = normalize_before @@ -808,11 +808,11 @@ class FusedMultiTransformer(Layer): super(FusedMultiTransformer, self).__init__() assert embed_dim > 0, ("Expected embed_dim to be greater than 0, " - "but recieved {}".format(embed_dim)) + "but received {}".format(embed_dim)) assert num_heads > 0, ("Expected nhead to be greater than 0, " - "but recieved {}".format(num_heads)) + "but received {}".format(num_heads)) assert dim_feedforward > 0, ( - "Expected dim_feedforward to be greater than 0, but recieved {}". + "Expected dim_feedforward to be greater than 0, but received {}". format(dim_feedforward)) self.normalize_before = normalize_before diff --git a/python/paddle/nn/functional/loss.py b/python/paddle/nn/functional/loss.py index ca3ac1772829dfa4d06870ce91a4705a706d7b26..0d5ad46a4fb5b3e6eb057976cdaf3885d7be3209 100755 --- a/python/paddle/nn/functional/loss.py +++ b/python/paddle/nn/functional/loss.py @@ -542,7 +542,7 @@ def margin_ranking_loss(input, name=None): r""" - This op the calcluate the the margin rank loss between the input, other and label, use the math function as follows. + This op the calcluate the margin rank loss between the input, other and label, use the math function as follows. .. math:: margin\_rank\_loss = max(0, -label * (input - other) + margin) @@ -879,7 +879,7 @@ def kl_div(input, label, reduction='mean', name=None): While :attr:`reduction` is :attr:`none`, output loss is in the same shape as input, loss in each point is calculated - seperately and no reduction is applied. + separately and no reduction is applied. While :attr:`reduction` is :attr:`mean`, output loss is in shape of [1] and loss value is the mean value of all losses. @@ -2006,7 +2006,7 @@ def sigmoid_focal_loss(logit, Available dtype is float32, float64. normalizer (Tensor, optional): The number normalizes the focal loss. It has to be a 1-D Tensor whose shape is `[1, ]`. The data type is float32, float64. - For object detection task, it is the the number of positive samples. + For object detection task, it is the number of positive samples. If set to None, the focal loss will not be normalized. Default is None. alpha(int|float, optional): Hyper-parameter to balance the positive and negative example, it should be between 0 and 1. Default value is set to 0.25. diff --git a/python/paddle/nn/layer/activation.py b/python/paddle/nn/layer/activation.py index cd82fe12fff6b1b1640f21d71aaeaedc61c2738a..7fd109843bede238a8bac59d8b88a514aa2638ed 100644 --- a/python/paddle/nn/layer/activation.py +++ b/python/paddle/nn/layer/activation.py @@ -367,7 +367,7 @@ class PReLU(Layer): Parameters: num_parameters (int, optional): Number of `weight` to learn. The supported values are: 1 - a single parameter `alpha` is used for all input channels; - Number of channels - a seperate `alpha` is used for each input channel. + Number of channels - a separate `alpha` is used for each input channel. Default is 1. init (float, optional): Init value of learnable `weight`. Default is 0.25. weight_attr(ParamAttr, optional): The parameter attribute for the learnable `weight`. diff --git a/python/paddle/nn/layer/transformer.py b/python/paddle/nn/layer/transformer.py index b0b6e62a602aaeadd1d60c23e2bc280d5b88cc96..340372f9b6a4e5b05ef1e36a462daa62fb50870a 100644 --- a/python/paddle/nn/layer/transformer.py +++ b/python/paddle/nn/layer/transformer.py @@ -163,9 +163,9 @@ class MultiHeadAttention(Layer): super(MultiHeadAttention, self).__init__() assert embed_dim > 0, ("Expected embed_dim to be greater than 0, " - "but recieved {}".format(embed_dim)) + "but received {}".format(embed_dim)) assert num_heads > 0, ("Expected num_heads to be greater than 0, " - "but recieved {}".format(num_heads)) + "but received {}".format(num_heads)) self.embed_dim = embed_dim self.kdim = kdim if kdim is not None else embed_dim @@ -508,12 +508,12 @@ class TransformerEncoderLayer(Layer): super(TransformerEncoderLayer, self).__init__() assert d_model > 0, ("Expected d_model to be greater than 0, " - "but recieved {}".format(d_model)) + "but received {}".format(d_model)) assert nhead > 0, ("Expected nhead to be greater than 0, " - "but recieved {}".format(nhead)) + "but received {}".format(nhead)) assert dim_feedforward > 0, ( "Expected dim_feedforward to be greater than 0, " - "but recieved {}".format(dim_feedforward)) + "but received {}".format(dim_feedforward)) attn_dropout = dropout if attn_dropout is None else attn_dropout act_dropout = dropout if act_dropout is None else act_dropout @@ -813,12 +813,12 @@ class TransformerDecoderLayer(Layer): super(TransformerDecoderLayer, self).__init__() assert d_model > 0, ("Expected d_model to be greater than 0, " - "but recieved {}".format(d_model)) + "but received {}".format(d_model)) assert nhead > 0, ("Expected nhead to be greater than 0, " - "but recieved {}".format(nhead)) + "but received {}".format(nhead)) assert dim_feedforward > 0, ( "Expected dim_feedforward to be greater than 0, " - "but recieved {}".format(dim_feedforward)) + "but received {}".format(dim_feedforward)) attn_dropout = dropout if attn_dropout is None else attn_dropout act_dropout = dropout if act_dropout is None else act_dropout @@ -1220,12 +1220,12 @@ class Transformer(Layer): super(Transformer, self).__init__() assert d_model > 0, ("Expected d_model to be greater than 0, " - "but recieved {}".format(d_model)) + "but received {}".format(d_model)) assert nhead > 0, ("Expected nhead to be greater than 0, " - "but recieved {}".format(nhead)) + "but received {}".format(nhead)) assert dim_feedforward > 0, ( "Expected dim_feedforward to be greater than 0, " - "but recieved {}".format(dim_feedforward)) + "but received {}".format(dim_feedforward)) if isinstance(bias_attr, (list, tuple)): if len(bias_attr) == 1: diff --git a/python/paddle/profiler/profiler.py b/python/paddle/profiler/profiler.py index 77adbaff34859cd983af90273e8404a9f8ed22fa..9df595bc3ae73653407ac1ea664ec9ce7e6e18d3 100644 --- a/python/paddle/profiler/profiler.py +++ b/python/paddle/profiler/profiler.py @@ -150,7 +150,7 @@ def make_scheduler(*, def _default_state_scheduler(step: int): r""" - A default state scheduler, keep recording from the begining of the profiler until ending. + A default state scheduler, keep recording from the beginning of the profiler until ending. """ return ProfilerState.RECORD diff --git a/python/paddle/profiler/timer.py b/python/paddle/profiler/timer.py index 1fb06ddc55e392a97499f72cbd0a2a365dd8b65e..815775ebc6aadc51a549adb6648e28fe5e5c3773 100644 --- a/python/paddle/profiler/timer.py +++ b/python/paddle/profiler/timer.py @@ -193,7 +193,7 @@ class TimerHook(Hook): def before_reader(self, benchmark): """ Initialize the start time of the dataloader. This function will be - called at the begining of `next` method in `_DataLoaderIterMultiProcess` or + called at the beginning of `next` method in `_DataLoaderIterMultiProcess` or `_DataLoaderIterSingleProcess`. """ @@ -220,8 +220,8 @@ class TimerHook(Hook): Record the cost for the current step. It will contain the cost of the loading data if there is a dataloader. Similar to `after_reader`, it will also update the maximum, minimum and the total time from the step 11 to the current step - as well as the the maximum and minimum speed of the model. This function will - be called in in `Profiler.step()`. + as well as the maximum and minimum speed of the model. This function will + be called in `Profiler.step()`. """ @@ -401,7 +401,7 @@ class Benchmark(object): # enter a new task but not calling beign() to record it. # we pause the timer until the end of new task, so that # the cost of new task is not added to the current event. - # eg. start evaluation in the traing task + # eg. start evaluation in the training task self.current_event.need_record = False else: # when the new task exits, continue timing for the current event. diff --git a/python/paddle/profiler/utils.py b/python/paddle/profiler/utils.py index fd75ab9550d52790e78e3abc7349d3b6b8be8da8..5e95c83129f53d6e275ac17bea0dc93db1bf124c 100644 --- a/python/paddle/profiler/utils.py +++ b/python/paddle/profiler/utils.py @@ -78,7 +78,7 @@ class RecordEvent(ContextDecorator): def begin(self): r""" - Record the time of begining. + Record the time of beginning. Examples: diff --git a/python/paddle/tensor/math.py b/python/paddle/tensor/math.py index 5ee372f7b956a2c05ebf3a352701b5966b327201..7cfae842337c642d9777cea50e87ac115652379e 100644 --- a/python/paddle/tensor/math.py +++ b/python/paddle/tensor/math.py @@ -3346,7 +3346,7 @@ def increment(x, value=1.0, name=None): def all(x, axis=None, keepdim=False, name=None): """ - Computes the the ``logical and`` of tensor elements over the given dimension. + Computes the ``logical and`` of tensor elements over the given dimension. Args: x (Tensor): An N-D Tensor, the input data type should be `bool`. @@ -3442,7 +3442,7 @@ def all(x, axis=None, keepdim=False, name=None): def any(x, axis=None, keepdim=False, name=None): """ - Computes the the ``logical or`` of tensor elements over the given dimension. + Computes the ``logical or`` of tensor elements over the given dimension. Args: x (Tensor): An N-D Tensor, the input data type should be `bool`. diff --git a/python/paddle/tensor/to_string.py b/python/paddle/tensor/to_string.py index 71c97d4cac986b42f5635778cb55e34df441375a..42d3bf9fca36410974be79d158d82c830da98b49 100644 --- a/python/paddle/tensor/to_string.py +++ b/python/paddle/tensor/to_string.py @@ -42,7 +42,7 @@ def set_printoptions(precision=None, Args: precision (int, optional): Number of digits of the floating number, default 8. threshold (int, optional): Total number of elements printed, default 1000. - edgeitems (int, optional): Number of elements in summary at the begining and ending of each dimension, default 3. + edgeitems (int, optional): Number of elements in summary at the beginning and ending of each dimension, default 3. sci_mode (bool, optional): Format the floating number with scientific notation or not, default False. linewidth (int, optional): Number of characters each line, default 80. diff --git a/python/paddle/vision/models/mobilenetv3.py b/python/paddle/vision/models/mobilenetv3.py index da7ae010c58f6babbe5a949c642cdbcace4e951c..70aa1b833d6483ce65ae45d0a15741aa3c163b6e 100644 --- a/python/paddle/vision/models/mobilenetv3.py +++ b/python/paddle/vision/models/mobilenetv3.py @@ -39,7 +39,7 @@ model_urls = { class SqueezeExcitation(nn.Layer): """ This block implements the Squeeze-and-Excitation block from https://arxiv.org/abs/1709.01507 (see Fig. 1). - Parameters ``activation``, and ``scale_activation`` correspond to ``delta`` and ``sigma`` in in eq. 3. + Parameters ``activation``, and ``scale_activation`` correspond to ``delta`` and ``sigma`` in eq. 3. This code is based on the torchvision code with modifications. You can also see at https://github.com/pytorch/vision/blob/main/torchvision/ops/misc.py#L127 Args: