Fix precison precision (#60940)

co63oc · web-flow · commit 23f9ff2b6e21 · 2024-01-19T10:20:08.000+08:00
diff --git a/paddle/fluid/inference/analysis/analyzer.cc b/paddle/fluid/inference/analysis/analyzer.cc
@@ -31,15 +31,15 @@ void Analyzer::RunAnalysis(Argument *argument) {
   PADDLE_ENFORCE_EQ(argument->analysis_passes_valid(),
                     true,
                     platform::errors::InvalidArgument(
-                        "analsis_passes is not valid in the argument."));
+                        "analysis_passes is not valid in the argument."));
   const bool disable_logs = argument->disable_logs();
   for (auto &pass : argument->analysis_passes()) {
     if (!disable_logs) {
       string::PrettyLogH1("--- Running analysis [%s]", pass);
     }
     if (!argument->enable_ir_optim() && pass == "ir_analysis_pass") continue;
 
-    auto *ptr = PassRegistry::Global().Retreive(pass);
+    auto *ptr = PassRegistry::Global().Retrieve(pass);
     PADDLE_ENFORCE_NOT_NULL(ptr,
                             platform::errors::PreconditionNotMet(
                                 "no analysis pass called %s", pass));
diff --git a/paddle/fluid/inference/analysis/ir_passes/dlnne_subgraph_pass.cc b/paddle/fluid/inference/analysis/ir_passes/dlnne_subgraph_pass.cc
@@ -81,7 +81,7 @@ void analysis::DlnneSubgraphPass::InferShapeForDlnneMainGraph() const {
   std::vector<framework::OpDesc *> all_ops = block->AllOps();
 
   for (size_t i = 0; i < block->OpSize(); i++) {
-    // the output_shape of bilinear_interp_v2 cannot be inferd by input shape,
+    // the output_shape of bilinear_interp_v2 cannot be inferred by input shape,
     // it also need the value of input tensor, so when call OpDesc->InferShape,
     // the output_shape of bilinear_interp_v2 is still dynamic, here we try to
     // infer the output_shape of bilinear_interp_v2 infer shape for
diff --git a/paddle/fluid/inference/analysis/ir_passes/tensorrt_subgraph_pass.cc b/paddle/fluid/inference/analysis/ir_passes/tensorrt_subgraph_pass.cc
@@ -142,7 +142,7 @@ void analysis::TensorRtSubgraphPass::ApplyImpl(
       static_cast<phi::DataType>(Get<int>("model_precision"));
   if (model_precision == phi::DataType::BFLOAT16) {
     LOG(WARNING)
-        << "Paddle-TRT not support bf16 mixed precison, just fallback.";
+        << "Paddle-TRT not support bf16 mixed precision, just fallback.";
     return;
   }
 
@@ -233,7 +233,7 @@ void analysis::TensorRtSubgraphPass::ApplyImpl(
               .Has(name),
           true,
           platform::errors::PreconditionNotMet(
-              "TRTEnegineManager shoud has engine %s, but not found.", name));
+              "TRTEngineManager should has engine %s, but not found.", name));
       paddle::inference::Singleton<
           inference::tensorrt::TRTEngineManager>::Global()
           .Get(name)
@@ -844,7 +844,7 @@ std::string TensorRtSubgraphPass::CreateTensorRTOp(
             << GetTrtEngineSerializedPath(
                    Get<std::string>("model_opt_cache_dir"), engine_key)
             << ". Engine deserialization failed: Serialized Engine Version "
-               "does not match Current Version, TRT engine will be rebuilded";
+               "does not match Current Version, TRT engine will be rebuilt";
       }
     }
   }
@@ -856,7 +856,7 @@ std::string TensorRtSubgraphPass::CreateTensorRTOp(
   }
 
   // the following code will NOT run in following situation:
-  // 1. calibraion mode (generate trt int8 calibraiton table data)
+  // 1. calibration mode (generate trt int8 calibration table data)
   // 2. already load serialized trt engine info.
   LOG(INFO) << "Prepare TRT engine (Optimize model structure, Select OP "
                "kernel etc). This process may cost a lot of time.";
diff --git a/paddle/fluid/inference/analysis/passes/inference_op_replace_pass.h b/paddle/fluid/inference/analysis/passes/inference_op_replace_pass.h
@@ -28,7 +28,7 @@ namespace analysis {
 
 /*
  * There are some ops (while, conditional_block_op etc) which have different
- * optimization points under predicion and training conditions.
+ * optimization points under prediction and training conditions.
  * So, We added the corresponding inference impl to these ops separately.
  * This pass replaces these ops with corresponding inference ops.
  */
diff --git a/paddle/fluid/inference/analysis/passes/memory_optimize_pass.cc b/paddle/fluid/inference/analysis/passes/memory_optimize_pass.cc
@@ -156,7 +156,7 @@ void MemoryOptimizePass::CollectVarMemorySize(
     return true;
   };
 
-  // MemoryOptimizePass surppose input model is directed acyclic graph
+  // MemoryOptimizePass suppose input model is directed acyclic graph
   // although it's not always the case. so black list is the best compromise
   // between performance and underlying principle.
   std::unordered_set<std::string> black_list;
diff --git a/paddle/fluid/inference/analysis/passes/passes.h b/paddle/fluid/inference/analysis/passes/passes.h
@@ -27,7 +27,7 @@ namespace analysis {
 struct PassRegistry {
   PassRegistry();
 
-  AnalysisPass* Retreive(const std::string& pass_type) {
+  AnalysisPass* Retrieve(const std::string& pass_type) {
     return passes_[pass_type].get();
   }
 
diff --git a/paddle/fluid/inference/api/analysis_config.cc b/paddle/fluid/inference/api/analysis_config.cc
@@ -816,7 +816,7 @@ void AnalysisConfig::EnableDlnne(
     int max_batch_size,
     bool use_static_batch,
     std::string weight_share_mode,
-    std::unordered_set<std::string> disable_nodes_by_ouputs,
+    std::unordered_set<std::string> disable_nodes_by_outputs,
     std::map<std::string, std::vector<int64_t>> dlnne_input_shape_dict,
     bool use_calib_mode,
     Precision precision_mode) {
@@ -825,7 +825,7 @@ void AnalysisConfig::EnableDlnne(
   dlnne_max_batchsize_ = max_batch_size;
   dlnne_use_static_batch_ = use_static_batch;
   dlnne_weight_share_mode_ = weight_share_mode;
-  dlnne_disable_nodes_by_outputs_ = disable_nodes_by_ouputs;
+  dlnne_disable_nodes_by_outputs_ = disable_nodes_by_outputs;
   dlnne_input_shape_dict_ = dlnne_input_shape_dict;
   dlnne_use_calib_mode_ = use_calib_mode;
   dlnne_precision_mode_ = precision_mode;
diff --git a/paddle/fluid/inference/api/analysis_predictor.cc b/paddle/fluid/inference/api/analysis_predictor.cc
@@ -1818,7 +1818,7 @@ void AnalysisPredictor::PrepareArgument() {
   argument_->SetAnalysisPasses(pass_builder->AnalysisPasses());
   argument_->SetScopeNotOwned(scope_.get());
 
-  // mixed precison.
+  // mixed precision.
   argument_->SetModelPrecision(static_cast<int>(model_precision_));
   argument_->SetMixedBlackList(config_.mixed_black_list_);
   argument_->SetMixedWhiteList(config_.mixed_white_list_);
diff --git a/paddle/fluid/inference/api/analysis_predictor.h b/paddle/fluid/inference/api/analysis_predictor.h
@@ -171,7 +171,7 @@ class AnalysisPredictor : public PaddlePredictor {
   ///
   /// \brief Get the Output Tensor object
   ///
-  /// \param[in] name otuput name
+  /// \param[in] name output name
   /// \return output tensor
   ///
   std::unique_ptr<ZeroCopyTensor> GetOutputTensor(
@@ -379,7 +379,7 @@ class AnalysisPredictor : public PaddlePredictor {
   ///
   /// \brief Prepare input data, only used in Run()
   ///
-  /// \param[in] input_datas inpute tensors
+  /// \param[in] input_datas input tensors
   /// \param[in] scope the scope used by predictor
   /// \return Whether the function executed successfully
   ///
@@ -389,7 +389,7 @@ class AnalysisPredictor : public PaddlePredictor {
   ///
   /// \brief Prepare input data, only used in Run()
   ///
-  /// \param[in] inputs inpute tensors
+  /// \param[in] inputs input tensors
   /// \param[in] scope the scope used by predictor
   /// \return Whether the function executed successfully
   ///
diff --git a/paddle/fluid/inference/api/helper.h b/paddle/fluid/inference/api/helper.h
@@ -474,14 +474,14 @@ static inline void DisplayMemoryInfo(platform::Place place,
       << "MB]";
 }
 
-static std::string Precision2String(AnalysisConfig::Precision precison) {
-  if (precison == AnalysisConfig::Precision::kFloat32)
+static std::string Precision2String(AnalysisConfig::Precision precision) {
+  if (precision == AnalysisConfig::Precision::kFloat32)
     return "fp32";
-  else if (precison == AnalysisConfig::Precision::kHalf)
+  else if (precision == AnalysisConfig::Precision::kHalf)
     return "fp16";
-  else if (precison == AnalysisConfig::Precision::kInt8)
+  else if (precision == AnalysisConfig::Precision::kInt8)
     return "int8";
-  else if (precison == AnalysisConfig::Precision::kBf16)
+  else if (precision == AnalysisConfig::Precision::kBf16)
     return "bf16";
   else
     return "none";

Original file line number	Diff line number	Diff line change
`@@ -27,7 +27,7 @@ namespace analysis {`
`27`	`27`	`struct PassRegistry {`
`28`	`28`	`PassRegistry();`
`29`	`29`
`30`		`- AnalysisPass* Retreive(const std::string& pass_type) {`
	`30`	`+ AnalysisPass* Retrieve(const std::string& pass_type) {`
`31`	`31`	`return passes_[pass_type].get();`
`32`	`32`	`}`
`33`	`33`