Fix usless useless, etc (#62323)

paddle/fluid/inference/CMakeLists.txt

@@ -93,7 +93,7 @@ set(SHARED_INFERENCE_SRCS
     ${CMAKE_CURRENT_SOURCE_DIR}/api/details/zero_copy_tensor.cc
     ${CMAKE_CURRENT_SOURCE_DIR}/utils/io_utils.cc)
 
-# NOTE(Aurelius84): For inference library, some DEPS is usless
+# NOTE(Aurelius84): For inference library, some DEPS is useless
 # such as non-infer operator related targets et.al.
 list(REMOVE_ITEM fluid_modules cinn_op_dialect)
 # NOTE(Aurelisu84): Remove pir dialect related target DEPS for inference

paddle/fluid/inference/tensorrt/convert/set_value_op.cc

@@ -25,7 +25,7 @@ limitations under the License. */
         PADDLE_ENFORCE_EQ(vec_##attr_name__.size(),                        \
                           1UL,                                             \
                           platform::errors::InvalidArgument(               \
-                              "attr axes/starst/ends/steps 's size in "    \
+                              "attr axes/starts/ends/steps 's size in "    \
                               "set_value must be one, but got %d",         \
                               vec_##attr_name__.size()));                  \
       }                                                                    \

paddle/fluid/inference/tensorrt/dynamic_shape_infermeta.cc

@@ -259,7 +259,7 @@ inline const nvinfer1::IDimensionExpr* CalcOutputSize(
   return output_size;
 }
 
-nvinfer1::DimsExprs UnflodInferMeta(
+nvinfer1::DimsExprs UnfoldInferMeta(
     int output_index,
     const nvinfer1::DimsExprs* inputs,
     int nb_inputs,
@@ -879,7 +879,7 @@ nvinfer1::DimsExprs SolveInferMeta(
 PD_REGISTER_DYNAMIC_INFER_META_FN(gather_nd, GatherNdInferMeta);
 PD_REGISTER_DYNAMIC_INFER_META_FN(yolo_box, YoloBoxInferMeta);
 PD_REGISTER_DYNAMIC_INFER_META_FN(instance_norm, InstanceNormInferMeta);
-PD_REGISTER_DYNAMIC_INFER_META_FN(unfold, UnflodInferMeta);
+PD_REGISTER_DYNAMIC_INFER_META_FN(unfold, UnfoldInferMeta);
 PD_REGISTER_DYNAMIC_INFER_META_FN(scatter_nd_add, ScatterNdAddInferMeta);
 PD_REGISTER_DYNAMIC_INFER_META_FN(inverse, UnchangedInferMeta);
 PD_REGISTER_DYNAMIC_INFER_META_FN(moe, MoeInferMeta);

paddle/fluid/inference/tensorrt/engine.cc

@@ -52,7 +52,7 @@ void TensorRTEngine::Weight::SetDataType(phi::DataType type) {
 #endif
     default:
       paddle::platform::errors::InvalidArgument(
-          "Paddle-TRT loads weighths failed, found not supported data type %s.",
+          "Paddle-TRT loads weights failed, found not supported data type %s.",
           type);
       break;
   }

paddle/fluid/inference/tensorrt/op_teller.cc

@@ -1460,7 +1460,7 @@ struct SimpleOpTypeSetTeller : public Teller {
       }
       if (desc.Output("Out").size() != 1) {
         VLOG(3) << "The input op's Output(\"Out\").size() "
-                   "should equal to 1, but reveceid Output(\"Out\").size() = "
+                   "should equal to 1, but received Output(\"Out\").size() = "
                 << desc.Output("Out").size() << ".";
         return false;
       }
@@ -2080,29 +2080,31 @@ struct SimpleOpTypeSetTeller : public Teller {
       auto inputs = desc.Inputs();
       bool has_bias_qk = (inputs.find("BiasQK") == inputs.end()) ? false : true;
       if (has_bias_qk) {
-        auto* biasqk_desc =
+        auto* bias_qk_desc =
             block->FindVarRecursive(desc.Input("BiasQK").front());
-        const auto biasqk_shape = biasqk_desc->GetShape();
+        const auto bias_qk_shape = bias_qk_desc->GetShape();
         // The BiasQK's shape requires to be
         // [batch, 1, 1, length] or [batch, head, length, length].
-        bool has_same_shape = head_number == biasqk_shape[1] &&
-                              input_shape[1] == biasqk_shape[2] &&
-                              input_shape[1] == biasqk_shape[3];
-        bool is_broadcastable = biasqk_shape[1] == 1 && biasqk_shape[2] == 1 &&
-                                input_shape[1] == biasqk_shape[3];
-        is_broadcastable =
-            is_broadcastable || (biasqk_shape[0] == 1 && biasqk_shape[1] == 1 &&
-                                 input_shape[1] == biasqk_shape[2] &&
-                                 input_shape[1] == biasqk_shape[3]);
+        bool has_same_shape = head_number == bias_qk_shape[1] &&
+                              input_shape[1] == bias_qk_shape[2] &&
+                              input_shape[1] == bias_qk_shape[3];
+        bool is_broadcastable = bias_qk_shape[1] == 1 &&
+                                bias_qk_shape[2] == 1 &&
+                                input_shape[1] == bias_qk_shape[3];
+        is_broadcastable = is_broadcastable ||
+                           (bias_qk_shape[0] == 1 && bias_qk_shape[1] == 1 &&
+                            input_shape[1] == bias_qk_shape[2] &&
+                            input_shape[1] == bias_qk_shape[3]);
         if (!(has_same_shape || is_broadcastable)) {
           VLOG(3) << "The BiasQK's shape is invalid, expect [" << input_shape[0]
                   << ", 1, 1, " << input_shape[1] << "] "
                   << "or [" << input_shape[0] << ", " << head_number << ", "
                   << input_shape[1] << ", " << input_shape[1] << "] "
                   << "or [" << input_shape[0] << "/1, " << 1 << ", "
                   << input_shape[1] << ", " << input_shape[1] << "] "
-                  << "but got [" << biasqk_shape[0] << ", " << biasqk_shape[1]
-                  << ", " << biasqk_shape[2] << ", " << biasqk_shape[3] << "].";
+                  << "but got [" << bias_qk_shape[0] << ", " << bias_qk_shape[1]
+                  << ", " << bias_qk_shape[2] << ", " << bias_qk_shape[3]
+                  << "].";
           return false;
         }
       } else {
@@ -2140,23 +2142,24 @@ struct SimpleOpTypeSetTeller : public Teller {
       auto inputs = desc.Inputs();
       bool has_bias_qk = (inputs.find("BiasQK") == inputs.end()) ? false : true;
       if (has_bias_qk) {
-        auto* biasqk_desc =
+        auto* bias_qk_desc =
             block->FindVarRecursive(desc.Input("BiasQK").front());
-        const auto biasqk_shape = biasqk_desc->GetShape();
+        const auto bias_qk_shape = bias_qk_desc->GetShape();
         // The BiasQK's shape requires to be
         // [batch, 1, 1, length] or [batch, head, length, length].
-        bool has_same_shape = head_number == biasqk_shape[1] &&
-                              input_shape[1] == biasqk_shape[2] &&
-                              input_shape[1] == biasqk_shape[3];
-        bool is_broadcastable = biasqk_shape[1] == 1 && biasqk_shape[2] == 1 &&
-                                input_shape[1] == biasqk_shape[3];
+        bool has_same_shape = head_number == bias_qk_shape[1] &&
+                              input_shape[1] == bias_qk_shape[2] &&
+                              input_shape[1] == bias_qk_shape[3];
+        bool is_broadcastable = bias_qk_shape[1] == 1 &&
+                                bias_qk_shape[2] == 1 &&
+                                input_shape[1] == bias_qk_shape[3];
         if (!(has_same_shape || is_broadcastable)) {
           VLOG(3) << "The BiasQK's shape is invalid, expect [" << input_shape[0]
                   << ", 1, 1, " << input_shape[1] << "] or [" << input_shape[0]
                   << ", " << head_number << ", " << input_shape[1] << ", "
-                  << input_shape[1] << "] but [" << biasqk_shape[0] << ", "
-                  << biasqk_shape[1] << ", " << biasqk_shape[2] << ", "
-                  << biasqk_shape[3] << "].";
+                  << input_shape[1] << "] but [" << bias_qk_shape[0] << ", "
+                  << bias_qk_shape[1] << ", " << bias_qk_shape[2] << ", "
+                  << bias_qk_shape[3] << "].";
           return false;
         }
       } else {

paddle/fluid/inference/tensorrt/op_teller.h

@@ -34,7 +34,7 @@ namespace tensorrt {
 
 /*
  * Single Op teller definition.
- * One can override this and define a more complex tell logic, considerring more
+ * One can override this and define a more complex tell logic, considering more
  * issues such as op_desc.
  */
 struct Teller {

paddle/fluid/inference/tensorrt/plugin_arg_mapping_context.cc

@@ -76,7 +76,7 @@ paddle::any PluginArgumentMappingContext::Attr(
       break;
     };
     default: {
-      LOG(ERROR) << "Can't conver op's attribute [" << attr_name
+      LOG(ERROR) << "Can't cover op's attribute [" << attr_name
                  << "] to paddle any.";
     }
   }

paddle/fluid/inference/tensorrt/test_arg_mapping_context.cc

@@ -21,7 +21,7 @@ namespace paddle {
 namespace inference {
 namespace tensorrt {
 
-TEST(ArgMappingContexTest, BasicFunction) {
+TEST(ArgMappingContextTest, BasicFunction) {
   paddle::framework::proto::OpDesc op;
   op.set_type("imaged_op");
   auto *input_var = op.add_inputs();
@@ -86,8 +86,8 @@ TEST(ArgMappingContexTest, BasicFunction) {
   int int_attr = any_cast<int>(context.Attr("int_attr"));
   EXPECT_EQ(int_attr, 1);
 
-  float flaot_attr = any_cast<float>(context.Attr("float_attr"));
-  EXPECT_EQ(flaot_attr, 1);
+  float float_attr = any_cast<float>(context.Attr("float_attr"));
+  EXPECT_EQ(float_attr, 1);
 
   std::string string_attr = any_cast<std::string>(context.Attr("string_attr"));
   EXPECT_EQ(string_attr, "1");

paddle/fluid/inference/tensorrt/trt_int8_calibrator.h

@@ -87,7 +87,7 @@ class TRTCalibratorEngine {
   std::unique_ptr<TensorRTEngine> engine_;
 };
 /*
- * Manager to control the TensorRT Int8 calibration creation and deltetion.
+ * Manager to control the TensorRT Int8 calibration creation and deletion.
  */
 class TRTCalibratorEngineManager {
  public:

paddle/fluid/inference/utils/shape_range_info.proto

@@ -16,7 +16,7 @@ syntax = "proto2";
 package paddle.inference.proto;
 
 // To support trt dynamic shape, record the runtime shape
-// information of all tmp tensors in the Compution graph.
+// information of all tmp tensors in the Computation graph.
 message ShapeRangeInfos {
   message ShapeRangeInfo {
     required string name = 1;

paddle/fluid/inference/utils/table_printer.cc

@@ -57,18 +57,18 @@ std::string TablePrinter::PrintTable() {
 }
 
 TablePrinter::TablePrinter(const std::vector<std::string>& header) {
-  size_t terminal_witdh = 500;
+  size_t terminal_width = 500;
 #ifdef _WIN32
   CONSOLE_SCREEN_BUFFER_INFO csbi;
   int ret = GetConsoleScreenBufferInfo(GetStdHandle(STD_OUTPUT_HANDLE), &csbi);
   if (ret && (csbi.dwSize.X != 0)) {
-    terminal_witdh = csbi.dwSize.X;
+    terminal_width = csbi.dwSize.X;
   }
 #else
   struct winsize terminal_size;
   int status = ioctl(STDOUT_FILENO, TIOCGWINSZ, &terminal_size);
   if (status == 0 && terminal_size.ws_col != 0) {
-    terminal_witdh = terminal_size.ws_col;
+    terminal_width = terminal_size.ws_col;
   }
 #endif
 
@@ -77,8 +77,8 @@ TablePrinter::TablePrinter(const std::vector<std::string>& header) {
     widths_.emplace_back(0);
   }
 
-  terminal_witdh = terminal_witdh - (2 * num_cols) - (num_cols + 1);
-  int avg_width = static_cast<int>(terminal_witdh / num_cols);  // NOLINT
+  terminal_width = terminal_width - (2 * num_cols) - (num_cols + 1);
+  int avg_width = static_cast<int>(terminal_width / num_cols);  // NOLINT
 
   for (size_t i = 0; i < num_cols; ++i) {
     shares_.emplace_back(avg_width);

paddle/fluid/ir_adaptor/translator/op_compat_gen.py

@@ -48,7 +48,7 @@ def to_phi_and_fluid_op_name(op_item):
         op_compat_infos = yaml.safe_load(f)
     op_name_mappings: Dict[str, str] = {}
     op_arg_name_mappings: Dict[str, Dict[str, str]] = {}
-    op_mutable_attribues: Dict[str, Set[str]] = {}
+    op_mutable_attributes: Dict[str, Set[str]] = {}
     op_mutable_attribute_infos: Dict[str, Dict[str, List[str]]] = {}
 
     for op_compat_item in op_compat_infos:
@@ -70,15 +70,15 @@ def insert_new_arg_mappings(op_name: str, arg_mapping: Dict[str, str]):
         def insert_new_mutable_attributes(
             op_name: str, mutable_attribute_infos: Dict[str, Dict[str, str]]
         ):
-            if op_name not in op_mutable_attribues:
-                op_mutable_attribues[op_name] = set()
+            if op_name not in op_mutable_attributes:
+                op_mutable_attributes[op_name] = set()
             if op_name not in op_mutable_attribute_infos:
                 op_mutable_attribute_infos[op_name] = {}
             for (
                 attribute_name,
                 mutable_attribute_info,
             ) in mutable_attribute_infos.items():
-                op_mutable_attribues[op_name].add(attribute_name)
+                op_mutable_attributes[op_name].add(attribute_name)
                 op_mutable_attribute_infos[op_name][attribute_name] = []
                 for k, v in mutable_attribute_info.items():
                     if k == 'tensor_name' or k == 'tensors_name':
@@ -168,12 +168,12 @@ def insert_new_mutable_attributes(
         {"out_grad_in": "Out@GRAD", "out_grad_out": "Out@GRAD"}
     )
 
-    op_name_normailzer_template = env.get_template("op_compat_info.cc.j2")
+    op_name_normalizer_template = env.get_template("op_compat_info.cc.j2")
     with open(output_source_file, 'wt') as f:
-        op_compat_definition = op_name_normailzer_template.render(
+        op_compat_definition = op_name_normalizer_template.render(
             op_name_pairs=op_name_mappings,
             op_arg_name_pairs=op_arg_name_mappings,
-            op_mutable_attributes=op_mutable_attribues,
+            op_mutable_attributes=op_mutable_attributes,
             op_mutable_attribute_infos=op_mutable_attribute_infos,
         )
         f.write(op_compat_definition)
@@ -184,7 +184,7 @@ def insert_new_mutable_attributes(
 # =====================================
 def ParseArguments():
     parser = argparse.ArgumentParser(
-        description='Generate OP Compatiable info Files By Yaml'
+        description='Generate OP Compatible info Files By Yaml'
     )
     parser.add_argument('--op_compat_yaml_file', type=str)
     parser.add_argument('--output_source_file', type=str)