[CodeStyle][Typos][I-[12-14],I-[16-20]] Fix typos (indiates,indeces,inferrence,infering,imformation,infomation,informations,Infor,infor,inheritted,initilization)

_typos.toml

@@ -12,6 +12,13 @@ extend-exclude = [
 [default]
 # Ignore 1-3 letter words, refer to https://github.com/crate-ci/typos/issues/1079
 extend-ignore-words-re = ["^[a-zA-Z]{1,3}$"]
+# refer to https://github.com/crate-ci/typos/blob/master/docs/reference.md#example-configurations
+extend-ignore-re = [
+    # Ignore lines by `# typos: disable-line`
+    "(?Rm)^.*(#|//)\\s*typos:\\s*disable-line$",
+    # Ignore block by `# typos: off` and `# typos: on`
+    "(?s)(#|//)\\s*typos:\\s*off.*?\\n\\s*(#|//)\\s*typos:\\s*on"
+]
 
 [default.extend-words]
 # PaddlePaddle specific words
@@ -69,19 +76,8 @@ fron = 'fron'
 fullfill = 'fullfill'
 Indexs = 'Indexs'
 indexs = 'indexs'
-indiates = 'indiates'
-indeces = 'indeces'
-inferrence = 'inferrence'
 Infered = 'Infered'
 infered = 'infered'
-infering = 'infering'
-informations = 'informations'
-imformation = 'imformation'
-infomation = 'infomation'
-Infor = 'Infor'
-infor = 'infor'
-inheritted = 'inheritted'
-initilization = 'initilization'
 initilized = 'initilized'
 initalized = 'initalized'
 initalize = 'initalize'

paddle/cinn/hlir/dialect/operator/transforms/lowering_pass/utils.cc

@@ -117,7 +117,7 @@ OpLoweringGroupPtr BuildOpLoweringGroup(pir::Operation* fusion_op_ptr) {
   if (FLAGS_cinn_enable_map_expr) {
     cinn::adt::TryGenerateMapExprFromGroup(group);
   }
-  // Rebuild other informations
+  // Rebuild other information
   // TODO(zhangyuqin1998): Do we need group.master_ops?
   return group;
 }

paddle/cinn/hlir/framework/pir/utils.cc

@@ -95,7 +95,7 @@ std::string GetDebugInfo(const std::unordered_set<std::string>& names) {
   return debug_info;
 }
 
-// OpTransInfo contains informations used to detect subgraphs
+// OpTransInfo contains information used to detect subgraphs
 // supported by the CINN compiler.
 class OpTransInfo {
   using DeParamCondT =

paddle/cinn/ir/ir.h

@@ -848,7 +848,7 @@ struct ForBase {
   BindInfo bind_info_;
 };
 
-/// LLVM loop unroll metadata infomation
+/// LLVM loop unroll metadata information
 struct LLVMForLoopMeta {
   enum UnrollMode { DefaultUnroll, FullyUnroll, NoUnroll };
 

paddle/cinn/poly/stage.h

@@ -57,7 +57,7 @@ struct StageForloopInfo {
   ir::DeviceAPI device;
 };
 
-//! Store the informations about some other tensor `compute_at` this tensor.
+//! Store the information about some other tensor `compute_at` this tensor.
 struct ComputeAtInfo {
   ComputeAtInfo(const std::string& consumer_tensor_name,
                 const std::string& producer_tensor_name,
@@ -84,7 +84,7 @@ struct ComputeAtInfo {
 };
 
 /**
- * Meta infomation for tensor.
+ * Meta information for tensor.
  */
 struct TensorScheduleMeta {
   //! Store the information of all the other producer tensors `compute_at` this

paddle/fluid/distributed/ps/service/brpc_utils.cc

@@ -321,7 +321,7 @@ std::string GetIntTypeEndpoint(const std::string& ip, const uint32_t& port) {
 
   if (nullptr == hp) {
     LOG(ERROR) << "Brpc Start failed, ip_port= " << ip_port
-               << " , Error infomation: " << hstrerror(h_errno);
+               << " , Error information: " << hstrerror(h_errno);
   }
 
   int i = 0;

paddle/fluid/eager/api/generated/eager_generated/backwards/scale_node.h

@@ -18,7 +18,7 @@
 #include "paddle/fluid/eager/tensor_wrapper.h"
 
 /*
-    Each Operation has a specific GradNode inheritted from GradNodeBase
+    Each Operation has a specific GradNode inherited from GradNodeBase
     A specific GradNode defines
     1. Input Tensors
     2. overrides operator() to perform actual backward computations

paddle/fluid/framework/new_executor/interpreter/interpreter_util.cc

@@ -859,7 +859,7 @@ void BuildOpFuncList(const phi::Place& place,
                 op->Attr<bool>(kAllKernelsMustComputeRuntimeShape))) {
             RuntimeInferShapeContext infer_shape_ctx(*op, runtime_context);
             // TODO(Aurelius84): In case of control flow ops, they are NOT
-            // inheritted from OperatorWithKernel.
+            // inherited from OperatorWithKernel.
             op_with_kernel->Info().infer_shape_(&infer_shape_ctx);
           }
         }

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

@@ -92,7 +92,7 @@ class EmbEltwiseLayerNormOpConverter : public OpConverter {
           output_fp16,
           1,
           common::errors::InvalidArgument(
-              "Only Precision::KHalf(fp16) is supported when infering "
+              "Only Precision::KHalf(fp16) is supported when inferring "
               "ernie(bert) model with config.EnableVarseqlen(). "
               "But Precision::KFloat32 is setted."));
 

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

@@ -145,7 +145,7 @@ class PrelnEmbEltwiseLayerNormOpConverter : public OpConverter {
         output_fp16,
         1,
         common::errors::InvalidArgument(
-            "Only Precision::KHalf(fp16) is supported when infering "
+            "Only Precision::KHalf(fp16) is supported when inferring "
             "ernie(bert) model with config.EnableVarseqlen(). "
             "But Precision::KFloat32 is setted."));
 

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

@@ -91,7 +91,7 @@ class PromptTuningEmbEltwiseLayerNormOpConverter : public OpConverter {
         output_fp16,
         1,
         common::errors::InvalidArgument(
-            "Only Precision::KHalf(fp16) is supported when infering "
+            "Only Precision::KHalf(fp16) is supported when inferring "
             "ernie(bert) model with config.EnableVarseqlen(). "
             "But Precision::KFloat32 is setted."));
 

paddle/fluid/operators/generator/generate_op.py

@@ -309,7 +309,7 @@ def add_grad_op_compat_name(grad_op_item, args_name_map):
         if new_op_name != op_name:
             forward_op_item['op_name'] = op_name
 
-        # add complex promote infomation
+        # add complex promote information
         if "complex_promote" in op_args:
             forward_op_item["complex_promote"] = op_args["complex_promote"]
             if has_backward:

paddle/fluid/pybind/tensor.cc

@@ -878,7 +878,7 @@ void BindTensor(pybind11::module &m) {  // NOLINT
 
            Returns:
                tuple: contains ipc name, data size, data type,
-                      tensor dims and lod imformation.
+                      tensor dims and lod information.
 
            Examples:
                 .. code-block:: python

paddle/phi/infermeta/unary.cc

@@ -1242,7 +1242,7 @@ void EigvalshInferMeta(const MetaTensor& x,
 void EinsumInferMeta(const std::vector<const MetaTensor*>& inputs,
                      const std::string& equation,
                      MetaTensor* out) {
-  // collect the following informations to prepare einsum.
+  // collect the following information to prepare einsum.
   LabelMap labelshape(0);
   LabelMap labeltype(LabelType::Reduction);
   std::vector<LabelMap> label2perms(inputs.size(), LabelMap(-1));

paddle/phi/kernels/funcs/seq2col.h

@@ -35,7 +35,7 @@ struct Seq2ColFunctor {
   /*
     Convert sequences to frames.
 
-    1. Dimension infomation:
+    1. Dimension information:
 
        Sequences                   Frames
     (N, seq_length)  ->  (N, frame_length, n_frames)
@@ -105,7 +105,7 @@ struct Col2SeqFunctor {
   /*
     Accumulate output gradient d_out to d_x.
 
-    1. Dimension infomation:
+    1. Dimension information:
 
               d_out                        d_x
     (N, frame_length, n_frames)  ->  (N, seq_length)

paddle/phi/kernels/impl/einsum_impl.h

@@ -603,7 +603,7 @@ void EinsumKernelImpl(const Context& dev_ctx,
     VLOG(5) << "      inputs [ " << i << " ].shape=" << i->dims();
   }
   ValidationCheck(equation);
-  // collect the following informations to prepare einsum.
+  // collect the following information to prepare einsum.
   LabelMap labelshape(0);
   LabelMap labeltype(LabelType::Reduction);
   std::vector<LabelMap> label2perms(inputs.size(), LabelMap(-1));

paddle/phi/kernels/sparse/cpu/elementwise_kernel.cc

@@ -240,11 +240,11 @@ void ElementWiseCooKernelImpl(const Context& dev_ctx,
         common::make_ddim(
             {static_cast<int64_t>(sparse_dim), static_cast<int64_t>(nnz)}),
         DataLayout::NCHW);
-    auto indeces_dim = common::vectorize(
+    auto indices_dim = common::vectorize(
         slice_ddim(x.values().dims(), 1, x.values().dims().size()));
-    indeces_dim.insert(indeces_dim.begin(), nnz);
+    indices_dim.insert(indices_dim.begin(), nnz);
     DenseTensorMeta values_meta(
-        x.dtype(), common::make_ddim(indeces_dim), DataLayout::NCHW);
+        x.dtype(), common::make_ddim(indices_dim), DataLayout::NCHW);
     phi::DenseTensor out_indices = phi::Empty(dev_ctx, std::move(indices_meta));
     phi::DenseTensor out_values = phi::Empty(dev_ctx, std::move(values_meta));
 

paddle/phi/kernels/sparse/gpu/convolution.cu.h

@@ -109,7 +109,7 @@ inline IntT* SortedAndUniqueIndex(const Context& dev_ctx,
 /**
  * @brief: update the out index and indices
  * unique_keys: save the index of the output feature list
- * unique_values: indiates the index of key before deduplication
+ * unique_values: indicates the index of key before deduplication
  * out_indexs: indicates the position of the output index in the rulebook
  * rulebook_len: indicates the length of rulebook
  * out_dims: indicates the output dims

paddle/pir/include/core/ir_context.h

@@ -105,7 +105,7 @@ class IR_API IrContext {
   AbstractAttribute *GetRegisteredAbstractAttribute(TypeId id);
 
   ///
-  /// \brief Register an op infomation to IrContext
+  /// \brief Register an op information to IrContext
   ///
   void RegisterOpInfo(Dialect *dialect,
                       TypeId op_id,
@@ -118,12 +118,12 @@ class IR_API IrContext {
                       void (*verify_region)(Operation *));
 
   ///
-  /// \brief Get registered operation infomation.
+  /// \brief Get registered operation information.
   ///
   OpInfo GetRegisteredOpInfo(const std::string &name);
 
   ///
-  /// \brief Get registered operation infomation map.
+  /// \brief Get registered operation information map.
   ///
   const OpInfoMap &registered_op_info_map();
 

python/paddle/distributed/auto_parallel/static/auto_align_tool.py

@@ -402,7 +402,7 @@ def find_diff_vars(fixed_vars_map, query_vars_map):
         return diff_var_name_list
 
     @staticmethod
-    def diff_informations(right_dir, wrong_dir):
+    def diff_information(right_dir, wrong_dir):
         """
         Find the corresponding operator according to the variable name.
         """
@@ -448,7 +448,7 @@ def diff_informations(right_dir, wrong_dir):
         return diff_ops_varname_dict
 
     @staticmethod
-    def diff_informations_from_dirs(right_dirs, wrong_dirs):
+    def diff_information_from_dirs(right_dirs, wrong_dirs):
         right_vars_list = []
         right_program_list = []
         right_dist_attr_map = {}

python/paddle/distributed/auto_parallel/static/engine.py

@@ -1338,12 +1338,12 @@ def _initialize(self, mode, init_parameters=True):
             )
 
         if self._in_pir_mode:
-            # FIXME(ljz) avoid shared same tensro more than once in different mode
+            # FIXME(ljz) avoid shared same tensor more than once in different mode
             if mode != "train":
                 return
             # TODO(2024-Q2)
             # 1. unify random control
-            # 2. initilization of non-parameter buffer
+            # 2. initialization of non-parameter buffer
             # 3. run startup program for pir
             # 4. lazy init adaption
             # 5. amp init adaption

python/paddle/distributed/fleet/utils/log_util.py

@@ -157,7 +157,7 @@ def check_memory_usage(msg=""):
         mem_msg = f"checking pinned memory usage {msg}:"
         for key in mem_dict:
             mem_msg += f"\n{key}: {mem_dict[key]}GB"
-        logger.infor(mem_msg)
+        logger.info(mem_msg)
 
     if hasattr(paddle.device, 'cpu') and hasattr(
         paddle.device.cpu, 'max_memory_allocated'

python/paddle/distributed/rpc/rpc.py

@@ -365,7 +365,7 @@ class `WorkerInfo` with attribute `name`, `rank`, `ip` and `port`.
 
 def get_all_worker_infos() -> list[WorkerInfo]:
     """
-    Get all worker informations.
+    Get all worker information.
 
     Returns:
         List[WorkerInfo].

python/paddle/framework/io_utils.py

@@ -215,7 +215,7 @@ def _pickle_loads_mac(path, f):
 
 def _pack_loaded_dict(load_obj):
     if isinstance(load_obj, dict):
-        unpack_info = 'UnpackBigParamInfor@@'
+        unpack_info = 'UnpackBigParamInfor@@'  # typos: disable-line
         if unpack_info in load_obj:
             removes = []
             for key, value in load_obj[unpack_info].items():
@@ -233,7 +233,7 @@ def _pack_loaded_dict(load_obj):
 
 def _unpack_saved_dict(saved_obj, protocol):
     temp_saved_obj = {}
-    unpack_infor = {}
+    unpack_info = {}
     # When pickle protocol=2 or protocol=3 the serialized object cannot be larger than 4G.
     if 1 < protocol < 4:
         if isinstance(saved_obj, dict):
@@ -244,9 +244,9 @@ def _unpack_saved_dict(saved_obj, protocol):
                     )
                     num_element = np.prod(value.shape)
                     if num_element > MAX_NUMBER_OF_ELEMENT:
-                        unpack_infor[key] = {}
-                        unpack_infor[key]["OriginShape"] = value.shape
-                        unpack_infor[key]["slices"] = []
+                        unpack_info[key] = {}
+                        unpack_info[key]["OriginShape"] = value.shape
+                        unpack_info[key]["slices"] = []
                         value = value.flatten()
                         for i in range(
                             int(
@@ -256,20 +256,20 @@ def _unpack_saved_dict(saved_obj, protocol):
                             )
                         ):
                             part_name = key + "@@." + str(i)
-                            unpack_infor[key]["slices"].append(part_name)
+                            unpack_info[key]["slices"].append(part_name)
                             temp_saved_obj[part_name] = value[
                                 i
                                 * MAX_NUMBER_OF_ELEMENT : MAX_NUMBER_OF_ELEMENT
                                 * (i + 1)
                             ]
 
-    if unpack_infor:
-        for key, value in unpack_infor.items():
+    if unpack_info:
+        for key, value in unpack_info.items():
             if key in saved_obj:
                 saved_obj.pop(key)
                 for part in value['slices']:
                     saved_obj[part] = temp_saved_obj[part]
-        saved_obj['UnpackBigParamInfor@@'] = unpack_infor
+        saved_obj['UnpackBigParamInfor@@'] = unpack_info  # typos: disable-line
     return saved_obj
 
 

test/deprecated/auto_parallel/test_align_tool_deprecated.py

@@ -97,10 +97,8 @@ def test_align_tool(self):
                         os.mkdir("./serial")
                     align_tool.save("./serial", vars, fetch_list)
                     break
-            AutoAlignTool.diff_informations("./serial", "./serial")
-            AutoAlignTool.diff_informations_from_dirs(
-                ["./serial"], ["./serial"]
-            )
+            AutoAlignTool.diff_information("./serial", "./serial")
+            AutoAlignTool.diff_information_from_dirs(["./serial"], ["./serial"])
             break
 
         print("test auto parallel align tool successfully!")

tools/parallel_UT_rule.py

@@ -89,7 +89,6 @@
     'test_sampling_id_op',
     'test_nce',
     'graph_helper_test',
-    'test_static_shape_inferrence_for_shape_tensor',
     'test_layer_norm_mkldnn_op',
     'test_fleet_launch_async',
     'test_multi_gru_fuse_pass',
@@ -1570,7 +1569,6 @@
     'test_sysconfig',
     'test_sync_batch_norm_pass',
     'test_switch',
-    'test_static_shape_inferrence_for_shape_tensor',
     'test_static_analysis',
     'test_squared_mat_sub_fuse_pass',
     'test_spawn_and_init_parallel_env',