[CodeStyle][Typos][I-[1-10]] Fix typo(identiy,indentify,implemention,implementd,implementated,impliment,implment,implicitely,Inproper,inconsistence,uncorrectly,Indext)

_typos.toml

@@ -80,18 +80,6 @@ framwork = 'framwork'
 frequence = 'frequence'
 fron = 'fron'
 fullfill = 'fullfill'
-identiy = 'identiy'
-indentify = 'indentify'
-implemention = 'implemention'
-implementated = 'implementated'
-implementd = 'implementd'
-impliment = 'impliment'
-implment = 'implment'
-implicitely = 'implicitely'
-Inproper = 'Inproper'
-inconsistence = 'inconsistence'
-uncorrectly = 'uncorrectly'
-Indext = 'Indext'
 Indexs = 'Indexs'
 indexs = 'indexs'
 indiates = 'indiates'

paddle/fluid/framework/fleet/heter_ps/heter_comm_kernel.cu

@@ -335,7 +335,7 @@ __global__ void scatter_dvals_by_unit_kernel(TUnit* d_dest_vals,
   }
 }
 
-// cuda implemention of  heter_comm_kernel.h
+// cuda implementation of  heter_comm_kernel.h
 template <typename T, typename StreamType>
 void HeterCommKernel::fill_idx(T* idx,
                                int64_t len,

paddle/phi/api/generator/dist_api_gen.py

@@ -458,7 +458,7 @@
 """
 
 # TODO(GhostScreaming): Some operators generate shape info in runtime,
-# bincount. As a result, dist_output's global shape is set uncorrectly,
+# bincount. As a result, dist_output's global shape is set incorrectly,
 # because it's generated in InferMeta function. A temporally solution is
 # use black op list to set DistTensor shape extra.
 SINGLE_SET_DIST_OUT_DIMS = """
@@ -615,7 +615,7 @@ def parse_infer_meta(self, infer_meta_config):
             infer_meta['local_shape'] = None
         # Inplace op that changes shape should not change its global shape
         # in inferMeta, otherwise, it may fails in reshard pass because of
-        # the inconsistence of dist_atttr and shape.
+        # the inconsistency of dist_atttr and shape.
         if 'global_shape' not in infer_meta_config:
             infer_meta['global_shape'] = None
         return infer_meta

paddle/phi/kernels/gpu/cross_entropy_kernel.cu

@@ -1289,7 +1289,7 @@ void CrossEntropyWithSoftmaxCUDAKernel(const GPUContext& dev_ctx,
       return;
     }
 
-    // if axis is not the last, we need a new impliment
+    // if axis is not the last, we need a new implement
     if (soft_label) {
       auto* logits_data = softmax->data<T>();
       auto* labels_data = labels.data<T>();

paddle/utils/optional.h

@@ -25,7 +25,7 @@
 #include <new>
 #include <type_traits>
 
-#include "none.h"
+#include "paddle/utils/none.h"
 
 namespace paddle {
 
@@ -104,7 +104,7 @@ class reference_content {
  public:  // structors
   ~reference_content() {}
 
-  reference_content(RefT r) : content_(r) {}
+  reference_content(RefT r) : content_(r) {}  // NOLINT
 
   reference_content(const reference_content& operand)
       : content_(operand.content_) {}
@@ -207,11 +207,13 @@ class optional_base : public optional_tag {
 
   // Creates an optional<T> uninitialized.
   // No-throw
-  optional_base(none_t) : m_initialized(false) {}
+  optional_base(none_t) : m_initialized(false) {}  // NOLINT
 
   // Creates an optional<T> initialized with 'val'.
   // Can throw if T::T(T const&) does
-  optional_base(argument_type val) : m_initialized(false) { construct(val); }
+  optional_base(argument_type val) : m_initialized(false) {  // NOLINT
+    construct(val);
+  }
 
   // Creates an optional<T> initialized with 'val' IFF cond is true, otherwise
   // creates an uninitialzed optional<T>.
@@ -342,7 +344,7 @@ class optional_base : public optional_tag {
     construct(factory, tag);
   }
 
-  // Constructs using any expression implicitely convertible to the single
+  // Constructs using any expression implicitly convertible to the single
   // argument
   // of a one-argument T constructor.
   // Converting constructions of optional<T> from optional<U> uses this function
@@ -355,7 +357,7 @@ class optional_base : public optional_tag {
     m_initialized = true;
   }
 
-  // Assigns using a form any expression implicitely convertible to the single
+  // Assigns using a form any expression implicitly convertible to the single
   // argument
   // of a T's assignment operator.
   // Converting assignments of optional<T> from optional<U> uses this function
@@ -473,11 +475,11 @@ class optional : public optional_detail::optional_base<T> {
 
   // Creates an optional<T> uninitialized.
   // No-throw
-  optional(none_t none_) : base(none_) {}
+  optional(none_t none_) : base(none_) {}  // NOLINT
 
   // Creates an optional<T> initialized with 'val'.
   // Can throw if T::T(T const&) does
-  optional(argument_type val) : base(val) {}
+  optional(argument_type val) : base(val) {}  // NOLINT
 
   // Creates an optional<T> initialized with 'val' IFF cond is true, otherwise
   // creates an uninitialized optional.
@@ -495,7 +497,7 @@ class optional : public optional_detail::optional_base<T> {
   // Creates an optional<T> with an expression which can be either
   //  (a) An instance of InPlaceFactory (i.e. in_place(a,b,...,n);
   //  (b) An instance of TypedInPlaceFactory ( i.e. in_place<T>(a,b,...,n);
-  //  (c) Any expression implicitely convertible to the single type
+  //  (c) Any expression implicitly convertible to the single type
   //      of a one-argument T's constructor.
   //  (d*) Weak compilers (BCB) might also resolved Expr as optional<T> and
   //  optional<U>
@@ -623,7 +625,7 @@ inline typename optional<T>::reference_const_type get(optional<T> const& opt) {
 }
 
 template <class T>
-inline typename optional<T>::reference_type get(optional<T>& opt) {
+inline typename optional<T>::reference_type get(optional<T>& opt) {  // NOLINT
   return opt.get();
 }
 
@@ -651,7 +653,7 @@ inline typename optional<T>::reference_const_type get_optional_value_or(
 
 template <class T>
 inline typename optional<T>::reference_type get_optional_value_or(
-    optional<T>& opt, typename optional<T>::reference_type v) {
+    optional<T>& opt, typename optional<T>::reference_type v) {  // NOLINT
   return opt.get_value_or(v);
 }
 
@@ -665,7 +667,8 @@ inline typename optional<T>::pointer_const_type get_pointer(
 }
 
 template <class T>
-inline typename optional<T>::pointer_type get_pointer(optional<T>& opt) {
+inline typename optional<T>::pointer_type get_pointer(
+    optional<T>& opt) {  // NOLINT
   return opt.get_ptr();
 }
 

python/paddle/distributed/passes/pass_utils.py

@@ -1119,7 +1119,7 @@ def add_persistable_var(op_idx, program_type):
                     f"Cannot infer chunk_id for op {op.name()} at index {idx}"
                 )
 
-        # Step2.2: indentify the job_type of the op
+        # Step2.2: identify the job_type of the op
         if op_role == int(OpRole.Optimize):
             job_type = "optimizer"
         elif op_role == int(OpRole.Backward) and split_bw:

python/paddle/profiler/profiler.py

@@ -675,7 +675,7 @@ def stop(self) -> None:
             self.record_event = None
         if self.current_state == ProfilerState.READY:
             warn(
-                "Inproper Profiler state transform: READY->CLOSED, profiler will start and stop without saving data"
+                "Improper Profiler state transform: READY->CLOSED, profiler will start and stop without saving data"
             )
             self.profiler.start()
             self.profiler.stop()

test/deprecated/legacy_test/auto_parallel_op_test.py

@@ -352,7 +352,7 @@ def convert_input_dims_map_to_placements(
     return placements_map
 
 
-# TODO: This method has been implementd in
+# TODO: This method has been implemented in
 # paddle/phi/core/distributed/auto_parallel/placement_types.h, bind it
 # python and it's logic.
 def placements_to_dims_map(placements: list, tensor_ndim: int) -> tuple[int]:

test/ir/pir/cinn/test_anchor_fusion.py

@@ -66,7 +66,7 @@ def check_accuracy_and_kernel_num(
         if kernel_num is not None:
             utils.check_jit_kernel_number(static_compute, kernel_num)
 
-    def test_identiy_iters_fusion(self):
+    def test_identity_iters_fusion(self):
         #        T
         #      / | \
         #     /  |  \

test/legacy_test/auto_parallel_op_test.py

@@ -351,7 +351,7 @@ def convert_input_dims_map_to_placements(
     return placements_map
 
 
-# TODO: This method has been implementd in
+# TODO: This method has been implemented in
 # paddle/phi/core/distributed/auto_parallel/placement_types.h, bind it
 # python and it's logic.
 def placements_to_dims_map(placements: list, tensor_ndim: int) -> tuple[int]:

test/legacy_test/test_dist_fleet_base.py

@@ -47,7 +47,7 @@
 class FleetDistRunnerBase:
     """
     run_pserver,run_trainer : after init role, using transpiler split program
-    net : implment by child class, the network of model
+    net : implement by child class, the network of model
     do training : exe run program
     """
 

test/legacy_test/test_dist_fleet_heter_base.py

@@ -40,7 +40,7 @@
 class FleetDistHeterRunnerBase:
     """
     run_pserver,run_trainer : after init role, using transpiler split program
-    net : implment by child class, the network of model
+    net : implement by child class, the network of model
     do training : exe run program
     """
 

test/legacy_test/test_elementwise_div_op.py

@@ -195,7 +195,7 @@ def compute_gradient_y(self, grad_out, out, y):
 )
 class TestElementwiseDivOpBF16(ElementwiseDivOp):
     def init_args(self):
-        # In due to output data type inconsistence of bfloat16 paddle op, we disable the dygraph check.
+        # In due to output data type inconsistency of bfloat16 paddle op, we disable the dygraph check.
         self.check_dygraph = False
         self.place = core.CUDAPlace(0)
 

test/legacy_test/test_quantile_and_nanquantile.py

@@ -28,7 +28,7 @@ class TestQuantileAndNanquantile(unittest.TestCase):
     """
     This class is used for numerical precision testing. If there is
     a corresponding numpy API, the precision comparison can be performed directly.
-    Otherwise, it needs to be verified by numpy implementated function.
+    Otherwise, it needs to be verified by numpy implemented function.
     """
 
     def setUp(self):

tools/CrossStackProfiler/CspFileReader.py

@@ -144,18 +144,18 @@ def _checkArgs(self):
         self._checkArgsKey("minTimeStamp", int)
 
     def getFileListByGroup(self, groupId):
-        lIndext = 0
-        rIndext = 0
+        lIndex = 0
+        rIndex = 0
 
         if self._organizeForm == FILEORGANIZEFORM_BYTRAINER:
-            lIndext = groupId * self._groupSize
-            rIndext = (groupId + 1) * self._groupSize
+            lIndex = groupId * self._groupSize
+            rIndex = (groupId + 1) * self._groupSize
         elif self._organizeForm == FILEORGANIZEFORM_BYRANK:
-            lIndext = groupId * self._groupSize * self._gpuPerTrainer
-            rIndext = (groupId + 1) * self._groupSize * self._gpuPerTrainer
+            lIndex = groupId * self._groupSize * self._gpuPerTrainer
+            rIndex = (groupId + 1) * self._groupSize * self._gpuPerTrainer
 
         try:
-            return self._fileList[lIndext:rIndext]
+            return self._fileList[lIndex:rIndex]
         except IndexError:
             raise IndexError("invalid index of file list")