[HEU][CodeStyle][Typos][T-[1-5]] Fix typo(targt, Taget, templat,temporaily,temporily,Temperarily,temporaly,Temperary)

_typos.toml

@@ -269,14 +269,6 @@ suppport = 'suppport'
 SWTICH = 'SWTICH'
 Swith = 'Swith'
 sysyem = 'sysyem'
-targt = 'targt'
-Taget = 'Taget'
-templat = 'templat'
-temporaily = 'temporaily'
-temporily = 'temporily'
-Temperarily = 'Temperarily'
-temporaly = 'temporaly'
-Temperary = 'Temperary'
 tenosr = 'tenosr'
 iterm = 'iterm'
 termiante = 'termiante'

paddle/cinn/hlir/dialect/operator/transforms/pd_to_cinn_pass.cc

@@ -41,21 +41,21 @@ using paddle::dialect::FullOp;
 
 namespace {
 
-template <typename TagetOpT, typename SourceOpT>
+template <typename TargetOpT, typename SourceOpT>
 bool IsDefinedBy(const SourceOpT &op, const size_t idx) {
   const pir::Operation *defined_op = op->operand_source(idx).defining_op();
-  return defined_op && defined_op->isa<TagetOpT>();
+  return defined_op && defined_op->isa<TargetOpT>();
 }
 
-template <typename TagetOpT, typename SourceOpT>
-TagetOpT CastDefinedTo(const SourceOpT &op, const size_t idx) {
-  PADDLE_ENFORCE_EQ(IsDefinedBy<TagetOpT>(op, idx),
+template <typename TargetOpT, typename SourceOpT>
+TargetOpT CastDefinedTo(const SourceOpT &op, const size_t idx) {
+  PADDLE_ENFORCE_EQ(IsDefinedBy<TargetOpT>(op, idx),
                     true,
                     ::common::errors::PreconditionNotMet(
                         "Required defined op shall not be nullptr and can cast "
                         "to target type."));
   pir::Operation *defined_op = op->operand_source(idx).defining_op();
-  return defined_op->dyn_cast<TagetOpT>();
+  return defined_op->dyn_cast<TargetOpT>();
 }
 
 template <typename T = int>

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

@@ -236,7 +236,7 @@ std::ostream& operator<<(std::ostream& os, const FusionInfo& fusion_info) {
 
 std::vector<const ::pir::Operation*> TopologySort(
     const OpLoweringGroup& group) {
-  // NOTE(Aurelius84): Use simplest one-by-one order temporaly.
+  // NOTE(Aurelius84): Use simplest one-by-one order temporarily.
   auto* block = group.GetParentBlock();
   std::vector<const ::pir::Operation*> ops;
   ops.reserve(block->size());

paddle/cinn/hlir/pe/schedule.cc

@@ -211,7 +211,7 @@ int GetArrayPackingFactor(int shape,
                           const cinn::common::Target &target) {
   int split_base = GetBasicFactor(type, target);
   int split_factor = 1;
-  // temporily use shape-1 instead of shape for isl wrong for1 elimination
+  // temporarily use shape-1 instead of shape for isl wrong for1 elimination
   int i = split_base * split_base < shape ? split_base * split_base : shape;
   for (; i > 1; i--) {
     if (shape % i == 0) {

paddle/fluid/ir_adaptor/translator/CMakeLists.txt

@@ -8,7 +8,7 @@ set(sparse_op_yaml
     ${PADDLE_SOURCE_DIR}/paddle/phi/ops/yaml/sparse_ops.yaml,${PADDLE_SOURCE_DIR}/paddle/phi/ops/yaml/sparse_backward.yaml
 )
 set(op_compat_source_file ${PD_PROGRAM_TRANSLATOR_SOURCE_DIR}/op_compat_info.cc)
-set(op_compat_templat_file
+set(op_compat_template_file
     ${PD_PROGRAM_TRANSLATOR_SOURCE_DIR}/op_compat_info.cc.j2)
 
 add_custom_command(
@@ -17,7 +17,7 @@ add_custom_command(
     ${PYTHON_EXECUTABLE} ${op_gen_file} --op_compat_yaml_file
     ${op_compat_yaml_file} --sparse_op_yaml ${sparse_op_yaml}
     --output_source_file ${op_compat_source_file}
-  DEPENDS ${op_gen_file} ${op_compat_yaml_file} ${op_compat_templat_file}
+  DEPENDS ${op_gen_file} ${op_compat_yaml_file} ${op_compat_template_file}
   VERBATIM)
 file(GLOB PD_PROGRAM_TRANSLATOR_SRCS "*.cc")
 

paddle/phi/kernels/funcs/segmented_array.h

@@ -171,7 +171,7 @@ struct PointerArraySetter : public ArraySetterBase<Context> {
 
   // need_alloc : tensor data needs extra buffer or not.
   // use_cuda_graph: tensor data shall be captured by cuda_graph or not.
-  // pre_alloc_host_buf: tensor data is temporaily stored by pinned memory or
+  // pre_alloc_host_buf: tensor data is temporarily stored by pinned memory or
   // not.
   PointerArraySetter(const Context& ctx,
                      std::vector<DenseTensor*>* t,

python/paddle/nn/functional/loss.py

@@ -4510,9 +4510,9 @@ def adaptive_log_softmax_with_loss(
             Tensor(shape=[], dtype=float32, place=Place(cpu), stop_gradient=True,
             1.14779019)
     """
-    targt_dim = label.dim()
+    target_dim = label.dim()
 
-    if targt_dim == 1:
+    if target_dim == 1:
         if input.shape[0] != label.shape[0]:
             raise ValueError(
                 'Input and label should have the same size '
@@ -4523,7 +4523,7 @@ def adaptive_log_softmax_with_loss(
                 '1D label tensor expects 2D input tensors, '
                 f'but found inputs with size {input.shape}'
             )
-    elif targt_dim == 0:
+    elif target_dim == 0:
         if input.dim() != 1:
             raise ValueError(
                 '0D label tensor expects 1D input tensors, '
@@ -4534,7 +4534,7 @@ def adaptive_log_softmax_with_loss(
             '0D or 1D label tensor expected, ' 'multi-label not supported'
         )
 
-    is_batched = targt_dim > 0
+    is_batched = target_dim > 0
     input = input if is_batched else input.unsqueeze(0)
     label = label if is_batched else label.unsqueeze(0)
 

test/dygraph_to_static/test_break_continue.py

@@ -351,7 +351,7 @@ def init_dygraph_func(self):
     def test_transformed_static_result(self):
         self.init_dygraph_func()
         dygraph_res = self.run_dygraph_mode()
-        # NOTE(SigureMo): Temperary run the test in sequential run mode to avoid dependency
+        # NOTE(SigureMo): Temporarily run the test in sequential run mode to avoid dependency
         # on the execution order of the test cases.
         if use_pir_api():
             with exe_sequential_run_guard(True):

test/sot/test_step_profiler.py

@@ -43,7 +43,7 @@ def forward(self, x):
 
 
 class TestStepProfilerSmokeTest(unittest.TestCase):
-    # Temperarily disable this test
+    # Temporarily disable this test
     # @sot_step_profiler_guard(True)
     @strict_mode_guard(False)
     def test_step_profiler_smoke(self):