

"""simple docstring"""



import warnings
from collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


SCREAMING_SNAKE_CASE_					:	Any							  =						logging.get_logger(__name__)

SCREAMING_SNAKE_CASE_					:	Optional[Any]							  =						{
    'nvidia/segformer-b0-finetuned-ade-512-512': (
        'https://huggingface.co/nvidia/segformer-b0-finetuned-ade-512-512/resolve/main/config.json'
    ),
    # See all SegFormer models at https://huggingface.co/models?filter=segformer
}



class 					a						(       _lowerCamelCase				):



    """simple docstring"""



    UpperCAmelCase						 =					"segformer"

    def __init__(     self: Optional[Any]    ,						UpperCamelCase: Union[str, Any]=3    ,						UpperCamelCase: int=4    ,						UpperCamelCase: int=[2, 2, 2, 2]    ,						UpperCamelCase: List[str]=[8, 4, 2, 1]    ,						UpperCamelCase: List[Any]=[32, 64, 1_60, 2_56]    ,						UpperCamelCase: Any=[7, 3, 3, 3]    ,						UpperCamelCase: Union[str, Any]=[4, 2, 2, 2]    ,						UpperCamelCase: Tuple=[1, 2, 5, 8]    ,						UpperCamelCase: Optional[int]=[4, 4, 4, 4]    ,						UpperCamelCase: Dict="gelu"    ,						UpperCamelCase: Optional[Any]=0.0    ,						UpperCamelCase: List[str]=0.0    ,						UpperCamelCase: Union[str, Any]=0.1    ,						UpperCamelCase: List[Any]=0.02    ,						UpperCamelCase: int=0.1    ,						UpperCamelCase: Optional[int]=1e-6    ,						UpperCamelCase: int=2_56    ,						UpperCamelCase: Union[str, Any]=2_55    ,						**UpperCamelCase: Optional[Any]    ,						):






         """simple docstring"""


         super().__init__(**UpperCamelCase       )

         if "reshape_last_stage" in kwargs and kwargs["reshape_last_stage"] is False:
              warnings.warn(
                  """Reshape_last_stage is set to False in this config. This argument is deprecated and will soon be"""
                  """ removed, as the behaviour will default to that of reshape_last_stage = True."""    ,						UpperCamelCase    ,						)

         A__										=  num_channels
         A__										=  num_encoder_blocks
         A__										=  depths
         A__										=  sr_ratios
         A__										=  hidden_sizes
         A__										=  patch_sizes
         A__										=  strides
         A__										=  mlp_ratios
         A__										=  num_attention_heads
         A__										=  hidden_act
         A__										=  hidden_dropout_prob
         A__										=  attention_probs_dropout_prob
         A__										=  classifier_dropout_prob
         A__										=  initializer_range
         A__										=  drop_path_rate
         A__										=  layer_norm_eps
         A__										=  decoder_hidden_size
         A__										=  kwargs.get("""reshape_last_stage"""    ,						UpperCamelCase       )
         A__										=  semantic_loss_ignore_index



class 					a						(       _lowerCamelCase				):



    """simple docstring"""



    UpperCAmelCase						 =					version.parse("1.11"				)

    @property
    def 				UpperCamelCase	(     self: List[str]       ):






         """simple docstring"""


         return OrderedDict(
             [
                 ("""pixel_values""", {0: """batch""", 1: """num_channels""", 2: """height""", 3: """width"""}),
             ]       )

    @property
    def 				UpperCamelCase	(     self: int       ):






         """simple docstring"""


         return 1e-4





    @property
    def 				UpperCamelCase	(     self: Optional[int]       ):






         """simple docstring"""


         return 12









"""simple docstring"""



def  _snake_case     (    UpperCAmelCase_  :					int			):
     A__										=  generate_pascal_triangle(UpperCAmelCase_			)
     for row_idx in range(UpperCAmelCase_			):
          # Print left spaces
          for _ in range(num_rows - row_idx - 1			):
               print(end=""" """			)
          # Print row values
          for col_idx in range(row_idx + 1			):
               if col_idx != row_idx:
                    print(triangle[row_idx][col_idx]					,   end=""" """			)
               else:
                    print(triangle[row_idx][col_idx]					,   end=""""""			)
          print()





def  _snake_case     (    UpperCAmelCase_  :					int			):

     if not isinstance(UpperCAmelCase_					,   UpperCAmelCase_			):
          raise TypeError("""The input value of 'num_rows' should be 'int'"""			)

     if num_rows == 0:
          return []
     elif num_rows < 0:
          raise ValueError(
              """The input value of 'num_rows' should be greater than or equal to 0"""			)

     A__										=  []
     for current_row_idx in range(UpperCAmelCase_			):
          A__										=  populate_current_row(UpperCAmelCase_					,   UpperCAmelCase_			)
          triangle.append(UpperCAmelCase_			)
     return triangle





def  _snake_case     (    UpperCAmelCase_  :					list[list[int]]					,   UpperCAmelCase_  :					int			):
     A__										=  [-1] * (current_row_idx + 1)
     # first and last elements of current row are equal to 1
     A__			,				A__										=  1, 1
     for current_col_idx in range(1					,   UpperCAmelCase_			):
          calculate_current_element(
              UpperCAmelCase_					,   UpperCAmelCase_					,   UpperCAmelCase_					,   UpperCAmelCase_			)
     return current_row





def  _snake_case     (    UpperCAmelCase_  :					list[list[int]]					,   UpperCAmelCase_  :					list[int]					,   UpperCAmelCase_  :					int					,   UpperCAmelCase_  :					int					,   ):
     A__										=  triangle[current_row_idx - 1][current_col_idx - 1]
     A__										=  triangle[current_row_idx - 1][current_col_idx]
     A__										=  above_to_left_elt + above_to_right_elt





def  _snake_case     (    UpperCAmelCase_  :					int			):

     if not isinstance(UpperCAmelCase_					,   UpperCAmelCase_			):
          raise TypeError("""The input value of 'num_rows' should be 'int'"""			)

     if num_rows == 0:
          return []
     elif num_rows < 0:
          raise ValueError(
              """The input value of 'num_rows' should be greater than or equal to 0"""			)

     A__										=  [[1]]

     for row_index in range(1					,   UpperCAmelCase_			):
          A__										=  [0] + result[-1] + [0]
          A__										=  row_index + 1
          # Calculate the number of distinct elements in a row
          A__										=  sum(divmod(UpperCAmelCase_					,   2			)			)
          A__										=  [
              temp_row[i - 1] + temp_row[i] for i in range(1					,   distinct_elements + 1			)
          ]
          A__										=  row_first_half[: (row_index + 1) // 2]
          row_second_half.reverse()
          A__										=  row_first_half + row_second_half
          result.append(UpperCAmelCase_			)

     return result





def  _snake_case     (    ):
     from collections.abc import Callable
     from timeit import timeit

     def benchmark_a_function(UpperCAmelCase_  :					Callable					,   UpperCAmelCase_  :					int			) -> None:
          A__										=  F"""{func.__name__}({value})"""
          A__										=  timeit(F"""__main__.{call}"""					,   setup="""import __main__"""			)
          # print(f"{call:38} = {func(value)} -- {timing:.4f} seconds")
          print(F"""{call:38} -- {timing:.4f} seconds"""			)

     for value in range(15			):  # (1, 7, 14):
          for func in (generate_pascal_triangle, generate_pascal_triangle_optimized):
               benchmark_a_function(UpperCAmelCase_					,   UpperCAmelCase_			)
          print()


if __name__ == "__main__":
 import doctest

 doctest.testmod()
 benchmark()






