
"""simple docstring"""


from typing import Tuple, Union

from ...modeling_outputs import BackboneOutput
from ...modeling_utils import PreTrainedModel
from ...utils import is_timm_available, is_torch_available, requires_backends
from ...utils.backbone_utils import BackboneMixin
from .configuration_timm_backbone import TimmBackboneConfig


if is_timm_available():
						import timm


if is_torch_available():
						from torch import Tensor




class  __lowerCamelCase  ( lowerCAmelCase						,	lowerCAmelCase			):
				a__:      Dict          =    'pixel_values'
				a__:      Any          =    False
				a__:      List[Any]          =    TimmBackboneConfig




				def __init__(				self							,						UpperCAmelCase							,						**UpperCAmelCase   ):
							requires_backends(self							,						'''timm'''   )
							super().__init__(UpperCAmelCase   )
							lowerCamelCase_					=  config

							if config.backbone is None:
										raise ValueError('''backbone is not set in the config. Please set it to a timm model name.'''   )

							if config.backbone not in timm.list_models():
										raise ValueError(f"backbone {config.backbone} is not supported by timm."   )

							if hasattr(UpperCAmelCase							,						'''out_features'''   ) and config.out_features is not None:
										raise ValueError('''out_features is not supported by TimmBackbone. Please use out_indices instead.'''   )

							lowerCamelCase_					=  getattr(UpperCAmelCase							,						'''use_pretrained_backbone'''							,						UpperCAmelCase   )
							if pretrained is None:
										raise ValueError('''use_pretrained_backbone is not set in the config. Please set it to True or False.'''   )

							# We just take the final layer by default. This matches the default for the transformers models.
							lowerCamelCase_					=  config.out_indices if getattr(UpperCAmelCase							,						'''out_indices'''							,						UpperCAmelCase   ) is not None else (-1,)

							lowerCamelCase_					=  timm.create_model(
							    config.backbone							,						pretrained=UpperCAmelCase							,						features_only=config.features_only							,						in_chans=config.num_channels							,						out_indices=UpperCAmelCase							,						**UpperCAmelCase							,						)
							# These are used to control the output of the model when called. If output_hidden_states is True, then
							# return_layers is modified to include all layers.
							lowerCamelCase_					=  self._backbone.return_layers
							lowerCamelCase_					=  {layer['''module''']: str(UpperCAmelCase   ) for i, layer in enumerate(self._backbone.feature_info.info   )}
							super()._init_backbone(UpperCAmelCase   )




				@classmethod
				def        UpperCAmelCase__						(				cls							,						UpperCAmelCase							,						*UpperCAmelCase							,						**UpperCAmelCase   ):
							requires_backends(cls							,						['''vision''', '''timm''']   )
							from ...models.timm_backbone import TimmBackboneConfig

							lowerCamelCase_					=  kwargs.pop('''config'''							,						TimmBackboneConfig()   )

							lowerCamelCase_					=  kwargs.pop('''use_timm_backbone'''							,						UpperCAmelCase   )
							if not use_timm:
										raise ValueError('''use_timm_backbone must be True for timm backbones'''   )

							lowerCamelCase_					=  kwargs.pop('''num_channels'''							,						config.num_channels   )
							lowerCamelCase_					=  kwargs.pop('''features_only'''							,						config.features_only   )
							lowerCamelCase_					=  kwargs.pop('''use_pretrained_backbone'''							,						config.use_pretrained_backbone   )
							lowerCamelCase_					=  kwargs.pop('''out_indices'''							,						config.out_indices   )
							lowerCamelCase_					=  TimmBackboneConfig(
							    backbone=UpperCAmelCase							,						num_channels=UpperCAmelCase							,						features_only=UpperCAmelCase							,						use_pretrained_backbone=UpperCAmelCase							,						out_indices=UpperCAmelCase							,						)
							return super()._from_config(UpperCAmelCase							,						**UpperCAmelCase   )




				def        UpperCAmelCase__						(				self							,						UpperCAmelCase   ):
							pass





				def        UpperCAmelCase__						(				self							,						UpperCAmelCase							,						UpperCAmelCase=None							,						UpperCAmelCase=None							,						UpperCAmelCase=None							,						**UpperCAmelCase   ):
							lowerCamelCase_					=  return_dict if return_dict is not None else self.config.use_return_dict
							lowerCamelCase_					=  (
							    output_hidden_states if output_hidden_states is not None else self.config.output_hidden_states
							)
							lowerCamelCase_					=  output_attentions if output_attentions is not None else self.config.output_attentions

							if output_attentions:
										raise ValueError('''Cannot output attentions for timm backbones at the moment'''   )

							if output_hidden_states:
										# We modify the return layers to include all the stages of the backbone
										lowerCamelCase_					=  self._all_layers
										lowerCamelCase_					=  self._backbone(UpperCAmelCase							,						**UpperCAmelCase   )
										lowerCamelCase_					=  self._return_layers
										lowerCamelCase_					=  tuple(hidden_states[i] for i in self.out_indices   )
							else:
										lowerCamelCase_					=  self._backbone(UpperCAmelCase							,						**UpperCAmelCase   )
										lowerCamelCase_					=  None

							lowerCamelCase_					=  tuple(UpperCAmelCase   )
							lowerCamelCase_					=  tuple(UpperCAmelCase   ) if hidden_states is not None else None

							if not return_dict:
										lowerCamelCase_					=  (feature_maps,)
										if output_hidden_states:
													lowerCamelCase_					=  output + (hidden_states,)
										return output

							return BackboneOutput(feature_maps=UpperCAmelCase							,						hidden_states=UpperCAmelCase							,						attentions=UpperCAmelCase   )





"""simple docstring"""


def  lowercase						(	lowerCAmelCase__						):
			lowerCamelCase_					=  generate_pascal_triangle(lowerCAmelCase__						)
			for row_idx in range(lowerCAmelCase__						):
						# 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  lowercase						(	lowerCAmelCase__						):

			if not isinstance(lowerCAmelCase__	,lowerCAmelCase__						):
						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'''						)

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






def  lowercase						(	lowerCAmelCase__	,lowerCAmelCase__						):
			lowerCamelCase_					=  [-1] * (current_row_idx + 1)
			# first and last elements of current row are equal to 1
			lowerCamelCase_		, lowerCamelCase_					=  1, 1
			for current_col_idx in range(1	,lowerCAmelCase__						):
						calculate_current_element(
						    lowerCAmelCase__	,lowerCAmelCase__	,lowerCAmelCase__	,lowerCAmelCase__						)
			return current_row






def  lowercase						(	lowerCAmelCase__	,lowerCAmelCase__	,lowerCAmelCase__	,lowerCAmelCase__	,):
			lowerCamelCase_					=  triangle[current_row_idx - 1][current_col_idx - 1]
			lowerCamelCase_					=  triangle[current_row_idx - 1][current_col_idx]
			lowerCamelCase_					=  above_to_left_elt + above_to_right_elt






def  lowercase						(	lowerCAmelCase__						):

			if not isinstance(lowerCAmelCase__	,lowerCAmelCase__						):
						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'''						)

			lowerCamelCase_					=  [[1]]

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

			return result






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

			def benchmark_a_function(lowerCAmelCase__	,lowerCAmelCase__						) -> None:
						lowerCamelCase_					=  f"{func.__name__}({value})"
						lowerCamelCase_					=  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(lowerCAmelCase__	,lowerCAmelCase__						)
						print()


if __name__ == "__main__":
						import doctest

						doctest.testmod()
						benchmark()



