

def 			A_      (    _UpperCAmelCase    ):
						SCREAMING_SNAKE_CASE_: List[Any]  		=       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 			A_      (    _UpperCAmelCase    ):

						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"    )

						SCREAMING_SNAKE_CASE_: list[list[int]]  		=       []
						for current_row_idx in range(_UpperCAmelCase    ):
												SCREAMING_SNAKE_CASE_: List[Any]  		=       populate_current_row(_UpperCAmelCase				,	_UpperCAmelCase    )
												triangle.append(_UpperCAmelCase    )
						return triangle







def 			A_      (    _UpperCAmelCase				,	_UpperCAmelCase    ):
						SCREAMING_SNAKE_CASE_: Dict  		=       [-1] * (current_row_idx + 1)
						# first and last elements of current row are equal to 1
						SCREAMING_SNAKE_CASE_		,    SCREAMING_SNAKE_CASE_: Tuple  		=       1, 1
						for current_col_idx in range(1				,	_UpperCAmelCase    ):
												calculate_current_element(
												    _UpperCAmelCase				,	_UpperCAmelCase				,	_UpperCAmelCase				,	_UpperCAmelCase    )
						return current_row







def 			A_      (    _UpperCAmelCase				,	_UpperCAmelCase				,	_UpperCAmelCase				,	_UpperCAmelCase				,	):
						SCREAMING_SNAKE_CASE_: str  		=       triangle[current_row_idx - 1][current_col_idx - 1]
						SCREAMING_SNAKE_CASE_: Optional[int]  		=       triangle[current_row_idx - 1][current_col_idx]
						SCREAMING_SNAKE_CASE_: str  		=       above_to_left_elt + above_to_right_elt







def 			A_      (    _UpperCAmelCase    ):

						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"    )

						SCREAMING_SNAKE_CASE_: list[list[int]]  		=       [[1]]

						for row_index in range(1				,	_UpperCAmelCase    ):
												SCREAMING_SNAKE_CASE_: Any  		=       [0] + result[-1] + [0]
												SCREAMING_SNAKE_CASE_: Tuple  		=       row_index + 1
												# Calculate the number of distinct elements in a row
												SCREAMING_SNAKE_CASE_: Any  		=       sum(divmod(_UpperCAmelCase				,	2    )    )
												SCREAMING_SNAKE_CASE_: Optional[int]  		=       [
												    temp_row[i - 1] + temp_row[i] for i in range(1				,	distinct_elements + 1    )
												]
												SCREAMING_SNAKE_CASE_: Tuple  		=       row_first_half[: (row_index + 1) // 2]
												row_second_half.reverse()
												SCREAMING_SNAKE_CASE_: List[str]  		=       row_first_half + row_second_half
												result.append(_UpperCAmelCase    )

						return result







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

						def benchmark_a_function(_UpperCAmelCase				,	_UpperCAmelCase    ) -> None:
												SCREAMING_SNAKE_CASE_: int  		=       f"{func.__name__}({value})"
												SCREAMING_SNAKE_CASE_: List[str]  		=       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()









from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowerCAmelCase							:  Optional[int]   	=						{"""configuration_wavlm""": ["""WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP""", """WavLMConfig"""]}

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCAmelCase							:  Any   	=						[
						    """WAVLM_PRETRAINED_MODEL_ARCHIVE_LIST""",
						    """WavLMForAudioFrameClassification""",
						    """WavLMForCTC""",
						    """WavLMForSequenceClassification""",
						    """WavLMForXVector""",
						    """WavLMModel""",
						    """WavLMPreTrainedModel""",
						]

if TYPE_CHECKING:
						from .configuration_wavlm import WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP, WavLMConfig

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_wavlm import (
												    WAVLM_PRETRAINED_MODEL_ARCHIVE_LIST,
												    WavLMForAudioFrameClassification,
												    WavLMForCTC,
												    WavLMForSequenceClassification,
												    WavLMForXVector,
												    WavLMModel,
												    WavLMPreTrainedModel,
												)

else:
						import sys

						lowerCAmelCase							:  Union[str, Any]   	=						_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)






