
'''simple docstring'''




def 						lowerCAmelCase_							(  snake_case__		):




    '''simple docstring'''



    A			:  List[str]   =		0
    A			:  List[Any]   =		len(snake_case__		)

    for i in range(n - 1		):
        for j in range(i + 1						,							snake_case__		):
            if arr[i] > arr[j]:
                num_inversions += 1

    return num_inversions







def 						lowerCAmelCase_							(  snake_case__		):




    '''simple docstring'''



    if len(snake_case__		) <= 1:
        return arr, 0
    A			:  Any   =		len(snake_case__		) // 2
    A			:  str   =		arr[0:mid]
    A			:  str   =		arr[mid:]

    A,    A			:  List[str]   =		count_inversions_recursive(snake_case__		)
    A,    A			:  Dict   =		count_inversions_recursive(snake_case__		)
    A,    A			:  Dict   =		_count_cross_inversions(snake_case__						,							snake_case__		)

    A			:  Tuple   =		inversion_p + inversions_q + cross_inversions
    return c, num_inversions







def 						lowerCAmelCase_							(  snake_case__						,							snake_case__		):




    '''simple docstring'''



    A			:  Any   =		[]
    A			:  List[Any]   =		0
    while i < len(snake_case__		) and j < len(snake_case__		):
        if p[i] > q[j]:
            # if P[1] > Q[j], then P[k] > Q[k] for all  i < k <= len(P)
            # These are all inversions. The claim emerges from the
            # property that P is sorted.
            num_inversion += len(snake_case__		) - i
            r.append(q[j]		)
            j += 1
        else:
            r.append(p[i]		)
            i += 1

    if i < len(snake_case__		):
        r.extend(p[i:]		)
    else:
        r.extend(q[j:]		)

    return r, num_inversion







def 						lowerCAmelCase_							(  ):




    '''simple docstring'''



    A			:  Dict   =		[10, 2, 1, 5, 5, 2, 11]

    # this arr has 8 inversions:
    # (10, 2), (10, 1), (10, 5), (10, 5), (10, 2), (2, 1), (5, 2), (5, 2)

    A			:  Optional[Any]   =		count_inversions_bf(snake_case__		)
    A,    A			:  Dict   =		count_inversions_recursive(snake_case__		)

    assert num_inversions_bf == num_inversions_recursive == 8

    print('''number of inversions = '''						,							snake_case__		)

    # testing an array with zero inversion (a sorted arr_1)

    arr_a.sort()
    A			:  Any   =		count_inversions_bf(snake_case__		)
    A,    A			:  List[Any]   =		count_inversions_recursive(snake_case__		)

    assert num_inversions_bf == num_inversions_recursive == 0
    print('''number of inversions = '''						,							snake_case__		)

    # an empty list should also have zero inversions
    A			:  str   =		[]
    A			:  Tuple   =		count_inversions_bf(snake_case__		)
    A,    A			:  Tuple   =		count_inversions_recursive(snake_case__		)

    assert num_inversions_bf == num_inversions_recursive == 0
    print('''number of inversions = '''						,							snake_case__		)


if __name__ == "__main__":
      main()






'''simple docstring'''




from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowercase     :							Any       						=     logging.get_logger(__name__)

lowercase     :							int       						=     {
    'facebook/timesformer': 'https://huggingface.co/facebook/timesformer/resolve/main/config.json',
}





class 					A							(				__snake_case		):
     __magic_name__          =						'''timesformer'''





     def __init__(				self		,     SCREAMING_SNAKE_CASE=224		,     SCREAMING_SNAKE_CASE=16		,     SCREAMING_SNAKE_CASE=3		,     SCREAMING_SNAKE_CASE=8		,     SCREAMING_SNAKE_CASE=768		,     SCREAMING_SNAKE_CASE=12		,     SCREAMING_SNAKE_CASE=12		,     SCREAMING_SNAKE_CASE=3072		,     SCREAMING_SNAKE_CASE="gelu"		,     SCREAMING_SNAKE_CASE=0.0		,     SCREAMING_SNAKE_CASE=0.0		,     SCREAMING_SNAKE_CASE=0.02		,     SCREAMING_SNAKE_CASE=1e-6		,     SCREAMING_SNAKE_CASE=True		,     SCREAMING_SNAKE_CASE="divided_space_time"		,     SCREAMING_SNAKE_CASE=0		,     **SCREAMING_SNAKE_CASE		,     )					->							Tuple:






         """simple docstring"""






         super().__init__(**SCREAMING_SNAKE_CASE      )

         A			:  List[Any]   =		image_size
         A			:  List[str]   =		patch_size
         A			:  List[str]   =		num_channels
         A			:  str   =		num_frames

         A			:  Any   =		hidden_size
         A			:  Dict   =		num_hidden_layers
         A			:  Any   =		num_attention_heads
         A			:  Optional[Any]   =		intermediate_size
         A			:  Union[str, Any]   =		hidden_act
         A			:  Tuple   =		hidden_dropout_prob
         A			:  Optional[int]   =		attention_probs_dropout_prob
         A			:  Tuple   =		initializer_range
         A			:  List[Any]   =		layer_norm_eps
         A			:  Union[str, Any]   =		qkv_bias

         A			:  List[str]   =		attention_type
         A			:  Union[str, Any]   =		drop_path_rate




