



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


UpperCAmelCase							=       logging.get_logger(__name__)

UpperCAmelCase							=       {
    """facebook/regnet-y-040""": """https://huggingface.co/facebook/regnet-y-040/blob/main/config.json""",
}

class 			__snake_case   ( SCREAMING_SNAKE_CASE):







							'''simple docstring'''






							UpperCamelCase__					:   Any       =       """regnet"""
							UpperCamelCase__					:   Tuple       =       ["""x""", """y"""]


							def __init__(				self	,	a_=3	,	a_=32	,	a_=[128, 192, 512, 1_088]	,	a_=[2, 6, 12, 2]	,	a_=64	,	a_="y"	,	a_="relu"	,	**a_	,	):
											super().__init__(**a_		)
											if layer_type not in self.layer_types:
															raise ValueError(F'''layer_type={layer_type} is not one of {",".join(self.layer_types		)}'''		)
											a__					   =		num_channels
											a__					   =		embedding_size
											a__					   =		hidden_sizes
											a__					   =		depths
											a__					   =		groups_width
											a__					   =		layer_type
											a__					   =		hidden_act
											# always downsample in the first stage
											a__					   =		True






from collections import defaultdict

def       A_   (						__a  :					str		):

				"""simple docstring"""
				a__					   =		defaultdict(__a		)
				# Creating a dictionary containing count of each word
				for word in sentence.split():
								occurrence[word] += 1
				return occurrence


if __name__ == "__main__":
	for word, count in word_occurrence("""INPUT STRING""").items():
		print(f"""{word}: {count}""")

