




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


__lowerCamelCase   :						Dict				=			logging.get_logger(__name__)

__lowerCamelCase   :						int				=			{
    '''google/canine-s''': '''https://huggingface.co/google/canine-s/resolve/main/config.json''',
    # See all CANINE models at https://huggingface.co/models?filter=canine
}


class    lowerCamelCase    (		_lowerCamelCase						):






			'''simple docstring'''





			UpperCamelCase__								='''canine'''

			def __init__( self			:   Optional[int]       ,						lowerCamelCase_			:   Union[str, Any]=768       ,						lowerCamelCase_			:   Tuple=12       ,						lowerCamelCase_			:   Optional[int]=12       ,						lowerCamelCase_			:   Any=3072       ,						lowerCamelCase_			:   List[Any]="gelu"       ,						lowerCamelCase_			:   Optional[Any]=0.1       ,						lowerCamelCase_			:   Optional[int]=0.1       ,						lowerCamelCase_			:   Tuple=16384       ,						lowerCamelCase_			:   int=16       ,						lowerCamelCase_			:   Union[str, Any]=0.0_2       ,						lowerCamelCase_			:   int=1E-12       ,						lowerCamelCase_			:   Tuple=0       ,						lowerCamelCase_			:   List[Any]=0XE000       ,						lowerCamelCase_			:   Union[str, Any]=0XE001       ,						lowerCamelCase_			:   List[str]=4       ,						lowerCamelCase_			:   List[str]=4       ,						lowerCamelCase_			:   Union[str, Any]=8       ,						lowerCamelCase_			:   Union[str, Any]=16384       ,						lowerCamelCase_			:   int=128       ,						**lowerCamelCase_			:   Union[str, Any]       ,						)						->   int:
								super().__init__(pad_token_id=lowerCamelCase_       ,						bos_token_id=lowerCamelCase_       ,						eos_token_id=lowerCamelCase_       ,						**lowerCamelCase_  )

								__magic_name__							:	str    							=							max_position_embeddings
								__magic_name__							:	int    							=							hidden_size
								__magic_name__							:	str    							=							num_hidden_layers
								__magic_name__							:	str    							=							num_attention_heads
								__magic_name__							:	Optional[Any]    							=							intermediate_size
								__magic_name__							:	Dict    							=							hidden_act
								__magic_name__							:	List[str]    							=							hidden_dropout_prob
								__magic_name__							:	Optional[int]    							=							attention_probs_dropout_prob
								__magic_name__							:	List[str]    							=							initializer_range
								__magic_name__							:	List[str]    							=							type_vocab_size
								__magic_name__							:	Optional[int]    							=							layer_norm_eps

								# Character config:
								__magic_name__							:	Union[str, Any]    							=							downsampling_rate
								__magic_name__							:	Optional[Any]    							=							upsampling_kernel_size
								__magic_name__							:	List[str]    							=							num_hash_functions
								__magic_name__							:	Union[str, Any]    							=							num_hash_buckets
								__magic_name__							:	Tuple    							=							local_transformer_stride









import requests







def 		lowercase__   (		__A:	str							,__A:	str				):





					'''simple docstring'''






					__magic_name__							:	Tuple    							=							{'''Content-Type''': '''application/json'''}
					__magic_name__							:	Union[str, Any]    							=							requests.post(__A							,json={'''text''': message_body}							,headers=__A				)
					if response.status_code != 2_0_0:
										__magic_name__							:	int    							=							(
										    '''Request to slack returned an error '''
										    F'''{response.status_code}, the response is:\n{response.text}'''
										)
										raise ValueError(__A				)


if __name__ == "__main__":
	# Set the slack url to the one provided by Slack when you create the webhook at
	# https://my.slack.com/services/new/incoming-webhook/
	send_slack_message('''<YOUR MESSAGE BODY>''', '''<SLACK CHANNEL URL>''')



