





"""simple docstring"""


import requests

def      UpperCamelCase							(SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE     ):
						UpperCamelCase				:		List[Any]				   =			{"""Content-Type""": """application/json"""}
						UpperCamelCase				:		str				   =			requests.post(SCREAMING_SNAKE_CASE							,     json={"""text""": message_body}							,     headers=SCREAMING_SNAKE_CASE     )
						if response.status_code != 200:
												UpperCamelCase				:		str				   =			(
												    """Request to slack returned an error """
												    f"""{response.status_code}, the response is:\n{response.text}"""
												)
												raise ValueError(SCREAMING_SNAKE_CASE     )


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>""")









'''simple docstring'''

from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
)


a    :							Tuple										=    {
    'configuration_encodec': [
        'ENCODEC_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'EncodecConfig',
    ],
    'feature_extraction_encodec': ['EncodecFeatureExtractor'],
}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							a    :							str										=    [
							    'ENCODEC_PRETRAINED_MODEL_ARCHIVE_LIST',
							    'EncodecModel',
							    'EncodecPreTrainedModel',
							]

if TYPE_CHECKING:
							from .configuration_encodec import (
							    ENCODEC_PRETRAINED_CONFIG_ARCHIVE_MAP,
							    EncodecConfig,
							)
							from .feature_extraction_encodec import EncodecFeatureExtractor

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_encodec import (
														    ENCODEC_PRETRAINED_MODEL_ARCHIVE_LIST,
														    EncodecModel,
														    EncodecPreTrainedModel,
														)

else:
							import sys

							a    :							List[Any]										=    _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)

