



'''simple docstring'''






import requests
def  lowerCamelCase__			(		_A					,     _A							):
  a		:   Union[str, Any]	  =	{'Content-Type': 'application/json'}
  a		:   Dict	  =	requests.post(lowerCAmelCase_					,     json={'text': message_body}					,     headers=lowerCAmelCase_							)
  if response.status_code != 200:
    a		:   Union[str, Any]	  =	(
        'Request to slack returned an error '
        f"""{response.status_code}, the response is:\n{response.text}"""
    )
    raise ValueError(lowerCAmelCase_							)


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>')



from typing import TYPE_CHECKING

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


__a	 =      {"""configuration_reformer""": ["""REFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""", """ReformerConfig"""]}

try:
 if not is_sentencepiece_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 __a	 =      ["""ReformerTokenizer"""]

try:
 if not is_tokenizers_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 __a	 =      ["""ReformerTokenizerFast"""]

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 __a	 =      [
     """REFORMER_PRETRAINED_MODEL_ARCHIVE_LIST""",
     """ReformerAttention""",
     """ReformerForMaskedLM""",
     """ReformerForQuestionAnswering""",
     """ReformerForSequenceClassification""",
     """ReformerLayer""",
     """ReformerModel""",
     """ReformerModelWithLMHead""",
     """ReformerPreTrainedModel""",
 ]


if TYPE_CHECKING:
 from .configuration_reformer import REFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, ReformerConfig

 try:
  if not is_sentencepiece_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .tokenization_reformer import ReformerTokenizer

 try:
  if not is_tokenizers_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .tokenization_reformer_fast import ReformerTokenizerFast

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_reformer import (
      REFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
      ReformerAttention,
      ReformerForMaskedLM,
      ReformerForQuestionAnswering,
      ReformerForSequenceClassification,
      ReformerLayer,
      ReformerModel,
      ReformerModelWithLMHead,
      ReformerPreTrainedModel,
  )

else:
 import sys

 __a	 =      _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)



