





'''simple docstring'''



from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


__magic_name__   :						int    =			{
    """configuration_bloom""": ["""BLOOM_PRETRAINED_CONFIG_ARCHIVE_MAP""", """BloomConfig""", """BloomOnnxConfig"""],
}
try:
 if not is_tokenizers_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 __magic_name__   :						str    =			["""BloomTokenizerFast"""]

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 __magic_name__   :						Union[str, Any]    =			[
     """BLOOM_PRETRAINED_MODEL_ARCHIVE_LIST""",
     """BloomForCausalLM""",
     """BloomModel""",
     """BloomPreTrainedModel""",
     """BloomForSequenceClassification""",
     """BloomForTokenClassification""",
     """BloomForQuestionAnswering""",
 ]

if TYPE_CHECKING:
 from .configuration_bloom import BLOOM_PRETRAINED_CONFIG_ARCHIVE_MAP, BloomConfig, BloomOnnxConfig

 try:
  if not is_tokenizers_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .tokenization_bloom_fast import BloomTokenizerFast

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_bloom import (
      BLOOM_PRETRAINED_MODEL_ARCHIVE_LIST,
      BloomForCausalLM,
      BloomForQuestionAnswering,
      BloomForSequenceClassification,
      BloomForTokenClassification,
      BloomModel,
      BloomPreTrainedModel,
  )

else:
 import sys

 __magic_name__   :						Optional[Any]    =			_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)









'''simple docstring'''



from __future__ import annotations

import numpy as np




def 				snake_case_      (		SCREAMING_SNAKE_CASE__       ):







  '''simple docstring'''



  return np.maximum(0					,	SCREAMING_SNAKE_CASE__       )


if __name__ == "__main__":
 print(np.array(relu([-1, 0, 5])))  # --> [0, 0, 5]


