


from __future__ import annotations



def 							UpperCamelCase_( lowerCamelCase_					)       ->		list:
    if len(lowerCamelCase_					) == 0:
        return []
    _lowercase						,							_lowercase			:				Any 						=						min(lowerCamelCase_					), max(lowerCamelCase_					)
    _lowercase			:				Tuple 						=						int(max_value - min_value					) + 1
    _lowercase			:				list[list] 						=						[[] for _ in range(lowerCamelCase_					)]

    for i in my_list:
        buckets[int(i - min_value					)].append(lowerCamelCase_					)

    return [v for bucket in buckets for v in sorted(lowerCamelCase_					)]


if __name__ == "__main__":
 from doctest import testmod

 testmod()
 assert bucket_sort([4, 5, 3, 2, 1]) == [1, 2, 3, 4, 5]
 assert bucket_sort([0, 1, -10, 15, 2, -2]) == [-10, -2, 0, 1, 2, 15]






from typing import TYPE_CHECKING

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


SCREAMING_SNAKE_CASE			: str				   =					{
    "configuration_gpt_bigcode": ["GPT_BIGCODE_PRETRAINED_CONFIG_ARCHIVE_MAP", "GPTBigCodeConfig"],
}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 SCREAMING_SNAKE_CASE			: int				   =					[
     "GPT_BIGCODE_PRETRAINED_MODEL_ARCHIVE_LIST",
     "GPTBigCodeForSequenceClassification",
     "GPTBigCodeForTokenClassification",
     "GPTBigCodeForCausalLM",
     "GPTBigCodeModel",
     "GPTBigCodePreTrainedModel",
 ]

if TYPE_CHECKING:
 from .configuration_gpt_bigcode import GPT_BIGCODE_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTBigCodeConfig

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_gpt_bigcode import (
      GPT_BIGCODE_PRETRAINED_MODEL_ARCHIVE_LIST,
      GPTBigCodeForCausalLM,
      GPTBigCodeForSequenceClassification,
      GPTBigCodeForTokenClassification,
      GPTBigCodeModel,
      GPTBigCodePreTrainedModel,
  )


else:
 import sys

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


