






"""simple docstring"""







from typing import TYPE_CHECKING

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


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

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			a			:    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

			a			:    int				 =		_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)














"""simple docstring"""







from __future__ import annotations





def 						lowercase__(A ,		A						)    ->list[str]:




						"""simple docstring"""



						if partitions <= 0:
												raise ValueError("partitions must be a positive number!"						)
						if partitions > number_of_bytes:
												raise ValueError("partitions can not > number_of_bytes!"						)
						lowercase__    :				List[str]=	number_of_bytes // partitions
						lowercase__    :				Dict=	[]
						for i in range(A						):
												lowercase__    :				Union[str, Any]=	i * bytes_per_partition + 1
												lowercase__    :				Any=	(
												    number_of_bytes if i == partitions - 1 else (i + 1) * bytes_per_partition
												)
												allocation_list.append(f'''{start_bytes}-{end_bytes}'''						)
						return allocation_list


if __name__ == "__main__":
			import doctest

			doctest.testmod()






