





from __future__ import annotations

import numpy as np





def  __magic_name__  (				lowercase				)				-> Tuple:

							"""simple docstring"""



							return np.maximum(0				,       lowercase				)


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






from typing import TYPE_CHECKING

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


UpperCAmelCase_							=				{
    """configuration_m2m_100""": ["""M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP""", """M2M100Config""", """M2M100OnnxConfig"""],
    """tokenization_m2m_100""": ["""M2M100Tokenizer"""],
}


try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCAmelCase_							=				[
							    """M2M_100_PRETRAINED_MODEL_ARCHIVE_LIST""",
							    """M2M100ForConditionalGeneration""",
							    """M2M100Model""",
							    """M2M100PreTrainedModel""",
							]


if TYPE_CHECKING:
							from .configuration_mam_aaa import M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP, MaMaaaConfig, MaMaaaOnnxConfig
							from .tokenization_mam_aaa import MaMaaaTokenizer

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_mam_aaa import (
														    M2M_100_PRETRAINED_MODEL_ARCHIVE_LIST,
														    MaMaaaForConditionalGeneration,
														    MaMaaaModel,
														    MaMaaaPreTrainedModel,
														)


else:
							import sys

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