



import re

from ..utils import cached_file


# docstyle-ignore
SCREAMING_SNAKE_CASE_:Dict					=						"""
Human: <<task>>

Assistant: """


SCREAMING_SNAKE_CASE_:Dict					=						"""huggingface-tools/default-prompts"""
SCREAMING_SNAKE_CASE_:Optional[int]					=						{"""chat""": """chat_prompt_template.txt""", """run""": """run_prompt_template.txt"""}




def      __UpperCamelCase     (  _lowerCAmelCase				,					_lowerCAmelCase				,					_lowerCAmelCase="run"		)	->  Union[str, Any]:



    """simple docstring"""






    if prompt_or_repo_id is None:
        A			:	Optional[int]										=       DEFAULT_PROMPTS_REPO

    # prompt is considered a repo ID when it does not contain any kind of space
    if re.search("""\\s"""				,					lowerCamelCase__		) is not None:
        return prompt_or_repo_id

    A			:	Optional[Any]										=       cached_file(
        lowerCamelCase__				,					PROMPT_FILES[mode]				,					repo_type="""dataset"""				,					user_agent={"""agent""": agent_name}		)
    with open(lowerCamelCase__				,					"""r"""				,					encoding="""utf-8"""		) as f:
        return f.read()







from typing import TYPE_CHECKING

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


SCREAMING_SNAKE_CASE_:Any					=						{
    """configuration_mobilenet_v2""": [
        """MOBILENET_V2_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """MobileNetV2Config""",
        """MobileNetV2OnnxConfig""",
    ],
}

try:
     if not is_vision_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     SCREAMING_SNAKE_CASE_:List[Any]					=						["""MobileNetV2FeatureExtractor"""]
     SCREAMING_SNAKE_CASE_:Tuple					=						["""MobileNetV2ImageProcessor"""]


try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     SCREAMING_SNAKE_CASE_:Any					=						[
         """MOBILENET_V2_PRETRAINED_MODEL_ARCHIVE_LIST""",
         """MobileNetV2ForImageClassification""",
         """MobileNetV2ForSemanticSegmentation""",
         """MobileNetV2Model""",
         """MobileNetV2PreTrainedModel""",
         """load_tf_weights_in_mobilenet_v2""",
     ]


if TYPE_CHECKING:
     from .configuration_mobilenet_va import (
         MOBILENET_V2_PRETRAINED_CONFIG_ARCHIVE_MAP,
         MobileNetVaConfig,
         MobileNetVaOnnxConfig,
     )

     try:
          if not is_vision_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .feature_extraction_mobilenet_va import MobileNetVaFeatureExtractor
          from .image_processing_mobilenet_va import MobileNetVaImageProcessor

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_mobilenet_va import (
              MOBILENET_V2_PRETRAINED_MODEL_ARCHIVE_LIST,
              MobileNetVaForImageClassification,
              MobileNetVaForSemanticSegmentation,
              MobileNetVaModel,
              MobileNetVaPreTrainedModel,
              load_tf_weights_in_mobilenet_va,
          )


else:
     import sys

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


