





"""simple docstring"""




from typing import TYPE_CHECKING

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


UpperCamelCase_	 ={"""configuration_vilt""": ["""VILT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """ViltConfig"""]}

try:
						if not is_vision_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						UpperCamelCase_	 =["""ViltFeatureExtractor"""]
						UpperCamelCase_	 =["""ViltImageProcessor"""]
						UpperCamelCase_	 =["""ViltProcessor"""]

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						UpperCamelCase_	 =[
						    """VILT_PRETRAINED_MODEL_ARCHIVE_LIST""",
						    """ViltForImageAndTextRetrieval""",
						    """ViltForImagesAndTextClassification""",
						    """ViltForTokenClassification""",
						    """ViltForMaskedLM""",
						    """ViltForQuestionAnswering""",
						    """ViltLayer""",
						    """ViltModel""",
						    """ViltPreTrainedModel""",
						]


if TYPE_CHECKING:
						from .configuration_vilt import VILT_PRETRAINED_CONFIG_ARCHIVE_MAP, ViltConfig

						try:
												if not is_vision_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .feature_extraction_vilt import ViltFeatureExtractor
												from .image_processing_vilt import ViltImageProcessor
												from .processing_vilt import ViltProcessor

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_vilt import (
												    VILT_PRETRAINED_MODEL_ARCHIVE_LIST,
												    ViltForImageAndTextRetrieval,
												    ViltForImagesAndTextClassification,
												    ViltForMaskedLM,
												    ViltForQuestionAnswering,
												    ViltForTokenClassification,
												    ViltLayer,
												    ViltModel,
												    ViltPreTrainedModel,
												)


else:
						import sys

						UpperCamelCase_	 =_LazyModule(__name__, globals()["""__file__"""], _import_structure)









import os

from apache_beam.io.filesystems import FileSystems
from apache_beam.pipeline import Pipeline

from .logging import get_logger


_UpperCAmelCase						:    List[str]      =  2 << 20  # 2mb
_UpperCAmelCase						:    Optional[int]      =  get_logger(__name__)




class  __lowerCAmelCase							(				lowerCAmelCase):






       def        SCREAMING_SNAKE_CASE     ( self:       str					):
         lowercase     :str   						=    self._options.get_all_options().get("runner"					)
         return runner in [None, "DirectRunner", "PortableRunner"]







def    UpperCAmelCase__	(  lowerCamelCase,      lowerCamelCase,      lowerCamelCase=False ):
  lowercase     :str   						=    FileSystems
  if fs.exists(lowerCamelCase ):
    if force_upload:
      logger.info(F"Remote path already exist: {remote_file_path}. Overwriting it as force_upload=True." )
    else:
      logger.info(F"Remote path already exist: {remote_file_path}. Skipping it as force_upload=False." )
      return
  with fs.create(lowerCamelCase ) as remote_file:
    with open(lowerCamelCase,      "rb" ) as local_file:
      lowercase     :int   						=    local_file.read(lowerCamelCase )
      while chunk:
        remote_file.write(lowerCamelCase )
        lowercase     :List[Any]   						=    local_file.read(lowerCamelCase )







def    UpperCAmelCase__	(  lowerCamelCase,      lowerCamelCase,      lowerCamelCase=False ):
  lowercase     :Union[str, Any]   						=    FileSystems
  if os.path.exists(lowerCamelCase ):
    if force_download:
      logger.info(F"Local path already exist: {remote_file_path}. Overwriting it as force_upload=True." )
    else:
      logger.info(F"Local path already exist: {remote_file_path}. Skipping it as force_upload=False." )
      return
  with fs.open(lowerCamelCase ) as remote_file:
    with open(lowerCamelCase,      "wb" ) as local_file:
      lowercase     :Optional[Any]   						=    remote_file.read(lowerCamelCase )
      while chunk:
        local_file.write(lowerCamelCase )
        lowercase     :Dict   						=    remote_file.read(lowerCamelCase )



