




from ctypes import c_float, sizeof
from enum import Enum
from typing import TYPE_CHECKING, Optional, Union


if TYPE_CHECKING:
     from .. import AutoFeatureExtractor, AutoProcessor, AutoTokenizer  # tests_ignore




class  __lowerCAmelCase							(				lowerCAmelCase):
       _a			       =    c_float






       @property
       def        SCREAMING_SNAKE_CASE     ( self:       List[str]					):
         return sizeof(self.value					)







def    UpperCAmelCase__	(  lowerCamelCase,      lowerCamelCase,      lowerCamelCase = 0 ):
  # < 0 is possible if using a dynamic axis
  if dimension <= 0:
    lowercase     :Union[str, Any]   						=    fixed_dimension

  dimension -= num_token_to_add
  return dimension



def    UpperCAmelCase__	(  lowerCamelCase,      lowerCamelCase ):
  return num_parameters * dtype.size







def    UpperCAmelCase__	(  lowerCamelCase ):
  from .. import AutoFeatureExtractor, AutoProcessor, AutoTokenizer  # tests_ignore

  try:
    return AutoProcessor.from_pretrained(lowerCamelCase )
  except (ValueError, OSError, KeyError):
    lowercase						,     lowercase     :Any   						=    None, None
    try:
      lowercase     :List[str]   						=    AutoTokenizer.from_pretrained(lowerCamelCase )
    except (OSError, KeyError):
      pass
    try:
      lowercase     :Optional[int]   						=    AutoFeatureExtractor.from_pretrained(lowerCamelCase )
    except (OSError, KeyError):
      pass

    if tokenizer is not None and feature_extractor is not None:
      raise ValueError(
          F"Couldn't auto-detect preprocessor for {model_name}. Found both a tokenizer and a feature extractor." )
    elif tokenizer is None and feature_extractor is None:
      return None
    elif tokenizer is not None:
      return tokenizer
    else:
      return feature_extractor









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 )



