



"""simple docstring"""

import functools
import logging
import os
import sys
import threading
from logging import (
    CRITICAL,  # NOQA
    DEBUG,  # NOQA
    ERROR,  # NOQA
    FATAL,  # NOQA
    INFO,  # NOQA
    NOTSET,  # NOQA
    WARN,  # NOQA
    WARNING,  # NOQA
)
from typing import Optional

import huggingface_hub.utils as hf_hub_utils
from tqdm import auto as tqdm_lib


lowercase__					:						Optional[int]												=			threading.Lock()
lowercase__					:						Optional[logging.Handler]												=			None

lowercase__					:						Optional[int]												=			{
    '''debug''': logging.DEBUG,
    '''info''': logging.INFO,
    '''warning''': logging.WARNING,
    '''error''': logging.ERROR,
    '''critical''': logging.CRITICAL,
}

lowercase__					:						Tuple												=			logging.WARNING

lowercase__					:						Optional[int]												=			True




def __lowercase    (							):
    snake_case_				:  Dict       =			os.getenv('''TRANSFORMERS_VERBOSITY'''	,    _a					)
    if env_level_str:
        if env_level_str in log_levels:
            return log_levels[env_level_str]
        else:
            logging.getLogger().warning(
                f"Unknown option TRANSFORMERS_VERBOSITY={env_level_str}, "
                f"has to be one of: { ', '.join(log_levels.keys()					) }"					)
    return _default_log_level




def __lowercase    (							):
    return __name__.split('''.'''					)[0]




def __lowercase    (							):
    return logging.getLogger(_get_library_name()					)




def __lowercase    (							):
    global _default_handler

    with _lock:
        if _default_handler:
            # This library has already configured the library root logger.
            return
        snake_case_				:  Tuple       =			logging.StreamHandler()  # Set sys.stderr as stream.
        snake_case_				:  str       =			sys.stderr.flush

        # Apply our default configuration to the library root logger.
        snake_case_				:  Optional[int]       =			_get_library_root_logger()
        library_root_logger.addHandler(_default_handler					)
        library_root_logger.setLevel(_get_default_logging_level()					)
        snake_case_				:  Optional[int]       =			False




def __lowercase    (							):
    global _default_handler

    with _lock:
        if not _default_handler:
            return

        snake_case_				:  List[Any]       =			_get_library_root_logger()
        library_root_logger.removeHandler(_default_handler					)
        library_root_logger.setLevel(logging.NOTSET					)
        snake_case_				:  Optional[Any]       =			None




def __lowercase    (							):
    return log_levels




def __lowercase    (							_a = None					):

    if name is None:
        snake_case_				:  int       =			_get_library_name()

    _configure_library_root_logger()
    return logging.getLogger(_a					)




def __lowercase    (							):
    _configure_library_root_logger()
    return _get_library_root_logger().getEffectiveLevel()




def __lowercase    (							_a					):
    _configure_library_root_logger()
    _get_library_root_logger().setLevel(_a					)




def __lowercase    (							):
    return set_verbosity(_a					)




def __lowercase    (							):
    return set_verbosity(_a					)




def __lowercase    (							):
    return set_verbosity(_a					)




def __lowercase    (							):
    return set_verbosity(_a					)




def __lowercase    (							):
    _configure_library_root_logger()

    assert _default_handler is not None
    _get_library_root_logger().removeHandler(_default_handler					)




def __lowercase    (							):
    _configure_library_root_logger()

    assert _default_handler is not None
    _get_library_root_logger().addHandler(_default_handler					)




def __lowercase    (							_a					):
    _configure_library_root_logger()

    assert handler is not None
    _get_library_root_logger().addHandler(_a					)




def __lowercase    (							_a					):
    _configure_library_root_logger()

    assert handler is not None and handler not in _get_library_root_logger().handlers
    _get_library_root_logger().removeHandler(_a					)




def __lowercase    (							):
    _configure_library_root_logger()
    snake_case_				:  Optional[int]       =			False




def __lowercase    (							):
    _configure_library_root_logger()
    snake_case_				:  str       =			True




def __lowercase    (							):
    snake_case_				:  Tuple       =			_get_library_root_logger().handlers

    for handler in handlers:
        snake_case_				:  str       =			logging.Formatter('''[%(levelname)s|%(filename)s:%(lineno)s] %(asctime)s >> %(message)s'''					)
        handler.setFormatter(_a					)




def __lowercase    (							):
    snake_case_				:  Optional[Any]       =			_get_library_root_logger().handlers

    for handler in handlers:
        handler.setFormatter(_a					)




def __lowercase    (							self	,    *_a	,    **_a					):
    snake_case_				:  str       =			os.getenv('''TRANSFORMERS_NO_ADVISORY_WARNINGS'''	,    _a					)
    if no_advisory_warnings:
        return
    self.warning(*_a	,    **_a					)


lowercase__					:						List[str]												=			warning_advice




@functools.lru_cache(_a					)
def __lowercase    (							self	,    *_a	,    **_a					):
    self.warning(*_a	,    **_a					)


lowercase__					:						int												=			warning_once




class  _UpperCAmelCase :

 def __init__(  self	: Any						,  *lowercase_	: List[str]						,  **lowercase_	: Union[str, Any]       ):  # pylint: disable=unused-argument
     snake_case_				:  Optional[Any]       =			args[0] if args else None

 def __iter__(  self	: int       ):
     return iter(self._iterator       )

 def __getattr__(  self	: List[str]						,  lowercase_	: str       ):

     def empty_fn(*lowercase_	: Optional[Any]						,  **lowercase_	: Tuple       ):  # pylint: disable=unused-argument
         return

     return empty_fn

 def __enter__(  self	: int       ):
     return self






 def __exit__(  self	: Tuple						,  lowercase_	: Union[str, Any]						,  lowercase_	: int						,  lowercase_	: Any       ):
     return





class  _UpperCAmelCase :

 def __call__(  self	: Tuple						,  *lowercase_	: Optional[int]						,  **lowercase_	: int       ):
     if _tqdm_active:
         return tqdm_lib.tqdm(*lowercase_						,  **lowercase_       )
     else:
         return EmptyTqdm(*lowercase_						,  **lowercase_       )

 def 		_snake_case      (  self	: List[Any]						,  *lowercase_	: str						,  **lowercase_	: str       ):
     snake_case_				:  Union[str, Any]       =			None
     if _tqdm_active:
         return tqdm_lib.tqdm.set_lock(*lowercase_						,  **lowercase_       )






 def 		_snake_case      (  self	: str       ):
     if _tqdm_active:
         return tqdm_lib.tqdm.get_lock()





lowercase__					:						Dict												=			_tqdm_cls()




def __lowercase    (							):
    global _tqdm_active
    return bool(_tqdm_active					)




def __lowercase    (							):
    global _tqdm_active
    snake_case_				:  str       =			True
    hf_hub_utils.enable_progress_bars()






def __lowercase    (							):
    global _tqdm_active
    snake_case_				:  int       =			False
    hf_hub_utils.disable_progress_bars()










"""simple docstring"""

import unittest

from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision, slow, torch_device


if is_torch_available():
     import torch

     from transformers import AutoModelForImageClassification

if is_vision_available():
     from transformers import AutoImageProcessor




@require_torch
@require_vision
class  _UpperCAmelCase (    unittest.TestCase):

 @slow
 def 		_snake_case      (  self	: List[Any]       ):
     snake_case_				:  List[Any]       =			AutoImageProcessor.from_pretrained('''microsoft/dit-base-finetuned-rvlcdip'''       )
     snake_case_				:  List[Any]       =			AutoModelForImageClassification.from_pretrained('''microsoft/dit-base-finetuned-rvlcdip'''       )
     model.to(lowercase_       )

     from datasets import load_dataset

     snake_case_				:  str       =			load_dataset('''nielsr/rvlcdip-demo'''       )

     snake_case_				:  Tuple       =			dataset['''train'''][0]['''image'''].convert('''RGB'''       )

     snake_case_				:  Union[str, Any]       =			image_processor(lowercase_						,  return_tensors='''pt'''       ).to(lowercase_       )

     # forward pass
     with torch.no_grad():
         snake_case_				:  List[Any]       =			model(**lowercase_       )
         snake_case_				:  int       =			outputs.logits

     snake_case_				:  Any       =			torch.Size((1, 16)       )
     self.assertEqual(logits.shape						,  lowercase_       )

     snake_case_				:  Any       =			torch.tensor(
         [-0.41_58, -0.40_92, -0.43_47]						,  device=lowercase_						,  dtype=torch.float						,  )
     self.assertTrue(torch.allclose(logits[0, :3]						,  lowercase_						,  atol=1E-4       )       )





