


import argparse
import logging
import sys
from unittest.mock import patch

import run_glue_with_pabee

from transformers.testing_utils import TestCasePlus


logging.basicConfig(level=logging.DEBUG)

__UpperCAmelCase			:			Tuple			      =					logging.getLogger()


def   a						(				):






       """simple docstring"""





       UpperCamelCase     :						Optional[int] 						=		argparse.ArgumentParser()
       parser.add_argument('''-f'''							)
       UpperCamelCase     :						List[str] 						=		parser.parse_args()
       return args.f



class  UpperCAmelCase_						(				_a):
       '''simple docstring'''






       def 			_lowercase (  self    ):




              """simple docstring"""




              UpperCamelCase     :						Optional[Any] 						=		logging.StreamHandler(sys.stdout    )
              logger.addHandler(__SCREAMING_SNAKE_CASE    )

              UpperCamelCase     :						List[Any] 						=		self.get_auto_remove_tmp_dir()
              UpperCamelCase     :						Any 						=		f"""
            run_glue_with_pabee.py
            --model_type albert
            --model_name_or_path albert-base-v2
            --data_dir ./tests/fixtures/tests_samples/MRPC/
            --output_dir {tmp_dir}
            --overwrite_output_dir
            --task_name mrpc
            --do_train
            --do_eval
            --per_gpu_train_batch_size=2
            --per_gpu_eval_batch_size=1
            --learning_rate=2e-5
            --max_steps=50
            --warmup_steps=2
            --seed=42
            --max_seq_length=128
            """.split()

              with patch.object(__SCREAMING_SNAKE_CASE			,       '''argv'''			,       __SCREAMING_SNAKE_CASE    ):
                     UpperCamelCase     :						Dict 						=		run_glue_with_pabee.main()
                     for value in result.values():
                            self.assertGreaterEqual(__SCREAMING_SNAKE_CASE			,       0.75    )





from typing import TYPE_CHECKING

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


__UpperCAmelCase			:			int			      =					{"configuration_vilt": ["VILT_PRETRAINED_CONFIG_ARCHIVE_MAP", "ViltConfig"]}

try:
  if not is_vision_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  __UpperCAmelCase			:			Optional[Any]			      =					["ViltFeatureExtractor"]
  __UpperCAmelCase			:			Union[str, Any]			      =					["ViltImageProcessor"]
  __UpperCAmelCase			:			Dict			      =					["ViltProcessor"]

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  __UpperCAmelCase			:			List[Any]			      =					[
      "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			:			Any			      =					_LazyModule(__name__, globals()["__file__"], _import_structure)

