


'''simple docstring'''



from typing import TYPE_CHECKING

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


A__						:   Optional[int]				=    {
    """configuration_transfo_xl""": ["""TRANSFO_XL_PRETRAINED_CONFIG_ARCHIVE_MAP""", """TransfoXLConfig"""],
    """tokenization_transfo_xl""": ["""TransfoXLCorpus""", """TransfoXLTokenizer"""],
}

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      A__						:   Dict				=    [
          """TRANSFO_XL_PRETRAINED_MODEL_ARCHIVE_LIST""",
          """AdaptiveEmbedding""",
          """TransfoXLForSequenceClassification""",
          """TransfoXLLMHeadModel""",
          """TransfoXLModel""",
          """TransfoXLPreTrainedModel""",
          """load_tf_weights_in_transfo_xl""",
      ]

try:
      if not is_tf_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      A__						:   List[Any]				=    [
          """TF_TRANSFO_XL_PRETRAINED_MODEL_ARCHIVE_LIST""",
          """TFAdaptiveEmbedding""",
          """TFTransfoXLForSequenceClassification""",
          """TFTransfoXLLMHeadModel""",
          """TFTransfoXLMainLayer""",
          """TFTransfoXLModel""",
          """TFTransfoXLPreTrainedModel""",
      ]


if TYPE_CHECKING:
      from .configuration_transfo_xl import TRANSFO_XL_PRETRAINED_CONFIG_ARCHIVE_MAP, TransfoXLConfig
      from .tokenization_transfo_xl import TransfoXLCorpus, TransfoXLTokenizer

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_transfo_xl import (
                TRANSFO_XL_PRETRAINED_MODEL_ARCHIVE_LIST,
                AdaptiveEmbedding,
                TransfoXLForSequenceClassification,
                TransfoXLLMHeadModel,
                TransfoXLModel,
                TransfoXLPreTrainedModel,
                load_tf_weights_in_transfo_xl,
            )

      try:
            if not is_tf_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_tf_transfo_xl import (
                TF_TRANSFO_XL_PRETRAINED_MODEL_ARCHIVE_LIST,
                TFAdaptiveEmbedding,
                TFTransfoXLForSequenceClassification,
                TFTransfoXLLMHeadModel,
                TFTransfoXLMainLayer,
                TFTransfoXLModel,
                TFTransfoXLPreTrainedModel,
            )

else:
      import sys

      A__						:   int				=    _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)













import enum
import shutil
import sys


__UpperCamelCase,	__UpperCamelCase:	Optional[int] = shutil.get_terminal_size()

__UpperCamelCase:	Optional[Any] = {"""UP""": """A""", """DOWN""": """B""", """RIGHT""": """C""", """LEFT""": """D"""}


class       __lowerCAmelCase					(       enum.Enum      ):


	'''simple docstring'''





	_A													=				0
	_A													=				1


def       SCREAMING_SNAKE_CASE__  (       _lowercase     : List[Any]   ,    _lowercase     : Union[str, Any]=""			)   ->							int:




		'''simple docstring'''
		sys.stdout.write(str(_lowercase			) + end			)
		sys.stdout.flush()


def       SCREAMING_SNAKE_CASE__  (       _lowercase     : Optional[Any]   ,    _lowercase     : Union[str, Any]   ,    _lowercase     : Optional[int]=""			)   ->							str:




		'''simple docstring'''
		forceWrite(f"""\u001b[{color}m{content}\u001b[0m"""   ,    _lowercase			)


def       SCREAMING_SNAKE_CASE__  (       )   ->							int:




		'''simple docstring'''
		forceWrite('\r'			)


def       SCREAMING_SNAKE_CASE__  (       _lowercase     : int   ,    _lowercase     : str			)   ->							List[Any]:




		'''simple docstring'''
		forceWrite(f"""\033[{num_lines}{CURSOR_TO_CHAR[direction.upper()]}"""			)


def       SCREAMING_SNAKE_CASE__  (       )   ->							Dict:




		'''simple docstring'''
		forceWrite(' ' * TERMINAL_WIDTH			)
		reset_cursor()





def       SCREAMING_SNAKE_CASE__  (       )   ->							List[str]:




		'''simple docstring'''
		reset_cursor()
		forceWrite('-' * TERMINAL_WIDTH			)


