




from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_tokenizers_available,
    is_torch_available,
)


UpperCamelCase__         =      {"""configuration_fnet""": ["""FNET_PRETRAINED_CONFIG_ARCHIVE_MAP""", """FNetConfig"""]}

try:
     if not is_sentencepiece_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     UpperCamelCase__         =      ["""FNetTokenizer"""]

try:
     if not is_tokenizers_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     UpperCamelCase__         =      ["""FNetTokenizerFast"""]

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     UpperCamelCase__         =      [
         """FNET_PRETRAINED_MODEL_ARCHIVE_LIST""",
         """FNetForMaskedLM""",
         """FNetForMultipleChoice""",
         """FNetForNextSentencePrediction""",
         """FNetForPreTraining""",
         """FNetForQuestionAnswering""",
         """FNetForSequenceClassification""",
         """FNetForTokenClassification""",
         """FNetLayer""",
         """FNetModel""",
         """FNetPreTrainedModel""",
     ]


if TYPE_CHECKING:
     from .configuration_fnet import FNET_PRETRAINED_CONFIG_ARCHIVE_MAP, FNetConfig

     try:
          if not is_sentencepiece_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .tokenization_fnet import FNetTokenizer

     try:
          if not is_tokenizers_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .tokenization_fnet_fast import FNetTokenizerFast

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_fnet import (
              FNET_PRETRAINED_MODEL_ARCHIVE_LIST,
              FNetForMaskedLM,
              FNetForMultipleChoice,
              FNetForNextSentencePrediction,
              FNetForPreTraining,
              FNetForQuestionAnswering,
              FNetForSequenceClassification,
              FNetForTokenClassification,
              FNetLayer,
              FNetModel,
              FNetPreTrainedModel,
          )


else:
     import sys

     UpperCamelCase__         =      _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)










import enum
import shutil
import sys


UpperCamelCase__      ,     UpperCamelCase__         =      shutil.get_terminal_size()

UpperCamelCase__         =      {"""UP""": """A""", """DOWN""": """B""", """RIGHT""": """C""", """LEFT""": """D"""}
class       a__   ( enum.Enum				):
						_a							:   Any =   0
						_a							:   Dict =   1







def      _a				(						SCREAMING_SNAKE_CASE_							:    Tuple				,				SCREAMING_SNAKE_CASE_							:    Dict=""					):
					sys.stdout.write(str(SCREAMING_SNAKE_CASE_					) + end					)
					sys.stdout.flush()







def      _a				(						SCREAMING_SNAKE_CASE_							:    Any				,				SCREAMING_SNAKE_CASE_							:    Union[str, Any]				,				SCREAMING_SNAKE_CASE_							:    str=""					):
					forceWrite(F"""\u001b[{color}m{content}\u001b[0m"""				,				SCREAMING_SNAKE_CASE_					)







def      _a				(						):
					forceWrite("\r"					)







def      _a				(						SCREAMING_SNAKE_CASE_							:    int				,				SCREAMING_SNAKE_CASE_							:    str					):
					forceWrite(F"""\033[{num_lines}{CURSOR_TO_CHAR[direction.upper()]}"""					)







def      _a				(						):
					forceWrite(" " * TERMINAL_WIDTH					)
					reset_cursor()







def      _a				(						):
					reset_cursor()
					forceWrite("-" * TERMINAL_WIDTH					)




