
'''simple docstring'''
import os
import sys
from contextlib import contextmanager


# Windows only
if os.name == "nt":
  import ctypes
  import msvcrt  # noqa






  class    UpperCAmelCase_				(	ctypes.Structure					):
   UpperCAmelCase_		    =						[("""size""", ctypes.c_int), ("""visible""", ctypes.c_byte)]

def 						UpperCamelCase_     (	):
    """simple docstring"""






    if os.name == "nt":
        snake_case_ :    List[Any]     			=						CursorInfo()
        snake_case_ :    List[Any]     			=						ctypes.windll.kernelaa.GetStdHandle(-1_1       )
        ctypes.windll.kernelaa.GetConsoleCursorInfo(_SCREAMING_SNAKE_CASE,		ctypes.byref(_SCREAMING_SNAKE_CASE       )       )
        snake_case_ :    Dict     			=						False
        ctypes.windll.kernelaa.SetConsoleCursorInfo(_SCREAMING_SNAKE_CASE,		ctypes.byref(_SCREAMING_SNAKE_CASE       )       )
    elif os.name == "posix":
        sys.stdout.write("\033[?25l"       )
        sys.stdout.flush()

def 						UpperCamelCase_     (	):
    """simple docstring"""






    if os.name == "nt":
        snake_case_ :    str     			=						CursorInfo()
        snake_case_ :    str     			=						ctypes.windll.kernelaa.GetStdHandle(-1_1       )
        ctypes.windll.kernelaa.GetConsoleCursorInfo(_SCREAMING_SNAKE_CASE,		ctypes.byref(_SCREAMING_SNAKE_CASE       )       )
        snake_case_ :    Optional[Any]     			=						True
        ctypes.windll.kernelaa.SetConsoleCursorInfo(_SCREAMING_SNAKE_CASE,		ctypes.byref(_SCREAMING_SNAKE_CASE       )       )
    elif os.name == "posix":
        sys.stdout.write("\033[?25h"       )
        sys.stdout.flush()


@contextmanager
def 						UpperCamelCase_     (	):
    """simple docstring"""






    try:
        hide_cursor()
        yield
    finally:
        show_cursor()






'''simple docstring'''
from typing import TYPE_CHECKING

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


a_											=						{
    "configuration_biogpt": ["BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP", "BioGptConfig"],
    "tokenization_biogpt": ["BioGptTokenizer"],
}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  a_											=						[
      "BIOGPT_PRETRAINED_MODEL_ARCHIVE_LIST",
      "BioGptForCausalLM",
      "BioGptForTokenClassification",
      "BioGptForSequenceClassification",
      "BioGptModel",
      "BioGptPreTrainedModel",
  ]


if TYPE_CHECKING:
  from .configuration_biogpt import BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP, BioGptConfig
  from .tokenization_biogpt import BioGptTokenizer

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_biogpt import (
        BIOGPT_PRETRAINED_MODEL_ARCHIVE_LIST,
        BioGptForCausalLM,
        BioGptForSequenceClassification,
        BioGptForTokenClassification,
        BioGptModel,
        BioGptPreTrainedModel,
    )


else:
  import sys

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




