
"""simple docstring"""


import enum
import shutil
import sys


A_							,   A_    							=					shutil.get_terminal_size()

A_    							=					{"""UP""": """A""", """DOWN""": """B""", """RIGHT""": """C""", """LEFT""": """D"""}




class  __lowerCamelCase  ( enum.Enum			):
				a__:      Union[str, Any]          =    0
				a__:      List[str]          =    1






def  lowercase						(	lowerCAmelCase__	,lowerCAmelCase__=""						):
			sys.stdout.write(str(lowerCAmelCase__						) + end						)
			sys.stdout.flush()






def  lowercase						(	lowerCAmelCase__	,lowerCAmelCase__	,lowerCAmelCase__=""						):
			forceWrite(f"\u001b[{color}m{content}\u001b[0m"	,lowerCAmelCase__						)






def  lowercase						(	):
			forceWrite('''\r'''						)






def  lowercase						(	lowerCAmelCase__	,lowerCAmelCase__						):
			forceWrite(f"\033[{num_lines}{CURSOR_TO_CHAR[direction.upper()]}"						)






def  lowercase						(	):
			forceWrite(''' ''' * TERMINAL_WIDTH						)
			reset_cursor()






def  lowercase						(	):
			reset_cursor()
			forceWrite('''-''' * TERMINAL_WIDTH						)





"""simple docstring"""


from typing import TYPE_CHECKING

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


A_    							=					{
    """configuration_gpt_neo""": ["""GPT_NEO_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GPTNeoConfig""", """GPTNeoOnnxConfig"""],
}

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						A_    							=					[
						    """GPT_NEO_PRETRAINED_MODEL_ARCHIVE_LIST""",
						    """GPTNeoForCausalLM""",
						    """GPTNeoForQuestionAnswering""",
						    """GPTNeoForSequenceClassification""",
						    """GPTNeoForTokenClassification""",
						    """GPTNeoModel""",
						    """GPTNeoPreTrainedModel""",
						    """load_tf_weights_in_gpt_neo""",
						]

try:
						if not is_flax_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						A_    							=					[
						    """FlaxGPTNeoForCausalLM""",
						    """FlaxGPTNeoModel""",
						    """FlaxGPTNeoPreTrainedModel""",
						]


if TYPE_CHECKING:
						from .configuration_gpt_neo import GPT_NEO_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTNeoConfig, GPTNeoOnnxConfig

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_gpt_neo import (
												    GPT_NEO_PRETRAINED_MODEL_ARCHIVE_LIST,
												    GPTNeoForCausalLM,
												    GPTNeoForQuestionAnswering,
												    GPTNeoForSequenceClassification,
												    GPTNeoForTokenClassification,
												    GPTNeoModel,
												    GPTNeoPreTrainedModel,
												    load_tf_weights_in_gpt_neo,
												)

						try:
												if not is_flax_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_flax_gpt_neo import FlaxGPTNeoForCausalLM, FlaxGPTNeoModel, FlaxGPTNeoPreTrainedModel


else:
						import sys

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



