


from typing import TYPE_CHECKING

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


A_    :					Union[str, Any]             ={"""configuration_t5""": ["""T5_PRETRAINED_CONFIG_ARCHIVE_MAP""", """T5Config""", """T5OnnxConfig"""]}

try:
	if not is_sentencepiece_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	A_    :					Optional[Any]             =["""T5Tokenizer"""]

try:
	if not is_tokenizers_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	A_    :					List[str]             =["""T5TokenizerFast"""]

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	A_    :					str             =[
	    """T5_PRETRAINED_MODEL_ARCHIVE_LIST""",
	    """T5EncoderModel""",
	    """T5ForConditionalGeneration""",
	    """T5Model""",
	    """T5PreTrainedModel""",
	    """load_tf_weights_in_t5""",
	    """T5ForQuestionAnswering""",
	]

try:
	if not is_tf_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	A_    :					Any             =[
	    """TF_T5_PRETRAINED_MODEL_ARCHIVE_LIST""",
	    """TFT5EncoderModel""",
	    """TFT5ForConditionalGeneration""",
	    """TFT5Model""",
	    """TFT5PreTrainedModel""",
	]

try:
	if not is_flax_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	A_    :					str             =[
	    """FlaxT5EncoderModel""",
	    """FlaxT5ForConditionalGeneration""",
	    """FlaxT5Model""",
	    """FlaxT5PreTrainedModel""",
	]


if TYPE_CHECKING:
	from .configuration_ta import T5_PRETRAINED_CONFIG_ARCHIVE_MAP, TaConfig, TaOnnxConfig

	try:
		if not is_sentencepiece_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .tokenization_ta import TaTokenizer

	try:
		if not is_tokenizers_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .tokenization_ta_fast import TaTokenizerFast

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_ta import (
		    T5_PRETRAINED_MODEL_ARCHIVE_LIST,
		    TaEncoderModel,
		    TaForConditionalGeneration,
		    TaForQuestionAnswering,
		    TaModel,
		    TaPreTrainedModel,
		    load_tf_weights_in_ta,
		)

	try:
		if not is_tf_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_tf_ta import (
		    TF_T5_PRETRAINED_MODEL_ARCHIVE_LIST,
		    TFTaEncoderModel,
		    TFTaForConditionalGeneration,
		    TFTaModel,
		    TFTaPreTrainedModel,
		)

	try:
		if not is_flax_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_flax_ta import (
		    FlaxTaEncoderModel,
		    FlaxTaForConditionalGeneration,
		    FlaxTaModel,
		    FlaxTaPreTrainedModel,
		)


else:
	import sys

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



from collections.abc import Callable

A_    :					Any             =Callable[[float], float]  # type alias for a real -> real function




def   lowerCamelCase_       (					UpperCAmelCase__       ,    UpperCAmelCase__       ,    UpperCAmelCase__       ,    ):



						"""simple docstring"""




						a_					=		float(UpperCAmelCase__      )
						while True:
												try:
																		a_					=		prev_guess - function(UpperCAmelCase__      ) / derivative(UpperCAmelCase__      )
												except ZeroDivisionError:
																		raise ZeroDivisionError("""Could not find root"""      ) from None
												if abs(prev_guess - next_guess      ) < 10**-5:
																		return next_guess
												a_					=		next_guess




def   lowerCamelCase_       (					UpperCAmelCase__      ):



						"""simple docstring"""




						return (x**3) - (2 * x) - 5




def   lowerCamelCase_       (					UpperCAmelCase__      ):



						"""simple docstring"""




						return 3 * (x**2) - 2


if __name__ == "__main__":
	print(newton(f, fa, 3))