


"""simple docstring"""
from typing import TYPE_CHECKING

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


UpperCAmelCase   =	{
    'configuration_bart': ['BART_PRETRAINED_CONFIG_ARCHIVE_MAP', 'BartConfig', 'BartOnnxConfig'],
    'tokenization_bart': ['BartTokenizer'],
}

try:
	if not is_tokenizers_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	UpperCAmelCase   =	['BartTokenizerFast']

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	UpperCAmelCase   =	[
	    'BART_PRETRAINED_MODEL_ARCHIVE_LIST',
	    'BartForCausalLM',
	    'BartForConditionalGeneration',
	    'BartForQuestionAnswering',
	    'BartForSequenceClassification',
	    'BartModel',
	    'BartPretrainedModel',
	    'PretrainedBartModel',
	]

try:
	if not is_tf_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	UpperCAmelCase   =	[
	    'TFBartForConditionalGeneration',
	    'TFBartForSequenceClassification',
	    'TFBartModel',
	    'TFBartPretrainedModel',
	]

try:
	if not is_flax_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	UpperCAmelCase   =	[
	    'FlaxBartDecoderPreTrainedModel',
	    'FlaxBartForCausalLM',
	    'FlaxBartForConditionalGeneration',
	    'FlaxBartForQuestionAnswering',
	    'FlaxBartForSequenceClassification',
	    'FlaxBartModel',
	    'FlaxBartPreTrainedModel',
	]

if TYPE_CHECKING:
	from .configuration_bart import BART_PRETRAINED_CONFIG_ARCHIVE_MAP, BartConfig, BartOnnxConfig
	from .tokenization_bart import BartTokenizer

	try:
		if not is_tokenizers_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .tokenization_bart_fast import BartTokenizerFast

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_bart import (
		    BART_PRETRAINED_MODEL_ARCHIVE_LIST,
		    BartForCausalLM,
		    BartForConditionalGeneration,
		    BartForQuestionAnswering,
		    BartForSequenceClassification,
		    BartModel,
		    BartPretrainedModel,
		    PretrainedBartModel,
		)

	try:
		if not is_tf_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_tf_bart import (
		    TFBartForConditionalGeneration,
		    TFBartForSequenceClassification,
		    TFBartModel,
		    TFBartPretrainedModel,
		)

	try:
		if not is_flax_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_flax_bart import (
		    FlaxBartDecoderPreTrainedModel,
		    FlaxBartForCausalLM,
		    FlaxBartForConditionalGeneration,
		    FlaxBartForQuestionAnswering,
		    FlaxBartForSequenceClassification,
		    FlaxBartModel,
		    FlaxBartPreTrainedModel,
		)

else:
	import sys

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





"""simple docstring"""
import timeit




class   lowercase__							:





   def __init__(       self			,      SCREAMING_SNAKE_CASE)     ->     Tuple:
      if isinstance(SCREAMING_SNAKE_CASE			,      SCREAMING_SNAKE_CASE):  # Initializes a matrix identical to the one provided.
         _lowerCamelCase  :				List[str]      =		arg
         _lowerCamelCase  :				List[str]      =		len(SCREAMING_SNAKE_CASE)
      else:  # Initializes a square matrix of the given size and set values to zero.
         _lowerCamelCase  :				List[Any]      =		arg
         _lowerCamelCase  :				Union[str, Any]      =		[[0 for _ in range(self.n)] for _ in range(self.n)]





   def __mul__(       self			,      SCREAMING_SNAKE_CASE)     ->     Optional[Any]:
      _lowerCamelCase  :				List[Any]      =		Matrix(self.n)
      for i in range(self.n):
         for j in range(self.n):
            for k in range(self.n):
               matrix.t[i][j] += self.t[i][k] * b.t[k][j]
      return matrix







def 							_snake_case			(      __snake_case       :			Union[str, Any]	,   __snake_case       :			List[Any]      ):




   """simple docstring"""







   _lowerCamelCase  :				List[Any]      =		Matrix([[1, 0], [0, 1]]      )
   while b > 0:
      if b & 1:
         matrix *= a
      a *= a
      b >>= 1
   return matrix

def 							_snake_case			(      __snake_case       :			List[str]	,   __snake_case       :			str	,   __snake_case       :			List[Any]      ):




   """simple docstring"""







   if n == 1:
      return fa
   elif n == 2:
      return fa
   _lowerCamelCase  :				Any      =		Matrix([[1, 1], [1, 0]]      )
   _lowerCamelCase  :				List[str]      =		modular_exponentiation(__snake_case	,   n - 2      )
   return fa * matrix.t[0][0] + fa * matrix.t[0][1]

def 							_snake_case			(      __snake_case       :			int	,   __snake_case       :			Optional[int]	,   __snake_case       :			List[Any]      ):




   """simple docstring"""







   if n == 1:
      return fa
   elif n == 2:
      return fa

   _lowerCamelCase  :				Optional[Any]      =		fa
   _lowerCamelCase  :				int      =		fa
   n -= 2

   while n > 0:
      _lowerCamelCase      ,						_lowerCamelCase  :				Tuple      =		fn_a + fn_a, fn_a
      n -= 1

   return fn_a

def 							_snake_case			(      ):




   """simple docstring"""







   _lowerCamelCase  :				List[str]      =		"""
from random import randint
from __main__ import fibonacci_with_matrix_exponentiation
"""
   _lowerCamelCase  :				int      =		"""fibonacci_with_matrix_exponentiation(randint(1,70000), 1, 1)"""
   _lowerCamelCase  :				Tuple      =		timeit.timeit(setup=__snake_case	,   stmt=__snake_case	,   number=100      )
   print("""With matrix exponentiation the average execution time is """	,   exec_time / 100      )
   return exec_time

def 							_snake_case			(      ):




   """simple docstring"""







   _lowerCamelCase  :				Dict      =		"""
from random import randint
from __main__ import simple_fibonacci
"""
   _lowerCamelCase  :				Optional[int]      =		"""simple_fibonacci(randint(1,70000), 1, 1)"""
   _lowerCamelCase  :				List[Any]      =		timeit.timeit(setup=__snake_case	,   stmt=__snake_case	,   number=100      )
   print(
       """Without matrix exponentiation the average execution time is """	,   exec_time / 100      )
   return exec_time

def 							_snake_case			(      ):




   """simple docstring"""







   matrix_exponentiation_time()
   simple_fibonacci_time()


if __name__ == "__main__":
 main()

