
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,
)


if is_sentencepiece_available():
	from ..ta.tokenization_ta import TaTokenizer
else:
	from ...utils.dummy_sentencepiece_objects import TaTokenizer

UpperCAmelCase       =					TaTokenizer

if is_tokenizers_available():
	from ..ta.tokenization_ta_fast import TaTokenizerFast
else:
	from ...utils.dummy_tokenizers_objects import TaTokenizerFast

UpperCAmelCase       =					TaTokenizerFast

UpperCAmelCase       =					{'''configuration_mt5''': ['''MT5Config''', '''MT5OnnxConfig''']}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	UpperCAmelCase       =					[
	    '''MT5EncoderModel''',
	    '''MT5ForConditionalGeneration''',
	    '''MT5ForQuestionAnswering''',
	    '''MT5Model''',
	    '''MT5PreTrainedModel''',
	    '''MT5Stack''',
	]

try:
	if not is_tf_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	UpperCAmelCase       =					['''TFMT5EncoderModel''', '''TFMT5ForConditionalGeneration''', '''TFMT5Model''']

try:
	if not is_flax_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	UpperCAmelCase       =					['''FlaxMT5EncoderModel''', '''FlaxMT5ForConditionalGeneration''', '''FlaxMT5Model''']


if TYPE_CHECKING:
	from .configuration_mta import MTaConfig, MTaOnnxConfig

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_mta import (
		    MTaEncoderModel,
		    MTaForConditionalGeneration,
		    MTaForQuestionAnswering,
		    MTaModel,
		    MTaPreTrainedModel,
		    MTaStack,
		)

	try:
		if not is_tf_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_tf_mta import TFMTaEncoderModel, TFMTaForConditionalGeneration, TFMTaModel

	try:
		if not is_flax_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_flax_mta import FlaxMTaEncoderModel, FlaxMTaForConditionalGeneration, FlaxMTaModel

else:
	import sys

	UpperCAmelCase       =					_LazyModule(
	    __name__,
	    globals()['''__file__'''],
	    _import_structure,
	    extra_objects={'''MT5Tokenizer''': MTaTokenizer, '''MT5TokenizerFast''': MTaTokenizerFast},
	    module_spec=__spec__,
	)








def 			SCREAMING_SNAKE_CASE (			_UpperCAmelCase = 200					)     ->	int:
    lowerCamelCase__       : Dict   					=						[1, 2, 5, 10, 20, 50, 100, 200]
    lowerCamelCase__       : Union[str, Any]   					=						[0] * (pence + 1)
    lowerCamelCase__       : List[str]   					=						1  # base case: 1 way to make 0 pence

    for coin in coins:
        for i in range(_UpperCAmelCase		,      pence + 1		,      1					):
            number_of_ways[i] += number_of_ways[i - coin]
    return number_of_ways[pence]


if __name__ == "__main__":
    assert solution(2_00) == 7_36_82





