'''simple docstring'''





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,
)


SCREAMING_SNAKE_CASE_:     str  ={
    'configuration_xlm_roberta': [
        'XLM_ROBERTA_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'XLMRobertaConfig',
        'XLMRobertaOnnxConfig',
    ],
}

try:
    if not is_sentencepiece_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    SCREAMING_SNAKE_CASE_:     List[str]  =['XLMRobertaTokenizer']

try:
    if not is_tokenizers_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    SCREAMING_SNAKE_CASE_:     int  =['XLMRobertaTokenizerFast']

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    SCREAMING_SNAKE_CASE_:     Tuple  =[
        'XLM_ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST',
        'XLMRobertaForCausalLM',
        'XLMRobertaForMaskedLM',
        'XLMRobertaForMultipleChoice',
        'XLMRobertaForQuestionAnswering',
        'XLMRobertaForSequenceClassification',
        'XLMRobertaForTokenClassification',
        'XLMRobertaModel',
        'XLMRobertaPreTrainedModel',
    ]

try:
    if not is_tf_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    SCREAMING_SNAKE_CASE_:     List[Any]  =[
        'TF_XLM_ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST',
        'TFXLMRobertaForCausalLM',
        'TFXLMRobertaForMaskedLM',
        'TFXLMRobertaForMultipleChoice',
        'TFXLMRobertaForQuestionAnswering',
        'TFXLMRobertaForSequenceClassification',
        'TFXLMRobertaForTokenClassification',
        'TFXLMRobertaModel',
        'TFXLMRobertaPreTrainedModel',
    ]

try:
    if not is_flax_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    SCREAMING_SNAKE_CASE_:     List[Any]  =[
        'FLAX_XLM_ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST',
        'FlaxXLMRobertaForMaskedLM',
        'FlaxXLMRobertaForCausalLM',
        'FlaxXLMRobertaForMultipleChoice',
        'FlaxXLMRobertaForQuestionAnswering',
        'FlaxXLMRobertaForSequenceClassification',
        'FlaxXLMRobertaForTokenClassification',
        'FlaxXLMRobertaModel',
        'FlaxXLMRobertaPreTrainedModel',
    ]

if TYPE_CHECKING:
    from .configuration_xlm_roberta import (
        XLM_ROBERTA_PRETRAINED_CONFIG_ARCHIVE_MAP,
        XLMRobertaConfig,
        XLMRobertaOnnxConfig,
    )

    try:
        if not is_sentencepiece_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .tokenization_xlm_roberta import XLMRobertaTokenizer

    try:
        if not is_tokenizers_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .tokenization_xlm_roberta_fast import XLMRobertaTokenizerFast

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_xlm_roberta import (
            XLM_ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST,
            XLMRobertaForCausalLM,
            XLMRobertaForMaskedLM,
            XLMRobertaForMultipleChoice,
            XLMRobertaForQuestionAnswering,
            XLMRobertaForSequenceClassification,
            XLMRobertaForTokenClassification,
            XLMRobertaModel,
            XLMRobertaPreTrainedModel,
        )

    try:
        if not is_tf_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_tf_xlm_roberta import (
            TF_XLM_ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST,
            TFXLMRobertaForCausalLM,
            TFXLMRobertaForMaskedLM,
            TFXLMRobertaForMultipleChoice,
            TFXLMRobertaForQuestionAnswering,
            TFXLMRobertaForSequenceClassification,
            TFXLMRobertaForTokenClassification,
            TFXLMRobertaModel,
            TFXLMRobertaPreTrainedModel,
        )

    try:
        if not is_flax_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_flax_xlm_roberta import (
            FLAX_XLM_ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST,
            FlaxXLMRobertaForCausalLM,
            FlaxXLMRobertaForMaskedLM,
            FlaxXLMRobertaForMultipleChoice,
            FlaxXLMRobertaForQuestionAnswering,
            FlaxXLMRobertaForSequenceClassification,
            FlaxXLMRobertaForTokenClassification,
            FlaxXLMRobertaModel,
            FlaxXLMRobertaPreTrainedModel,
        )

else:
    import sys

    SCREAMING_SNAKE_CASE_:     Optional[Any]  =_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)









'''simple docstring'''





# Function to print upper half of diamond (pyramid)





def 						__snake_case(				_lowerCAmelCase		)		-> Any:
      for i in range(0     ,   _lowerCAmelCase		):
            for _ in range(0     ,   n - i - 1		):  # printing spaces
                  print(""" """     ,   end=""""""		)
            for _ in range(0     ,   i + 1		):  # printing stars
                  print("""* """     ,   end=""""""		)
            print()





def 						__snake_case(				_lowerCAmelCase		)		-> List[str]:
      for i in range(_lowerCAmelCase     ,   0     ,   -1		):
            for _ in range(_lowerCAmelCase     ,   0     ,   -1		):  # printing stars
                  print("""* """     ,   end=""""""		)
            print()
            for _ in range(n - i + 1     ,   0     ,   -1		):  # printing spaces
                  print(""" """     ,   end=""""""		)





def 						__snake_case(				_lowerCAmelCase		)		-> List[Any]:
      if n <= 0:
            print("""       ...       ....        nothing printing :("""		)
            return
      floyd(_lowerCAmelCase		)  # upper half
      reverse_floyd(_lowerCAmelCase		)  # lower half


if __name__ == "__main__":
       print(R"| /\ | |- |  |-  |--| |\  /| |-")
       print(R"|/  \| |- |_ |_  |__| | \/ | |_")
       __a          =		1
       while K:
              __a          =		int(input("enter the number and , and see the magic : "))
              print()
              pretty_print(user_number)
              __a          =		int(input("press 0 to exit... and 1 to continue..."))

       print("Good Bye...")
