'''simple docstring'''





from typing import TYPE_CHECKING

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


SCREAMING_SNAKE_CASE_:     Dict  ={
    'configuration_xlm': ['XLM_PRETRAINED_CONFIG_ARCHIVE_MAP', 'XLMConfig', 'XLMOnnxConfig'],
    'tokenization_xlm': ['XLMTokenizer'],
}

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    SCREAMING_SNAKE_CASE_:     Tuple  =[
        'XLM_PRETRAINED_MODEL_ARCHIVE_LIST',
        'XLMForMultipleChoice',
        'XLMForQuestionAnswering',
        'XLMForQuestionAnsweringSimple',
        'XLMForSequenceClassification',
        'XLMForTokenClassification',
        'XLMModel',
        'XLMPreTrainedModel',
        'XLMWithLMHeadModel',
    ]

try:
    if not is_tf_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    SCREAMING_SNAKE_CASE_:     int  =[
        'TF_XLM_PRETRAINED_MODEL_ARCHIVE_LIST',
        'TFXLMForMultipleChoice',
        'TFXLMForQuestionAnsweringSimple',
        'TFXLMForSequenceClassification',
        'TFXLMForTokenClassification',
        'TFXLMMainLayer',
        'TFXLMModel',
        'TFXLMPreTrainedModel',
        'TFXLMWithLMHeadModel',
    ]


if TYPE_CHECKING:
    from .configuration_xlm import XLM_PRETRAINED_CONFIG_ARCHIVE_MAP, XLMConfig, XLMOnnxConfig
    from .tokenization_xlm import XLMTokenizer

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_xlm import (
            XLM_PRETRAINED_MODEL_ARCHIVE_LIST,
            XLMForMultipleChoice,
            XLMForQuestionAnswering,
            XLMForQuestionAnsweringSimple,
            XLMForSequenceClassification,
            XLMForTokenClassification,
            XLMModel,
            XLMPreTrainedModel,
            XLMWithLMHeadModel,
        )

    try:
        if not is_tf_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_tf_xlm import (
            TF_XLM_PRETRAINED_MODEL_ARCHIVE_LIST,
            TFXLMForMultipleChoice,
            TFXLMForQuestionAnsweringSimple,
            TFXLMForSequenceClassification,
            TFXLMForTokenClassification,
            TFXLMMainLayer,
            TFXLMModel,
            TFXLMPreTrainedModel,
            TFXLMWithLMHeadModel,
        )

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...")
