


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,
)


lowercase_           =	{'configuration_t5': ['T5_PRETRAINED_CONFIG_ARCHIVE_MAP', 'T5Config', 'T5OnnxConfig']}

try:
       if not is_sentencepiece_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowercase_           =	['T5Tokenizer']

try:
       if not is_tokenizers_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowercase_           =	['T5TokenizerFast']

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowercase_           =	[
           '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:
       lowercase_           =	[
           'TF_T5_PRETRAINED_MODEL_ARCHIVE_LIST',
           'TFT5EncoderModel',
           'TFT5ForConditionalGeneration',
           'TFT5Model',
           'TFT5PreTrainedModel',
       ]

try:
       if not is_flax_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowercase_           =	[
           '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

       lowercase_           =	_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)





class        A_					:




      '''simple docstring'''


      def __init__(				self:       Tuple						,      a:       Dict=None				):
       __lowerCamelCase		:							List[Any]							=						data
       __lowerCamelCase		:							Optional[Any]							=						None




      def __repr__(				self:       Optional[int]				):
       __lowerCamelCase		:							Any							=						''
       __lowerCamelCase		:							List[Any]							=						self
       while temp:
        string_rep += F'<{temp.data}> ---> '
        __lowerCamelCase		:							Any							=						temp.next
       string_rep += "<END>"
       return string_rep



def       UpperCamelCase__     (  SCREAMING_SNAKE_CASE__						):

 # if elements_list is empty
 if not elements_list:
  raise Exception('The Elements List is empty'						)

 # Set first element as Head
 __lowerCamelCase		:							Optional[int]							=						Node(elements_list[0]						)
 __lowerCamelCase		:							List[str]							=						head
 # Loop through elements from position 1
 for data in elements_list[1:]:
  __lowerCamelCase		:							str							=						Node(SCREAMING_SNAKE_CASE__						)
  __lowerCamelCase		:							Tuple							=						current.next
 return head


lowercase_           =	[1, 3, 5, 3_2, 4_4, 1_2, 4_3]
print(F"""List: {list_data}""")
print('Creating Linked List from List.')
lowercase_           =	make_linked_list(list_data)
print('Linked List:')



print(linked_list)

