


'''simple docstring'''
from collections.abc import Sequence





def 					a__       (					lowerCAmelCase__ = None						)    ->	int:
    if nums is None or not nums:
        raise ValueError('''Input sequence should not be empty'''						)

    UpperCAmelCase__			:		int													=				nums[0]
    for i in range(1  ,					len(lowerCAmelCase__						)						):
        UpperCAmelCase__			:		str													=				nums[i]
        UpperCAmelCase__			:		Dict													=				max(lowerCAmelCase__  ,					ans + num  ,					lowerCAmelCase__						)

    return ans


if __name__ == "__main__":
  import doctest

  doctest.testmod()

  # Try on a sample input from the user
  UpperCamelCase__    					=      int(input('''Enter number of elements : ''').strip())
  UpperCamelCase__    					=      list(map(int, input('''\nEnter the numbers : ''').strip().split()))[:n]
  print(max_subsequence_sum(array))




'''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_distilbert''': [
        '''DISTILBERT_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''DistilBertConfig''',
        '''DistilBertOnnxConfig''',
    ],
    '''tokenization_distilbert''': ['''DistilBertTokenizer'''],
}

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

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCamelCase__    					=      [
      '''DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST''',
      '''DistilBertForMaskedLM''',
      '''DistilBertForMultipleChoice''',
      '''DistilBertForQuestionAnswering''',
      '''DistilBertForSequenceClassification''',
      '''DistilBertForTokenClassification''',
      '''DistilBertModel''',
      '''DistilBertPreTrainedModel''',
  ]

try:
  if not is_tf_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCamelCase__    					=      [
      '''TF_DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST''',
      '''TFDistilBertForMaskedLM''',
      '''TFDistilBertForMultipleChoice''',
      '''TFDistilBertForQuestionAnswering''',
      '''TFDistilBertForSequenceClassification''',
      '''TFDistilBertForTokenClassification''',
      '''TFDistilBertMainLayer''',
      '''TFDistilBertModel''',
      '''TFDistilBertPreTrainedModel''',
  ]

try:
  if not is_flax_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCamelCase__    					=      [
      '''FlaxDistilBertForMaskedLM''',
      '''FlaxDistilBertForMultipleChoice''',
      '''FlaxDistilBertForQuestionAnswering''',
      '''FlaxDistilBertForSequenceClassification''',
      '''FlaxDistilBertForTokenClassification''',
      '''FlaxDistilBertModel''',
      '''FlaxDistilBertPreTrainedModel''',
  ]


if TYPE_CHECKING:
  from .configuration_distilbert import (
      DISTILBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
      DistilBertConfig,
      DistilBertOnnxConfig,
  )
  from .tokenization_distilbert import DistilBertTokenizer

  try:
    if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .tokenization_distilbert_fast import DistilBertTokenizerFast

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_distilbert import (
        DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
        DistilBertForMaskedLM,
        DistilBertForMultipleChoice,
        DistilBertForQuestionAnswering,
        DistilBertForSequenceClassification,
        DistilBertForTokenClassification,
        DistilBertModel,
        DistilBertPreTrainedModel,
    )

  try:
    if not is_tf_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_tf_distilbert import (
        TF_DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
        TFDistilBertForMaskedLM,
        TFDistilBertForMultipleChoice,
        TFDistilBertForQuestionAnswering,
        TFDistilBertForSequenceClassification,
        TFDistilBertForTokenClassification,
        TFDistilBertMainLayer,
        TFDistilBertModel,
        TFDistilBertPreTrainedModel,
    )

  try:
    if not is_flax_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_flax_distilbert import (
        FlaxDistilBertForMaskedLM,
        FlaxDistilBertForMultipleChoice,
        FlaxDistilBertForQuestionAnswering,
        FlaxDistilBertForSequenceClassification,
        FlaxDistilBertForTokenClassification,
        FlaxDistilBertModel,
        FlaxDistilBertPreTrainedModel,
    )

else:
  import sys

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