





def    __lowercase   (      _SCREAMING_SNAKE_CASE ,						_SCREAMING_SNAKE_CASE	) ->   None:


      '''simple docstring'''


      SCREAMING_SNAKE_CASE		=						len(_SCREAMING_SNAKE_CASE	)
      print("""The following activities are selected:"""	)

      # The first activity is always selected
      SCREAMING_SNAKE_CASE		=						0
      print(_SCREAMING_SNAKE_CASE ,						end=""","""	)

      # Consider rest of the activities
      for j in range(_SCREAMING_SNAKE_CASE	):
            # If this activity has start time greater than
            # or equal to the finish time of previously
            # selected activity, then select it
            if start[j] >= finish[i]:
                  print(_SCREAMING_SNAKE_CASE ,						end=""","""	)
                  SCREAMING_SNAKE_CASE		=						j


if __name__ == "__main__":
      import doctest

      doctest.testmod()

      SCREAMING_SNAKE_CASE_						   =       [1, 3, 0, 5, 8, 5]
      SCREAMING_SNAKE_CASE_						   =       [2, 4, 6, 7, 9, 9]
      print_max_activities(start, finish)









from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_tokenizers_available,
    is_torch_available,
)


SCREAMING_SNAKE_CASE_						   =       {
    """configuration_llama""": ["""LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LlamaConfig"""],
}

try:
      if not is_sentencepiece_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      SCREAMING_SNAKE_CASE_						   =       ["""LlamaTokenizer"""]

try:
      if not is_tokenizers_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      SCREAMING_SNAKE_CASE_						   =       ["""LlamaTokenizerFast"""]

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      SCREAMING_SNAKE_CASE_						   =       [
          """LlamaForCausalLM""",
          """LlamaModel""",
          """LlamaPreTrainedModel""",
          """LlamaForSequenceClassification""",
      ]


if TYPE_CHECKING:
      from .configuration_llama import LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP, LlamaConfig

      try:
            if not is_sentencepiece_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .tokenization_llama import LlamaTokenizer

      try:
            if not is_tokenizers_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .tokenization_llama_fast import LlamaTokenizerFast

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_llama import LlamaForCausalLM, LlamaForSequenceClassification, LlamaModel, LlamaPreTrainedModel


else:
      import sys

      SCREAMING_SNAKE_CASE_						   =       _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)


