






def 						_A     (       SCREAMING_SNAKE_CASE__						:			float  ,						SCREAMING_SNAKE_CASE__						:			float ):
    UpperCamelCase :int										=     float()
    try:
        UpperCamelCase :List[Any]										=     mass * acceleration
    except Exception:
        return -0.0
    return force


if __name__ == "__main__":
       import doctest

       # run doctest
       doctest.testmod()

       # demo
       __snake_case							      =						1_2.5
       __snake_case							      =						10
       __snake_case							      =						newtons_second_law_of_motion(mass, acceleration)
       print("""The force is """, force, """N""")













from typing import TYPE_CHECKING

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


__snake_case							      =						{
    """configuration_open_llama""": ["""OPEN_LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP""", """OpenLlamaConfig"""],
}

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

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

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 __snake_case							      =						[
     """OpenLlamaForCausalLM""",
     """OpenLlamaModel""",
     """OpenLlamaPreTrainedModel""",
     """OpenLlamaForSequenceClassification""",
 ]


if TYPE_CHECKING:
 from .configuration_open_llama import OPEN_LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP, OpenLlamaConfig

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

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

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_open_llama import (
      OpenLlamaForCausalLM,
      OpenLlamaForSequenceClassification,
      OpenLlamaModel,
      OpenLlamaPreTrainedModel,
  )


else:
 import sys

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





