

from typing import TYPE_CHECKING

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


_SCREAMING_SNAKE_CASE					:  Union[str, Any]             =      {
    '''configuration_llama''': ['''LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''LlamaConfig'''],
}

try:
       if not is_sentencepiece_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       _SCREAMING_SNAKE_CASE					:  List[Any]             =      ['''LlamaTokenizer''']

try:
       if not is_tokenizers_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       _SCREAMING_SNAKE_CASE					:  Optional[int]             =      ['''LlamaTokenizerFast''']

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       _SCREAMING_SNAKE_CASE					:  List[Any]             =      [
           '''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					:  Optional[int]             =      _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)





import warnings

from .generation import TFGenerationMixin






class 	UpperCAmelCase__		(	A__	):






  """simple docstring"""


  warnings.warn(
      "Importing `TFGenerationMixin` from `src/transformers/generation_tf_utils.py` is deprecated and will "
      "be removed in Transformers v5. Import as `from transformers import TFGenerationMixin` instead."						,					A__						,					)


