from typing import TYPE_CHECKING

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


lowerCAmelCase__							= {
    'configuration_open_llama': ['OPEN_LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'OpenLlamaConfig'],
}

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

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

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCAmelCase__							= [
        '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

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

from ..utils import DummyObject, requires_backends
class 				a_ (						metaclass=SCREAMING_SNAKE_CASE						):






 '''simple docstring'''






 UpperCAmelCase_	 =					['tensorflow_text']




 def __init__(			self					:  Tuple			,    *lowercase__					:  str			,    **lowercase__					:  Union[str, Any]):







        '''simple docstring'''



        requires_backends(self			,    ['tensorflow_text'])
