



'''simple docstring'''






from ...configuration_utils import PretrainedConfig
from ...utils import logging


A_							: List[Any]						 =	logging.get_logger(__name__)

A_							: Optional[int]						 =	{
    """sayakpaul/vit-msn-base""": """https://huggingface.co/sayakpaul/vit-msn-base/resolve/main/config.json""",
    # See all ViT MSN models at https://huggingface.co/models?filter=vit_msn
}



class 							lowercase       (  _lowerCamelCase				):


 """simple docstring"""


 UpperCAmelCase							=  """vit_msn"""







 def __init__(							self  ,a_=768  ,a_=12  ,a_=12  ,a_=3_072  ,a_="gelu"  ,a_=0.0  ,a_=0.0  ,a_=0.02  ,a_=1E-0_6  ,a_=224  ,a_=16  ,a_=3  ,a_=True  ,**a_  ,)		->   Dict:
        super().__init__(**a_							)

        _UpperCAmelCase  :						Optional[int]			     = hidden_size
        _UpperCAmelCase  :						Optional[int]			     = num_hidden_layers
        _UpperCAmelCase  :						Any			     = num_attention_heads
        _UpperCAmelCase  :						Tuple			     = intermediate_size
        _UpperCAmelCase  :						Tuple			     = hidden_act
        _UpperCAmelCase  :						Tuple			     = hidden_dropout_prob
        _UpperCAmelCase  :						str			     = attention_probs_dropout_prob
        _UpperCAmelCase  :						Optional[Any]			     = initializer_range
        _UpperCAmelCase  :						Tuple			     = layer_norm_eps
        _UpperCAmelCase  :						List[str]			     = image_size
        _UpperCAmelCase  :						Any			     = patch_size
        _UpperCAmelCase  :						str			     = num_channels
        _UpperCAmelCase  :						Union[str, Any]			     = qkv_bias








'''simple docstring'''






from typing import TYPE_CHECKING

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


A_							: Optional[Any]						 =	{
    """configuration_llama""": ["""LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LlamaConfig"""],
}

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

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

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   A_							: Optional[int]						 =	[
       """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

   A_							: Any						 =	_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)



