




'''simple docstring'''

from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


a       :						List[str]								=		{
    '''configuration_chinese_clip''': [
        '''CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''ChineseCLIPConfig''',
        '''ChineseCLIPOnnxConfig''',
        '''ChineseCLIPTextConfig''',
        '''ChineseCLIPVisionConfig''',
    ],
    '''processing_chinese_clip''': ['''ChineseCLIPProcessor'''],
}

try:
						if not is_vision_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						a       :						str								=		['''ChineseCLIPFeatureExtractor''']
						a       :						Any								=		['''ChineseCLIPImageProcessor''']

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						a       :						Optional[Any]								=		[
						    '''CHINESE_CLIP_PRETRAINED_MODEL_ARCHIVE_LIST''',
						    '''ChineseCLIPModel''',
						    '''ChineseCLIPPreTrainedModel''',
						    '''ChineseCLIPTextModel''',
						    '''ChineseCLIPVisionModel''',
						]

if TYPE_CHECKING:
						from .configuration_chinese_clip import (
						    CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP,
						    ChineseCLIPConfig,
						    ChineseCLIPOnnxConfig,
						    ChineseCLIPTextConfig,
						    ChineseCLIPVisionConfig,
						)
						from .processing_chinese_clip import ChineseCLIPProcessor

						try:
												if not is_vision_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .feature_extraction_chinese_clip import ChineseCLIPFeatureExtractor, ChineseCLIPImageProcessor

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_chinese_clip import (
												    CHINESE_CLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
												    ChineseCLIPModel,
												    ChineseCLIPPreTrainedModel,
												    ChineseCLIPTextModel,
												    ChineseCLIPVisionModel,
												)

else:
						import sys

						a       :						int								=		_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)













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


__a   :							Dict						= logging.get_logger(__name__)

__a   :							Dict						= {
    "bigcode/gpt_bigcode-santacoder": "https://huggingface.co/bigcode/gpt_bigcode-santacoder/resolve/main/config.json",
}


class    __lowercase   (						lowercase_	):







     '''simple docstring'''
     SCREAMING_SNAKE_CASE     =					"gpt_bigcode"
     SCREAMING_SNAKE_CASE     =					["past_key_values"]
     SCREAMING_SNAKE_CASE     =					{
         "hidden_size": "n_embd",
         "max_position_embeddings": "n_positions",
         "num_attention_heads": "n_head",
         "num_hidden_layers": "n_layer",
     }




     def __init__(					self							:      List[str]			,						UpperCamelCase_							:      Dict=50_257			,						UpperCamelCase_							:      int=1_024			,						UpperCamelCase_							:      List[Any]=768			,						UpperCamelCase_							:      str=12			,						UpperCamelCase_							:      Union[str, Any]=12			,						UpperCamelCase_							:      Optional[Any]=None			,						UpperCamelCase_							:      Tuple="gelu_pytorch_tanh"			,						UpperCamelCase_							:      Optional[Any]=0.1			,						UpperCamelCase_							:      List[str]=0.1			,						UpperCamelCase_							:      Optional[int]=0.1			,						UpperCamelCase_							:      int=1e-5			,						UpperCamelCase_							:      Tuple=0.02			,						UpperCamelCase_							:      Any=True			,						UpperCamelCase_							:      List[Any]=True			,						UpperCamelCase_							:      Dict=50_256			,						UpperCamelCase_							:      Optional[Any]=50_256			,						UpperCamelCase_							:      int=True			,						UpperCamelCase_							:      List[Any]=True			,						UpperCamelCase_							:      List[Any]=True			,						**UpperCamelCase_							:      int			,						):


         """simple docstring"""



         __A       =						vocab_size
         __A       =						n_positions
         __A       =						n_embd
         __A       =						n_layer
         __A       =						n_head
         __A       =						n_inner
         __A       =						activation_function
         __A       =						resid_pdrop
         __A       =						embd_pdrop
         __A       =						attn_pdrop
         __A       =						layer_norm_epsilon
         __A       =						initializer_range
         __A       =						scale_attn_weights
         __A       =						use_cache
         __A       =						attention_softmax_in_fpaa
         __A       =						scale_attention_softmax_in_fpaa
         __A       =						multi_query

         __A       =						bos_token_id
         __A       =						eos_token_id

         super().__init__(bos_token_id=UpperCamelCase_			,						eos_token_id=UpperCamelCase_			,						**UpperCamelCase_					)




