




"""simple docstring"""

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


_lowerCamelCase	:      Any   =							logging.get_logger(__name__)

_lowerCamelCase	:      Optional[int]   =							{
    """openbmb/cpm-ant-10b""": """https://huggingface.co/openbmb/cpm-ant-10b/blob/main/config.json"""
    # See all CPMAnt models at https://huggingface.co/models?filter=cpmant
}

class 							lowercase   (     a_):
				__lowerCAmelCase     :     List[str]								= "cpmant"







				def __init__(				self :       Tuple   ,  _lowerCamelCase :       int = 3_07_20   ,  _lowerCamelCase :       int = 40_96   ,  _lowerCamelCase :       int = 32   ,  _lowerCamelCase :       int = 1_28   ,  _lowerCamelCase :       int = 1_02_40   ,  _lowerCamelCase :       int = 48   ,  _lowerCamelCase :       int = 0.0   ,  _lowerCamelCase :       int = 5_12   ,  _lowerCamelCase :       int = 20_48   ,  _lowerCamelCase :       int = 1E-6   ,  _lowerCamelCase :       float = 1.0   ,  _lowerCamelCase :       int = 32   ,  _lowerCamelCase :       int = 32   ,  _lowerCamelCase :       int = 32   ,  _lowerCamelCase :       bool = True   ,  **_lowerCamelCase :       Tuple   ,  ):



					"""simple docstring"""

					super().__init__(**UpperCAmelCase_							)
					A_	:					Union[str, Any]						 =		prompt_types
					A_	:					List[str]						 =		prompt_length
					A_	:					List[Any]						 =		segment_types
					A_	:					Any						 =		hidden_size
					A_	:					Optional[int]						 =		num_attention_heads
					A_	:					Union[str, Any]						 =		dim_head
					A_	:					int						 =		dim_ff
					A_	:					Union[str, Any]						 =		num_hidden_layers
					A_	:					List[Any]						 =		position_bias_num_buckets
					A_	:					Optional[int]						 =		position_bias_max_distance
					A_	:					str						 =		dropout_p
					A_	:					List[str]						 =		eps
					A_	:					Dict						 =		use_cache
					A_	:					Tuple						 =		vocab_size
					A_	:					Optional[Any]						 =		init_std






'''simple docstring'''





from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


UpperCamelCase       :     Dict			=    logging.get_logger(__name__)

UpperCamelCase       :     Tuple			=    {
    """flaubert/flaubert_small_cased""": """https://huggingface.co/flaubert/flaubert_small_cased/resolve/main/config.json""",
    """flaubert/flaubert_base_uncased""": """https://huggingface.co/flaubert/flaubert_base_uncased/resolve/main/config.json""",
    """flaubert/flaubert_base_cased""": """https://huggingface.co/flaubert/flaubert_base_cased/resolve/main/config.json""",
    """flaubert/flaubert_large_cased""": """https://huggingface.co/flaubert/flaubert_large_cased/resolve/main/config.json""",
}



class   UpperCamelCase					(       a_       ):







    """simple docstring"""





    A     :    int				=			"flaubert"
    A     :    List[str]				=			{
        "hidden_size": "emb_dim",
        "num_attention_heads": "n_heads",
        "num_hidden_layers": "n_layers",
        "n_words": "vocab_size",  # For backward compatibility
    }





    def __init__(					self     :						str							,							UpperCAmelCase_     :						Optional[int]=False							,							UpperCAmelCase_     :						List[Any]=0.0							,							UpperCAmelCase_     :						List[Any]=3_0_1_4_5							,							UpperCAmelCase_     :						Union[str, Any]=2_0_4_8							,							UpperCAmelCase_     :						Tuple=1_2							,							UpperCAmelCase_     :						str=1_6							,							UpperCAmelCase_     :						Tuple=0.1							,							UpperCAmelCase_     :						str=0.1							,							UpperCAmelCase_     :						str=True							,							UpperCAmelCase_     :						Union[str, Any]=False							,							UpperCAmelCase_     :						Any=False							,							UpperCAmelCase_     :						str=False							,							UpperCAmelCase_     :						Tuple=1							,							UpperCAmelCase_     :						str=True							,							UpperCAmelCase_     :						Tuple=5_1_2							,							UpperCAmelCase_     :						List[str]=2_0_4_8**-0.5							,							UpperCAmelCase_     :						List[Any]=1e-12							,							UpperCAmelCase_     :						Tuple=0.02							,							UpperCAmelCase_     :						Any=0							,							UpperCAmelCase_     :						List[Any]=1							,							UpperCAmelCase_     :						str=2							,							UpperCAmelCase_     :						Optional[Any]=3							,							UpperCAmelCase_     :						List[str]=5							,							UpperCAmelCase_     :						str=True							,							UpperCAmelCase_     :						List[Any]="first"							,							UpperCAmelCase_     :						Any=True							,							UpperCAmelCase_     :						Union[str, Any]=None							,							UpperCAmelCase_     :						Union[str, Any]=True							,							UpperCAmelCase_     :						Any=0.1							,							UpperCAmelCase_     :						List[Any]=5							,							UpperCAmelCase_     :						List[Any]=5							,							UpperCAmelCase_     :						Union[str, Any]=0							,							UpperCAmelCase_     :						Optional[Any]=0							,							UpperCAmelCase_     :						List[Any]=2							,							UpperCAmelCase_     :						List[Any]=0							,							**UpperCAmelCase_     :						List[Any]							,							):


         """simple docstring"""







         a					:							Any							= pre_norm
         a					:							str							= layerdrop
         a					:							int							= vocab_size
         a					:							str							= emb_dim
         a					:							Any							= n_layers
         a					:							Dict							= n_heads
         a					:							Union[str, Any]							= dropout
         a					:							List[Any]							= attention_dropout
         a					:							List[str]							= gelu_activation
         a					:							int							= sinusoidal_embeddings
         a					:							Union[str, Any]							= causal
         a					:							str							= asm
         a					:							Tuple							= n_langs
         a					:							Optional[Any]							= use_lang_emb
         a					:							str							= layer_norm_eps
         a					:							Optional[Any]							= bos_index
         a					:							Union[str, Any]							= eos_index
         a					:							str							= pad_index
         a					:							List[str]							= unk_index
         a					:							Dict							= mask_index
         a					:							Optional[Any]							= is_encoder
         a					:							str							= max_position_embeddings
         a					:							Optional[Any]							= embed_init_std
         a					:							str							= init_std
         a					:							Union[str, Any]							= summary_type
         a					:							Tuple							= summary_use_proj
         a					:							Tuple							= summary_activation
         a					:							str							= summary_proj_to_labels
         a					:							List[str]							= summary_first_dropout
         a					:							Any							= start_n_top
         a					:							Optional[Any]							= end_n_top
         a					:							List[Any]							= mask_token_id
         a					:							Optional[Any]							= lang_id

         if "n_words" in kwargs:
              a					:							int							= kwargs['n_words']

         super().__init__(pad_token_id=UpperCAmelCase_							,							bos_token_id=UpperCAmelCase_							,							**UpperCAmelCase_)






class   UpperCamelCase					(       a_       ):







    """simple docstring"""





    @property
    def    SCREAMING_SNAKE_CASE_     (					self     :						str):


         """simple docstring"""







         if self.task == "multiple-choice":
              a					:							int							= {0: 'batch', 1: 'choice', 2: 'sequence'}
         else:
              a					:							Tuple							= {0: 'batch', 1: 'sequence'}
         return OrderedDict(
             [
                 ('input_ids', dynamic_axis),
                 ('attention_mask', dynamic_axis),
             ])

