



from collections import OrderedDict
from typing import Mapping

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


_snake_case		=  logging.get_logger(__name__)

_snake_case		=  {
    "camembert-base": "https://huggingface.co/camembert-base/resolve/main/config.json",
    "umberto-commoncrawl-cased-v1": (
        "https://huggingface.co/Musixmatch/umberto-commoncrawl-cased-v1/resolve/main/config.json"
    ),
    "umberto-wikipedia-uncased-v1": (
        "https://huggingface.co/Musixmatch/umberto-wikipedia-uncased-v1/resolve/main/config.json"
    ),
}



class   UpperCAmelCase_    (       a):
							lowerCamelCase__   			=		'camembert'







							def __init__(   self,			__a=3_0522,			__a=768,			__a=12,			__a=12,			__a=3072,			__a="gelu",			__a=0.1,			__a=0.1,			__a=512,			__a=2,			__a=0.02,			__a=1E-12,			__a=1,			__a=0,			__a=2,			__a="absolute",			__a=True,			__a=None,			**__a,			):

														'''simple docstring'''

														super().__init__(pad_token_id=__a,			bos_token_id=__a,			eos_token_id=__a,			**__a)

														_lowerCAmelCase     :							Optional[Any]    =    vocab_size
														_lowerCAmelCase     :							Optional[int]    =    hidden_size
														_lowerCAmelCase     :							Union[str, Any]    =    num_hidden_layers
														_lowerCAmelCase     :							Optional[int]    =    num_attention_heads
														_lowerCAmelCase     :							Tuple    =    hidden_act
														_lowerCAmelCase     :							Tuple    =    intermediate_size
														_lowerCAmelCase     :							Optional[Any]    =    hidden_dropout_prob
														_lowerCAmelCase     :							Tuple    =    attention_probs_dropout_prob
														_lowerCAmelCase     :							List[Any]    =    max_position_embeddings
														_lowerCAmelCase     :							Optional[Any]    =    type_vocab_size
														_lowerCAmelCase     :							str    =    initializer_range
														_lowerCAmelCase     :							List[Any]    =    layer_norm_eps
														_lowerCAmelCase     :							int    =    position_embedding_type
														_lowerCAmelCase     :							Dict    =    use_cache
														_lowerCAmelCase     :							Dict    =    classifier_dropout



class   UpperCAmelCase_    (       a):







							@property
							def    snake_case__      (   self):

														'''simple docstring'''

														if self.task == "multiple-choice":
																					_lowerCAmelCase     :							Optional[Any]    =    {0: "batch", 1: "choice", 2: "sequence"}
														else:
																					_lowerCAmelCase     :							Union[str, Any]    =    {0: "batch", 1: "sequence"}
														return OrderedDict(
														    [
														        ("input_ids", dynamic_axis),
														        ("attention_mask", dynamic_axis),
														    ])






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


UpperCamelCase__    			=			logging.get_logger(__name__)

UpperCamelCase__    			=			{
    """edbeeching/decision-transformer-gym-hopper-medium""": (
        """https://huggingface.co/edbeeching/decision-transformer-gym-hopper-medium/resolve/main/config.json"""
    ),
    # See all DecisionTransformer models at https://huggingface.co/models?filter=decision_transformer
}
class 			a__    (					snake_case__      ):
						_a							:    Optional[int]					=    """decision_transformer"""
						_a							:    Optional[int]					=    ["""past_key_values"""]
						_a							:    Dict					=    {
						    """max_position_embeddings""": """n_positions""",
						    """num_attention_heads""": """n_head""",
						    """num_hidden_layers""": """n_layer""",
						}






						def __init__(   self		,			_A=1_7		,			_A=4		,			_A=1_2_8		,			_A=4_0_9_6		,			_A=True		,			_A=1		,			_A=1_0_2_4		,			_A=3		,			_A=1		,			_A=None		,			_A="relu"		,			_A=0.1		,			_A=0.1		,			_A=0.1		,			_A=1E-5		,			_A=0.02		,			_A=True		,			_A=True		,			_A=5_0_2_5_6		,			_A=5_0_2_5_6		,			_A=False		,			_A=False		,			**_A		,			):




											"""simple docstring"""



											__lowerCAmelCase				   =       state_dim
											__lowerCAmelCase				   =       act_dim
											__lowerCAmelCase				   =       hidden_size
											__lowerCAmelCase				   =       max_ep_len
											__lowerCAmelCase				   =       action_tanh
											__lowerCAmelCase				   =       vocab_size
											__lowerCAmelCase				   =       n_positions
											__lowerCAmelCase				   =       n_layer
											__lowerCAmelCase				   =       n_head
											__lowerCAmelCase				   =       n_inner
											__lowerCAmelCase				   =       activation_function
											__lowerCAmelCase				   =       resid_pdrop
											__lowerCAmelCase				   =       embd_pdrop
											__lowerCAmelCase				   =       attn_pdrop
											__lowerCAmelCase				   =       layer_norm_epsilon
											__lowerCAmelCase				   =       initializer_range
											__lowerCAmelCase				   =       scale_attn_weights
											__lowerCAmelCase				   =       use_cache
											__lowerCAmelCase				   =       scale_attn_by_inverse_layer_idx
											__lowerCAmelCase				   =       reorder_and_upcast_attn

											__lowerCAmelCase				   =       bos_token_id
											__lowerCAmelCase				   =       eos_token_id

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




