



'''simple docstring'''



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


_lowercase    :    Tuple			     =  logging.get_logger(__name__)

_lowercase    :    Optional[Any]			     =  {
    """uw-madison/mra-base-512-4""": """https://huggingface.co/uw-madison/mra-base-512-4/resolve/main/config.json""",
}






class  UpperCamelCase__(     lowerCAmelCase ):
				__magic_name__       :   Tuple							= "mra"




				def __init__(	self    :				str   ,					lowerCAmelCase    :				List[Any]=50265   ,					lowerCAmelCase    :				List[Any]=768   ,					lowerCAmelCase    :				Any=12   ,					lowerCAmelCase    :				Union[str, Any]=12   ,					lowerCAmelCase    :				str=3072   ,					lowerCAmelCase    :				Any="gelu"   ,					lowerCAmelCase    :				int=0.1   ,					lowerCAmelCase    :				Any=0.1   ,					lowerCAmelCase    :				Dict=512   ,					lowerCAmelCase    :				Any=1   ,					lowerCAmelCase    :				List[str]=0.02   ,					lowerCAmelCase    :				int=1E-5   ,					lowerCAmelCase    :				Optional[Any]="absolute"   ,					lowerCAmelCase    :				Any=4   ,					lowerCAmelCase    :				Union[str, Any]="full"   ,					lowerCAmelCase    :				Any=0   ,					lowerCAmelCase    :				Optional[int]=0   ,					lowerCAmelCase    :				Any=1   ,					lowerCAmelCase    :				Any=0   ,					lowerCAmelCase    :				Dict=2   ,					**lowerCAmelCase    :				List[Any]   ,					)->  Any:

										"""simple docstring"""




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

										UpperCAmelCase         =			vocab_size
										UpperCAmelCase         =			max_position_embeddings
										UpperCAmelCase         =			hidden_size
										UpperCAmelCase         =			num_hidden_layers
										UpperCAmelCase         =			num_attention_heads
										UpperCAmelCase         =			intermediate_size
										UpperCAmelCase         =			hidden_act
										UpperCAmelCase         =			hidden_dropout_prob
										UpperCAmelCase         =			attention_probs_dropout_prob
										UpperCAmelCase         =			initializer_range
										UpperCAmelCase         =			type_vocab_size
										UpperCAmelCase         =			layer_norm_eps
										UpperCAmelCase         =			position_embedding_type
										UpperCAmelCase         =			block_per_row
										UpperCAmelCase         =			approx_mode
										UpperCAmelCase         =			initial_prior_first_n_blocks
										UpperCAmelCase         =			initial_prior_diagonal_n_blocks









'''simple docstring'''



from typing import TYPE_CHECKING

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


_lowercase    :    Any			     =  {
    """configuration_gpt_bigcode""": ["""GPT_BIGCODE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GPTBigCodeConfig"""],
}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_lowercase    :    Optional[int]			     =  [
	    """GPT_BIGCODE_PRETRAINED_MODEL_ARCHIVE_LIST""",
	    """GPTBigCodeForSequenceClassification""",
	    """GPTBigCodeForTokenClassification""",
	    """GPTBigCodeForCausalLM""",
	    """GPTBigCodeModel""",
	    """GPTBigCodePreTrainedModel""",
	]

if TYPE_CHECKING:
	from .configuration_gpt_bigcode import GPT_BIGCODE_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTBigCodeConfig

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_gpt_bigcode import (
		    GPT_BIGCODE_PRETRAINED_MODEL_ARCHIVE_LIST,
		    GPTBigCodeForCausalLM,
		    GPTBigCodeForSequenceClassification,
		    GPTBigCodeForTokenClassification,
		    GPTBigCodeModel,
		    GPTBigCodePreTrainedModel,
		)


else:
	import sys

	_lowercase    :    Tuple			     =  _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)





