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


lowerCamelCase_  :       Tuple					      =     logging.get_logger(__name__)

lowerCamelCase_  :       Tuple					      =     {
    """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 				_UpperCamelCase (    _A     ):






			'''simple docstring'''

			__UpperCamelCase					:  Any    					=       """cpmant"""

			def __init__(				self       :				List[Any]  ,		snake_case_       :				int = 3_0720  ,		snake_case_       :				int = 4096  ,		snake_case_       :				int = 32  ,		snake_case_       :				int = 128  ,		snake_case_       :				int = 1_0240  ,		snake_case_       :				int = 48  ,		snake_case_       :				int = 0.0  ,		snake_case_       :				int = 512  ,		snake_case_       :				int = 2048  ,		snake_case_       :				int = 1e-6  ,		snake_case_       :				float = 1.0  ,		snake_case_       :				int = 32  ,		snake_case_       :				int = 32  ,		snake_case_       :				int = 32  ,		snake_case_       :				bool = True  ,		**snake_case_       :				str  ,		):
							super().__init__(**snake_case_					)
							UpperCamelCase_:							Tuple		=  prompt_types
							UpperCamelCase_:							Union[str, Any]		=  prompt_length
							UpperCamelCase_:							Tuple		=  segment_types
							UpperCamelCase_:							Dict		=  hidden_size
							UpperCamelCase_:							str		=  num_attention_heads
							UpperCamelCase_:							Any		=  dim_head
							UpperCamelCase_:							str		=  dim_ff
							UpperCamelCase_:							Any		=  num_hidden_layers
							UpperCamelCase_:							List[str]		=  position_bias_num_buckets
							UpperCamelCase_:							Dict		=  position_bias_max_distance
							UpperCamelCase_:							Any		=  dropout_p
							UpperCamelCase_:							int		=  eps
							UpperCamelCase_:							Tuple		=  use_cache
							UpperCamelCase_:							Tuple		=  vocab_size
							UpperCamelCase_:							Optional[int]		=  init_std








import warnings

from ...utils import logging
from .image_processing_mobilenet_va import MobileNetVaImageProcessor


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

class 				_UpperCamelCase (    _A     ):






			'''simple docstring'''

			def __init__(				self       :				Dict  ,		*snake_case_       :				Optional[int]  ,		**snake_case_       :				List[Any]					):
							warnings.warn(
							    """The class MobileNetV2FeatureExtractor is deprecated and will be removed in version 5 of Transformers."""
							    """ Please use MobileNetV2ImageProcessor instead."""  ,		snake_case_  ,		)
							super().__init__(*snake_case_  ,		**snake_case_					)






