


'''simple docstring'''






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


__UpperCAmelCase    				=							logging.get_logger(__name__)

__UpperCAmelCase    				=							{
    # pcqm4mv1 now deprecated
    """graphormer-base""": """https://huggingface.co/clefourrier/graphormer-base-pcqm4mv2/resolve/main/config.json""",
    # See all Graphormer models at https://huggingface.co/models?filter=graphormer
}




class 		a__				(							_A  ):





							'''simple docstring'''






							lowercase__			:   Dict							=      """graphormer"""
							lowercase__			:   Any							=      ["""past_key_values"""]







							def __init__(		self					,    lowerCamelCase_ = 1					,    lowerCamelCase_ = 5_12 * 9					,    lowerCamelCase_ = 5_12 * 3					,    lowerCamelCase_ = 5_12					,    lowerCamelCase_ = 5_12					,    lowerCamelCase_ = 5_12					,    lowerCamelCase_ = 1_28					,    lowerCamelCase_ = 5					,    lowerCamelCase_ = 10_24					,    lowerCamelCase_ = "multi_hop"					,    lowerCamelCase_ = 5_12					,    lowerCamelCase_ = False					,    lowerCamelCase_ = 12					,    lowerCamelCase_ = 7_68					,    lowerCamelCase_ = 7_68					,    lowerCamelCase_ = 32					,    lowerCamelCase_ = 0.1					,    lowerCamelCase_ = 0.1					,    lowerCamelCase_ = 0.0					,    lowerCamelCase_ = False					,    lowerCamelCase_ = False					,    lowerCamelCase_ = False					,    lowerCamelCase_ = "gelu"					,    lowerCamelCase_ = None					,    lowerCamelCase_ = False					,    lowerCamelCase_ = 0					,    lowerCamelCase_ = False					,    lowerCamelCase_ = 0.0					,    lowerCamelCase_ = 8					,    lowerCamelCase_ = None					,    lowerCamelCase_ = None					,    lowerCamelCase_ = True					,    lowerCamelCase_ = True					,    lowerCamelCase_=0					,    lowerCamelCase_=1					,    lowerCamelCase_=2					,    **lowerCamelCase_					,    )       ->							Optional[Any]:
														lowerCAmelCase__          =	num_classes
														lowerCAmelCase__          =	num_atoms
														lowerCAmelCase__          =	num_in_degree
														lowerCAmelCase__          =	num_out_degree
														lowerCAmelCase__          =	num_edges
														lowerCAmelCase__          =	num_spatial
														lowerCAmelCase__          =	num_edge_dis
														lowerCAmelCase__          =	edge_type
														lowerCAmelCase__          =	multi_hop_max_dist
														lowerCAmelCase__          =	spatial_pos_max
														lowerCAmelCase__          =	max_nodes
														lowerCAmelCase__          =	num_hidden_layers
														lowerCAmelCase__          =	embedding_dim
														lowerCAmelCase__          =	embedding_dim
														lowerCAmelCase__          =	ffn_embedding_dim
														lowerCAmelCase__          =	num_attention_heads
														lowerCAmelCase__          =	dropout
														lowerCAmelCase__          =	attention_dropout
														lowerCAmelCase__          =	layerdrop
														lowerCAmelCase__          =	encoder_normalize_before
														lowerCAmelCase__          =	pre_layernorm
														lowerCAmelCase__          =	apply_graphormer_init
														lowerCAmelCase__          =	activation_fn
														lowerCAmelCase__          =	embed_scale
														lowerCAmelCase__          =	freeze_embeddings
														lowerCAmelCase__          =	num_trans_layers_to_freeze
														lowerCAmelCase__          =	share_input_output_embed
														lowerCAmelCase__          =	traceable
														lowerCAmelCase__          =	q_noise
														lowerCAmelCase__          =	qn_block_size

														# These parameters are here for future extensions
														# atm, the model only supports self attention
														lowerCAmelCase__          =	kdim
														lowerCAmelCase__          =	vdim
														lowerCAmelCase__          =	self_attention
														lowerCAmelCase__          =	bias

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

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_					)






