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     snake_case_			(						__A			):
   __A      :						Union[str, Any]   =							"graphormer"
   __A      :						Optional[Any]   =							["past_key_values"]






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

       # These parameters are here for future extensions
       # atm, the model only supports self attention
       lowercase__					:  Any          =							kdim
       lowercase__					:  Optional[Any]          =							vdim
       lowercase__					:  Any          =							self_attention
       lowercase__					:  Any          =							bias

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




from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


UpperCamelCase    				=		{'''configuration_vit_hybrid''': ['''VIT_HYBRID_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ViTHybridConfig''']}

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      UpperCamelCase    				=		[
          '''VIT_HYBRID_PRETRAINED_MODEL_ARCHIVE_LIST''',
          '''ViTHybridForImageClassification''',
          '''ViTHybridModel''',
          '''ViTHybridPreTrainedModel''',
      ]

try:
      if not is_vision_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      UpperCamelCase    				=		['''ViTHybridImageProcessor''']


if TYPE_CHECKING:
      from .configuration_vit_hybrid import VIT_HYBRID_PRETRAINED_CONFIG_ARCHIVE_MAP, ViTHybridConfig

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_vit_hybrid import (
                VIT_HYBRID_PRETRAINED_MODEL_ARCHIVE_LIST,
                ViTHybridForImageClassification,
                ViTHybridModel,
                ViTHybridPreTrainedModel,
            )

      try:
            if not is_vision_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .image_processing_vit_hybrid import ViTHybridImageProcessor


else:
      import sys

      UpperCamelCase    				=		_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)



