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


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

UpperCAmelCase__	:  Any      =   {
    # 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 UpperCAmelCase     (		SCREAMING_SNAKE_CASE__     ):





   '''simple docstring'''
   __UpperCamelCase	:					Union[str, Any]				       =					'''graphormer'''
   __UpperCamelCase	:					List[Any]				       =					['''past_key_values''']


   def __init__(      self  :							Dict    ,    lowerCAmelCase_  :							int = 1    ,    lowerCAmelCase_  :							int = 5_1_2 * 9    ,    lowerCAmelCase_  :							int = 5_1_2 * 3    ,    lowerCAmelCase_  :							int = 5_1_2    ,    lowerCAmelCase_  :							int = 5_1_2    ,    lowerCAmelCase_  :							int = 5_1_2    ,    lowerCAmelCase_  :							int = 1_2_8    ,    lowerCAmelCase_  :							int = 5    ,    lowerCAmelCase_  :							int = 1_0_2_4    ,    lowerCAmelCase_  :							str = "multi_hop"    ,    lowerCAmelCase_  :							int = 5_1_2    ,    lowerCAmelCase_  :							bool = False    ,    lowerCAmelCase_  :							int = 1_2    ,    lowerCAmelCase_  :							int = 7_6_8    ,    lowerCAmelCase_  :							int = 7_6_8    ,    lowerCAmelCase_  :							int = 3_2    ,    lowerCAmelCase_  :							float = 0.1    ,    lowerCAmelCase_  :							float = 0.1    ,    lowerCAmelCase_  :							float = 0.0    ,    lowerCAmelCase_  :							bool = False    ,    lowerCAmelCase_  :							bool = False    ,    lowerCAmelCase_  :							bool = False    ,    lowerCAmelCase_  :							str = "gelu"    ,    lowerCAmelCase_  :							float = None    ,    lowerCAmelCase_  :							bool = False    ,    lowerCAmelCase_  :							int = 0    ,    lowerCAmelCase_  :							bool = False    ,    lowerCAmelCase_  :							float = 0.0    ,    lowerCAmelCase_  :							int = 8    ,    lowerCAmelCase_  :							int = None    ,    lowerCAmelCase_  :							int = None    ,    lowerCAmelCase_  :							bool = True    ,    lowerCAmelCase_  :							bool = True    ,    lowerCAmelCase_  :							List[Any]=0    ,    lowerCAmelCase_  :							Optional[int]=1    ,    lowerCAmelCase_  :							Optional[int]=2    ,    **lowerCAmelCase_  :							int    ,    ):

      """simple docstring"""
      _A:						List[str]	    = num_classes
      _A:						Dict	    = num_atoms
      _A:						int	    = num_in_degree
      _A:						Tuple	    = num_out_degree
      _A:						Dict	    = num_edges
      _A:						Optional[int]	    = num_spatial
      _A:						List[Any]	    = num_edge_dis
      _A:						List[Any]	    = edge_type
      _A:						Optional[int]	    = multi_hop_max_dist
      _A:						Optional[int]	    = spatial_pos_max
      _A:						Tuple	    = max_nodes
      _A:						Dict	    = num_hidden_layers
      _A:						Dict	    = embedding_dim
      _A:						List[str]	    = embedding_dim
      _A:						List[Any]	    = ffn_embedding_dim
      _A:						Union[str, Any]	    = num_attention_heads
      _A:						List[Any]	    = dropout
      _A:						Optional[int]	    = attention_dropout
      _A:						Tuple	    = layerdrop
      _A:						str	    = encoder_normalize_before
      _A:						List[str]	    = pre_layernorm
      _A:						Union[str, Any]	    = apply_graphormer_init
      _A:						Any	    = activation_fn
      _A:						Any	    = embed_scale
      _A:						int	    = freeze_embeddings
      _A:						str	    = num_trans_layers_to_freeze
      _A:						int	    = share_input_output_embed
      _A:						str	    = traceable
      _A:						Dict	    = q_noise
      _A:						Dict	    = qn_block_size

      # These parameters are here for future extensions
      # atm, the model only supports self attention
      _A:						Dict	    = kdim
      _A:						str	    = vdim
      _A:						List[str]	    = self_attention
      _A:						int	    = bias

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






import pytest

from datasets.utils.version import Version






@pytest.mark.parametrize(
    '''other, expected_equality'''	,	[
        (Version('''1.0.0'''   ), True),
        ('''1.0.0''', True),
        (Version('''2.0.0'''   ), False),
        ('''2.0.0''', False),
        ('''1''', False),
        ('''a''', False),
        (1, False),
        (None, False),
    ]	,	)
def 						lowerCamelCase__							(      a	,	a   )   ->     str:
   _A:						Tuple	    = Version('''1.0.0'''   )
   assert (version == other) is expected_equality
   assert (version != other) is not expected_equality
   assert (hash(a   ) == hash(a   )) is expected_equality



