




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


lowerCamelCase_  						=   logging.get_logger(__name__)

lowerCamelCase_  						=   {
    # 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					( __lowerCamelCase     ):


     """simple docstring"""


     _A				:    List[Any]									=  "graphormer"
     _A				:    str									=  ["past_key_values"]




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


         '''simple docstring'''





         SCREAMING_SNAKE_CASE__								=num_classes
         SCREAMING_SNAKE_CASE__								=num_atoms
         SCREAMING_SNAKE_CASE__								=num_in_degree
         SCREAMING_SNAKE_CASE__								=num_out_degree
         SCREAMING_SNAKE_CASE__								=num_edges
         SCREAMING_SNAKE_CASE__								=num_spatial
         SCREAMING_SNAKE_CASE__								=num_edge_dis
         SCREAMING_SNAKE_CASE__								=edge_type
         SCREAMING_SNAKE_CASE__								=multi_hop_max_dist
         SCREAMING_SNAKE_CASE__								=spatial_pos_max
         SCREAMING_SNAKE_CASE__								=max_nodes
         SCREAMING_SNAKE_CASE__								=num_hidden_layers
         SCREAMING_SNAKE_CASE__								=embedding_dim
         SCREAMING_SNAKE_CASE__								=embedding_dim
         SCREAMING_SNAKE_CASE__								=ffn_embedding_dim
         SCREAMING_SNAKE_CASE__								=num_attention_heads
         SCREAMING_SNAKE_CASE__								=dropout
         SCREAMING_SNAKE_CASE__								=attention_dropout
         SCREAMING_SNAKE_CASE__								=layerdrop
         SCREAMING_SNAKE_CASE__								=encoder_normalize_before
         SCREAMING_SNAKE_CASE__								=pre_layernorm
         SCREAMING_SNAKE_CASE__								=apply_graphormer_init
         SCREAMING_SNAKE_CASE__								=activation_fn
         SCREAMING_SNAKE_CASE__								=embed_scale
         SCREAMING_SNAKE_CASE__								=freeze_embeddings
         SCREAMING_SNAKE_CASE__								=num_trans_layers_to_freeze
         SCREAMING_SNAKE_CASE__								=share_input_output_embed
         SCREAMING_SNAKE_CASE__								=traceable
         SCREAMING_SNAKE_CASE__								=q_noise
         SCREAMING_SNAKE_CASE__								=qn_block_size

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

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












import unittest
from dataclasses import dataclass
from typing import Optional

from transformers.utils import ModelOutput
@dataclass
class       __a					( __lowerCamelCase     ):


     """simple docstring"""


     _A				:    float
     _A				:    Optional[float]									=  None
     _A				:    Optional[float]									=  None






class       __a					( unittest.TestCase     ):


     """simple docstring"""


     def   __A				(	self			: Dict						)		->   Optional[int]:


         '''simple docstring'''





         SCREAMING_SNAKE_CASE__								=ModelOutputTest(a=3_0						)
         self.assertEqual(x.a				,3_0						)
         self.assertIsNone(x.b						)
         self.assertIsNone(x.c						)
         with self.assertRaises(_UpperCamelCase						):
             SCREAMING_SNAKE_CASE__								=x.d




     def   __A				(	self			: Tuple						)		->   Dict:


         '''simple docstring'''





         SCREAMING_SNAKE_CASE__								=ModelOutputTest(a=3_0				,b=1_0						)
         self.assertEqual(x[0]				,3_0						)
         self.assertEqual(x[1]				,1_0						)
         self.assertEqual(x[:2]				,(3_0, 1_0)						)
         self.assertEqual(x[:]				,(3_0, 1_0)						)

         SCREAMING_SNAKE_CASE__								=ModelOutputTest(a=3_0				,c=1_0						)
         self.assertEqual(x[0]				,3_0						)
         self.assertEqual(x[1]				,1_0						)
         self.assertEqual(x[:2]				,(3_0, 1_0)						)
         self.assertEqual(x[:]				,(3_0, 1_0)						)




     def   __A				(	self			: List[str]						)		->   Dict:


         '''simple docstring'''





         SCREAMING_SNAKE_CASE__								=ModelOutputTest(a=3_0				,b=1_0						)
         self.assertEqual(x["""a"""]				,3_0						)
         self.assertEqual(x["""b"""]				,1_0						)
         with self.assertRaises(_UpperCamelCase						):
             SCREAMING_SNAKE_CASE__								=x["""c"""]

         SCREAMING_SNAKE_CASE__								=ModelOutputTest(a=3_0				,c=1_0						)
         self.assertEqual(x["""a"""]				,3_0						)
         self.assertEqual(x["""c"""]				,1_0						)
         with self.assertRaises(_UpperCamelCase						):
             SCREAMING_SNAKE_CASE__								=x["""b"""]




     def   __A				(	self			: Optional[int]						)		->   List[str]:


         '''simple docstring'''





         SCREAMING_SNAKE_CASE__								=ModelOutputTest(a=3_0						)
         self.assertEqual(list(x.keys()						)				,["""a"""]						)
         self.assertEqual(list(x.values()						)				,[3_0]						)
         self.assertEqual(list(x.items()						)				,[("""a""", 3_0)]						)
         self.assertEqual(list(_UpperCamelCase						)				,["""a"""]						)

         SCREAMING_SNAKE_CASE__								=ModelOutputTest(a=3_0				,b=1_0						)
         self.assertEqual(list(x.keys()						)				,["""a""", """b"""]						)
         self.assertEqual(list(x.values()						)				,[3_0, 1_0]						)
         self.assertEqual(list(x.items()						)				,[("""a""", 3_0), ("""b""", 1_0)]						)
         self.assertEqual(list(_UpperCamelCase						)				,["""a""", """b"""]						)

         SCREAMING_SNAKE_CASE__								=ModelOutputTest(a=3_0				,c=1_0						)
         self.assertEqual(list(x.keys()						)				,["""a""", """c"""]						)
         self.assertEqual(list(x.values()						)				,[3_0, 1_0]						)
         self.assertEqual(list(x.items()						)				,[("""a""", 3_0), ("""c""", 1_0)]						)
         self.assertEqual(list(_UpperCamelCase						)				,["""a""", """c"""]						)

         with self.assertRaises(_UpperCamelCase						):
             SCREAMING_SNAKE_CASE__								=x.update({"""d""": 2_0}						)
         with self.assertRaises(_UpperCamelCase						):
             del x["a"]
         with self.assertRaises(_UpperCamelCase						):
             SCREAMING_SNAKE_CASE__								=x.pop("""a"""						)
         with self.assertRaises(_UpperCamelCase						):
             SCREAMING_SNAKE_CASE__								=x.setdefault("""d"""				,3_2						)




     def   __A				(	self			: int						)		->   List[Any]:


         '''simple docstring'''





         SCREAMING_SNAKE_CASE__								=ModelOutputTest(a=3_0						)
         SCREAMING_SNAKE_CASE__								=1_0
         self.assertEqual(x.a				,1_0						)
         self.assertEqual(x["""a"""]				,1_0						)




     def   __A				(	self			: Union[str, Any]						)		->   Optional[Any]:


         '''simple docstring'''





         SCREAMING_SNAKE_CASE__								=ModelOutputTest(a=3_0						)
         SCREAMING_SNAKE_CASE__								=1_0
         self.assertEqual(x.a				,1_0						)
         self.assertEqual(x["""a"""]				,1_0						)




     def   __A				(	self			: Dict						)		->   List[str]:


         '''simple docstring'''





         SCREAMING_SNAKE_CASE__								=ModelOutputTest({"""a""": 3_0, """b""": 1_0}						)
         self.assertEqual(list(x.keys()						)				,["""a""", """b"""]						)
         self.assertEqual(x.a				,3_0						)
         self.assertEqual(x.b				,1_0						)




     def   __A				(	self			: Optional[int]						)		->   int:


         '''simple docstring'''





         SCREAMING_SNAKE_CASE__								=ModelOutputTest([("""a""", 3_0), ("""b""", 1_0)]						)
         self.assertEqual(list(x.keys()						)				,["""a""", """b"""]						)
         self.assertEqual(x.a				,3_0						)
         self.assertEqual(x.b				,1_0						)

         with self.assertRaises(_UpperCamelCase						):
             SCREAMING_SNAKE_CASE__								=ModelOutputTest([("""a""", 3_0), (1_0, 1_0)]						)

         SCREAMING_SNAKE_CASE__								=ModelOutputTest(a=(3_0, 3_0)						)
         self.assertEqual(list(x.keys()						)				,["""a"""]						)
         self.assertEqual(x.a				,(3_0, 3_0)						)






