




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 							__lowercase   (			__UpperCamelCase    ):
     _lowerCAmelCase		       =						"graphormer"
     _lowerCAmelCase		       =						["past_key_values"]



     def __init__(  self   :							str      ,		lowercase__   :							int = 1      ,		lowercase__   :							int = 5_1_2 * 9      ,		lowercase__   :							int = 5_1_2 * 3      ,		lowercase__   :							int = 5_1_2      ,		lowercase__   :							int = 5_1_2      ,		lowercase__   :							int = 5_1_2      ,		lowercase__   :							int = 1_2_8      ,		lowercase__   :							int = 5      ,		lowercase__   :							int = 1_0_2_4      ,		lowercase__   :							str = "multi_hop"      ,		lowercase__   :							int = 5_1_2      ,		lowercase__   :							bool = False      ,		lowercase__   :							int = 1_2      ,		lowercase__   :							int = 7_6_8      ,		lowercase__   :							int = 7_6_8      ,		lowercase__   :							int = 3_2      ,		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__   :							List[str]=0      ,		lowercase__   :							Dict=1      ,		lowercase__   :							Dict=2      ,		**lowercase__   :							Union[str, Any]      ,		):
       a_		    =  num_classes
       a_		    =  num_atoms
       a_		    =  num_in_degree
       a_		    =  num_out_degree
       a_		    =  num_edges
       a_		    =  num_spatial
       a_		    =  num_edge_dis
       a_		    =  edge_type
       a_		    =  multi_hop_max_dist
       a_		    =  spatial_pos_max
       a_		    =  max_nodes
       a_		    =  num_hidden_layers
       a_		    =  embedding_dim
       a_		    =  embedding_dim
       a_		    =  ffn_embedding_dim
       a_		    =  num_attention_heads
       a_		    =  dropout
       a_		    =  attention_dropout
       a_		    =  layerdrop
       a_		    =  encoder_normalize_before
       a_		    =  pre_layernorm
       a_		    =  apply_graphormer_init
       a_		    =  activation_fn
       a_		    =  embed_scale
       a_		    =  freeze_embeddings
       a_		    =  num_trans_layers_to_freeze
       a_		    =  share_input_output_embed
       a_		    =  traceable
       a_		    =  q_noise
       a_		    =  qn_block_size

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

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





import json
import os
import unittest

from transformers import HerbertTokenizer, HerbertTokenizerFast
from transformers.models.herbert.tokenization_herbert import VOCAB_FILES_NAMES
from transformers.testing_utils import get_tests_dir, require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin

@require_tokenizers
class 						UpperCAmelCase__     (     __UpperCamelCase		,unittest.TestCase  ):




			'''simple docstring'''






			UpperCamelCase     		=			HerbertTokenizer
			UpperCamelCase     		=			HerbertTokenizerFast
			UpperCamelCase     		=			True




			def 					snake_case__	(  self				:					Tuple					):
					'''simple docstring'''





					super().setUp()

					# Use a simpler test file without japanese/chinese characters
					with open(F'{get_tests_dir()}/fixtures/sample_text_no_unicode.txt'			,			encoding='''utf-8'''					) as f_data:
							__UpperCAmelCase       :	List[str]						=      f_data.read().replace('''\n\n'''			,			'''\n'''					).strip()

					__UpperCAmelCase       :	Dict						=      [
					    '''<s>''',
					    '''</s>''',
					    '''l''',
					    '''o''',
					    '''w''',
					    '''e''',
					    '''r''',
					    '''s''',
					    '''t''',
					    '''i''',
					    '''d''',
					    '''n''',
					    '''w</w>''',
					    '''r</w>''',
					    '''t</w>''',
					    '''lo''',
					    '''low''',
					    '''er</w>''',
					    '''low</w>''',
					    '''lowest</w>''',
					    '''newer</w>''',
					    '''wider</w>''',
					    ''',</w>''',
					    '''<unk>''',
					]
					__UpperCAmelCase       :	Tuple						=      dict(zip(a_			,			range(len(a_					)					)					)					)
					__UpperCAmelCase       :	Optional[int]						=      ['''l o 123''', '''lo w 1456''', '''e r</w> 1789''', '''''']

					__UpperCAmelCase       :	str						=      os.path.join(self.tmpdirname			,			VOCAB_FILES_NAMES['''vocab_file''']					)
					__UpperCAmelCase       :	List[str]						=      os.path.join(self.tmpdirname			,			VOCAB_FILES_NAMES['''merges_file''']					)
					with open(self.vocab_file			,			'''w'''					) as fp:
							fp.write(json.dumps(a_					)					)
					with open(self.merges_file			,			'''w'''					) as fp:
							fp.write('''\n'''.join(a_					)					)




			def 					snake_case__	(  self				:					Union[str, Any]			,			a_				:					Optional[Any]					):
					'''simple docstring'''





					__UpperCAmelCase       :	List[str]						=      '''lower newer'''
					__UpperCAmelCase       :	List[Any]						=      '''lower newer'''
					return input_text, output_text




			def 					snake_case__	(  self				:					int					):
					'''simple docstring'''





					__UpperCAmelCase       :	Any						=      self.tokenizer_class(vocab_file=self.vocab_file			,			merges_file=self.merges_file					)

					__UpperCAmelCase       :	Optional[int]						=      '''lower'''
					__UpperCAmelCase       :	Any						=      ['''low''', '''er</w>''']
					__UpperCAmelCase       :	Any						=      tokenizer.tokenize(a_					)
					self.assertListEqual(a_			,			a_					)

					__UpperCAmelCase       :	int						=      tokens + ['''<unk>''']
					__UpperCAmelCase       :	Optional[Any]						=      [16, 17, 23]
					self.assertListEqual(tokenizer.convert_tokens_to_ids(a_					)			,			a_					)




			def 					snake_case__	(  self				:					List[Any]					):
					'''simple docstring'''





					if not self.test_rust_tokenizer:
							return

					__UpperCAmelCase       :	str						=      self.get_tokenizer()
					__UpperCAmelCase       :	Optional[int]						=      self.get_rust_tokenizer()

					__UpperCAmelCase       :	Tuple						=      '''lower,newer'''

					__UpperCAmelCase       :	Optional[int]						=      tokenizer.tokenize(a_					)
					__UpperCAmelCase       :	Tuple						=      rust_tokenizer.tokenize(a_					)
					self.assertListEqual(a_			,			a_					)

					__UpperCAmelCase       :	Optional[Any]						=      tokenizer.encode(a_			,			add_special_tokens=a_					)
					__UpperCAmelCase       :	Union[str, Any]						=      rust_tokenizer.encode(a_			,			add_special_tokens=a_					)
					self.assertListEqual(a_			,			a_					)

					__UpperCAmelCase       :	Tuple						=      self.get_rust_tokenizer()
					__UpperCAmelCase       :	Union[str, Any]						=      tokenizer.encode(a_					)
					__UpperCAmelCase       :	str						=      rust_tokenizer.encode(a_					)
					self.assertListEqual(a_			,			a_					)




			@slow
			def 					snake_case__	(  self				:					Tuple					):
					'''simple docstring'''





					__UpperCAmelCase       :	List[Any]						=      self.tokenizer_class.from_pretrained('''allegro/herbert-base-cased'''					)

					__UpperCAmelCase       :	Tuple						=      tokenizer.encode('''konstruowanie sekwencji'''			,			add_special_tokens=a_					)
					__UpperCAmelCase       :	int						=      tokenizer.encode('''konstruowanie wielu sekwencji'''			,			add_special_tokens=a_					)

					__UpperCAmelCase       :	Union[str, Any]						=      tokenizer.build_inputs_with_special_tokens(a_					)
					__UpperCAmelCase       :	Any						=      tokenizer.build_inputs_with_special_tokens(a_			,			a_					)

					assert encoded_sentence == [0] + text + [2]
					assert encoded_pair == [0] + text + [2] + text_a + [2]





