
"""simple docstring"""


import glob
import os

from get_test_info import get_tester_classes


if __name__ == "__main__":
		_lowercase											=			[]

		_lowercase											=			os.path.join('''tests''', '''models''', '''**''', '''test_modeling_*.py''')
		_lowercase											=			glob.glob(pattern)
		# TODO: deal with TF/Flax too
		_lowercase											=			[
		    x for x in test_files if not (x.startswith('''test_modeling_tf_''') or x.startswith('''test_modeling_flax_'''))
		]

		for test_file in test_files:
				_lowercase											=			get_tester_classes(test_file)
				for tester_class in tester_classes:
						# A few tester classes don't have `parent` parameter in `__init__`.
						# TODO: deal this better
						try:
								_lowercase											=			tester_class(parent=None)
						except Exception:
								continue
						if hasattr(tester, '''get_config'''):
								_lowercase											=			tester.get_config()
								for k, v in config.to_dict().items():
										if isinstance(v, int):
												_lowercase											=			None
												if k in ["vocab_size"]:
														_lowercase											=			1_00
												elif k in ["max_position_embeddings"]:
														_lowercase											=			1_28
												elif k in ["hidden_size", "d_model"]:
														_lowercase											=			40
												elif k == ["num_layers", "num_hidden_layers", "num_encoder_layers", "num_decoder_layers"]:
														_lowercase											=			5
												if target is not None and v > target:
														failures.append(
														    F"""{tester_class.__name__} will produce a `config` of type `{config.__class__.__name__}`"""
														    F""" with config[\"{k}\"] = {v} which is too large for testing! Set its value to be smaller"""
														    F""" than {target}."""
														)

		if len(failures) > 0:
				raise Exception(F"""There were {len(failures)} failures:\n""" + '''\n'''.join(failures))

"""simple docstring"""


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 			lowerCAmelCase_			( _lowercase						,   unittest.TestCase      ):



						'''simple docstring'''


						_lowerCamelCase:      List[str] =      HerbertTokenizer
						_lowerCamelCase:      Any =      HerbertTokenizerFast
						_lowerCamelCase:      Optional[int] =      True


						def   _SCREAMING_SNAKE_CASE (	self       : Dict )       ->				Tuple:
							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:
								A  				=				f_data.read().replace('\n\n'					,'\n' ).strip()

							A  				=				[
							    '<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>',
							]
							A  				=				dict(zip(A_					,range(len(A_ ) ) ) )
							A  				=				['l o 123', 'lo w 1456', 'e r</w> 1789', '']

							A  				=				os.path.join(self.tmpdirname					,VOCAB_FILES_NAMES['vocab_file'] )
							A  				=				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   _SCREAMING_SNAKE_CASE (	self       : Tuple					,A_       : List[str] )       ->				int:
							A  				=				'lower newer'
							A  				=				'lower newer'
							return input_text, output_text


						def   _SCREAMING_SNAKE_CASE (	self       : List[Any] )       ->				int:
							A  				=				self.tokenizer_class(vocab_file=self.vocab_file					,merges_file=self.merges_file )

							A  				=				'lower'
							A  				=				['low', 'er</w>']
							A  				=				tokenizer.tokenize(A_ )
							self.assertListEqual(A_					,A_ )

							A  				=				tokens + ['<unk>']
							A  				=				[16, 17, 23]
							self.assertListEqual(tokenizer.convert_tokens_to_ids(A_ )					,A_ )


						def   _SCREAMING_SNAKE_CASE (	self       : Dict )       ->				Optional[int]:
							if not self.test_rust_tokenizer:
								return

							A  				=				self.get_tokenizer()
							A  				=				self.get_rust_tokenizer()

							A  				=				'lower,newer'

							A  				=				tokenizer.tokenize(A_ )
							A  				=				rust_tokenizer.tokenize(A_ )
							self.assertListEqual(A_					,A_ )

							A  				=				tokenizer.encode(A_					,add_special_tokens=A_ )
							A  				=				rust_tokenizer.encode(A_					,add_special_tokens=A_ )
							self.assertListEqual(A_					,A_ )

							A  				=				self.get_rust_tokenizer()
							A  				=				tokenizer.encode(A_ )
							A  				=				rust_tokenizer.encode(A_ )
							self.assertListEqual(A_					,A_ )




						@slow
						def   _SCREAMING_SNAKE_CASE (	self       : str )       ->				List[Any]:
							A  				=				self.tokenizer_class.from_pretrained('allegro/herbert-base-cased' )

							A  				=				tokenizer.encode('konstruowanie sekwencji'					,add_special_tokens=A_ )
							A  				=				tokenizer.encode('konstruowanie wielu sekwencji'					,add_special_tokens=A_ )

							A  				=				tokenizer.build_inputs_with_special_tokens(A_ )
							A  				=				tokenizer.build_inputs_with_special_tokens(A_					,A_ )

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