

import json
import os
import unittest

from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin







@require_tokenizers
class 					lowercase							(			lowercase_      ,    unittest.TestCase     ):
				__SCREAMING_SNAKE_CASE   :					int			     =     MgpstrTokenizer
				__SCREAMING_SNAKE_CASE   :					Any			     =     False
				__SCREAMING_SNAKE_CASE   :					int			     =     {}
				__SCREAMING_SNAKE_CASE   :					List[str]			     =     False




				def        a				(   self			):
											super().setUp()

											# fmt: off
											snake_case_     							=       ['[GO]', '[s]', '0', '1', '2', '3', '4', '5', '6', '7', '8', '9', 'a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j', 'k', 'l', 'm', 'n', 'o', 'p', 'q', 'r', 's', 't', 'u', 'v', 'w', 'x', 'y', 'z']
											# fmt: on
											snake_case_     							=       dict(zip(snake_case ,  range(len(snake_case			)			)			)			)

											snake_case_     							=       os.path.join(self.tmpdirname ,  VOCAB_FILES_NAMES['vocab_file']			)
											with open(self.vocab_file ,  'w' ,  encoding='utf-8'			) as fp:
																		fp.write(json.dumps(snake_case			) + '\n'			)




				def        a				(   self ,  **snake_case			):
											return MgpstrTokenizer.from_pretrained(self.tmpdirname ,  **snake_case			)




				def        a				(   self ,  snake_case			):
											snake_case_     							=       'tester'
											snake_case_     							=       'tester'
											return input_text, output_text




				@unittest.skip('MGP-STR always lower cases letters.'			)
				def        a				(   self			):
											pass




				def        a				(   self			):
											snake_case_     							=       self.get_tokenizers(do_lower_case=snake_case			)
											for tokenizer in tokenizers:
																		with self.subTest(F'''{tokenizer.__class__.__name__}'''			):
																									snake_case_     							=       '[SPECIAL_TOKEN]'

																									tokenizer.add_special_tokens({'cls_token': special_token}			)
																									snake_case_     							=       tokenizer.encode([special_token] ,  add_special_tokens=snake_case			)
																									self.assertEqual(len(snake_case			) ,  1			)

																									snake_case_     							=       tokenizer.decode(snake_case ,  skip_special_tokens=snake_case			)
																									self.assertTrue(special_token not in decoded			)




				def        a				(   self			):
											snake_case_     							=       self.get_tokenizers()
											for tokenizer in tokenizers:
																		with self.subTest(F'''{tokenizer.__class__.__name__}'''			):
																									snake_case_							,       snake_case_     							=       self.get_input_output_texts(snake_case			)

																									snake_case_     							=       tokenizer.tokenize(snake_case			)
																									snake_case_     							=       tokenizer.convert_tokens_to_ids(snake_case			)
																									snake_case_     							=       tokenizer.encode(snake_case ,  add_special_tokens=snake_case			)
																									self.assertListEqual(snake_case ,  snake_case			)

																									snake_case_     							=       tokenizer.convert_ids_to_tokens(snake_case			)
																									self.assertNotEqual(len(snake_case			) ,  0			)
																									snake_case_     							=       tokenizer.decode(snake_case			)
																									self.assertIsInstance(snake_case ,  snake_case			)

																									self.assertEqual(text_a.replace(' ' ,  ''			) ,  snake_case			)




				@unittest.skip('MGP-STR tokenizer only handles one sequence.'			)
				def        a				(   self			):
											pass




				@unittest.skip('inputs cannot be pretokenized in MgpstrTokenizer'			)
				def        a				(   self			):
											pass







import tempfile
import unittest

from make_student import create_student_by_copying_alternating_layers

from transformers import AutoConfig
from transformers.file_utils import cached_property
from transformers.testing_utils import require_torch


_UpperCAmelCase						:  Dict									=			"""sshleifer/bart-tiny-random"""
_UpperCAmelCase						:  Optional[Any]									=			"""patrickvonplaten/t5-tiny-random"""







@require_torch
class 					lowercase							(			unittest.TestCase     ):




				@cached_property
				def        a				(   self			):
											return AutoConfig.from_pretrained(snake_case			)




				def        a				(   self			):
											snake_case_							,       *snake_case_     							=       create_student_by_copying_alternating_layers(snake_case ,  tempfile.mkdtemp() ,  e=1 ,  d=1			)
											self.assertEqual(student.config.num_hidden_layers ,  1			)




				def        a				(   self			):
											snake_case_							,       *snake_case_     							=       create_student_by_copying_alternating_layers(snake_case ,  tempfile.mkdtemp() ,  e=1 ,  d=snake_case			)




				def        a				(   self			):
											snake_case_							,       *snake_case_     							=       create_student_by_copying_alternating_layers(snake_case ,  tempfile.mkdtemp() ,  e=1 ,  d=snake_case			)
											self.assertEqual(student.config.encoder_layers ,  1			)
											self.assertEqual(student.config.decoder_layers ,  self.teacher_config.encoder_layers			)




				def        a				(   self			):
											snake_case_							,       *snake_case_     							=       create_student_by_copying_alternating_layers(snake_case ,  tempfile.mkdtemp() ,  e=1 ,  d=1			)
											self.assertEqual(student.config.encoder_layers ,  1			)
											self.assertEqual(student.config.decoder_layers ,  1			)




				def        a				(   self			):
											with self.assertRaises(snake_case			):
																		create_student_by_copying_alternating_layers(snake_case ,  tempfile.mkdtemp() ,  e=snake_case ,  d=snake_case			)




