





import copy
import tempfile
import unittest

from huggingface_hub import HfFolder, delete_repo
from parameterized import parameterized
from requests.exceptions import HTTPError

from transformers import AutoConfig, GenerationConfig
from transformers.testing_utils import TOKEN, USER, is_staging_test





class 						_A(					unittest.TestCase   ):


				"""simple docstring"""


				@parameterized.expand([(None,), ('foo.json',)]     )
				def 					UpperCAmelCase_		(			self     ,					_A     ):
									__A	:						Any       =				GenerationConfig(
									    do_sample=_A     ,					temperature=0.7     ,					length_penalty=1.0     ,					bad_words_ids=[[1, 2, 3], [4, 5]]     ,					)
									with tempfile.TemporaryDirectory() as tmp_dir:
														config.save_pretrained(_A     ,					config_name=_A     )
														__A	:						int       =				GenerationConfig.from_pretrained(_A     ,					config_name=_A     )

									# Checks parameters that were specified
									self.assertEqual(loaded_config.do_sample     ,					_A     )
									self.assertEqual(loaded_config.temperature     ,					0.7     )
									self.assertEqual(loaded_config.length_penalty     ,					1.0     )
									self.assertEqual(loaded_config.bad_words_ids     ,					[[1, 2, 3], [4, 5]]     )

									# Checks parameters that were not specified (defaults)
									self.assertEqual(loaded_config.top_k     ,					50     )
									self.assertEqual(loaded_config.max_length     ,					20     )
									self.assertEqual(loaded_config.max_time     ,					_A     )



				def 					UpperCAmelCase_		(			self     ):
									__A	:						Dict       =				AutoConfig.from_pretrained('gpt2'     )
									__A	:						str       =				GenerationConfig.from_model_config(_A     )
									__A	:						int       =				GenerationConfig()

									# The generation config has loaded a few non-default parameters from the model config
									self.assertNotEqual(_A     ,					_A     )

									# One of those parameters is eos_token_id -- check if it matches
									self.assertNotEqual(generation_config_from_model.eos_token_id     ,					default_generation_config.eos_token_id     )
									self.assertEqual(generation_config_from_model.eos_token_id     ,					model_config.eos_token_id     )



				def 					UpperCAmelCase_		(			self     ):
									__A	:						Tuple       =				GenerationConfig()
									__A	:						Any       =				{
									    'max_new_tokens': 1024,
									    'foo': 'bar',
									}
									__A	:						List[str]       =				copy.deepcopy(_A     )
									__A	:						Union[str, Any]       =				generation_config.update(**_A     )

									# update_kwargs was not modified (no side effects)
									self.assertEqual(_A     ,					_A     )

									# update_kwargs was used to update the config on valid attributes
									self.assertEqual(generation_config.max_new_tokens     ,					1024     )

									# `.update()` returns a dictionary of unused kwargs
									self.assertEqual(_A     ,					{'foo': 'bar'}     )



				def 					UpperCAmelCase_		(			self     ):
									__A	:						List[Any]       =				GenerationConfig()
									__A	:						Optional[int]       =				'bar'

									with tempfile.TemporaryDirectory('test-generation-config'     ) as tmp_dir:
														generation_config.save_pretrained(_A     )

														__A	:						List[Any]       =				GenerationConfig.from_pretrained(_A     )
									# update_kwargs was used to update the config on valid attributes
									self.assertEqual(new_config.foo     ,					'bar'     )

									__A	:						Any       =				GenerationConfig.from_model_config(_A     )
									assert not hasattr(_A     ,					'foo'     )  # no new kwargs should be initialized if from config





				def 					UpperCAmelCase_		(			self     ):
									__A	:						str       =				GenerationConfig()
									self.assertEqual(default_config.temperature     ,					1.0     )
									self.assertEqual(default_config.do_sample     ,					_A     )
									self.assertEqual(default_config.num_beams     ,					1     )

									__A	:						Optional[int]       =				GenerationConfig(
									    do_sample=_A     ,					temperature=0.7     ,					length_penalty=1.0     ,					bad_words_ids=[[1, 2, 3], [4, 5]]     ,					)
									self.assertEqual(config.temperature     ,					0.7     )
									self.assertEqual(config.do_sample     ,					_A     )
									self.assertEqual(config.num_beams     ,					1     )

									with tempfile.TemporaryDirectory() as tmp_dir:
														config.save_pretrained(_A     )
														__A	:						List[Any]       =				GenerationConfig.from_pretrained(_A     ,					temperature=1.0     )

									self.assertEqual(loaded_config.temperature     ,					1.0     )
									self.assertEqual(loaded_config.do_sample     ,					_A     )
									self.assertEqual(loaded_config.num_beams     ,					1     )  # default value





@is_staging_test
class 						_A(					unittest.TestCase   ):


				"""simple docstring"""


				@classmethod
				def 					UpperCAmelCase_		(			cls     ):
									__A	:						Optional[int]       =				TOKEN
									HfFolder.save_token(_A     )



				@classmethod
				def 					UpperCAmelCase_		(			cls     ):
									try:
														delete_repo(token=cls._token     ,					repo_id='test-generation-config'     )
									except HTTPError:
														pass

									try:
														delete_repo(token=cls._token     ,					repo_id='valid_org/test-generation-config-org'     )
									except HTTPError:
														pass



				def 					UpperCAmelCase_		(			self     ):
									__A	:						Optional[Any]       =				GenerationConfig(
									    do_sample=_A     ,					temperature=0.7     ,					length_penalty=1.0     ,					)
									config.push_to_hub('test-generation-config'     ,					use_auth_token=self._token     )

									__A	:						List[Any]       =				GenerationConfig.from_pretrained(F"""{USER}/test-generation-config"""     )
									for k, v in config.to_dict().items():
														if k != "transformers_version":
																			self.assertEqual(_A     ,					getattr(_A     ,					_A     )     )

        # Reset repo
									delete_repo(token=self._token     ,					repo_id='test-generation-config'     )

									# Push to hub via save_pretrained
									with tempfile.TemporaryDirectory() as tmp_dir:
														config.save_pretrained(
														    _A     ,					repo_id='test-generation-config'     ,					push_to_hub=_A     ,					use_auth_token=self._token     )

									__A	:						Optional[Any]       =				GenerationConfig.from_pretrained(F"""{USER}/test-generation-config"""     )
									for k, v in config.to_dict().items():
														if k != "transformers_version":
																			self.assertEqual(_A     ,					getattr(_A     ,					_A     )     )





				def 					UpperCAmelCase_		(			self     ):
									__A	:						Union[str, Any]       =				GenerationConfig(
									    do_sample=_A     ,					temperature=0.7     ,					length_penalty=1.0     ,					)
									config.push_to_hub('valid_org/test-generation-config-org'     ,					use_auth_token=self._token     )

									__A	:						str       =				GenerationConfig.from_pretrained('valid_org/test-generation-config-org'     )
									for k, v in config.to_dict().items():
														if k != "transformers_version":
																			self.assertEqual(_A     ,					getattr(_A     ,					_A     )     )

        # Reset repo
									delete_repo(token=self._token     ,					repo_id='valid_org/test-generation-config-org'     )

									# Push to hub via save_pretrained
									with tempfile.TemporaryDirectory() as tmp_dir:
														config.save_pretrained(
														    _A     ,					repo_id='valid_org/test-generation-config-org'     ,					push_to_hub=_A     ,					use_auth_token=self._token     )

									__A	:						Union[str, Any]       =				GenerationConfig.from_pretrained('valid_org/test-generation-config-org'     )
									for k, v in config.to_dict().items():
														if k != "transformers_version":
																			self.assertEqual(_A     ,					getattr(_A     ,					_A     )     )











import unittest

from transformers import BertGenerationTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_torch, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


UpperCAmelCase						:   List[str]			  =     '''▁'''

UpperCAmelCase						:   Optional[Any]			  =     get_tests_dir('''fixtures/test_sentencepiece.model''')





@require_sentencepiece
class 						_A(					snake_case__				, unittest.TestCase   ):


				"""simple docstring"""


				UpperCamelCase    :  Optional[int]					    =	BertGenerationTokenizer
				UpperCamelCase    :  str					    =	False
				UpperCamelCase    :  Tuple					    =	True



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

									__A	:						Tuple       =				BertGenerationTokenizer(_A     ,					keep_accents=_A     )
									tokenizer.save_pretrained(self.tmpdirname     )



				def 					UpperCAmelCase_		(			self     ):
									__A	:						str       =				'<s>'
									__A	:						str       =				1

									self.assertEqual(self.get_tokenizer()._convert_token_to_id(_A     )     ,					_A     )
									self.assertEqual(self.get_tokenizer()._convert_id_to_token(_A     )     ,					_A     )



				def 					UpperCAmelCase_		(			self     ):
									__A	:						int       =				list(self.get_tokenizer().get_vocab().keys()     )

									self.assertEqual(vocab_keys[0]     ,					'<unk>'     )
									self.assertEqual(vocab_keys[1]     ,					'<s>'     )
									self.assertEqual(vocab_keys[-1]     ,					'<pad>'     )
									self.assertEqual(len(_A     )     ,					1002     )



				def 					UpperCAmelCase_		(			self     ):
									self.assertEqual(self.get_tokenizer().vocab_size     ,					1000     )



				def 					UpperCAmelCase_		(			self     ):
									__A	:						str       =				BertGenerationTokenizer(_A     ,					keep_accents=_A     )

									__A	:						Dict       =				tokenizer.tokenize('This is a test'     )
									self.assertListEqual(_A     ,					['▁This', '▁is', '▁a', '▁t', 'est']     )

									self.assertListEqual(
									    tokenizer.convert_tokens_to_ids(_A     )     ,					[285, 46, 10, 170, 382]     ,					)

									__A	:						int       =				tokenizer.tokenize('I was born in 92000, and this is falsé.'     )
									self.assertListEqual(
									    _A     ,					[
									        SPIECE_UNDERLINE + 'I',
									        SPIECE_UNDERLINE + 'was',
									        SPIECE_UNDERLINE + 'b',
									        'or',
									        'n',
									        SPIECE_UNDERLINE + 'in',
									        SPIECE_UNDERLINE + '',
									        '9',
									        '2',
									        '0',
									        '0',
									        '0',
									        ',',
									        SPIECE_UNDERLINE + 'and',
									        SPIECE_UNDERLINE + 'this',
									        SPIECE_UNDERLINE + 'is',
									        SPIECE_UNDERLINE + 'f',
									        'al',
									        's',
									        'é',
									        '.',
									    ]     ,					)
									__A	:						Dict       =				tokenizer.convert_tokens_to_ids(_A     )
									self.assertListEqual(
									    _A     ,					[8, 21, 84, 55, 24, 19, 7, 0, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 0, 4]     ,					)

									__A	:						Optional[int]       =				tokenizer.convert_ids_to_tokens(_A     )
									self.assertListEqual(
									    _A     ,					[
									        SPIECE_UNDERLINE + 'I',
									        SPIECE_UNDERLINE + 'was',
									        SPIECE_UNDERLINE + 'b',
									        'or',
									        'n',
									        SPIECE_UNDERLINE + 'in',
									        SPIECE_UNDERLINE + '',
									        '<unk>',
									        '2',
									        '0',
									        '0',
									        '0',
									        ',',
									        SPIECE_UNDERLINE + 'and',
									        SPIECE_UNDERLINE + 'this',
									        SPIECE_UNDERLINE + 'is',
									        SPIECE_UNDERLINE + 'f',
									        'al',
									        's',
									        '<unk>',
									        '.',
									    ]     ,					)



				@cached_property
				def 					UpperCAmelCase_		(			self     ):
									return BertGenerationTokenizer.from_pretrained('google/bert_for_seq_generation_L-24_bbc_encoder'     )



				@slow
				def 					UpperCAmelCase_		(			self     ):
									__A	:						List[Any]       =				'Hello World!'
									__A	:						Optional[Any]       =				[18536, 2260, 101]

									self.assertListEqual(_A     ,					self.big_tokenizer.encode(_A     )     )



				@slow
				def 					UpperCAmelCase_		(			self     ):
									__A	:						Dict       =				(
									    'This is a very long text with a lot of weird characters, such as: . , ~ ? ( ) " [ ] ! : - . Also we will'
									    ' add words that should not exsist and be tokenized to <unk>, such as saoneuhaoesuth'
									)
									__A	:						int       =				[
									    871,
									    419,
									    358,
									    946,
									    991,
									    2521,
									    452,
									    358,
									    1357,
									    387,
									    7751,
									    3536,
									    112,
									    985,
									    456,
									    126,
									    865,
									    938,
									    5400,
									    5734,
									    458,
									    1368,
									    467,
									    786,
									    2462,
									    5246,
									    1159,
									    633,
									    865,
									    4519,
									    457,
									    582,
									    852,
									    2557,
									    427,
									    916,
									    508,
									    405,
									    34324,
									    497,
									    391,
									    408,
									    11342,
									    1244,
									    385,
									    100,
									    938,
									    985,
									    456,
									    574,
									    362,
									    12597,
									    3200,
									    3129,
									    1172,
									]

									self.assertListEqual(_A     ,					self.big_tokenizer.encode(_A     )     )



				@require_torch
				@slow
				def 					UpperCAmelCase_		(			self     ):
									import torch

									from transformers import BertGenerationConfig, BertGenerationEncoder

									# Build sequence
									__A	:						Tuple       =				list(self.big_tokenizer.get_vocab().keys()     )[:10]
									__A	:						List[Any]       =				' '.join(_A     )
									__A	:						Union[str, Any]       =				self.big_tokenizer.encode_plus(_A     ,					return_tensors='pt'     ,					return_token_type_ids=_A     )
									__A	:						Optional[Any]       =				self.big_tokenizer.batch_encode_plus(
									    [sequence + ' ' + sequence]     ,					return_tensors='pt'     ,					return_token_type_ids=_A     )

									__A	:						int       =				BertGenerationConfig()
									__A	:						List[str]       =				BertGenerationEncoder(_A     )

									assert model.get_input_embeddings().weight.shape[0] >= self.big_tokenizer.vocab_size

									with torch.no_grad():
														model(**_A     )
														model(**_A     )





				@slow
				def 					UpperCAmelCase_		(			self     ):
									# fmt: off
									__A	:						str       =				{'input_ids': [[39286, 458, 36335, 2001, 456, 13073, 13266, 455, 113, 7746, 1741, 11157, 391, 13073, 13266, 455, 113, 3967, 35412, 113, 4936, 109, 3870, 2377, 113, 30084, 45720, 458, 134, 17496, 112, 503, 11672, 113, 118, 112, 5665, 13347, 38687, 112, 1496, 31389, 112, 3268, 47264, 134, 962, 112, 16377, 8035, 23130, 430, 12169, 15518, 28592, 458, 146, 41697, 109, 391, 12169, 15518, 16689, 458, 146, 41358, 109, 452, 726, 4034, 111, 763, 35412, 5082, 388, 1903, 111, 9051, 391, 2870, 48918, 1900, 1123, 550, 998, 112, 9586, 15985, 455, 391, 410, 22955, 37636, 114], [448, 17496, 419, 3663, 385, 763, 113, 27533, 2870, 3283, 13043, 1639, 24713, 523, 656, 24013, 18550, 2521, 517, 27014, 21244, 420, 1212, 1465, 391, 927, 4833, 388, 578, 11786, 114, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [484, 2169, 7687, 21932, 18146, 726, 363, 17032, 3391, 114, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], 'attention_mask': [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
									# fmt: on

									self.tokenizer_integration_test_util(
									    expected_encoding=_A     ,					model_name='google/bert_for_seq_generation_L-24_bbc_encoder'     ,					revision='c817d1fd1be2ffa69431227a1fe320544943d4db'     ,					)




