



'''simple docstring'''




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


UpperCamelCase__ :			Any												=				logging.get_logger(__name__)

UpperCamelCase__ :			Dict												=				{
    '''facebook/xglm-564M''': '''https://huggingface.co/facebook/xglm-564M/resolve/main/config.json''',
    # See all XGLM models at https://huggingface.co/models?filter=xglm
}






class 		_UpperCamelCase						(							lowerCamelCase__					):


			'''simple docstring'''

			_A   :	List[str]    					=	'''xglm'''
			_A   :	Optional[int]    					=	['''past_key_values''']

			_A   :	List[str]    					=	{
			    '''num_attention_heads''': '''attention_heads''',
			    '''hidden_size''': '''d_model''',
			    '''num_hidden_layers''': '''num_layers''',
			}

			def __init__(							self  :				Optional[int]							,  lowerCAmelCase__  :				Optional[int]=2_5_6_0_0_8							,  lowerCAmelCase__  :				Optional[Any]=2_0_4_8							,  lowerCAmelCase__  :				str=1_0_2_4							,  lowerCAmelCase__  :				Tuple=4_0_9_6							,  lowerCAmelCase__  :				Optional[int]=2_4							,  lowerCAmelCase__  :				Dict=1_6							,  lowerCAmelCase__  :				List[str]="gelu"							,  lowerCAmelCase__  :				Dict=0.1							,  lowerCAmelCase__  :				List[str]=0.1							,  lowerCAmelCase__  :				Union[str, Any]=0.0							,  lowerCAmelCase__  :				str=0.0							,  lowerCAmelCase__  :				Union[str, Any]=0.02							,  lowerCAmelCase__  :				Optional[int]=True							,  lowerCAmelCase__  :				str=True							,  lowerCAmelCase__  :				Optional[int]=2							,  lowerCAmelCase__  :				int=1							,  lowerCAmelCase__  :				Tuple=0							,  lowerCAmelCase__  :				List[Any]=2							,  **lowerCAmelCase__  :				Dict							,  ):





					"""simple docstring"""






					__SCREAMING_SNAKE_CASE :	int					 =	vocab_size
					__SCREAMING_SNAKE_CASE :	Dict					 =	max_position_embeddings
					__SCREAMING_SNAKE_CASE :	str					 =	d_model
					__SCREAMING_SNAKE_CASE :	Optional[Any]					 =	ffn_dim
					__SCREAMING_SNAKE_CASE :	Optional[Any]					 =	num_layers
					__SCREAMING_SNAKE_CASE :	List[str]					 =	attention_heads
					__SCREAMING_SNAKE_CASE :	int					 =	activation_function
					__SCREAMING_SNAKE_CASE :	List[Any]					 =	dropout
					__SCREAMING_SNAKE_CASE :	Any					 =	attention_dropout
					__SCREAMING_SNAKE_CASE :	Optional[int]					 =	activation_dropout
					__SCREAMING_SNAKE_CASE :	List[Any]					 =	layerdrop
					__SCREAMING_SNAKE_CASE :	Optional[Any]					 =	init_std
					__SCREAMING_SNAKE_CASE :	Optional[int]					 =	scale_embedding  # scale factor will be sqrt(d_model) if True
					__SCREAMING_SNAKE_CASE :	int					 =	use_cache

					super().__init__(
					    pad_token_id=lowerCAmelCase__							,  bos_token_id=lowerCAmelCase__							,  eos_token_id=lowerCAmelCase__							,  decoder_start_token_id=lowerCAmelCase__							,  **lowerCAmelCase__							,  )




'''simple docstring'''




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__ :			Any												=				'''▁'''

UpperCamelCase__ :			Dict												=				get_tests_dir('''fixtures/test_sentencepiece.model''')






@require_sentencepiece
class 		_UpperCamelCase						(							lowerCamelCase__					,      unittest.TestCase					):


			'''simple docstring'''

			_A   :	Dict    					=	BertGenerationTokenizer
			_A   :	List[Any]    					=	False
			_A   :	Union[str, Any]    					=	True

			def UpperCamelCase__      (							self  :				Optional[Any]		):





					"""simple docstring"""






					super().setUp()

					__SCREAMING_SNAKE_CASE :	Dict					 =	BertGenerationTokenizer(lowerCAmelCase__							,  keep_accents=lowerCAmelCase__		)
					tokenizer.save_pretrained(self.tmpdirname		)

			def UpperCamelCase__      (							self  :				Optional[Any]		):





					"""simple docstring"""






					__SCREAMING_SNAKE_CASE :	int					 =	"""<s>"""
					__SCREAMING_SNAKE_CASE :	Optional[Any]					 =	1

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

			def UpperCamelCase__      (							self  :				Union[str, Any]		):





					"""simple docstring"""






					__SCREAMING_SNAKE_CASE :	Dict					 =	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(lowerCAmelCase__		)							,  1_0_0_2		)

			def UpperCamelCase__      (							self  :				Optional[int]		):





					"""simple docstring"""






					self.assertEqual(self.get_tokenizer().vocab_size							,  1_0_0_0		)

			def UpperCamelCase__      (							self  :				Optional[Any]		):





					"""simple docstring"""






					__SCREAMING_SNAKE_CASE :	Union[str, Any]					 =	BertGenerationTokenizer(lowerCAmelCase__							,  keep_accents=lowerCAmelCase__		)

					__SCREAMING_SNAKE_CASE :	Any					 =	tokenizer.tokenize("""This is a test"""		)
					self.assertListEqual(lowerCAmelCase__							,  ["""▁This""", """▁is""", """▁a""", """▁t""", """est"""]		)

					self.assertListEqual(
					    tokenizer.convert_tokens_to_ids(lowerCAmelCase__		)							,  [2_8_5, 4_6, 1_0, 1_7_0, 3_8_2]							,  )

					__SCREAMING_SNAKE_CASE :	Optional[Any]					 =	tokenizer.tokenize("""I was born in 92000, and this is falsé."""		)
					self.assertListEqual(
					    lowerCAmelCase__							,  [
					        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""",
					        """.""",
					    ]							,  )
					__SCREAMING_SNAKE_CASE :	Any					 =	tokenizer.convert_tokens_to_ids(lowerCAmelCase__		)
					self.assertListEqual(
					    lowerCAmelCase__							,  [8, 2_1, 8_4, 5_5, 2_4, 1_9, 7, 0, 6_0_2, 3_4_7, 3_4_7, 3_4_7, 3, 1_2, 6_6, 4_6, 7_2, 8_0, 6, 0, 4]							,  )

					__SCREAMING_SNAKE_CASE :	Any					 =	tokenizer.convert_ids_to_tokens(lowerCAmelCase__		)
					self.assertListEqual(
					    lowerCAmelCase__							,  [
					        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  :				List[str]		):





					"""simple docstring"""






					return BertGenerationTokenizer.from_pretrained("""google/bert_for_seq_generation_L-24_bbc_encoder"""		)

			@slow
			def UpperCamelCase__      (							self  :				Tuple		):





					"""simple docstring"""






					__SCREAMING_SNAKE_CASE :	Any					 =	"""Hello World!"""
					__SCREAMING_SNAKE_CASE :	Dict					 =	[1_8_5_3_6, 2_2_6_0, 1_0_1]

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

			@slow
			def UpperCamelCase__      (							self  :				Dict		):





					"""simple docstring"""






					__SCREAMING_SNAKE_CASE :	List[Any]					 =	(
					    """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"""
					)
					__SCREAMING_SNAKE_CASE :	Optional[int]					 =	[
					    8_7_1,
					    4_1_9,
					    3_5_8,
					    9_4_6,
					    9_9_1,
					    2_5_2_1,
					    4_5_2,
					    3_5_8,
					    1_3_5_7,
					    3_8_7,
					    7_7_5_1,
					    3_5_3_6,
					    1_1_2,
					    9_8_5,
					    4_5_6,
					    1_2_6,
					    8_6_5,
					    9_3_8,
					    5_4_0_0,
					    5_7_3_4,
					    4_5_8,
					    1_3_6_8,
					    4_6_7,
					    7_8_6,
					    2_4_6_2,
					    5_2_4_6,
					    1_1_5_9,
					    6_3_3,
					    8_6_5,
					    4_5_1_9,
					    4_5_7,
					    5_8_2,
					    8_5_2,
					    2_5_5_7,
					    4_2_7,
					    9_1_6,
					    5_0_8,
					    4_0_5,
					    3_4_3_2_4,
					    4_9_7,
					    3_9_1,
					    4_0_8,
					    1_1_3_4_2,
					    1_2_4_4,
					    3_8_5,
					    1_0_0,
					    9_3_8,
					    9_8_5,
					    4_5_6,
					    5_7_4,
					    3_6_2,
					    1_2_5_9_7,
					    3_2_0_0,
					    3_1_2_9,
					    1_1_7_2,
					]

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

			@require_torch
			@slow
			def UpperCamelCase__      (							self  :				str		):





					"""simple docstring"""






					import torch

					from transformers import BertGenerationConfig, BertGenerationEncoder

					# Build sequence
					__SCREAMING_SNAKE_CASE :	List[Any]					 =	list(self.big_tokenizer.get_vocab().keys()		)[:1_0]
					__SCREAMING_SNAKE_CASE :	int					 =	""" """.join(lowerCAmelCase__		)
					__SCREAMING_SNAKE_CASE :	Union[str, Any]					 =	self.big_tokenizer.encode_plus(lowerCAmelCase__							,  return_tensors="""pt"""							,  return_token_type_ids=lowerCAmelCase__		)
					__SCREAMING_SNAKE_CASE :	Optional[int]					 =	self.big_tokenizer.batch_encode_plus(
					    [sequence + """ """ + sequence]							,  return_tensors="""pt"""							,  return_token_type_ids=lowerCAmelCase__		)

					__SCREAMING_SNAKE_CASE :	Tuple					 =	BertGenerationConfig()
					__SCREAMING_SNAKE_CASE :	Any					 =	BertGenerationEncoder(lowerCAmelCase__		)

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

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



			@slow
			def UpperCamelCase__      (							self  :				List[str]		):





					"""simple docstring"""






					__SCREAMING_SNAKE_CASE :	Optional[Any]					 =	{"""input_ids""": [[3_9_2_8_6, 4_5_8, 3_6_3_3_5, 2_0_0_1, 4_5_6, 1_3_0_7_3, 1_3_2_6_6, 4_5_5, 1_1_3, 7_7_4_6, 1_7_4_1, 1_1_1_5_7, 3_9_1, 1_3_0_7_3, 1_3_2_6_6, 4_5_5, 1_1_3, 3_9_6_7, 3_5_4_1_2, 1_1_3, 4_9_3_6, 1_0_9, 3_8_7_0, 2_3_7_7, 1_1_3, 3_0_0_8_4, 4_5_7_2_0, 4_5_8, 1_3_4, 1_7_4_9_6, 1_1_2, 5_0_3, 1_1_6_7_2, 1_1_3, 1_1_8, 1_1_2, 5_6_6_5, 1_3_3_4_7, 3_8_6_8_7, 1_1_2, 1_4_9_6, 3_1_3_8_9, 1_1_2, 3_2_6_8, 4_7_2_6_4, 1_3_4, 9_6_2, 1_1_2, 1_6_3_7_7, 8_0_3_5, 2_3_1_3_0, 4_3_0, 1_2_1_6_9, 1_5_5_1_8, 2_8_5_9_2, 4_5_8, 1_4_6, 4_1_6_9_7, 1_0_9, 3_9_1, 1_2_1_6_9, 1_5_5_1_8, 1_6_6_8_9, 4_5_8, 1_4_6, 4_1_3_5_8, 1_0_9, 4_5_2, 7_2_6, 4_0_3_4, 1_1_1, 7_6_3, 3_5_4_1_2, 5_0_8_2, 3_8_8, 1_9_0_3, 1_1_1, 9_0_5_1, 3_9_1, 2_8_7_0, 4_8_9_1_8, 1_9_0_0, 1_1_2_3, 5_5_0, 9_9_8, 1_1_2, 9_5_8_6, 1_5_9_8_5, 4_5_5, 3_9_1, 4_1_0, 2_2_9_5_5, 3_7_6_3_6, 1_1_4], [4_4_8, 1_7_4_9_6, 4_1_9, 3_6_6_3, 3_8_5, 7_6_3, 1_1_3, 2_7_5_3_3, 2_8_7_0, 3_2_8_3, 1_3_0_4_3, 1_6_3_9, 2_4_7_1_3, 5_2_3, 6_5_6, 2_4_0_1_3, 1_8_5_5_0, 2_5_2_1, 5_1_7, 2_7_0_1_4, 2_1_2_4_4, 4_2_0, 1_2_1_2, 1_4_6_5, 3_9_1, 9_2_7, 4_8_3_3, 3_8_8, 5_7_8, 1_1_7_8_6, 1_1_4, 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], [4_8_4, 2_1_6_9, 7_6_8_7, 2_1_9_3_2, 1_8_1_4_6, 7_2_6, 3_6_3, 1_7_0_3_2, 3_3_9_1, 1_1_4, 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=lowerCAmelCase__							,  model_name="""google/bert_for_seq_generation_L-24_bbc_encoder"""							,  revision="""c817d1fd1be2ffa69431227a1fe320544943d4db"""							,  )