



"""simple docstring"""







import pickle
import shutil
import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, XGLMTokenizer, XGLMTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


__a       :	int             = get_tests_dir('fixtures/test_sentencepiece.model')







@require_sentencepiece
@require_tokenizers
class        _SCREAMING_SNAKE_CASE						(  lowercase__       , unittest.TestCase							):





							"""simple docstring"""





							_SCREAMING_SNAKE_CASE    =XGLMTokenizer
							_SCREAMING_SNAKE_CASE    =XGLMTokenizerFast
							_SCREAMING_SNAKE_CASE    =True
							_SCREAMING_SNAKE_CASE    =True




							def  lowercase		(   self:     List[Any]    ):

												'''simple docstring'''

												super().setUp()

												# We have a SentencePiece fixture for testing
												a__          =  XGLMTokenizer(__lowercase				,		keep_accents=__lowercase    )
												tokenizer.save_pretrained(self.tmpdirname    )




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

												'''simple docstring'''

												a__          =  '''<pad>'''
												a__          =  1

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




							def  lowercase		(   self:     Tuple    ):

												'''simple docstring'''

												a__          =  list(self.get_tokenizer().get_vocab().keys()    )

												self.assertEqual(vocab_keys[0]				,		'''<s>'''    )
												self.assertEqual(vocab_keys[1]				,		'''<pad>'''    )
												self.assertEqual(len(__lowercase    )				,		1008    )




							def  lowercase		(   self:     Tuple    ):

												'''simple docstring'''

												self.assertEqual(self.get_tokenizer().vocab_size				,		1008    )




							def  lowercase		(   self:     List[str]    ):

												'''simple docstring'''

												a__          =  XGLMTokenizer(__lowercase				,		keep_accents=__lowercase    )

												a__          =  tokenizer.tokenize('''This is a test'''    )
												self.assertListEqual(__lowercase				,		['''▁This''', '''▁is''', '''▁a''', '''▁t''', '''est''']    )

												self.assertListEqual(
												    tokenizer.convert_tokens_to_ids(__lowercase    )				,		[value + tokenizer.fairseq_offset for value in [285, 46, 10, 170, 382]]				,		)

												a__          =  tokenizer.tokenize('''I was born in 92000, and this is falsé.'''    )
												self.assertListEqual(
												    __lowercase				,		[
												        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__          =  tokenizer.convert_tokens_to_ids(__lowercase    )
												self.assertListEqual(
												    __lowercase				,		[
												        value + tokenizer.fairseq_offset
												        for value in [8, 21, 84, 55, 24, 19, 7, 2, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 2, 4]
												    ]				,		)

												a__          =  tokenizer.convert_ids_to_tokens(__lowercase    )
												self.assertListEqual(
												    __lowercase				,		[
												        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  lowercase		(   self:     List[str]    ):

												'''simple docstring'''

												return XGLMTokenizer.from_pretrained('''facebook/xglm-564M'''    )




							def  lowercase		(   self:     int    ):

												'''simple docstring'''

												with tempfile.NamedTemporaryFile() as f:
																	shutil.copyfile(__lowercase				,		f.name    )
																	a__          =  XGLMTokenizer(f.name				,		keep_accents=__lowercase    )
																	a__          =  pickle.dumps(__lowercase    )
												pickle.loads(__lowercase    )




							def  lowercase		(   self:     Dict    ):

												'''simple docstring'''

												if not self.test_rust_tokenizer:
																	return

												a__          =  self.get_tokenizer()
												a__          =  self.get_rust_tokenizer()

												a__          =  '''I was born in 92000, and this is falsé.'''

												a__          =  tokenizer.tokenize(__lowercase    )
												a__          =  rust_tokenizer.tokenize(__lowercase    )
												self.assertListEqual(__lowercase				,		__lowercase    )

												a__          =  tokenizer.encode(__lowercase				,		add_special_tokens=__lowercase    )
												a__          =  rust_tokenizer.encode(__lowercase				,		add_special_tokens=__lowercase    )
												self.assertListEqual(__lowercase				,		__lowercase    )

												a__          =  self.get_rust_tokenizer()
												a__          =  tokenizer.encode(__lowercase    )
												a__          =  rust_tokenizer.encode(__lowercase    )
												self.assertListEqual(__lowercase				,		__lowercase    )




							@slow
							def  lowercase		(   self:     List[Any]    ):

												'''simple docstring'''

												a__          =  '''Hello World!'''
												a__          =  [2, 31227, 4447, 35]

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




							@slow
							def  lowercase		(   self:     Union[str, Any]    ):

												'''simple docstring'''

												a__          =  (
												    '''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'''
												)
												# fmt: off
												a__          =  [2, 1018, 67, 11, 1988, 2617, 5631, 278, 11, 3407, 48, 71630, 28085, 4, 3234, 157, 13, 6, 5, 6, 4, 3526, 768, 15, 659, 57, 298, 3983, 864, 129, 21, 6, 5, 13675, 377, 652, 7580, 10341, 155, 2817, 422, 1666, 7, 1674, 53, 113, 202277, 17892, 33, 60, 87, 4, 3234, 157, 61, 2667, 52376, 19, 88, 23, 735]
												# fmt: on

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





							@slow
							def  lowercase		(   self:     Tuple    ):

												'''simple docstring'''

												a__          =  {
												    '''input_ids''': [[2, 108825, 1163, 15, 88010, 473, 15898, 157, 13672, 1857, 312, 8, 238021, 1163, 53, 13672, 1857, 312, 8, 53283, 182396, 8, 18566, 16, 36733, 4101, 8, 230, 244017, 122553, 7, 15, 132597, 4, 293, 12511, 7610, 4, 3414, 132597, 9, 4, 32361, 362, 4, 734, 28512, 32569, 18, 4, 32361, 26096, 14982, 73, 18715, 21433, 235261, 15, 492, 12427, 16, 53, 18715, 21433, 65454, 15, 23659, 563, 16, 278, 597, 2843, 595, 7931, 182396, 64186, 22, 886, 595, 132981, 53, 25540, 3449, 43982, 39901, 5951, 878, 330, 4, 27694, 80269, 312, 53, 6517, 11780, 611, 20408, 5], [2, 6, 132597, 67, 42897, 33, 592, 8, 163729, 25540, 361, 136997, 109514, 173230, 7, 501, 60, 102913, 196, 5631, 235, 63243, 473, 6, 231757, 74, 5277, 7905, 53, 3095, 37317, 22, 454, 183874, 5], [2, 268, 31298, 46530, 6, 132935, 43831, 7, 597, 32, 24, 3688, 9865, 5]],
												    '''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, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]
												}  # noqa: E501
												# fmt: on

												self.tokenizer_integration_test_util(
												    expected_encoding=__lowercase				,		model_name='''facebook/xglm-564M'''				,		padding=__lowercase				,		)










"""simple docstring"""







import copy
import os
from typing import TYPE_CHECKING, List, Union


if TYPE_CHECKING:
	pass

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


__a       :	List[Any]             = logging.get_logger(__name__)

__a       :	Tuple             = {
    'kakaobrain/align-base': 'https://huggingface.co/kakaobrain/align-base/resolve/main/config.json',
}







class        _SCREAMING_SNAKE_CASE						(  __snake_case							):





							"""simple docstring"""





							_SCREAMING_SNAKE_CASE    ='align_text_model'




							def __init__(   self:     Tuple				,		__A:     Optional[int]=30522				,		__A:     Tuple=768				,		__A:     Any=12				,		__A:     Any=12				,		__A:     Dict=3072				,		__A:     Tuple="gelu"				,		__A:     Union[str, Any]=0.1				,		__A:     List[str]=0.1				,		__A:     Optional[int]=512				,		__A:     Tuple=2				,		__A:     str=0.0_2				,		__A:     int=1e-12				,		__A:     Optional[int]=0				,		__A:     Optional[int]="absolute"				,		__A:     List[Any]=True				,		**__A:     Tuple				,		):

												'''simple docstring'''

												super().__init__(**__A    )

												a__          =  vocab_size
												a__          =  hidden_size
												a__          =  num_hidden_layers
												a__          =  num_attention_heads
												a__          =  hidden_act
												a__          =  intermediate_size
												a__          =  hidden_dropout_prob
												a__          =  attention_probs_dropout_prob
												a__          =  max_position_embeddings
												a__          =  type_vocab_size
												a__          =  initializer_range
												a__          =  layer_norm_eps
												a__          =  position_embedding_type
												a__          =  use_cache
												a__          =  pad_token_id





							@classmethod
							def  lowercase		(   cls:     Any				,		__A:     Union[str, os.PathLike]				,		**__A:     Tuple    ):

												'''simple docstring'''

												cls._set_token_in_kwargs(__A    )

												a__       ,a__          =  cls.get_config_dict(__A				,		**__A    )

												# get the text config dict if we are loading from AlignConfig
												if config_dict.get('''model_type'''    ) == "align":
																	a__          =  config_dict['''text_config''']

												if "model_type" in config_dict and hasattr(cls				,		'''model_type'''    ) and config_dict["model_type"] != cls.model_type:
																	logger.warning(
																	    F'You are using a model of type {config_dict["model_type"]} to instantiate a model of type '
																	    F'{cls.model_type}. This is not supported for all configurations of models and can yield errors.'    )

												return cls.from_dict(__A				,		**__A    )







class        _SCREAMING_SNAKE_CASE						(  __snake_case							):





							"""simple docstring"""





							_SCREAMING_SNAKE_CASE    ='align_vision_model'




							def __init__(   self:     Dict				,		__A:     int = 3				,		__A:     int = 600				,		__A:     float = 2.0				,		__A:     float = 3.1				,		__A:     int = 8				,		__A:     List[int] = [3, 3, 5, 3, 5, 5, 3]				,		__A:     List[int] = [32, 16, 24, 40, 80, 112, 192]				,		__A:     List[int] = [16, 24, 40, 80, 112, 192, 320]				,		__A:     List[int] = []				,		__A:     List[int] = [1, 2, 2, 2, 1, 2, 1]				,		__A:     List[int] = [1, 2, 2, 3, 3, 4, 1]				,		__A:     List[int] = [1, 6, 6, 6, 6, 6, 6]				,		__A:     float = 0.2_5				,		__A:     str = "swish"				,		__A:     int = 2560				,		__A:     str = "mean"				,		__A:     float = 0.0_2				,		__A:     float = 0.0_0_1				,		__A:     float = 0.9_9				,		__A:     float = 0.2				,		**__A:     List[Any]				,		):

												'''simple docstring'''

												super().__init__(**__A    )

												a__          =  num_channels
												a__          =  image_size
												a__          =  width_coefficient
												a__          =  depth_coefficient
												a__          =  depth_divisor
												a__          =  kernel_sizes
												a__          =  in_channels
												a__          =  out_channels
												a__          =  depthwise_padding
												a__          =  strides
												a__          =  num_block_repeats
												a__          =  expand_ratios
												a__          =  squeeze_expansion_ratio
												a__          =  hidden_act
												a__          =  hidden_dim
												a__          =  pooling_type
												a__          =  initializer_range
												a__          =  batch_norm_eps
												a__          =  batch_norm_momentum
												a__          =  drop_connect_rate
												a__          =  sum(__A    ) * 4





							@classmethod
							def  lowercase		(   cls:     Dict				,		__A:     Union[str, os.PathLike]				,		**__A:     List[Any]    ):

												'''simple docstring'''

												cls._set_token_in_kwargs(__A    )

												a__       ,a__          =  cls.get_config_dict(__A				,		**__A    )

												# get the vision config dict if we are loading from AlignConfig
												if config_dict.get('''model_type'''    ) == "align":
																	a__          =  config_dict['''vision_config''']

												if "model_type" in config_dict and hasattr(cls				,		'''model_type'''    ) and config_dict["model_type"] != cls.model_type:
																	logger.warning(
																	    F'You are using a model of type {config_dict["model_type"]} to instantiate a model of type '
																	    F'{cls.model_type}. This is not supported for all configurations of models and can yield errors.'    )

												return cls.from_dict(__A				,		**__A    )







class        _SCREAMING_SNAKE_CASE						(  __snake_case							):





							"""simple docstring"""





							_SCREAMING_SNAKE_CASE    ='align'
							_SCREAMING_SNAKE_CASE    =True




							def __init__(   self:     Optional[int]				,		__A:     Optional[int]=None				,		__A:     Dict=None				,		__A:     List[str]=640				,		__A:     Optional[int]=1.0				,		__A:     str=0.0_2				,		**__A:     List[str]				,		):

												'''simple docstring'''

												super().__init__(**__A    )

												if text_config is None:
																	a__          =  {}
																	logger.info('''text_config is None. Initializing the AlignTextConfig with default values.'''    )

												if vision_config is None:
																	a__          =  {}
																	logger.info('''vision_config is None. Initializing the AlignVisionConfig with default values.'''    )

												a__          =  AlignTextConfig(**__A    )
												a__          =  AlignVisionConfig(**__A    )

												a__          =  projection_dim
												a__          =  temperature_init_value
												a__          =  initializer_range




							@classmethod
							def  lowercase		(   cls:     Dict				,		__A:     AlignTextConfig				,		__A:     AlignVisionConfig				,		**__A:     str    ):

												'''simple docstring'''

												return cls(text_config=text_config.to_dict()				,		vision_config=vision_config.to_dict()				,		**__A    )





							def  lowercase		(   self:     Any    ):

												'''simple docstring'''

												a__          =  copy.deepcopy(self.__dict__    )
												a__          =  self.text_config.to_dict()
												a__          =  self.vision_config.to_dict()
												a__          =  self.__class__.model_type
												return output


