


"""simple docstring"""
import json
import os
from typing import Dict, List, Optional, Tuple

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


__SCREAMING_SNAKE_CASE							:    Any		=    logging.get_logger(__name__)


__SCREAMING_SNAKE_CASE							:    Union[str, Any]		=    {
    'vocab_file': 'vocab.json',
    'tokenizer_config_file': 'tokenizer_config.json',
    'merges_file': 'merges.txt',
}

__SCREAMING_SNAKE_CASE							:    List[str]		=    {
    'vocab_file': {
        'facebook/s2t-wav2vec2-large-en-de': (
            'https://huggingface.co/facebook/s2t-wav2vec2-large-en-de/resolve/main/vocab.json'
        ),
    },
    'tokenizer_config_file': {
        'facebook/s2t-wav2vec2-large-en-de': (
            'https://huggingface.co/facebook/s2t-wav2vec2-large-en-de/resolve/main/tokenizer_config.json'
        ),
    },
    'merges_file': {
        'facebook/s2t-wav2vec2-large-en-de': (
            'https://huggingface.co/facebook/s2t-wav2vec2-large-en-de/resolve/main/merges.txt'
        ),
    },
}

__SCREAMING_SNAKE_CASE							:    int		=    '</w>'
__SCREAMING_SNAKE_CASE							:    List[Any]		=    '@@ '







def 						_a				(      _SCREAMING_SNAKE_CASE				)    ->				Optional[int]:
							snake_case_           =		set()
							snake_case_           =		word[0]
							for char in word[1:]:
														pairs.add((prev_char, char)				)
														snake_case_           =		char
							return pairs


# Speech2Text2 has no max input length
__SCREAMING_SNAKE_CASE							:    Dict		=    {'facebook/s2t-wav2vec2-large-en-de': 1_024}





class      __A     (snake_case__):





							'''simple docstring'''

							__lowercase:		int							      =    VOCAB_FILES_NAMES
							__lowercase:		str							      =    PRETRAINED_VOCAB_FILES_MAP
							__lowercase:		Optional[Any]							      =    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							__lowercase:		Optional[Any]							      =    ["""input_ids""", """attention_mask"""]



							def __init__(				self							:      Any		,       UpperCAmelCase_							:      Dict		,       UpperCAmelCase_							:      Optional[int]="<s>"		,       UpperCAmelCase_							:      Optional[Any]="<pad>"		,       UpperCAmelCase_							:      List[Any]="</s>"		,       UpperCAmelCase_							:      List[str]="<unk>"		,       UpperCAmelCase_							:      Tuple=False		,       UpperCAmelCase_							:      Any=None		,       **UpperCAmelCase_							:      List[str]		,       )					->List[str]:



														"""simple docstring"""



														super().__init__(
														    unk_token=UpperCAmelCase_		,       bos_token=UpperCAmelCase_		,       eos_token=UpperCAmelCase_		,       pad_token=UpperCAmelCase_		,       do_lower_case=UpperCAmelCase_		,       **UpperCAmelCase_		,       )

														snake_case_           =		do_lower_case

														with open(UpperCAmelCase_		,       encoding="""utf-8"""       ) as vocab_handle:
																					snake_case_           =		json.load(UpperCAmelCase_       )
														snake_case_           =		{v: k for k, v in self.encoder.items()}

														if merges_file is None:
																					logger.info(F"""No merges files provided. {self.__class__.__name__} can only be used for decoding."""       )

																					snake_case_           =		None
																					snake_case_           =		None
														else:
																					with open(UpperCAmelCase_		,       encoding="""utf-8"""       ) as merges_handle:
																												snake_case_           =		merges_handle.read().split("""\n"""       )[:-1]

																					snake_case_           =		[tuple(merge.split()[:2]       ) for merge in merges]
																					snake_case_           =		dict(zip(UpperCAmelCase_		,       range(len(UpperCAmelCase_       )       )       )       )
																					snake_case_           =		{}



							@property
							def 		lowerCAmelCase       (				self							:      Dict       )					->int:



														"""simple docstring"""



														return len(self.decoder       )



							def 		lowerCAmelCase       (				self							:      int       )					->Dict:



														"""simple docstring"""



														return dict(self.encoder		,       **self.added_tokens_encoder       )



							def 		lowerCAmelCase       (				self							:      int		,       UpperCAmelCase_							:      List[Any]       )					->List[Any]:



														"""simple docstring"""



														snake_case_           =		tuple(token[:-1]       ) + (token[-1] + BPE_TOKEN_MERGES,)
														if token in self.cache:
																					return self.cache[token]
														snake_case_           =		get_pairs(UpperCAmelCase_       )

														if not pairs:
																					return token

														while True:
																					snake_case_           =		min(UpperCAmelCase_		,       key=lambda UpperCAmelCase_       : self.bpe_ranks.get(UpperCAmelCase_		,       float("""inf"""       )       )       )
																					if bigram not in self.bpe_ranks:
																												break
																					snake_case_       ,						snake_case_           =		bigram
																					snake_case_           =		[]
																					snake_case_           =		0
																					while i < len(UpperCAmelCase_       ):
																												try:
																																			snake_case_           =		word.index(UpperCAmelCase_		,       UpperCAmelCase_       )
																												except ValueError:
																																			new_word.extend(word[i:]       )
																																			break
																												else:
																																			new_word.extend(word[i:j]       )
																																			snake_case_           =		j

																												if word[i] == first and i < len(UpperCAmelCase_       ) - 1 and word[i + 1] == second:
																																			new_word.append(first + second       )
																																			i += 2
																												else:
																																			new_word.append(word[i]       )
																																			i += 1
																					snake_case_           =		tuple(UpperCAmelCase_       )
																					snake_case_           =		new_word
																					if len(UpperCAmelCase_       ) == 1:
																												break
																					else:
																												snake_case_           =		get_pairs(UpperCAmelCase_       )
														snake_case_           =		""" """.join(UpperCAmelCase_       )
														if word == "\n  " + BPE_TOKEN_MERGES:
																					snake_case_           =		"""\n""" + BPE_TOKEN_MERGES

														if word.endswith(UpperCAmelCase_       ):
																					snake_case_           =		word.replace(UpperCAmelCase_		,       """"""       )

														snake_case_           =		word.replace(""" """		,       UpperCAmelCase_       )
														snake_case_           =		word
														return word



							def 		lowerCAmelCase       (				self							:      Union[str, Any]		,       UpperCAmelCase_							:      Optional[Any]       )					->List[str]:



														"""simple docstring"""



														if self.bpe_ranks is None:
																					raise ValueError(
																					    """This tokenizer was instantiated without a `merges.txt` file, so"""
																					    """ that it can only be used for decoding, not for encoding."""
																					    """Make sure to provide `merges.txt` file at instantiation to enable """
																					    """encoding."""       )

														if self.do_lower_case:
																					snake_case_           =		text.lower()

														snake_case_           =		text.split()

														snake_case_           =		[]
														for token in text:
																					if token:
																												split_tokens.extend(list(self.bpe(UpperCAmelCase_       ).split(""" """       )       )       )

														return split_tokens



							def 		lowerCAmelCase       (				self							:      List[Any]		,       UpperCAmelCase_							:      str       )					->int:



														"""simple docstring"""



														return self.encoder.get(UpperCAmelCase_		,       self.encoder.get(self.unk_token       )       )



							def 		lowerCAmelCase       (				self							:      List[Any]		,       UpperCAmelCase_							:      int       )					->str:



														"""simple docstring"""



														snake_case_           =		self.decoder.get(UpperCAmelCase_		,       self.unk_token       )
														return result



							def 		lowerCAmelCase       (				self							:      Tuple		,       UpperCAmelCase_							:      List[str]       )					->str:



														"""simple docstring"""



														snake_case_           =		""" """.join(UpperCAmelCase_       )

														# make sure @@ tokens are concatenated
														snake_case_           =		"""""".join(string.split(UpperCAmelCase_       )       )

														return string



							def 		lowerCAmelCase       (				self							:      Any		,       UpperCAmelCase_							:      str		,       UpperCAmelCase_							:      Optional[str] = None       )					->Tuple[str]:



														"""simple docstring"""



														if not os.path.isdir(UpperCAmelCase_       ):
																					logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""       )
																					return
														snake_case_           =		os.path.join(
														    UpperCAmelCase_		,       (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]       )
														snake_case_           =		os.path.join(
														    UpperCAmelCase_		,       (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""merges_file"""]       )

														with open(UpperCAmelCase_		,       """w"""		,       encoding="""utf-8"""       ) as f:
																					f.write(json.dumps(self.encoder		,       indent=2		,       sort_keys=UpperCAmelCase_		,       ensure_ascii=UpperCAmelCase_       ) + """\n"""       )

														snake_case_           =		0
														if self.bpe_ranks is None:
																					return (vocab_file,)

														with open(UpperCAmelCase_		,       """w"""		,       encoding="""utf-8"""       ) as writer:
																					for bpe_tokens, token_index in sorted(self.bpe_ranks.items()		,       key=lambda UpperCAmelCase_       : kv[1]       ):
																												if index != token_index:
																																			logger.warning(
																																			    F"""Saving vocabulary to {merges_file}: BPE merge indices are not consecutive."""
																																			    """ Please check that the tokenizer is not corrupted!"""       )
																																			snake_case_           =		token_index
																												writer.write(""" """.join(UpperCAmelCase_       ) + """\n"""       )
																												index += 1

														return (vocab_file, merges_file)







"""simple docstring"""
import unittest

import torch

from diffusers import VQModel
from diffusers.utils import floats_tensor, torch_device
from diffusers.utils.testing_utils import enable_full_determinism

from .test_modeling_common import ModelTesterMixin, UNetTesterMixin


enable_full_determinism()





class      __A     (snake_case__						,		snake_case__						,		unittest.TestCase):





							'''simple docstring'''

							__lowercase:		str							      =    VQModel
							__lowercase:		Union[str, Any]							      =    """sample"""



							@property
							def 		lowerCAmelCase       (				self							:      List[str]		,       UpperCAmelCase_							:      List[str]=(32, 32)       )					->Tuple:



														"""simple docstring"""



														snake_case_           =		4
														snake_case_           =		3

														snake_case_           =		floats_tensor((batch_size, num_channels) + sizes       ).to(UpperCAmelCase_       )

														return {"sample": image}



							@property
							def 		lowerCAmelCase       (				self							:      Tuple       )					->str:



														"""simple docstring"""



														return (3, 32, 32)



							@property
							def 		lowerCAmelCase       (				self							:      List[Any]       )					->Any:



														"""simple docstring"""



														return (3, 32, 32)



							def 		lowerCAmelCase       (				self							:      Optional[int]       )					->Dict:



														"""simple docstring"""



														snake_case_           =		{
														    """block_out_channels""": [32, 64],
														    """in_channels""": 3,
														    """out_channels""": 3,
														    """down_block_types""": ["""DownEncoderBlock2D""", """DownEncoderBlock2D"""],
														    """up_block_types""": ["""UpDecoderBlock2D""", """UpDecoderBlock2D"""],
														    """latent_channels""": 3,
														}
														snake_case_           =		self.dummy_input
														return init_dict, inputs_dict



							def 		lowerCAmelCase       (				self							:      List[str]       )					->Dict:



														"""simple docstring"""



														pass



							def 		lowerCAmelCase       (				self							:      Optional[Any]       )					->List[str]:



														"""simple docstring"""



														pass



							def 		lowerCAmelCase       (				self							:      Any       )					->Union[str, Any]:



														"""simple docstring"""



														snake_case_       ,						snake_case_           =		VQModel.from_pretrained("""fusing/vqgan-dummy"""		,       output_loading_info=UpperCAmelCase_       )
														self.assertIsNotNone(UpperCAmelCase_       )
														self.assertEqual(len(loading_info["""missing_keys"""]       )		,       0       )

														model.to(UpperCAmelCase_       )
														snake_case_           =		model(**self.dummy_input       )

														assert image is not None, "Make sure output is not None"



							def 		lowerCAmelCase       (				self							:      Tuple       )					->Optional[Any]:



														"""simple docstring"""



														snake_case_           =		VQModel.from_pretrained("""fusing/vqgan-dummy"""       )
														model.to(UpperCAmelCase_       ).eval()

														torch.manual_seed(0       )
														if torch.cuda.is_available():
																					torch.cuda.manual_seed_all(0       )

														snake_case_           =		torch.randn(1		,       model.config.in_channels		,       model.config.sample_size		,       model.config.sample_size       )
														snake_case_           =		image.to(UpperCAmelCase_       )
														with torch.no_grad():
																					snake_case_           =		model(UpperCAmelCase_       ).sample

														snake_case_           =		output[0, -1, -3:, -3:].flatten().cpu()
														# fmt: off
														snake_case_           =		torch.tensor([-0.0_153, -0.4_044, -0.1_880, -0.5_161, -0.2_418, -0.4_072, -0.1_612, -0.0_633, -0.0_143]       )
														# fmt: on
														self.assertTrue(torch.allclose(UpperCAmelCase_		,       UpperCAmelCase_		,       atol=1E-3       )       )



