'''simple docstring'''




import json
import os
import unittest

from transformers import HerbertTokenizer, HerbertTokenizerFast
from transformers.models.herbert.tokenization_herbert import VOCAB_FILES_NAMES
from transformers.testing_utils import get_tests_dir, require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin


@require_tokenizers
class    UpperCAmelCase__	(							_snake_case       ,  unittest.TestCase      ):






   """simple docstring"""
   A				:							Any			     =     HerbertTokenizer
   A				:							List[str]			     =     HerbertTokenizerFast
   A				:							Any			     =     True
   def 		_lowerCamelCase			(self					)     ->  Dict:
        super().setUp()

        # Use a simpler test file without japanese/chinese characters
        with open(f'''{get_tests_dir()}/fixtures/sample_text_no_unicode.txt'''							,					encoding='utf-8'					) as f_data:
             lowercase_       :							List[str]  					=       f_data.read().replace('\n\n'							,					'\n'					).strip()

        lowercase_       :							Any  					=       [
            '<s>',
            '</s>',
            'l',
            'o',
            'w',
            'e',
            'r',
            's',
            't',
            'i',
            'd',
            'n',
            'w</w>',
            'r</w>',
            't</w>',
            'lo',
            'low',
            'er</w>',
            'low</w>',
            'lowest</w>',
            'newer</w>',
            'wider</w>',
            ',</w>',
            '<unk>',
        ]
        lowercase_       :							Optional[int]  					=       dict(zip(_a							,					range(len(_a					)					)					)					)
        lowercase_       :							Dict  					=       ['l o 123', 'lo w 1456', 'e r</w> 1789', '']

        lowercase_       :							Optional[int]  					=       os.path.join(self.tmpdirname							,					VOCAB_FILES_NAMES['vocab_file']					)
        lowercase_       :							List[str]  					=       os.path.join(self.tmpdirname							,					VOCAB_FILES_NAMES['merges_file']					)
        with open(self.vocab_file							,					'w'					) as fp:
             fp.write(json.dumps(_a					)					)
        with open(self.merges_file							,					'w'					) as fp:
             fp.write('\n'.join(_a					)					)
   def 		_lowerCamelCase			(self							,					_a					)     ->  Tuple:
        lowercase_       :							Union[str, Any]  					=       'lower newer'
        lowercase_       :							str  					=       'lower newer'
        return input_text, output_text
   def 		_lowerCamelCase			(self					)     ->  Optional[Any]:
        lowercase_       :							List[Any]  					=       self.tokenizer_class(vocab_file=self.vocab_file							,					merges_file=self.merges_file					)

        lowercase_       :							Tuple  					=       'lower'
        lowercase_       :							Any  					=       ['low', 'er</w>']
        lowercase_       :							Dict  					=       tokenizer.tokenize(_a					)
        self.assertListEqual(_a							,					_a					)

        lowercase_       :							List[str]  					=       tokens + ['<unk>']
        lowercase_       :							int  					=       [16, 17, 23]
        self.assertListEqual(tokenizer.convert_tokens_to_ids(_a					)							,					_a					)
   def 		_lowerCamelCase			(self					)     ->  Dict:
        if not self.test_rust_tokenizer:
             return

        lowercase_       :							str  					=       self.get_tokenizer()
        lowercase_       :							str  					=       self.get_rust_tokenizer()

        lowercase_       :							Optional[int]  					=       'lower,newer'

        lowercase_       :							int  					=       tokenizer.tokenize(_a					)
        lowercase_       :							Tuple  					=       rust_tokenizer.tokenize(_a					)
        self.assertListEqual(_a							,					_a					)

        lowercase_       :							List[str]  					=       tokenizer.encode(_a							,					add_special_tokens=_a					)
        lowercase_       :							List[str]  					=       rust_tokenizer.encode(_a							,					add_special_tokens=_a					)
        self.assertListEqual(_a							,					_a					)

        lowercase_       :							Optional[int]  					=       self.get_rust_tokenizer()
        lowercase_       :							Optional[Any]  					=       tokenizer.encode(_a					)
        lowercase_       :							List[Any]  					=       rust_tokenizer.encode(_a					)
        self.assertListEqual(_a							,					_a					)





   @slow
   def 		_lowerCamelCase			(self					)     ->  str:
        lowercase_       :							Optional[Any]  					=       self.tokenizer_class.from_pretrained('allegro/herbert-base-cased'					)

        lowercase_       :							Tuple  					=       tokenizer.encode('konstruowanie sekwencji'							,					add_special_tokens=_a					)
        lowercase_       :							List[str]  					=       tokenizer.encode('konstruowanie wielu sekwencji'							,					add_special_tokens=_a					)

        lowercase_       :							int  					=       tokenizer.build_inputs_with_special_tokens(_a					)
        lowercase_       :							Any  					=       tokenizer.build_inputs_with_special_tokens(_a							,					_a					)

        assert encoded_sentence == [0] + text + [2]
        assert encoded_pair == [0] + text + [2] + text_a + [2]





'''simple docstring'''




from dataclasses import dataclass
from typing import List, Optional, Union

import numpy as np
import PIL
from PIL import Image

from ...utils import BaseOutput, is_torch_available, is_transformers_available


@dataclass
# Copied from diffusers.pipelines.stable_diffusion.__init__.StableDiffusionPipelineOutput with Stable->Alt
class    UpperCAmelCase__	(							_snake_case      ):






   """simple docstring"""
   A				:							Union[List[PIL.Image.Image], np.ndarray]
   A				:							Optional[List[bool]]


if is_transformers_available() and is_torch_available():
 from .modeling_roberta_series import RobertaSeriesModelWithTransformation
 from .pipeline_alt_diffusion import AltDiffusionPipeline
 from .pipeline_alt_diffusion_imgaimg import AltDiffusionImgaImgPipeline




