


import random
import unittest

import numpy as np
import torch

from diffusers import DDIMScheduler, LDMSuperResolutionPipeline, UNetaDModel, VQModel
from diffusers.utils import PIL_INTERPOLATION, floats_tensor, load_image, slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch


enable_full_determinism()

class      __snake_case				(   unittest.TestCase):
					@property
					def 	a			(						self       :						Optional[Any]  )							->					Optional[int]:



											'''simple docstring'''





											__magic_name__					=      1
											__magic_name__					=      3
											__magic_name__					=      (3_2, 3_2)

											__magic_name__					=      floats_tensor((batch_size, num_channels) + sizes	,      rng=random.Random(0  )  ).to(_lowerCAmelCase  )
											return image
					@property
					def 	a			(						self       :						Tuple  )							->					str:



											'''simple docstring'''





											torch.manual_seed(0  )
											__magic_name__					=      UNetaDModel(
											    block_out_channels=(3_2, 6_4)	,      layers_per_block=2	,      sample_size=3_2	,      in_channels=6	,      out_channels=3	,      down_block_types=('DownBlock2D', 'AttnDownBlock2D')	,      up_block_types=('AttnUpBlock2D', 'UpBlock2D')	,      )
											return model
					@property
					def 	a			(						self       :						Any  )							->					int:



											'''simple docstring'''





											torch.manual_seed(0  )
											__magic_name__					=      VQModel(
											    block_out_channels=[3_2, 6_4]	,      in_channels=3	,      out_channels=3	,      down_block_types=['DownEncoderBlock2D', 'DownEncoderBlock2D']	,      up_block_types=['UpDecoderBlock2D', 'UpDecoderBlock2D']	,      latent_channels=3	,      )
											return model
					def 	a			(						self       :						Optional[Any]  )							->					List[str]:



											'''simple docstring'''





											__magic_name__					=      'cpu'
											__magic_name__					=      self.dummy_uncond_unet
											__magic_name__					=      DDIMScheduler()
											__magic_name__					=      self.dummy_vq_model

											__magic_name__					=      LDMSuperResolutionPipeline(unet=_lowerCAmelCase	,      vqvae=_lowerCAmelCase	,      scheduler=_lowerCAmelCase  )
											ldm.to(_lowerCAmelCase  )
											ldm.set_progress_bar_config(disable=_lowerCAmelCase  )

											__magic_name__					=      self.dummy_image.to(_lowerCAmelCase  )

											__magic_name__					=      torch.Generator(device=_lowerCAmelCase  ).manual_seed(0  )
											__magic_name__					=      ldm(image=_lowerCAmelCase	,      generator=_lowerCAmelCase	,      num_inference_steps=2	,      output_type='numpy'  ).images

											__magic_name__					=      image[0, -3:, -3:, -1]

											assert image.shape == (1, 6_4, 6_4, 3)
											__magic_name__					=      np.array([0.8678, 0.8245, 0.6381, 0.6830, 0.4385, 0.5599, 0.4641, 0.6201, 0.5150]  )

											assert np.abs(image_slice.flatten() - expected_slice  ).max() < 1E-2







					@unittest.skipIf(torch_device != 'cuda'	,      'This test requires a GPU'  )
					def 	a			(						self       :						Optional[int]  )							->					List[Any]:



											'''simple docstring'''





											__magic_name__					=      self.dummy_uncond_unet
											__magic_name__					=      DDIMScheduler()
											__magic_name__					=      self.dummy_vq_model

											# put models in fp16
											__magic_name__					=      unet.half()
											__magic_name__					=      vqvae.half()

											__magic_name__					=      LDMSuperResolutionPipeline(unet=_lowerCAmelCase	,      vqvae=_lowerCAmelCase	,      scheduler=_lowerCAmelCase  )
											ldm.to(_lowerCAmelCase  )
											ldm.set_progress_bar_config(disable=_lowerCAmelCase  )

											__magic_name__					=      self.dummy_image.to(_lowerCAmelCase  )

											__magic_name__					=      ldm(_lowerCAmelCase	,      num_inference_steps=2	,      output_type='numpy'  ).images

											assert image.shape == (1, 6_4, 6_4, 3)







@slow
@require_torch
class      __snake_case				(   unittest.TestCase):
					def 	a			(						self       :						Dict  )							->					Optional[Any]:



											'''simple docstring'''





											__magic_name__					=      load_image(
											    'https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main'
											    '/vq_diffusion/teddy_bear_pool.png'  )
											__magic_name__					=      init_image.resize((6_4, 6_4)	,      resample=PIL_INTERPOLATION['lanczos']  )

											__magic_name__					=      LDMSuperResolutionPipeline.from_pretrained('duongna/ldm-super-resolution'	,      device_map='auto'  )
											ldm.set_progress_bar_config(disable=_lowerCAmelCase  )

											__magic_name__					=      torch.manual_seed(0  )
											__magic_name__					=      ldm(image=_lowerCAmelCase	,      generator=_lowerCAmelCase	,      num_inference_steps=2_0	,      output_type='numpy'  ).images

											__magic_name__					=      image[0, -3:, -3:, -1]

											assert image.shape == (1, 2_5_6, 2_5_6, 3)
											__magic_name__					=      np.array([0.7644, 0.7679, 0.7642, 0.7633, 0.7666, 0.7560, 0.7425, 0.7257, 0.6907]  )

											assert np.abs(image_slice.flatten() - expected_slice  ).max() < 1E-2





import os
import unittest

from transformers import ElectraTokenizerFast
from transformers.models.electra.tokenization_electra import (
    VOCAB_FILES_NAMES,
    BasicTokenizer,
    ElectraTokenizer,
    WordpieceTokenizer,
    _is_control,
    _is_punctuation,
    _is_whitespace,
)
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin, filter_non_english

@require_tokenizers
class      __snake_case				(   _UpperCAmelCase	,      unittest.TestCase):
					SCREAMING_SNAKE_CASE_		:       str								=			ElectraTokenizer
					SCREAMING_SNAKE_CASE_		:       Any								=			ElectraTokenizerFast
					SCREAMING_SNAKE_CASE_		:       Tuple								=			True
					SCREAMING_SNAKE_CASE_		:       str								=			True
					SCREAMING_SNAKE_CASE_		:       str								=			filter_non_english
					def 	a			(						self       :						int  )							->					Optional[int]:



											'''simple docstring'''





											super().setUp()

											__magic_name__					=      [
											    '[UNK]',
											    '[CLS]',
											    '[SEP]',
											    '[PAD]',
											    '[MASK]',
											    'want',
											    '##want',
											    '##ed',
											    'wa',
											    'un',
											    'runn',
											    '##ing',
											    ',',
											    'low',
											    'lowest',
											]
											__magic_name__					=      os.path.join(self.tmpdirname	,      VOCAB_FILES_NAMES['vocab_file']  )
											with open(self.vocab_file	,      'w'	,      encoding='utf-8'  ) as vocab_writer:
																	vocab_writer.write(''.join([x + '\n' for x in vocab_tokens]  )  )
					def 	a			(						self       :						Tuple	,      _lowerCAmelCase       :						Dict  )							->					List[Any]:



											'''simple docstring'''





											__magic_name__					=      'UNwant\u00E9d,running'
											__magic_name__					=      'unwanted, running'
											return input_text, output_text
					def 	a			(						self       :						Union[str, Any]  )							->					Tuple:



											'''simple docstring'''





											__magic_name__					=      self.tokenizer_class(self.vocab_file  )

											__magic_name__					=      tokenizer.tokenize('UNwant\u00E9d,running'  )
											self.assertListEqual(_lowerCAmelCase	,      ['un', '##want', '##ed', ',', 'runn', '##ing']  )
											self.assertListEqual(tokenizer.convert_tokens_to_ids(_lowerCAmelCase  )	,      [9, 6, 7, 1_2, 1_0, 1_1]  )
					def 	a			(						self       :						Optional[int]  )							->					Dict:



											'''simple docstring'''





											if not self.test_rust_tokenizer:
																	return

											__magic_name__					=      self.get_tokenizer()
											__magic_name__					=      self.get_rust_tokenizer()

											__magic_name__					=      'UNwant\u00E9d,running'

											__magic_name__					=      tokenizer.tokenize(_lowerCAmelCase  )
											__magic_name__					=      rust_tokenizer.tokenize(_lowerCAmelCase  )
											self.assertListEqual(_lowerCAmelCase	,      _lowerCAmelCase  )

											__magic_name__					=      tokenizer.encode(_lowerCAmelCase	,      add_special_tokens=_lowerCAmelCase  )
											__magic_name__					=      rust_tokenizer.encode(_lowerCAmelCase	,      add_special_tokens=_lowerCAmelCase  )
											self.assertListEqual(_lowerCAmelCase	,      _lowerCAmelCase  )

											__magic_name__					=      self.get_rust_tokenizer()
											__magic_name__					=      tokenizer.encode(_lowerCAmelCase  )
											__magic_name__					=      rust_tokenizer.encode(_lowerCAmelCase  )
											self.assertListEqual(_lowerCAmelCase	,      _lowerCAmelCase  )

											# With lower casing
											__magic_name__					=      self.get_tokenizer(do_lower_case=_lowerCAmelCase  )
											__magic_name__					=      self.get_rust_tokenizer(do_lower_case=_lowerCAmelCase  )

											__magic_name__					=      'UNwant\u00E9d,running'

											__magic_name__					=      tokenizer.tokenize(_lowerCAmelCase  )
											__magic_name__					=      rust_tokenizer.tokenize(_lowerCAmelCase  )
											self.assertListEqual(_lowerCAmelCase	,      _lowerCAmelCase  )

											__magic_name__					=      tokenizer.encode(_lowerCAmelCase	,      add_special_tokens=_lowerCAmelCase  )
											__magic_name__					=      rust_tokenizer.encode(_lowerCAmelCase	,      add_special_tokens=_lowerCAmelCase  )
											self.assertListEqual(_lowerCAmelCase	,      _lowerCAmelCase  )

											__magic_name__					=      self.get_rust_tokenizer()
											__magic_name__					=      tokenizer.encode(_lowerCAmelCase  )
											__magic_name__					=      rust_tokenizer.encode(_lowerCAmelCase  )
											self.assertListEqual(_lowerCAmelCase	,      _lowerCAmelCase  )
					def 	a			(						self       :						str  )							->					Optional[Any]:



											'''simple docstring'''





											__magic_name__					=      BasicTokenizer()

											self.assertListEqual(tokenizer.tokenize('ah\u535A\u63A8zz'  )	,      ['ah', '\u535A', '\u63A8', 'zz']  )
					def 	a			(						self       :						Optional[int]  )							->					int:



											'''simple docstring'''





											__magic_name__					=      BasicTokenizer(do_lower_case=_lowerCAmelCase  )

											self.assertListEqual(
											    tokenizer.tokenize(' \tHeLLo!how  \n Are yoU?  '  )	,      ['hello', '!', 'how', 'are', 'you', '?']  )
											self.assertListEqual(tokenizer.tokenize('H\u00E9llo'  )	,      ['hello']  )
					def 	a			(						self       :						int  )							->					Union[str, Any]:



											'''simple docstring'''





											__magic_name__					=      BasicTokenizer(do_lower_case=_lowerCAmelCase	,      strip_accents=_lowerCAmelCase  )

											self.assertListEqual(
											    tokenizer.tokenize(' \tHäLLo!how  \n Are yoU?  '  )	,      ['hällo', '!', 'how', 'are', 'you', '?']  )
											self.assertListEqual(tokenizer.tokenize('H\u00E9llo'  )	,      ['h\u00E9llo']  )
					def 	a			(						self       :						Any  )							->					Tuple:



											'''simple docstring'''





											__magic_name__					=      BasicTokenizer(do_lower_case=_lowerCAmelCase	,      strip_accents=_lowerCAmelCase  )

											self.assertListEqual(
											    tokenizer.tokenize(' \tHäLLo!how  \n Are yoU?  '  )	,      ['hallo', '!', 'how', 'are', 'you', '?']  )
											self.assertListEqual(tokenizer.tokenize('H\u00E9llo'  )	,      ['hello']  )
					def 	a			(						self       :						List[str]  )							->					str:



											'''simple docstring'''





											__magic_name__					=      BasicTokenizer(do_lower_case=_lowerCAmelCase  )

											self.assertListEqual(
											    tokenizer.tokenize(' \tHäLLo!how  \n Are yoU?  '  )	,      ['hallo', '!', 'how', 'are', 'you', '?']  )
											self.assertListEqual(tokenizer.tokenize('H\u00E9llo'  )	,      ['hello']  )
					def 	a			(						self       :						Union[str, Any]  )							->					Optional[Any]:



											'''simple docstring'''





											__magic_name__					=      BasicTokenizer(do_lower_case=_lowerCAmelCase  )

											self.assertListEqual(
											    tokenizer.tokenize(' \tHeLLo!how  \n Are yoU?  '  )	,      ['HeLLo', '!', 'how', 'Are', 'yoU', '?']  )
					def 	a			(						self       :						int  )							->					int:



											'''simple docstring'''





											__magic_name__					=      BasicTokenizer(do_lower_case=_lowerCAmelCase	,      strip_accents=_lowerCAmelCase  )

											self.assertListEqual(
											    tokenizer.tokenize(' \tHäLLo!how  \n Are yoU?  '  )	,      ['HäLLo', '!', 'how', 'Are', 'yoU', '?']  )
					def 	a			(						self       :						Dict  )							->					int:



											'''simple docstring'''





											__magic_name__					=      BasicTokenizer(do_lower_case=_lowerCAmelCase	,      strip_accents=_lowerCAmelCase  )

											self.assertListEqual(
											    tokenizer.tokenize(' \tHäLLo!how  \n Are yoU?  '  )	,      ['HaLLo', '!', 'how', 'Are', 'yoU', '?']  )
					def 	a			(						self       :						Tuple  )							->					List[str]:



											'''simple docstring'''





											__magic_name__					=      BasicTokenizer(do_lower_case=_lowerCAmelCase	,      never_split=['[UNK]']  )

											self.assertListEqual(
											    tokenizer.tokenize(' \tHeLLo!how  \n Are yoU? [UNK]'  )	,      ['HeLLo', '!', 'how', 'Are', 'yoU', '?', '[UNK]']  )
					def 	a			(						self       :						Dict  )							->					List[str]:



											'''simple docstring'''





											__magic_name__					=      ['[UNK]', '[CLS]', '[SEP]', 'want', '##want', '##ed', 'wa', 'un', 'runn', '##ing']

											__magic_name__					=      {}
											for i, token in enumerate(_lowerCAmelCase  ):
																	__magic_name__					=      i
											__magic_name__					=      WordpieceTokenizer(vocab=_lowerCAmelCase	,      unk_token='[UNK]'  )

											self.assertListEqual(tokenizer.tokenize(''  )	,      []  )

											self.assertListEqual(tokenizer.tokenize('unwanted running'  )	,      ['un', '##want', '##ed', 'runn', '##ing']  )

											self.assertListEqual(tokenizer.tokenize('unwantedX running'  )	,      ['[UNK]', 'runn', '##ing']  )
					def 	a			(						self       :						List[str]  )							->					Union[str, Any]:



											'''simple docstring'''





											self.assertTrue(_is_whitespace(' '  )  )
											self.assertTrue(_is_whitespace('\t'  )  )
											self.assertTrue(_is_whitespace('\r'  )  )
											self.assertTrue(_is_whitespace('\n'  )  )
											self.assertTrue(_is_whitespace('\u00A0'  )  )

											self.assertFalse(_is_whitespace('A'  )  )
											self.assertFalse(_is_whitespace('-'  )  )
					def 	a			(						self       :						Optional[int]  )							->					Dict:



											'''simple docstring'''





											self.assertTrue(_is_control('\u0005'  )  )

											self.assertFalse(_is_control('A'  )  )
											self.assertFalse(_is_control(' '  )  )
											self.assertFalse(_is_control('\t'  )  )
											self.assertFalse(_is_control('\r'  )  )
					def 	a			(						self       :						List[Any]  )							->					List[str]:



											'''simple docstring'''





											self.assertTrue(_is_punctuation('-'  )  )
											self.assertTrue(_is_punctuation('$'  )  )
											self.assertTrue(_is_punctuation('`'  )  )
											self.assertTrue(_is_punctuation('.'  )  )

											self.assertFalse(_is_punctuation('A'  )  )
											self.assertFalse(_is_punctuation(' '  )  )
					def 	a			(						self       :						Optional[Any]  )							->					int:



											'''simple docstring'''





											__magic_name__					=      self.get_tokenizer()
											__magic_name__					=      self.get_rust_tokenizer()

											# Example taken from the issue https://github.com/huggingface/tokenizers/issues/340
											self.assertListEqual([tokenizer.tokenize(_lowerCAmelCase  ) for t in ['Test', '\xad', 'test']]	,      [['[UNK]'], [], ['[UNK]']]  )

											self.assertListEqual(
											    [rust_tokenizer.tokenize(_lowerCAmelCase  ) for t in ['Test', '\xad', 'test']]	,      [['[UNK]'], [], ['[UNK]']]  )
					@slow
					def 	a			(						self       :						str  )							->					List[str]:



											'''simple docstring'''





											__magic_name__					=      self.tokenizer_class.from_pretrained('google/electra-base-discriminator'  )

											__magic_name__					=      tokenizer.encode('sequence builders'	,      add_special_tokens=_lowerCAmelCase  )
											__magic_name__					=      tokenizer.encode('multi-sequence build'	,      add_special_tokens=_lowerCAmelCase  )

											__magic_name__					=      tokenizer.build_inputs_with_special_tokens(_lowerCAmelCase  )
											__magic_name__					=      tokenizer.build_inputs_with_special_tokens(_lowerCAmelCase	,      _lowerCAmelCase  )

											assert encoded_sentence == [1_0_1] + text + [1_0_2]
											assert encoded_pair == [1_0_1] + text + [1_0_2] + text_a + [1_0_2]
					def 	a			(						self       :						int  )							->					Union[str, Any]:



											'''simple docstring'''





											for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
																	with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})'''  ):
																							__magic_name__					=      self.rust_tokenizer_class.from_pretrained(_lowerCAmelCase	,      **_lowerCAmelCase  )

																							__magic_name__					=      F'''A, naïve {tokenizer_r.mask_token} AllenNLP sentence.'''
																							__magic_name__					=      tokenizer_r.encode_plus(
																							    _lowerCAmelCase	,      return_attention_mask=_lowerCAmelCase	,      return_token_type_ids=_lowerCAmelCase	,      return_offsets_mapping=_lowerCAmelCase	,      add_special_tokens=_lowerCAmelCase	,      )

																							__magic_name__					=      tokenizer_r.do_lower_case if hasattr(_lowerCAmelCase	,      'do_lower_case'  ) else False
																							__magic_name__					=      (
																							    [
																							        ((0, 0), tokenizer_r.cls_token),
																							        ((0, 1), 'A'),
																							        ((1, 2), ','),
																							        ((3, 5), 'na'),
																							        ((5, 6), '##ï'),
																							        ((6, 8), '##ve'),
																							        ((9, 1_5), tokenizer_r.mask_token),
																							        ((1_6, 2_1), 'Allen'),
																							        ((2_1, 2_3), '##NL'),
																							        ((2_3, 2_4), '##P'),
																							        ((2_5, 3_3), 'sentence'),
																							        ((3_3, 3_4), '.'),
																							        ((0, 0), tokenizer_r.sep_token),
																							    ]
																							    if not do_lower_case
																							    else [
																							        ((0, 0), tokenizer_r.cls_token),
																							        ((0, 1), 'a'),
																							        ((1, 2), ','),
																							        ((3, 8), 'naive'),
																							        ((9, 1_5), tokenizer_r.mask_token),
																							        ((1_6, 2_1), 'allen'),
																							        ((2_1, 2_3), '##nl'),
																							        ((2_3, 2_4), '##p'),
																							        ((2_5, 3_3), 'sentence'),
																							        ((3_3, 3_4), '.'),
																							        ((0, 0), tokenizer_r.sep_token),
																							    ]
																							)

																							self.assertEqual(
																							    [e[1] for e in expected_results]	,      tokenizer_r.convert_ids_to_tokens(tokens['input_ids']  )  )
																							self.assertEqual([e[0] for e in expected_results]	,      tokens['offset_mapping']  )







					def 	a			(						self       :						Any  )							->					int:



											'''simple docstring'''





											__magic_name__					=      ['的', '人', '有']
											__magic_name__					=      ''.join(_lowerCAmelCase  )
											for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
																	with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})'''  ):
																							__magic_name__					=      True
																							__magic_name__					=      self.tokenizer_class.from_pretrained(_lowerCAmelCase	,      **_lowerCAmelCase  )
																							__magic_name__					=      self.rust_tokenizer_class.from_pretrained(_lowerCAmelCase	,      **_lowerCAmelCase  )

																							__magic_name__					=      tokenizer_p.encode(_lowerCAmelCase	,      add_special_tokens=_lowerCAmelCase  )
																							__magic_name__					=      tokenizer_r.encode(_lowerCAmelCase	,      add_special_tokens=_lowerCAmelCase  )

																							__magic_name__					=      tokenizer_r.convert_ids_to_tokens(_lowerCAmelCase  )
																							__magic_name__					=      tokenizer_p.convert_ids_to_tokens(_lowerCAmelCase  )

																							# it is expected that each Chinese character is not preceded by "##"
																							self.assertListEqual(_lowerCAmelCase	,      _lowerCAmelCase  )
																							self.assertListEqual(_lowerCAmelCase	,      _lowerCAmelCase  )

																							__magic_name__					=      False
																							__magic_name__					=      self.rust_tokenizer_class.from_pretrained(_lowerCAmelCase	,      **_lowerCAmelCase  )
																							__magic_name__					=      self.tokenizer_class.from_pretrained(_lowerCAmelCase	,      **_lowerCAmelCase  )

																							__magic_name__					=      tokenizer_r.encode(_lowerCAmelCase	,      add_special_tokens=_lowerCAmelCase  )
																							__magic_name__					=      tokenizer_p.encode(_lowerCAmelCase	,      add_special_tokens=_lowerCAmelCase  )

																							__magic_name__					=      tokenizer_r.convert_ids_to_tokens(_lowerCAmelCase  )
																							__magic_name__					=      tokenizer_p.convert_ids_to_tokens(_lowerCAmelCase  )

																							# it is expected that only the first Chinese character is not preceded by "##".
																							__magic_name__					=      [
																							    F'''##{token}''' if idx != 0 else token for idx, token in enumerate(_lowerCAmelCase  )
																							]
																							self.assertListEqual(_lowerCAmelCase	,      _lowerCAmelCase  )
																							self.assertListEqual(_lowerCAmelCase	,      _lowerCAmelCase  )

