
import os
import unittest

from transformers import BertTokenizerFast
from transformers.models.bert.tokenization_bert import (
    VOCAB_FILES_NAMES,
    BasicTokenizer,
    BertTokenizer,
    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 				lowercase					(		_SCREAMING_SNAKE_CASE  ,   unittest.TestCase   ):
		__lowercase       :       Any	     =				BertTokenizer
		__lowercase       :       Any	     =				BertTokenizerFast
		__lowercase       :       Tuple	     =				True
		__lowercase       :       int	     =				True
		__lowercase       :       List[str]	     =				filter_non_english



		def __UpperCamelCase ( self       )  ->					Dict:
				"""simple docstring"""
				super().setUp()

				UpperCamelCase		=     [
				    '[UNK]',
				    '[CLS]',
				    '[SEP]',
				    '[PAD]',
				    '[MASK]',
				    'want',
				    '##want',
				    '##ed',
				    'wa',
				    'un',
				    'runn',
				    '##ing',
				    ',',
				    'low',
				    'lowest',
				]
				UpperCamelCase		=     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 __UpperCamelCase ( self				,      A_       )  ->					Tuple:
				"""simple docstring"""
				UpperCamelCase		=     'UNwant\u00E9d,running'
				UpperCamelCase		=     'unwanted, running'
				return input_text, output_text



		def __UpperCamelCase ( self       )  ->					List[Any]:
				"""simple docstring"""
				UpperCamelCase		=     self.tokenizer_class(self.vocab_file       )

				UpperCamelCase		=     tokenizer.tokenize('UNwant\u00E9d,running'       )
				self.assertListEqual(A_				,      ['un', '##want', '##ed', ',', 'runn', '##ing']       )
				self.assertListEqual(tokenizer.convert_tokens_to_ids(A_       )				,      [9, 6, 7, 12, 10, 11]       )



		def __UpperCamelCase ( self       )  ->					Optional[Any]:
				"""simple docstring"""
				if not self.test_rust_tokenizer:
						return

				UpperCamelCase		=     self.get_tokenizer()
				UpperCamelCase		=     self.get_rust_tokenizer()

				UpperCamelCase		=     'UNwant\u00E9d,running'

				UpperCamelCase		=     tokenizer.tokenize(A_       )
				UpperCamelCase		=     rust_tokenizer.tokenize(A_       )
				self.assertListEqual(A_				,      A_       )

				UpperCamelCase		=     tokenizer.encode(A_				,      add_special_tokens=A_       )
				UpperCamelCase		=     rust_tokenizer.encode(A_				,      add_special_tokens=A_       )
				self.assertListEqual(A_				,      A_       )

				UpperCamelCase		=     self.get_rust_tokenizer()
				UpperCamelCase		=     tokenizer.encode(A_       )
				UpperCamelCase		=     rust_tokenizer.encode(A_       )
				self.assertListEqual(A_				,      A_       )

				# With lower casing
				UpperCamelCase		=     self.get_tokenizer(do_lower_case=A_       )
				UpperCamelCase		=     self.get_rust_tokenizer(do_lower_case=A_       )

				UpperCamelCase		=     'UNwant\u00E9d,running'

				UpperCamelCase		=     tokenizer.tokenize(A_       )
				UpperCamelCase		=     rust_tokenizer.tokenize(A_       )
				self.assertListEqual(A_				,      A_       )

				UpperCamelCase		=     tokenizer.encode(A_				,      add_special_tokens=A_       )
				UpperCamelCase		=     rust_tokenizer.encode(A_				,      add_special_tokens=A_       )
				self.assertListEqual(A_				,      A_       )

				UpperCamelCase		=     self.get_rust_tokenizer()
				UpperCamelCase		=     tokenizer.encode(A_       )
				UpperCamelCase		=     rust_tokenizer.encode(A_       )
				self.assertListEqual(A_				,      A_       )



		def __UpperCamelCase ( self       )  ->					Tuple:
				"""simple docstring"""
				UpperCamelCase		=     BasicTokenizer()

				self.assertListEqual(tokenizer.tokenize('ah\u535A\u63A8zz'       )				,      ['ah', '\u535A', '\u63A8', 'zz']       )



		def __UpperCamelCase ( self       )  ->					Tuple:
				"""simple docstring"""
				UpperCamelCase		=     BasicTokenizer(do_lower_case=A_       )

				self.assertListEqual(
				    tokenizer.tokenize(' \tHeLLo!how  \n Are yoU?  '       )				,      ['hello', '!', 'how', 'are', 'you', '?']       )
				self.assertListEqual(tokenizer.tokenize('H\u00E9llo'       )				,      ['hello']       )



		def __UpperCamelCase ( self       )  ->					str:
				"""simple docstring"""
				UpperCamelCase		=     BasicTokenizer(do_lower_case=A_				,      strip_accents=A_       )

				self.assertListEqual(
				    tokenizer.tokenize(' \tHäLLo!how  \n Are yoU?  '       )				,      ['hällo', '!', 'how', 'are', 'you', '?']       )
				self.assertListEqual(tokenizer.tokenize('H\u00E9llo'       )				,      ['h\u00E9llo']       )



		def __UpperCamelCase ( self       )  ->					Optional[Any]:
				"""simple docstring"""
				UpperCamelCase		=     BasicTokenizer(do_lower_case=A_				,      strip_accents=A_       )

				self.assertListEqual(
				    tokenizer.tokenize(' \tHäLLo!how  \n Are yoU?  '       )				,      ['hallo', '!', 'how', 'are', 'you', '?']       )
				self.assertListEqual(tokenizer.tokenize('H\u00E9llo'       )				,      ['hello']       )



		def __UpperCamelCase ( self       )  ->					str:
				"""simple docstring"""
				UpperCamelCase		=     BasicTokenizer(do_lower_case=A_       )

				self.assertListEqual(
				    tokenizer.tokenize(' \tHäLLo!how  \n Are yoU?  '       )				,      ['hallo', '!', 'how', 'are', 'you', '?']       )
				self.assertListEqual(tokenizer.tokenize('H\u00E9llo'       )				,      ['hello']       )



		def __UpperCamelCase ( self       )  ->					Dict:
				"""simple docstring"""
				UpperCamelCase		=     BasicTokenizer(do_lower_case=A_       )

				self.assertListEqual(
				    tokenizer.tokenize(' \tHeLLo!how  \n Are yoU?  '       )				,      ['HeLLo', '!', 'how', 'Are', 'yoU', '?']       )



		def __UpperCamelCase ( self       )  ->					List[str]:
				"""simple docstring"""
				UpperCamelCase		=     BasicTokenizer(do_lower_case=A_				,      strip_accents=A_       )

				self.assertListEqual(
				    tokenizer.tokenize(' \tHäLLo!how  \n Are yoU?  '       )				,      ['HäLLo', '!', 'how', 'Are', 'yoU', '?']       )



		def __UpperCamelCase ( self       )  ->					Optional[Any]:
				"""simple docstring"""
				UpperCamelCase		=     BasicTokenizer(do_lower_case=A_				,      strip_accents=A_       )

				self.assertListEqual(
				    tokenizer.tokenize(' \tHäLLo!how  \n Are yoU?  '       )				,      ['HaLLo', '!', 'how', 'Are', 'yoU', '?']       )



		def __UpperCamelCase ( self       )  ->					Any:
				"""simple docstring"""
				UpperCamelCase		=     BasicTokenizer(do_lower_case=A_				,      never_split=['[UNK]']       )

				self.assertListEqual(
				    tokenizer.tokenize(' \tHeLLo!how  \n Are yoU? [UNK]'       )				,      ['HeLLo', '!', 'how', 'Are', 'yoU', '?', '[UNK]']       )



		def __UpperCamelCase ( self       )  ->					int:
				"""simple docstring"""
				UpperCamelCase		=     BasicTokenizer()
				UpperCamelCase		=     'a\n\'ll !!to?\'d of, can\'t.'
				UpperCamelCase		=     ['a', '\'', 'll', '!', '!', 'to', '?', '\'', 'd', 'of', ',', 'can', '\'', 't', '.']
				self.assertListEqual(tokenizer.tokenize(A_       )				,      A_       )



		def __UpperCamelCase ( self       )  ->					Optional[int]:
				"""simple docstring"""
				UpperCamelCase		=     ['[UNK]', '[CLS]', '[SEP]', 'want', '##want', '##ed', 'wa', 'un', 'runn', '##ing']

				UpperCamelCase		=     {}
				for i, token in enumerate(A_       ):
						UpperCamelCase		=     i
				UpperCamelCase		=     WordpieceTokenizer(vocab=A_				,      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 __UpperCamelCase ( self       )  ->					str:
				"""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 __UpperCamelCase ( self       )  ->					Tuple:
				"""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 __UpperCamelCase ( self       )  ->					Optional[int]:
				"""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 __UpperCamelCase ( self       )  ->					Optional[int]:
				"""simple docstring"""
				UpperCamelCase		=     self.get_tokenizer()
				UpperCamelCase		=     self.get_rust_tokenizer()

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

				self.assertListEqual(
				    [rust_tokenizer.tokenize(A_       ) for t in ['Test', '\xad', 'test']]				,      [['[UNK]'], [], ['[UNK]']]       )



		@slow
		def __UpperCamelCase ( self       )  ->					List[Any]:
				"""simple docstring"""
				UpperCamelCase		=     self.tokenizer_class.from_pretrained('bert-base-uncased'       )

				UpperCamelCase		=     tokenizer.encode('sequence builders'				,      add_special_tokens=A_       )
				UpperCamelCase		=     tokenizer.encode('multi-sequence build'				,      add_special_tokens=A_       )

				UpperCamelCase		=     tokenizer.build_inputs_with_special_tokens(A_       )
				UpperCamelCase		=     tokenizer.build_inputs_with_special_tokens(A_				,      A_       )

				assert encoded_sentence == [101] + text + [102]
				assert encoded_pair == [101] + text + [102] + text_a + [102]



		def __UpperCamelCase ( self       )  ->					List[Any]:
				"""simple docstring"""
				for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
						with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})'''       ):
								UpperCamelCase		=     self.rust_tokenizer_class.from_pretrained(A_				,      **A_       )

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

								UpperCamelCase		=     tokenizer_r.do_lower_case if hasattr(A_				,      'do_lower_case'       ) else False
								UpperCamelCase		=     (
								    [
								        ((0, 0), tokenizer_r.cls_token),
								        ((0, 1), 'A'),
								        ((1, 2), ','),
								        ((3, 5), 'na'),
								        ((5, 6), '##ï'),
								        ((6, 8), '##ve'),
								        ((9, 15), tokenizer_r.mask_token),
								        ((16, 21), 'Allen'),
								        ((21, 23), '##NL'),
								        ((23, 24), '##P'),
								        ((25, 33), 'sentence'),
								        ((33, 34), '.'),
								        ((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, 15), tokenizer_r.mask_token),
								        ((16, 21), 'allen'),
								        ((21, 23), '##nl'),
								        ((23, 24), '##p'),
								        ((25, 33), 'sentence'),
								        ((33, 34), '.'),
								        ((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 __UpperCamelCase ( self       )  ->					Dict:
				"""simple docstring"""
				UpperCamelCase		=     ['的', '人', '有']
				UpperCamelCase		=     ''.join(A_       )
				for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
						with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})'''       ):
								UpperCamelCase		=     True
								UpperCamelCase		=     self.tokenizer_class.from_pretrained(A_				,      **A_       )
								UpperCamelCase		=     self.rust_tokenizer_class.from_pretrained(A_				,      **A_       )

								UpperCamelCase		=     tokenizer_p.encode(A_				,      add_special_tokens=A_       )
								UpperCamelCase		=     tokenizer_r.encode(A_				,      add_special_tokens=A_       )

								UpperCamelCase		=     tokenizer_r.convert_ids_to_tokens(A_       )
								UpperCamelCase		=     tokenizer_p.convert_ids_to_tokens(A_       )

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

								UpperCamelCase		=     False
								UpperCamelCase		=     self.rust_tokenizer_class.from_pretrained(A_				,      **A_       )
								UpperCamelCase		=     self.tokenizer_class.from_pretrained(A_				,      **A_       )

								UpperCamelCase		=     tokenizer_r.encode(A_				,      add_special_tokens=A_       )
								UpperCamelCase		=     tokenizer_p.encode(A_				,      add_special_tokens=A_       )

								UpperCamelCase		=     tokenizer_r.convert_ids_to_tokens(A_       )
								UpperCamelCase		=     tokenizer_p.convert_ids_to_tokens(A_       )

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


import gc
import unittest

import numpy as np
import torch

from diffusers import StableDiffusionKDiffusionPipeline
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu


enable_full_determinism()


@slow
@require_torch_gpu
class 				lowercase					(		unittest.TestCase   ):



		def __UpperCamelCase ( self       )  ->					Dict:
				"""simple docstring"""
				# clean up the VRAM after each test
				super().tearDown()
				gc.collect()
				torch.cuda.empty_cache()



		def __UpperCamelCase ( self       )  ->					str:
				"""simple docstring"""
				UpperCamelCase		=     StableDiffusionKDiffusionPipeline.from_pretrained('CompVis/stable-diffusion-v1-4'       )
				UpperCamelCase		=     sd_pipe.to(A_       )
				sd_pipe.set_progress_bar_config(disable=A_       )

				sd_pipe.set_scheduler('sample_euler'       )

				UpperCamelCase		=     'A painting of a squirrel eating a burger'
				UpperCamelCase		=     torch.manual_seed(0       )
				UpperCamelCase		=     sd_pipe([prompt]				,      generator=A_				,      guidance_scale=9.0				,      num_inference_steps=20				,      output_type='np'       )

				UpperCamelCase		=     output.images

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

				assert image.shape == (1, 512, 512, 3)
				UpperCamelCase		=     np.array([0.0447, 0.0492, 0.0468, 0.0408, 0.0383, 0.0408, 0.0354, 0.0380, 0.0339]       )

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



		def __UpperCamelCase ( self       )  ->					Any:
				"""simple docstring"""
				UpperCamelCase		=     StableDiffusionKDiffusionPipeline.from_pretrained('stabilityai/stable-diffusion-2-1-base'       )
				UpperCamelCase		=     sd_pipe.to(A_       )
				sd_pipe.set_progress_bar_config(disable=A_       )

				sd_pipe.set_scheduler('sample_euler'       )

				UpperCamelCase		=     'A painting of a squirrel eating a burger'
				UpperCamelCase		=     torch.manual_seed(0       )
				UpperCamelCase		=     sd_pipe([prompt]				,      generator=A_				,      guidance_scale=9.0				,      num_inference_steps=20				,      output_type='np'       )

				UpperCamelCase		=     output.images

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

				assert image.shape == (1, 512, 512, 3)
				UpperCamelCase		=     np.array([0.1237, 0.1320, 0.1438, 0.1359, 0.1390, 0.1132, 0.1277, 0.1175, 0.1112]       )

				assert np.abs(image_slice.flatten() - expected_slice       ).max() < 5e-1



		def __UpperCamelCase ( self       )  ->					Optional[int]:
				"""simple docstring"""
				UpperCamelCase		=     StableDiffusionKDiffusionPipeline.from_pretrained('stabilityai/stable-diffusion-2-1-base'       )
				UpperCamelCase		=     sd_pipe.to(A_       )
				sd_pipe.set_progress_bar_config(disable=A_       )

				sd_pipe.set_scheduler('sample_dpmpp_2m'       )

				UpperCamelCase		=     'A painting of a squirrel eating a burger'
				UpperCamelCase		=     torch.manual_seed(0       )
				UpperCamelCase		=     sd_pipe(
				    [prompt]				,      generator=A_				,      guidance_scale=7.5				,      num_inference_steps=15				,      output_type='np'				,      use_karras_sigmas=A_				,      )

				UpperCamelCase		=     output.images

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

				assert image.shape == (1, 512, 512, 3)
				UpperCamelCase		=     np.array(
				    [0.1138_1689, 0.1211_2921, 0.138_9457, 0.1254_9606, 0.124_4964, 0.1083_1517, 0.1156_2866, 0.1086_7816, 0.1049_9048]       )

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