
"""simple docstring"""


import os
import unittest

from transformers import RealmTokenizerFast
from transformers.models.bert.tokenization_bert import (
    VOCAB_FILES_NAMES,
    BasicTokenizer,
    WordpieceTokenizer,
    _is_control,
    _is_punctuation,
    _is_whitespace,
)
from transformers.models.realm.tokenization_realm import RealmTokenizer
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin, filter_non_english




@require_tokenizers
class    __lowerCamelCase     (   lowerCamelCase__	,  unittest.TestCase ):
				a__:			Dict									=						RealmTokenizer
				a__:			Optional[Any]									=						RealmTokenizerFast
				a__:			Optional[int]									=						True
				a__:			List[str]									=						True
				a__:			Optional[int]									=						filter_non_english




				def 					UpperCAmelCase__	(							self      ):
							super().setUp()

							lowerCamelCase_ 		=     [
							    '''[UNK]''',
							    '''[CLS]''',
							    '''[SEP]''',
							    '''[PAD]''',
							    '''[MASK]''',
							    '''want''',
							    '''##want''',
							    '''##ed''',
							    '''wa''',
							    '''un''',
							    '''runn''',
							    '''##ing''',
							    ''',''',
							    '''low''',
							    '''lowest''',
							]
							lowerCamelCase_ 		=     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       ,	UpperCAmelCase      ):
							lowerCamelCase_ 		=     '''UNwant\u00E9d,running'''
							lowerCamelCase_ 		=     '''unwanted, running'''
							return input_text, output_text




				def 					UpperCAmelCase__	(							self      ):
							lowerCamelCase_ 		=     self.tokenizer_class(self.vocab_file      )

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




				def 					UpperCAmelCase__	(							self      ):






							if not self.test_rust_tokenizer:
										return

							lowerCamelCase_ 		=     self.get_tokenizer()
							lowerCamelCase_ 		=     self.get_rust_tokenizer()

							lowerCamelCase_ 		=     '''UNwant\u00E9d,running'''

							lowerCamelCase_ 		=     tokenizer.tokenize(lowercase_      )
							lowerCamelCase_ 		=     rust_tokenizer.tokenize(lowercase_      )
							self.assertListEqual(lowercase_       ,	lowercase_      )

							lowerCamelCase_ 		=     tokenizer.encode(lowercase_       ,	add_special_tokens=lowercase_      )
							lowerCamelCase_ 		=     rust_tokenizer.encode(lowercase_       ,	add_special_tokens=lowercase_      )
							self.assertListEqual(lowercase_       ,	lowercase_      )

							lowerCamelCase_ 		=     self.get_rust_tokenizer()
							lowerCamelCase_ 		=     tokenizer.encode(lowercase_      )
							lowerCamelCase_ 		=     rust_tokenizer.encode(lowercase_      )
							self.assertListEqual(lowercase_       ,	lowercase_      )

							# With lower casing
							lowerCamelCase_ 		=     self.get_tokenizer(do_lower_case=lowercase_      )
							lowerCamelCase_ 		=     self.get_rust_tokenizer(do_lower_case=lowercase_      )

							lowerCamelCase_ 		=     '''UNwant\u00E9d,running'''

							lowerCamelCase_ 		=     tokenizer.tokenize(lowercase_      )
							lowerCamelCase_ 		=     rust_tokenizer.tokenize(lowercase_      )
							self.assertListEqual(lowercase_       ,	lowercase_      )

							lowerCamelCase_ 		=     tokenizer.encode(lowercase_       ,	add_special_tokens=lowercase_      )
							lowerCamelCase_ 		=     rust_tokenizer.encode(lowercase_       ,	add_special_tokens=lowercase_      )
							self.assertListEqual(lowercase_       ,	lowercase_      )

							lowerCamelCase_ 		=     self.get_rust_tokenizer()
							lowerCamelCase_ 		=     tokenizer.encode(lowercase_      )
							lowerCamelCase_ 		=     rust_tokenizer.encode(lowercase_      )
							self.assertListEqual(lowercase_       ,	lowercase_      )




				def 					UpperCAmelCase__	(							self      ):
							lowerCamelCase_ 		=     BasicTokenizer()

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




				def 					UpperCAmelCase__	(							self      ):
							lowerCamelCase_ 		=     BasicTokenizer(do_lower_case=lowercase_      )

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




				def 					UpperCAmelCase__	(							self      ):
							lowerCamelCase_ 		=     BasicTokenizer(do_lower_case=lowercase_       ,	strip_accents=lowercase_      )

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




				def 					UpperCAmelCase__	(							self      ):
							lowerCamelCase_ 		=     BasicTokenizer(do_lower_case=lowercase_       ,	strip_accents=lowercase_      )

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




				def 					UpperCAmelCase__	(							self      ):
							lowerCamelCase_ 		=     BasicTokenizer(do_lower_case=lowercase_      )

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




				def 					UpperCAmelCase__	(							self      ):
							lowerCamelCase_ 		=     BasicTokenizer(do_lower_case=lowercase_      )

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




				def 					UpperCAmelCase__	(							self      ):
							lowerCamelCase_ 		=     BasicTokenizer(do_lower_case=lowercase_       ,	strip_accents=lowercase_      )

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




				def 					UpperCAmelCase__	(							self      ):
							lowerCamelCase_ 		=     BasicTokenizer(do_lower_case=lowercase_       ,	strip_accents=lowercase_      )

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




				def 					UpperCAmelCase__	(							self      ):
							lowerCamelCase_ 		=     BasicTokenizer(do_lower_case=lowercase_       ,	never_split=['''[UNK]''']      )

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




				def 					UpperCAmelCase__	(							self      ):
							lowerCamelCase_ 		=     ['''[UNK]''', '''[CLS]''', '''[SEP]''', '''want''', '''##want''', '''##ed''', '''wa''', '''un''', '''runn''', '''##ing''']

							lowerCamelCase_ 		=     {}
							for i, token in enumerate(lowercase_      ):
										lowerCamelCase_ 		=     i
							lowerCamelCase_ 		=     WordpieceTokenizer(vocab=lowercase_       ,	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      ):
							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      ):
							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      ):
							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      ):
							lowerCamelCase_ 		=     self.get_tokenizer()

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

							if self.test_rust_tokenizer:
										lowerCamelCase_ 		=     self.get_rust_tokenizer()
										self.assertListEqual(
										    [rust_tokenizer.tokenize(lowercase_      ) for t in ['''Test''', '''\xad''', '''test''']]       ,	[['''[UNK]'''], [], ['''[UNK]''']]      )




				@slow
				def 					UpperCAmelCase__	(							self      ):
							lowerCamelCase_ 		=     self.tokenizer_class.from_pretrained('''bert-base-uncased'''      )

							lowerCamelCase_ 		=     tokenizer.encode('''sequence builders'''       ,	add_special_tokens=lowercase_      )
							lowerCamelCase_ 		=     tokenizer.encode('''multi-sequence build'''       ,	add_special_tokens=lowercase_      )

							lowerCamelCase_ 		=     tokenizer.build_inputs_with_special_tokens(lowercase_      )
							lowerCamelCase_ 		=     tokenizer.build_inputs_with_special_tokens(lowercase_       ,	lowercase_      )

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




				def 					UpperCAmelCase__	(							self      ):






							for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
										with self.subTest(f"{tokenizer.__class__.__name__} ({pretrained_name})"      ):
													lowerCamelCase_ 		=     self.rust_tokenizer_class.from_pretrained(lowercase_       ,	**lowercase_      )

													lowerCamelCase_ 		=     f"A, naïve {tokenizer_r.mask_token} AllenNLP sentence."
													lowerCamelCase_ 		=     tokenizer_r.encode_plus(
													    lowercase_       ,	return_attention_mask=lowercase_       ,	return_token_type_ids=lowercase_       ,	return_offsets_mapping=lowercase_       ,	add_special_tokens=lowercase_       ,	)

													lowerCamelCase_ 		=     tokenizer_r.do_lower_case if hasattr(lowercase_       ,	'''do_lower_case'''      ) else False
													lowerCamelCase_ 		=     (
													    [
													        ((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''']      )





				@slow
				def 					UpperCAmelCase__	(							self      ):






							for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
										with self.subTest(f"{tokenizer.__class__.__name__} ({pretrained_name})"      ):
													lowerCamelCase_ 		=     self.rust_tokenizer_class.from_pretrained(lowercase_       ,	**lowercase_      )
													lowerCamelCase_ 		=     self.tokenizer_class.from_pretrained(lowercase_       ,	**lowercase_      )
													lowerCamelCase_ 		=     [['''Hello world!''', '''Nice to meet you!'''], ['''The cute cat.''', '''The adorable dog.''']]

													lowerCamelCase_ 		=     tokenizer_r.batch_encode_candidates(lowercase_       ,	max_length=10       ,	return_tensors='''np'''      )
													lowerCamelCase_ 		=     tokenizer_p.batch_encode_candidates(lowercase_       ,	max_length=10       ,	return_tensors='''np'''      )

													lowerCamelCase_ 		=     (2, 2, 10)

													self.assertEqual(encoded_sentence_r['''input_ids'''].shape       ,	lowercase_      )
													self.assertEqual(encoded_sentence_r['''attention_mask'''].shape       ,	lowercase_      )
													self.assertEqual(encoded_sentence_r['''token_type_ids'''].shape       ,	lowercase_      )

													self.assertEqual(encoded_sentence_p['''input_ids'''].shape       ,	lowercase_      )
													self.assertEqual(encoded_sentence_p['''attention_mask'''].shape       ,	lowercase_      )
													self.assertEqual(encoded_sentence_p['''token_type_ids'''].shape       ,	lowercase_      )








"""simple docstring"""


import tempfile
import unittest

import torch

from diffusers import UNetaDConditionModel
from diffusers.training_utils import EMAModel
from diffusers.utils.testing_utils import enable_full_determinism, skip_mps, torch_device


enable_full_determinism()




class    __lowerCamelCase     (   unittest.TestCase ):
				a__:			Union[str, Any]									=						'hf-internal-testing/tiny-stable-diffusion-pipe'
				a__:			Tuple									=						1
				a__:			int									=						77
				a__:			List[str]									=						32
				a__:			List[Any]									=						4
				a__:			str									=						64
				a__:			Optional[Any]									=						torch.manual_seed(0 )




				def 					UpperCAmelCase__	(							self       ,	UpperCAmelCase=0.9_9_9_9      ):
							lowerCamelCase_ 		=     UNetaDConditionModel.from_pretrained(self.model_id       ,	subfolder='''unet'''      )
							lowerCamelCase_ 		=     unet.to(UpperCAmelCase      )
							lowerCamelCase_ 		=     EMAModel(unet.parameters()       ,	decay=UpperCAmelCase       ,	model_cls=UpperCAmelCase       ,	model_config=unet.config      )
							return unet, ema_unet




				def 					UpperCAmelCase__	(							self      ):
							lowerCamelCase_ 		=     torch.randn(
							    self.batch_size       ,	self.num_in_channels       ,	self.latent_height       ,	self.latent_width       ,	generator=self.generator      ).to(UpperCAmelCase      )
							lowerCamelCase_ 		=     torch.randint(0       ,	1000       ,	size=(self.batch_size,)       ,	generator=self.generator      ).to(UpperCAmelCase      )
							lowerCamelCase_ 		=     torch.randn(
							    self.batch_size       ,	self.prompt_length       ,	self.text_encoder_hidden_dim       ,	generator=self.generator      ).to(UpperCAmelCase      )
							return noisy_latents, timesteps, encoder_hidden_states




				def 					UpperCAmelCase__	(							self       ,	UpperCAmelCase      ):
							lowerCamelCase_ 		=     {}
							for k, param in unet.state_dict().items():
										lowerCamelCase_ 		=     torch.randn_like(UpperCAmelCase      ) + (param * torch.randn_like(UpperCAmelCase      ))
										updated_state_dict.update({k: updated_param}      )
							unet.load_state_dict(UpperCAmelCase      )
							return unet




				def 					UpperCAmelCase__	(							self      ):
							lowerCamelCase_		,   lowerCamelCase_ 		=     self.get_models()
							# Take the first (hypothetical) EMA step.
							ema_unet.step(unet.parameters()      )
							assert ema_unet.optimization_step == 1

							# Take two more.
							for _ in range(2      ):
										ema_unet.step(unet.parameters()      )
							assert ema_unet.optimization_step == 3




				def 					UpperCAmelCase__	(							self      ):
							lowerCamelCase_		,   lowerCamelCase_ 		=     self.get_models()
							# Since the `unet` is not being updated (i.e., backprop'd)
							# there won't be any difference between the `params` of `unet`
							# and `ema_unet` even if we call `ema_unet.step(unet.parameters())`.
							ema_unet.step(unet.parameters()      )
							lowerCamelCase_ 		=     list(unet.parameters()      )
							for s_param, param in zip(ema_unet.shadow_params       ,	UpperCAmelCase      ):
										assert torch.allclose(UpperCAmelCase       ,	UpperCAmelCase      )

							# The above holds true even if we call `ema.step()` multiple times since
							# `unet` params are still not being updated.
							for _ in range(4      ):
										ema_unet.step(unet.parameters()      )
							for s_param, param in zip(ema_unet.shadow_params       ,	UpperCAmelCase      ):
										assert torch.allclose(UpperCAmelCase       ,	UpperCAmelCase      )




				def 					UpperCAmelCase__	(							self      ):
							lowerCamelCase_		,   lowerCamelCase_ 		=     self.get_models()
							# Here we simulate the parameter updates for `unet`. Since there might
							# be some parameters which are initialized to zero we take extra care to
							# initialize their values to something non-zero before the multiplication.
							lowerCamelCase_ 		=     self.simulate_backprop(UpperCAmelCase      )

							# Take the EMA step.
							ema_unet.step(unet_pseudo_updated_step_one.parameters()      )

							# Now the EMA'd parameters won't be equal to the original model parameters.
							lowerCamelCase_ 		=     list(unet_pseudo_updated_step_one.parameters()      )
							for s_param, param in zip(ema_unet.shadow_params       ,	UpperCAmelCase      ):
										assert ~torch.allclose(UpperCAmelCase       ,	UpperCAmelCase      )

							# Ensure this is the case when we take multiple EMA steps.
							for _ in range(4      ):
										ema_unet.step(unet.parameters()      )
							for s_param, param in zip(ema_unet.shadow_params       ,	UpperCAmelCase      ):
										assert ~torch.allclose(UpperCAmelCase       ,	UpperCAmelCase      )




				def 					UpperCAmelCase__	(							self      ):
							# If we call EMA step after a backpropagation consecutively for two times,
							# the shadow params from those two steps should be different.
							lowerCamelCase_		,   lowerCamelCase_ 		=     self.get_models()

							# First backprop + EMA
							lowerCamelCase_ 		=     self.simulate_backprop(UpperCAmelCase      )
							ema_unet.step(unet_step_one.parameters()      )
							lowerCamelCase_ 		=     ema_unet.shadow_params

							# Second backprop + EMA
							lowerCamelCase_ 		=     self.simulate_backprop(UpperCAmelCase      )
							ema_unet.step(unet_step_two.parameters()      )
							lowerCamelCase_ 		=     ema_unet.shadow_params

							for step_one, step_two in zip(UpperCAmelCase       ,	UpperCAmelCase      ):
										assert ~torch.allclose(UpperCAmelCase       ,	UpperCAmelCase      )




				def 					UpperCAmelCase__	(							self      ):
							# If there's no decay even if there are backprops, EMA steps
							# won't take any effect i.e., the shadow params would remain the
							# same.
							lowerCamelCase_		,   lowerCamelCase_ 		=     self.get_models(decay=0.0      )
							lowerCamelCase_ 		=     self.simulate_backprop(UpperCAmelCase      )
							ema_unet.step(unet_step_one.parameters()      )
							lowerCamelCase_ 		=     ema_unet.shadow_params

							lowerCamelCase_ 		=     self.simulate_backprop(UpperCAmelCase      )
							ema_unet.step(unet_step_two.parameters()      )
							lowerCamelCase_ 		=     ema_unet.shadow_params

							for step_one, step_two in zip(UpperCAmelCase       ,	UpperCAmelCase      ):
										assert torch.allclose(UpperCAmelCase       ,	UpperCAmelCase      )





				@skip_mps
				def 					UpperCAmelCase__	(							self      ):
							lowerCamelCase_		,   lowerCamelCase_ 		=     self.get_models()
							lowerCamelCase_		,   lowerCamelCase_		,   lowerCamelCase_ 		=     self.get_dummy_inputs()

							with tempfile.TemporaryDirectory() as tmpdir:
										ema_unet.save_pretrained(UpperCAmelCase      )
										lowerCamelCase_ 		=     UNetaDConditionModel.from_pretrained(UpperCAmelCase       ,	model_cls=UpperCAmelCase      )
										lowerCamelCase_ 		=     loaded_unet.to(unet.device      )

							# Since no EMA step has been performed the outputs should match.
							lowerCamelCase_ 		=     unet(UpperCAmelCase       ,	UpperCAmelCase       ,	UpperCAmelCase      ).sample
							lowerCamelCase_ 		=     loaded_unet(UpperCAmelCase       ,	UpperCAmelCase       ,	UpperCAmelCase      ).sample

							assert torch.allclose(UpperCAmelCase       ,	UpperCAmelCase       ,	atol=1e-4      )



