



import os
import unittest

from transformers import MobileBertTokenizer, MobileBertTokenizerFast
from transformers.models.bert.tokenization_bert import (
    VOCAB_FILES_NAMES,
    BasicTokenizer,
    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 	lowerCamelCase_    ( lowerCAmelCase__						,unittest.TestCase						):






						'''simple docstring'''
						a__   =  MobileBertTokenizer
						a__   =  MobileBertTokenizerFast
						a__   =  True
						a__   =  True
						a__   =  filter_non_english
						a__   =  "google/mobilebert-uncased"







						def 			SCREAMING_SNAKE_CASE__		(	self      :			List[str] )      ->				Optional[int]:
									super().setUp()

									A							:					Optional[Any]              =						[
									    "[UNK]",
									    "[CLS]",
									    "[SEP]",
									    "[PAD]",
									    "[MASK]",
									    "want",
									    "##want",
									    "##ed",
									    "wa",
									    "un",
									    "runn",
									    "##ing",
									    ",",
									    "low",
									    "lowest",
									]
									A							:					List[Any]              =						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] ) )

									A							:					int              =						[
									    (tokenizer_def[0], self.pre_trained_model_path, tokenizer_def[2])  # else the 'google/' prefix is stripped
									    for tokenizer_def in self.tokenizers_list
									]







						def 			SCREAMING_SNAKE_CASE__		(	self      :			Union[str, Any]	,	__lowerCamelCase      :			Optional[Any] )      ->				int:
									A							:					Optional[int]              =						"UNwant\u00E9d,running"
									A							:					List[str]              =						"unwanted, running"
									return input_text, output_text







						def 			SCREAMING_SNAKE_CASE__		(	self      :			int )      ->				Optional[Any]:
									A							:					int              =						self.tokenizer_class(self.vocab_file )

									A							:					List[Any]              =						tokenizer.tokenize("UNwant\u00E9d,running" )
									self.assertListEqual(_lowerCamelCase	,	["un", "##want", "##ed", ",", "runn", "##ing"] )
									self.assertListEqual(tokenizer.convert_tokens_to_ids(_lowerCamelCase )	,	[9, 6, 7, 12, 10, 11] )







						def 			SCREAMING_SNAKE_CASE__		(	self      :			Union[str, Any] )      ->				Optional[int]:





									if not self.test_rust_tokenizer:
												return

									A							:					str              =						self.get_tokenizer()
									A							:					Tuple              =						self.get_rust_tokenizer()

									A							:					Optional[int]              =						"UNwant\u00E9d,running"

									A							:					List[str]              =						tokenizer.tokenize(_lowerCamelCase )
									A							:					Tuple              =						rust_tokenizer.tokenize(_lowerCamelCase )
									self.assertListEqual(_lowerCamelCase	,	_lowerCamelCase )

									A							:					Any              =						tokenizer.encode(_lowerCamelCase	,	add_special_tokens=_lowerCamelCase )
									A							:					Dict              =						rust_tokenizer.encode(_lowerCamelCase	,	add_special_tokens=_lowerCamelCase )
									self.assertListEqual(_lowerCamelCase	,	_lowerCamelCase )

									A							:					str              =						self.get_rust_tokenizer()
									A							:					Optional[int]              =						tokenizer.encode(_lowerCamelCase )
									A							:					Union[str, Any]              =						rust_tokenizer.encode(_lowerCamelCase )
									self.assertListEqual(_lowerCamelCase	,	_lowerCamelCase )

									# With lower casing
									A							:					Any              =						self.get_tokenizer(do_lower_case=_lowerCamelCase )
									A							:					List[Any]              =						self.get_rust_tokenizer(do_lower_case=_lowerCamelCase )

									A							:					int              =						"UNwant\u00E9d,running"

									A							:					Optional[int]              =						tokenizer.tokenize(_lowerCamelCase )
									A							:					int              =						rust_tokenizer.tokenize(_lowerCamelCase )
									self.assertListEqual(_lowerCamelCase	,	_lowerCamelCase )

									A							:					Dict              =						tokenizer.encode(_lowerCamelCase	,	add_special_tokens=_lowerCamelCase )
									A							:					Dict              =						rust_tokenizer.encode(_lowerCamelCase	,	add_special_tokens=_lowerCamelCase )
									self.assertListEqual(_lowerCamelCase	,	_lowerCamelCase )

									A							:					Dict              =						self.get_rust_tokenizer()
									A							:					Union[str, Any]              =						tokenizer.encode(_lowerCamelCase )
									A							:					Union[str, Any]              =						rust_tokenizer.encode(_lowerCamelCase )
									self.assertListEqual(_lowerCamelCase	,	_lowerCamelCase )







						def 			SCREAMING_SNAKE_CASE__		(	self      :			Optional[int] )      ->				Tuple:
									A							:					Tuple              =						BasicTokenizer()

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







						def 			SCREAMING_SNAKE_CASE__		(	self      :			Any )      ->				int:
									A							:					Optional[Any]              =						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 			SCREAMING_SNAKE_CASE__		(	self      :			Optional[Any] )      ->				List[Any]:
									A							:					int              =						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 			SCREAMING_SNAKE_CASE__		(	self      :			int )      ->				Tuple:
									A							:					List[str]              =						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 			SCREAMING_SNAKE_CASE__		(	self      :			Union[str, Any] )      ->				str:
									A							:					Tuple              =						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 			SCREAMING_SNAKE_CASE__		(	self      :			Any )      ->				Optional[Any]:
									A							:					Optional[int]              =						BasicTokenizer(do_lower_case=_lowerCamelCase )

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







						def 			SCREAMING_SNAKE_CASE__		(	self      :			Dict )      ->				List[Any]:
									A							:					Optional[int]              =						BasicTokenizer(do_lower_case=_lowerCamelCase	,	strip_accents=_lowerCamelCase )

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







						def 			SCREAMING_SNAKE_CASE__		(	self      :			List[Any] )      ->				Optional[Any]:
									A							:					List[str]              =						BasicTokenizer(do_lower_case=_lowerCamelCase	,	strip_accents=_lowerCamelCase )

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







						def 			SCREAMING_SNAKE_CASE__		(	self      :			Union[str, Any] )      ->				Dict:
									A							:					Optional[Any]              =						BasicTokenizer(do_lower_case=_lowerCamelCase	,	never_split=["[UNK]"] )

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







						def 			SCREAMING_SNAKE_CASE__		(	self      :			Optional[int] )      ->				int:
									A							:					Dict              =						["[UNK]", "[CLS]", "[SEP]", "want", "##want", "##ed", "wa", "un", "runn", "##ing"]

									A							:					Any              =						{}
									for i, token in enumerate(_lowerCamelCase ):
												A							:					Optional[int]              =						i
									A							:					Optional[Any]              =						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 			SCREAMING_SNAKE_CASE__		(	self      :			Tuple )      ->				List[str]:
									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 			SCREAMING_SNAKE_CASE__		(	self      :			Optional[int] )      ->				Dict:
									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 			SCREAMING_SNAKE_CASE__		(	self      :			Optional[int] )      ->				Union[str, Any]:
									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 			SCREAMING_SNAKE_CASE__		(	self      :			List[str] )      ->				Tuple:
									A							:					Optional[Any]              =						self.get_tokenizer()
									A							:					str              =						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 			SCREAMING_SNAKE_CASE__		(	self      :			Any )      ->				List[str]:
									A							:					int              =						self.tokenizer_class.from_pretrained("google/mobilebert-uncased" )

									A							:					str              =						tokenizer.encode("sequence builders"	,	add_special_tokens=_lowerCamelCase )
									A							:					Dict              =						tokenizer.encode("multi-sequence build"	,	add_special_tokens=_lowerCamelCase )

									A							:					List[str]              =						tokenizer.build_inputs_with_special_tokens(_lowerCamelCase )
									A							:					str              =						tokenizer.build_inputs_with_special_tokens(_lowerCamelCase	,	_lowerCamelCase )

									assert encoded_sentence == [1_01] + text + [1_02]
									assert encoded_pair == [1_01] + text + [1_02] + text_a + [1_02]







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





									for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
												with self.subTest(F"""{tokenizer.__class__.__name__} ({pretrained_name})""" ):
															A							:					List[Any]              =						self.rust_tokenizer_class.from_pretrained(_lowerCamelCase	,	**_lowerCamelCase )

															A							:					int              =						F"""A, naïve {tokenizer_r.mask_token} AllenNLP sentence."""
															A							:					Any              =						tokenizer_r.encode_plus(
															    _lowerCamelCase	,	return_attention_mask=_lowerCamelCase	,	return_token_type_ids=_lowerCamelCase	,	return_offsets_mapping=_lowerCamelCase	,	add_special_tokens=_lowerCamelCase	,	)

															A							:					List[Any]              =						tokenizer_r.do_lower_case if hasattr(_lowerCamelCase	,	"do_lower_case" ) else False
															A							:					List[Any]              =						(
															    [
															        ((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 			SCREAMING_SNAKE_CASE__		(	self      :			List[Any] )      ->				List[Any]:
									A							:					List[Any]              =						["的", "人", "有"]
									A							:					Dict              =						"".join(_lowerCamelCase )
									for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
												with self.subTest(F"""{tokenizer.__class__.__name__} ({pretrained_name})""" ):
															A							:					Dict              =						True
															A							:					List[str]              =						self.tokenizer_class.from_pretrained(_lowerCamelCase	,	**_lowerCamelCase )
															A							:					Tuple              =						self.rust_tokenizer_class.from_pretrained(_lowerCamelCase	,	**_lowerCamelCase )

															A							:					Any              =						tokenizer_p.encode(_lowerCamelCase	,	add_special_tokens=_lowerCamelCase )
															A							:					Dict              =						tokenizer_r.encode(_lowerCamelCase	,	add_special_tokens=_lowerCamelCase )

															A							:					Union[str, Any]              =						tokenizer_r.convert_ids_to_tokens(_lowerCamelCase )
															A							:					Tuple              =						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 )

															A							:					Tuple              =						False
															A							:					List[str]              =						self.rust_tokenizer_class.from_pretrained(_lowerCamelCase	,	**_lowerCamelCase )
															A							:					str              =						self.tokenizer_class.from_pretrained(_lowerCamelCase	,	**_lowerCamelCase )

															A							:					Tuple              =						tokenizer_r.encode(_lowerCamelCase	,	add_special_tokens=_lowerCamelCase )
															A							:					Union[str, Any]              =						tokenizer_p.encode(_lowerCamelCase	,	add_special_tokens=_lowerCamelCase )

															A							:					int              =						tokenizer_r.convert_ids_to_tokens(_lowerCamelCase )
															A							:					Any              =						tokenizer_p.convert_ids_to_tokens(_lowerCamelCase )

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




import unittest
from typing import Tuple

import torch

from diffusers.utils import floats_tensor, randn_tensor, torch_all_close, torch_device
from diffusers.utils.testing_utils import require_torch

@require_torch
class 	lowerCamelCase_    :






						'''simple docstring'''







						@property
						def 			SCREAMING_SNAKE_CASE__		(	self      :			Optional[int] )      ->				str:
									return self.get_dummy_input()







						@property
						def 			SCREAMING_SNAKE_CASE__		(	self      :			int )      ->				Optional[Any]:
									if self.block_type == "down":
												return (4, 32, 16, 16)
									elif self.block_type == "mid":
												return (4, 32, 32, 32)
									elif self.block_type == "up":
												return (4, 32, 64, 64)

									raise ValueError(F"""'{self.block_type}' is not a supported block_type. Set it to 'up', 'mid', or 'down'.""" )







						def 			SCREAMING_SNAKE_CASE__		(	self      :			Dict	,	__lowerCamelCase      :			Union[str, Any]=True	,	__lowerCamelCase      :			int=False	,	__lowerCamelCase      :			int=False	,	__lowerCamelCase      :			Optional[int]=False	,	)      ->				Dict:
									A							:					Optional[Any]              =						4
									A							:					List[str]              =						32
									A							:					Any              =						(32, 32)

									A							:					str              =						torch.manual_seed(0 )
									A							:					int              =						torch.device(__lowerCamelCase )
									A							:					List[str]              =						(batch_size, num_channels) + sizes
									A							:					Dict              =						randn_tensor(__lowerCamelCase	,	generator=__lowerCamelCase	,	device=__lowerCamelCase )
									A							:					int              =						{"hidden_states": hidden_states}

									if include_temb:
												A							:					Any              =						1_28
												A							:					List[str]              =						randn_tensor((batch_size, temb_channels)	,	generator=__lowerCamelCase	,	device=__lowerCamelCase )

									if include_res_hidden_states_tuple:
												A							:					str              =						torch.manual_seed(1 )
												A							:					Tuple              =						(randn_tensor(__lowerCamelCase	,	generator=__lowerCamelCase	,	device=__lowerCamelCase ),)

									if include_encoder_hidden_states:
												A							:					Dict              =						floats_tensor((batch_size, 32, 32) ).to(__lowerCamelCase )

									if include_skip_sample:
												A							:					Optional[int]              =						randn_tensor(((batch_size, 3) + sizes)	,	generator=__lowerCamelCase	,	device=__lowerCamelCase )

									return dummy_input







						def 			SCREAMING_SNAKE_CASE__		(	self      :			List[Any] )      ->				Union[str, Any]:
									A							:					Dict              =						{
									    "in_channels": 32,
									    "out_channels": 32,
									    "temb_channels": 1_28,
									}
									if self.block_type == "up":
												A							:					Dict              =						32

									if self.block_type == "mid":
												init_dict.pop("out_channels" )

									A							:					str              =						self.dummy_input
									return init_dict, inputs_dict







						def 			SCREAMING_SNAKE_CASE__		(	self      :			str	,	__lowerCamelCase      :			Optional[int] )      ->				Union[str, Any]:
									A       , A							:					str              =						self.prepare_init_args_and_inputs_for_common()
									A							:					List[Any]              =						self.block_class(**__lowerCamelCase )
									unet_block.to(__lowerCamelCase )
									unet_block.eval()

									with torch.no_grad():
												A							:					int              =						unet_block(**__lowerCamelCase )

									if isinstance(__lowerCamelCase	,	__lowerCamelCase ):
												A							:					Union[str, Any]              =						output[0]

									self.assertEqual(output.shape	,	self.output_shape )

									A							:					Any              =						output[0, -1, -3:, -3:]
									A							:					Union[str, Any]              =						torch.tensor(__lowerCamelCase ).to(__lowerCamelCase )
									assert torch_all_close(output_slice.flatten()	,	__lowerCamelCase	,	atol=5e-3 )







						@unittest.skipIf(torch_device == "mps"	,	"Training is not supported in mps" )
						def 			SCREAMING_SNAKE_CASE__		(	self      :			Any )      ->				Dict:
									A       , A							:					Tuple              =						self.prepare_init_args_and_inputs_for_common()
									A							:					str              =						self.block_class(**__lowerCamelCase )
									model.to(__lowerCamelCase )
									model.train()
									A							:					Optional[int]              =						model(**__lowerCamelCase )

									if isinstance(__lowerCamelCase	,	__lowerCamelCase ):
												A							:					Optional[Any]              =						output[0]

									A							:					List[str]              =						torch.device(__lowerCamelCase )
									A							:					List[str]              =						randn_tensor(output.shape	,	device=__lowerCamelCase )
									A							:					Dict              =						torch.nn.functional.mse_loss(__lowerCamelCase	,	__lowerCamelCase )
									loss.backward()