
"""simple docstring"""

import os
import pickle
import unittest

from transformers import AutoTokenizer
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.models.bert_japanese.tokenization_bert_japanese import (
    VOCAB_FILES_NAMES,
    BertJapaneseTokenizer,
    CharacterTokenizer,
    JumanppTokenizer,
    MecabTokenizer,
    SudachiTokenizer,
    WordpieceTokenizer,
)
from transformers.testing_utils import custom_tokenizers, require_jumanpp, require_sudachi

from ...test_tokenization_common import TokenizerTesterMixin
@custom_tokenizers
class      _UpperCAmelCase							(		lowerCAmelCase__     ,			unittest.TestCase							):
      __SCREAMING_SNAKE_CASE   :							List[str]							      =	BertJapaneseTokenizer
      __SCREAMING_SNAKE_CASE   :							List[Any]							      =	False
      __SCREAMING_SNAKE_CASE   :							Dict							      =	True




      def     a_      (							self							)						->					Optional[int]:
          super().setUp()

          UpperCAmelCase									=					[
              '[UNK]',
              '[CLS]',
              '[SEP]',
              'こんにちは',
              'こん',
              'にちは',
              'ばんは',
              '##こん',
              '##にちは',
              '##ばんは',
              '世界',
              '##世界',
              '、',
              '##、',
              '。',
              '##。',
          ]

          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     a_      (							self   ,       lowercase_							)						->					List[str]:
          UpperCAmelCase									=					'こんにちは、世界。 \nこんばんは、世界。'
          UpperCAmelCase									=					'こんにちは 、 世界 。 こんばんは 、 世界 。'
          return input_text, output_text




      def     a_      (							self   ,       lowercase_							)						->					Optional[int]:
          UpperCAmelCase			,							UpperCAmelCase									=					self.get_input_output_texts(_lowerCamelCase							)
          UpperCAmelCase									=					tokenizer.encode(_lowerCamelCase   ,       add_special_tokens=_lowerCamelCase							)
          UpperCAmelCase									=					tokenizer.decode(_lowerCamelCase   ,       clean_up_tokenization_spaces=_lowerCamelCase							)
          return text, ids




      def     a_      (							self							)						->					Dict:
          pass  # TODO add if relevant




      def     a_      (							self							)						->					int:
          pass  # TODO add if relevant




      def     a_      (							self							)						->					List[str]:
          pass  # TODO add if relevant




      def     a_      (							self							)						->					int:
          UpperCAmelCase									=					self.tokenizer_class(self.vocab_file							)

          UpperCAmelCase									=					tokenizer.tokenize('こんにちは、世界。\nこんばんは、世界。'							)
          self.assertListEqual(_lowerCamelCase   ,       ['こんにちは', '、', '世界', '。', 'こん', '##ばんは', '、', '世界', '。']							)
          self.assertListEqual(tokenizer.convert_tokens_to_ids(_lowerCamelCase							)   ,       [3, 1_2, 1_0, 1_4, 4, 9, 1_2, 1_0, 1_4]							)




      def     a_      (							self							)						->					List[Any]:
          UpperCAmelCase									=					self.tokenizer_class(self.vocab_file   ,       word_tokenizer_type='mecab'							)
          self.assertIsNotNone(_lowerCamelCase							)

          UpperCAmelCase									=					'こんにちは、世界。\nこんばんは、世界。'
          UpperCAmelCase									=					tokenizer.tokenize(_lowerCamelCase							)
          self.assertListEqual(_lowerCamelCase   ,       ['こんにちは', '、', '世界', '。', 'こん', '##ばんは', '、', '世界', '。']							)
          self.assertListEqual(tokenizer.convert_tokens_to_ids(_lowerCamelCase							)   ,       [3, 1_2, 1_0, 1_4, 4, 9, 1_2, 1_0, 1_4]							)

          UpperCAmelCase									=					os.path.join(self.tmpdirname   ,       'tokenizer.bin'							)
          with open(_lowerCamelCase   ,       'wb'							) as handle:
              pickle.dump(_lowerCamelCase   ,       _lowerCamelCase							)

          with open(_lowerCamelCase   ,       'rb'							) as handle:
              UpperCAmelCase									=					pickle.load(_lowerCamelCase							)

          UpperCAmelCase									=					tokenizer_new.tokenize(_lowerCamelCase							)

          self.assertListEqual(_lowerCamelCase   ,       _lowerCamelCase							)




      def     a_      (							self							)						->					str:
          UpperCAmelCase									=					MecabTokenizer(mecab_dic='ipadic'							)

          self.assertListEqual(
              tokenizer.tokenize(' \tｱｯﾌﾟﾙストアでiPhone８ が  \n 発売された　。  '							)   ,       ['アップルストア', 'で', 'iPhone', '8', 'が', '発売', 'さ', 'れ', 'た', '。']   ,       )




      def     a_      (							self							)						->					List[str]:





          try:
              UpperCAmelCase									=					MecabTokenizer(mecab_dic='unidic_lite'							)
          except ModuleNotFoundError:
              return

          self.assertListEqual(
              tokenizer.tokenize(' \tｱｯﾌﾟﾙストアでiPhone８ が  \n 発売された　。  '							)   ,       ['アップル', 'ストア', 'で', 'iPhone', '8', 'が', '発売', 'さ', 'れ', 'た', '。']   ,       )




      def     a_      (							self							)						->					str:





          try:
              UpperCAmelCase									=					MecabTokenizer(mecab_dic='unidic'							)
          except ModuleNotFoundError:
              return

          self.assertListEqual(
              tokenizer.tokenize(' \tｱｯﾌﾟﾙストアでiPhone８ が  \n 発売された　。  '							)   ,       ['アップル', 'ストア', 'で', 'iPhone', '8', 'が', '発売', 'さ', 'れ', 'た', '。']   ,       )




      def     a_      (							self							)						->					List[Any]:
          UpperCAmelCase									=					MecabTokenizer(do_lower_case=_lowerCamelCase   ,       mecab_dic='ipadic'							)

          self.assertListEqual(
              tokenizer.tokenize(' \tｱｯﾌﾟﾙストアでiPhone８ が  \n 発売された　。  '							)   ,       ['アップルストア', 'で', 'iphone', '8', 'が', '発売', 'さ', 'れ', 'た', '。']   ,       )




      def     a_      (							self							)						->					Dict:





          try:
              UpperCAmelCase									=					MecabTokenizer(
                  do_lower_case=_lowerCamelCase   ,       normalize_text=_lowerCamelCase   ,       mecab_option='-d /usr/local/lib/mecab/dic/jumandic'							)
          except RuntimeError:
              # if dict doesn't exist in the system, previous code raises this error.
              return

          self.assertListEqual(
              tokenizer.tokenize(' \tｱｯﾌﾟﾙストアでiPhone８ が  \n 発売された　。  '							)   ,       ['ｱｯﾌﾟﾙストア', 'で', 'iPhone', '８', 'が', '発売', 'さ', 'れた', '\u3000', '。']   ,       )




      def     a_      (							self							)						->					Dict:
          UpperCAmelCase									=					MecabTokenizer(normalize_text=_lowerCamelCase   ,       mecab_dic='ipadic'							)

          self.assertListEqual(
              tokenizer.tokenize(' \tｱｯﾌﾟﾙストアでiPhone８ が  \n 発売された　。  '							)   ,       ['ｱｯﾌﾟﾙストア', 'で', 'iPhone', '８', 'が', '発売', 'さ', 'れ', 'た', '　', '。']   ,       )




      @require_sudachi
      def     a_      (							self							)						->					Optional[int]:
          UpperCAmelCase									=					self.tokenizer_class(self.vocab_file   ,       word_tokenizer_type='sudachi'							)
          self.assertIsNotNone(_lowerCamelCase							)

          UpperCAmelCase									=					'こんにちは、世界。\nこんばんは、世界。'
          UpperCAmelCase									=					tokenizer.tokenize(_lowerCamelCase							)
          self.assertListEqual(_lowerCamelCase   ,       ['こんにちは', '、', '世界', '。', 'こん', '##ばんは', '、', '世界', '。']							)
          self.assertListEqual(tokenizer.convert_tokens_to_ids(_lowerCamelCase							)   ,       [3, 1_2, 1_0, 1_4, 4, 9, 1_2, 1_0, 1_4]							)

          UpperCAmelCase									=					os.path.join(self.tmpdirname   ,       'tokenizer.bin'							)
          with open(_lowerCamelCase   ,       'wb'							) as handle:
              pickle.dump(_lowerCamelCase   ,       _lowerCamelCase							)

          with open(_lowerCamelCase   ,       'rb'							) as handle:
              UpperCAmelCase									=					pickle.load(_lowerCamelCase							)

          UpperCAmelCase									=					tokenizer_new.tokenize(_lowerCamelCase							)

          self.assertListEqual(_lowerCamelCase   ,       _lowerCamelCase							)




      @require_sudachi
      def     a_      (							self							)						->					Tuple:
          UpperCAmelCase									=					SudachiTokenizer(sudachi_dict_type='core'							)

          self.assertListEqual(
              tokenizer.tokenize(' \tｱｯﾌﾟﾙストアでiPhone８ が  \n 発売された　。  '							)   ,       [' ', '\t', 'アップル', 'ストア', 'で', 'iPhone', '8', ' ', 'が', ' ', ' ', '\n ', '発売', 'さ', 'れ', 'た', ' ', '。', ' ', ' ']   ,       )




      @require_sudachi
      def     a_      (							self							)						->					int:
          UpperCAmelCase									=					SudachiTokenizer(sudachi_dict_type='core'   ,       sudachi_split_mode='A'							)

          self.assertListEqual(tokenizer.tokenize('外国人参政権'							)   ,       ['外国', '人', '参政', '権']							)




      @require_sudachi
      def     a_      (							self							)						->					Tuple:
          UpperCAmelCase									=					SudachiTokenizer(sudachi_dict_type='core'   ,       sudachi_split_mode='B'							)

          self.assertListEqual(tokenizer.tokenize('外国人参政権'							)   ,       ['外国人', '参政権']							)




      @require_sudachi
      def     a_      (							self							)						->					Optional[Any]:
          UpperCAmelCase									=					SudachiTokenizer(sudachi_dict_type='core'   ,       sudachi_split_mode='C'							)

          self.assertListEqual(tokenizer.tokenize('外国人参政権'							)   ,       ['外国人参政権']							)




      @require_sudachi
      def     a_      (							self							)						->					List[Any]:
          UpperCAmelCase									=					SudachiTokenizer(do_lower_case=_lowerCamelCase   ,       sudachi_dict_type='core'							)

          self.assertListEqual(
              tokenizer.tokenize(' \tｱｯﾌﾟﾙストアでiPhone８ が  \n 発売された　。  '							)   ,       [' ', '\t', 'アップル', 'ストア', 'で', 'iphone', '8', ' ', 'が', ' ', ' ', '\n ', '発売', 'さ', 'れ', 'た', ' ', '。', ' ', ' ']   ,       )




      @require_sudachi
      def     a_      (							self							)						->					str:
          UpperCAmelCase									=					SudachiTokenizer(normalize_text=_lowerCamelCase   ,       sudachi_dict_type='core'							)

          self.assertListEqual(
              tokenizer.tokenize(' \tｱｯﾌﾟﾙストアでiPhone８ が  \n 発売された　。  '							)   ,       [' ', '\t', 'ｱｯﾌﾟﾙ', 'ストア', 'で', 'iPhone', '８', ' ', 'が', ' ', ' ', '\n ', '発売', 'さ', 'れ', 'た', '\u3000', '。', ' ', ' ']   ,       )




      @require_sudachi
      def     a_      (							self							)						->					Dict:
          UpperCAmelCase									=					SudachiTokenizer(trim_whitespace=_lowerCamelCase   ,       sudachi_dict_type='core'							)

          self.assertListEqual(
              tokenizer.tokenize(' \tｱｯﾌﾟﾙストアでiPhone８ が  \n 発売された　。  '							)   ,       ['アップル', 'ストア', 'で', 'iPhone', '8', 'が', '発売', 'さ', 'れ', 'た', '。']   ,       )




      @require_jumanpp
      def     a_      (							self							)						->					Optional[Any]:
          UpperCAmelCase									=					self.tokenizer_class(self.vocab_file   ,       word_tokenizer_type='jumanpp'							)
          self.assertIsNotNone(_lowerCamelCase							)

          UpperCAmelCase									=					'こんにちは、世界。\nこんばんは、世界。'
          UpperCAmelCase									=					tokenizer.tokenize(_lowerCamelCase							)
          self.assertListEqual(_lowerCamelCase   ,       ['こんにちは', '、', '世界', '。', 'こん', '##ばんは', '、', '世界', '。']							)
          self.assertListEqual(tokenizer.convert_tokens_to_ids(_lowerCamelCase							)   ,       [3, 1_2, 1_0, 1_4, 4, 9, 1_2, 1_0, 1_4]							)

          UpperCAmelCase									=					os.path.join(self.tmpdirname   ,       'tokenizer.bin'							)
          with open(_lowerCamelCase   ,       'wb'							) as handle:
              pickle.dump(_lowerCamelCase   ,       _lowerCamelCase							)

          with open(_lowerCamelCase   ,       'rb'							) as handle:
              UpperCAmelCase									=					pickle.load(_lowerCamelCase							)

          UpperCAmelCase									=					tokenizer_new.tokenize(_lowerCamelCase							)

          self.assertListEqual(_lowerCamelCase   ,       _lowerCamelCase							)




      @require_jumanpp
      def     a_      (							self							)						->					int:
          UpperCAmelCase									=					JumanppTokenizer()

          self.assertListEqual(
              tokenizer.tokenize(' \tｱｯﾌﾟﾙストアでiPhone８ が  \n 発売された　。  '							)   ,       ['アップル', 'ストア', 'で', 'iPhone', '8', '\u3000', 'が', '\u3000', '\u3000', '\u3000', '発売', 'さ', 'れた', '\u3000', '。']   ,       )




      @require_jumanpp
      def     a_      (							self							)						->					Tuple:
          UpperCAmelCase									=					JumanppTokenizer(do_lower_case=_lowerCamelCase							)

          self.assertListEqual(
              tokenizer.tokenize(' \tｱｯﾌﾟﾙストアでiPhone８ が  \n 発売された　。  '							)   ,       ['アップル', 'ストア', 'で', 'iphone', '8', '\u3000', 'が', '\u3000', '\u3000', '\u3000', '発売', 'さ', 'れた', '\u3000', '。']   ,       )




      @require_jumanpp
      def     a_      (							self							)						->					str:
          UpperCAmelCase									=					JumanppTokenizer(normalize_text=_lowerCamelCase							)

          self.assertListEqual(
              tokenizer.tokenize(' \tｱｯﾌﾟﾙストアでiPhone８ が  \n 発売された　。  '							)   ,       ['ｱ', 'ｯ', 'ﾌ', 'ﾟ', 'ﾙ', 'ストア', 'で', 'iPhone', '８', '\u3000', 'が', '\u3000', '\u3000', '\u3000', '発売', 'さ', 'れた', '\u3000', '。']   ,       )




      @require_jumanpp
      def     a_      (							self							)						->					List[str]:
          UpperCAmelCase									=					JumanppTokenizer(trim_whitespace=_lowerCamelCase							)

          self.assertListEqual(
              tokenizer.tokenize(' \tｱｯﾌﾟﾙストアでiPhone８ が  \n 発売された　。  '							)   ,       ['アップル', 'ストア', 'で', 'iPhone', '8', 'が', '発売', 'さ', 'れた', '。']   ,       )




      @require_jumanpp
      def     a_      (							self							)						->					int:
          UpperCAmelCase									=					JumanppTokenizer()

          self.assertListEqual(
              tokenizer.tokenize('ありがとうございますm(_ _)ｍ見つけるのが大変です。'							)   ,       ['ありがとう', 'ございます', 'm(_ _)m', '見つける', 'の', 'が', '大変です', '。']   ,       )




      def     a_      (							self							)						->					Optional[int]:
          UpperCAmelCase									=					['[UNK]', '[CLS]', '[SEP]', 'こんにちは', 'こん', 'にちは', 'ばんは', '##こん', '##にちは', '##ばんは']

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

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

          self.assertListEqual(tokenizer.tokenize('こんにちは'							)   ,       ['こんにちは']							)

          self.assertListEqual(tokenizer.tokenize('こんばんは'							)   ,       ['こん', '##ばんは']							)

          self.assertListEqual(tokenizer.tokenize('こんばんは こんばんにちは こんにちは'							)   ,       ['こん', '##ばんは', '[UNK]', 'こんにちは']							)




      def     a_      (							self							)						->					Union[str, Any]:
          UpperCAmelCase									=					BertJapaneseTokenizer.from_pretrained('nlp-waseda/roberta-base-japanese-with-auto-jumanpp'							)
          UpperCAmelCase									=					tokenizer.subword_tokenizer

          UpperCAmelCase									=					subword_tokenizer.tokenize('国境 の 長い トンネル を 抜ける と 雪国 であった 。'							)
          self.assertListEqual(_lowerCamelCase   ,       ['▁国境', '▁の', '▁長い', '▁トンネル', '▁を', '▁抜ける', '▁と', '▁雪', '国', '▁であった', '▁。']							)

          UpperCAmelCase									=					subword_tokenizer.tokenize('こんばんは こんばん にち は こんにちは'							)
          self.assertListEqual(_lowerCamelCase   ,       ['▁こん', 'ばん', 'は', '▁こん', 'ばん', '▁に', 'ち', '▁は', '▁こんにちは']							)




      def     a_      (							self							)						->					List[Any]:
          UpperCAmelCase									=					self.tokenizer_class.from_pretrained('cl-tohoku/bert-base-japanese'							)

          UpperCAmelCase									=					tokenizer.encode('ありがとう。'   ,       add_special_tokens=_lowerCamelCase							)
          UpperCAmelCase									=					tokenizer.encode('どういたしまして。'   ,       add_special_tokens=_lowerCamelCase							)

          UpperCAmelCase									=					tokenizer.build_inputs_with_special_tokens(_lowerCamelCase							)
          UpperCAmelCase									=					tokenizer.build_inputs_with_special_tokens(_lowerCamelCase   ,       _lowerCamelCase							)

          # 2 is for "[CLS]", 3 is for "[SEP]"
          assert encoded_sentence == [2] + text + [3]
          assert encoded_pair == [2] + text + [3] + text_a + [3]

@custom_tokenizers
class      _UpperCAmelCase							(		lowerCAmelCase__     ,			unittest.TestCase							):
      __SCREAMING_SNAKE_CASE   :							List[Any]							      =	BertJapaneseTokenizer
      __SCREAMING_SNAKE_CASE   :							List[Any]							      =	False




      def     a_      (							self							)						->					Any:
          super().setUp()

          UpperCAmelCase									=					['[UNK]', '[CLS]', '[SEP]', 'こ', 'ん', 'に', 'ち', 'は', 'ば', '世', '界', '、', '。']

          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     a_      (							self   ,       **lowercase_							)						->					Dict:
          return BertJapaneseTokenizer.from_pretrained(self.tmpdirname   ,       subword_tokenizer_type='character'   ,       **_lowerCamelCase							)




      def     a_      (							self   ,       lowercase_							)						->					Optional[int]:
          UpperCAmelCase									=					'こんにちは、世界。 \nこんばんは、世界。'
          UpperCAmelCase									=					'こ ん に ち は 、 世 界 。 こ ん ば ん は 、 世 界 。'
          return input_text, output_text




      def     a_      (							self							)						->					Optional[int]:
          pass  # TODO add if relevant




      def     a_      (							self							)						->					Dict:
          pass  # TODO add if relevant




      def     a_      (							self							)						->					Dict:
          pass  # TODO add if relevant




      def     a_      (							self							)						->					List[str]:
          UpperCAmelCase									=					self.tokenizer_class(self.vocab_file   ,       subword_tokenizer_type='character'							)

          UpperCAmelCase									=					tokenizer.tokenize('こんにちは、世界。 \nこんばんは、世界。'							)
          self.assertListEqual(
              _lowerCamelCase   ,       ['こ', 'ん', 'に', 'ち', 'は', '、', '世', '界', '。', 'こ', 'ん', 'ば', 'ん', 'は', '、', '世', '界', '。']							)
          self.assertListEqual(
              tokenizer.convert_tokens_to_ids(_lowerCamelCase							)   ,       [3, 4, 5, 6, 7, 1_1, 9, 1_0, 1_2, 3, 4, 8, 4, 7, 1_1, 9, 1_0, 1_2]							)




      def     a_      (							self							)						->					Optional[int]:
          UpperCAmelCase									=					['[UNK]', '[CLS]', '[SEP]', 'こ', 'ん', 'に', 'ち', 'は', 'ば', '世', '界', '、', '。']

          UpperCAmelCase									=					{}
          for i, token in enumerate(_lowerCamelCase							):
              UpperCAmelCase									=					i
          UpperCAmelCase									=					CharacterTokenizer(vocab=_lowerCamelCase   ,       unk_token='[UNK]'							)

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

          self.assertListEqual(tokenizer.tokenize('こんにちは'							)   ,       ['こ', 'ん', 'に', 'ち', 'は']							)

          self.assertListEqual(tokenizer.tokenize('こんにちほ'							)   ,       ['こ', 'ん', 'に', 'ち', '[UNK]']							)




      def     a_      (							self							)						->					List[str]:
          UpperCAmelCase									=					self.tokenizer_class.from_pretrained('cl-tohoku/bert-base-japanese-char'							)

          UpperCAmelCase									=					tokenizer.encode('ありがとう。'   ,       add_special_tokens=_lowerCamelCase							)
          UpperCAmelCase									=					tokenizer.encode('どういたしまして。'   ,       add_special_tokens=_lowerCamelCase							)

          UpperCAmelCase									=					tokenizer.build_inputs_with_special_tokens(_lowerCamelCase							)
          UpperCAmelCase									=					tokenizer.build_inputs_with_special_tokens(_lowerCamelCase   ,       _lowerCamelCase							)

          # 2 is for "[CLS]", 3 is for "[SEP]"
          assert encoded_sentence == [2] + text + [3]
          assert encoded_pair == [2] + text + [3] + text_a + [3]

@custom_tokenizers
class      _UpperCAmelCase							(		unittest.TestCase							):




      def     a_      (							self							)						->					int:
          UpperCAmelCase									=					'cl-tohoku/bert-base-japanese'
          UpperCAmelCase									=					AutoTokenizer.from_pretrained(_lowerCamelCase							)
          self.assertIsInstance(_lowerCamelCase   ,       _lowerCamelCase							)

class      _UpperCAmelCase							(		unittest.TestCase							):




      def     a_      (							self							)						->					Dict:
          UpperCAmelCase									=					'cl-tohoku/bert-base-japanese'
          with self.assertLogs('transformers'   ,       level='WARNING'							) as cm:
              BertTokenizer.from_pretrained(_lowerCamelCase							)
              self.assertTrue(
                  cm.records[0].message.startswith(
                      'The tokenizer class you load from this checkpoint is not the same type as the class this function'
                      ' is called from.'							)							)
          UpperCAmelCase									=					'bert-base-cased'
          with self.assertLogs('transformers'   ,       level='WARNING'							) as cm:
              BertJapaneseTokenizer.from_pretrained(_lowerCamelCase							)
              self.assertTrue(
                  cm.records[0].message.startswith(
                      'The tokenizer class you load from this checkpoint is not the same type as the class this function'
                      ' is called from.'							)							)





"""simple docstring"""

import torch

from diffusers import DDPMScheduler

from .test_schedulers import SchedulerCommonTest
class      _UpperCAmelCase							(		SCREAMING_SNAKE_CASE_							):
      __SCREAMING_SNAKE_CASE   :							str							      =	(DDPMScheduler,)




      def     a_      (							self   ,       **lowercase_							)						->					Union[str, Any]:
          UpperCAmelCase									=					{
              'num_train_timesteps': 1_0_0_0,
              'beta_start': 0.0_0_0_1,
              'beta_end': 0.0_2,
              'beta_schedule': 'linear',
              'variance_type': 'fixed_small',
              'clip_sample': True,
          }

          config.update(**lowercase_							)
          return config




      def     a_      (							self							)						->					int:
          for timesteps in [1, 5, 1_0_0, 1_0_0_0]:
              self.check_over_configs(num_train_timesteps=lowercase_							)




      def     a_      (							self							)						->					Optional[int]:
          for beta_start, beta_end in zip([0.0_0_0_1, 0.0_0_1, 0.0_1, 0.1]   ,       [0.0_0_2, 0.0_2, 0.2, 2]							):
              self.check_over_configs(beta_start=lowercase_   ,       beta_end=lowercase_							)




      def     a_      (							self							)						->					Dict:
          for schedule in ["linear", "squaredcos_cap_v2"]:
              self.check_over_configs(beta_schedule=lowercase_							)




      def     a_      (							self							)						->					Union[str, Any]:
          for variance in ["fixed_small", "fixed_large", "other"]:
              self.check_over_configs(variance_type=lowercase_							)




      def     a_      (							self							)						->					Optional[Any]:
          for clip_sample in [True, False]:
              self.check_over_configs(clip_sample=lowercase_							)




      def     a_      (							self							)						->					Tuple:
          self.check_over_configs(thresholding=lowercase_							)
          for threshold in [0.5, 1.0, 2.0]:
              for prediction_type in ["epsilon", "sample", "v_prediction"]:
                  self.check_over_configs(
                      thresholding=lowercase_   ,       prediction_type=lowercase_   ,       sample_max_value=lowercase_   ,       )




      def     a_      (							self							)						->					Any:
          for prediction_type in ["epsilon", "sample", "v_prediction"]:
              self.check_over_configs(prediction_type=lowercase_							)




      def     a_      (							self							)						->					Union[str, Any]:
          for t in [0, 5_0_0, 9_9_9]:
              self.check_over_forward(time_step=lowercase_							)




      def     a_      (							self							)						->					Optional[Any]:
          UpperCAmelCase									=					self.scheduler_classes[0]
          UpperCAmelCase									=					self.get_scheduler_config()
          UpperCAmelCase									=					scheduler_class(**lowercase_							)

          assert torch.sum(torch.abs(scheduler._get_variance(0							) - 0.0							)							) < 1E-5
          assert torch.sum(torch.abs(scheduler._get_variance(4_8_7							) - 0.0_0_9_7_9							)							) < 1E-5
          assert torch.sum(torch.abs(scheduler._get_variance(9_9_9							) - 0.0_2							)							) < 1E-5




      def     a_      (							self							)						->					str:
          UpperCAmelCase									=					self.scheduler_classes[0]
          UpperCAmelCase									=					self.get_scheduler_config()
          UpperCAmelCase									=					scheduler_class(**lowercase_							)

          UpperCAmelCase									=					len(lowercase_							)

          UpperCAmelCase									=					self.dummy_model()
          UpperCAmelCase									=					self.dummy_sample_deter
          UpperCAmelCase									=					torch.manual_seed(0							)

          for t in reversed(range(lowercase_							)							):
              # 1. predict noise residual
              UpperCAmelCase									=					model(lowercase_   ,       lowercase_							)

              # 2. predict previous mean of sample x_t-1
              UpperCAmelCase									=					scheduler.step(lowercase_   ,       lowercase_   ,       lowercase_   ,       generator=lowercase_							).prev_sample

              # if t > 0:
              #     noise = self.dummy_sample_deter
              #     variance = scheduler.get_variance(t) ** (0.5) * noise
              #
              # sample = pred_prev_sample + variance
              UpperCAmelCase									=					pred_prev_sample

          UpperCAmelCase									=					torch.sum(torch.abs(lowercase_							)							)
          UpperCAmelCase									=					torch.mean(torch.abs(lowercase_							)							)

          assert abs(result_sum.item() - 2_5_8.9_6_0_6							) < 1E-2
          assert abs(result_mean.item() - 0.3_3_7_2							) < 1E-3




      def     a_      (							self							)						->					Union[str, Any]:
          UpperCAmelCase									=					self.scheduler_classes[0]
          UpperCAmelCase									=					self.get_scheduler_config(prediction_type='v_prediction'							)
          UpperCAmelCase									=					scheduler_class(**lowercase_							)

          UpperCAmelCase									=					len(lowercase_							)

          UpperCAmelCase									=					self.dummy_model()
          UpperCAmelCase									=					self.dummy_sample_deter
          UpperCAmelCase									=					torch.manual_seed(0							)

          for t in reversed(range(lowercase_							)							):
              # 1. predict noise residual
              UpperCAmelCase									=					model(lowercase_   ,       lowercase_							)

              # 2. predict previous mean of sample x_t-1
              UpperCAmelCase									=					scheduler.step(lowercase_   ,       lowercase_   ,       lowercase_   ,       generator=lowercase_							).prev_sample

              # if t > 0:
              #     noise = self.dummy_sample_deter
              #     variance = scheduler.get_variance(t) ** (0.5) * noise
              #
              # sample = pred_prev_sample + variance
              UpperCAmelCase									=					pred_prev_sample

          UpperCAmelCase									=					torch.sum(torch.abs(lowercase_							)							)
          UpperCAmelCase									=					torch.mean(torch.abs(lowercase_							)							)

          assert abs(result_sum.item() - 2_0_2.0_2_9_6							) < 1E-2
          assert abs(result_mean.item() - 0.2_6_3_1							) < 1E-3




      def     a_      (							self							)						->					Optional[Any]:
          UpperCAmelCase									=					self.scheduler_classes[0]
          UpperCAmelCase									=					self.get_scheduler_config()
          UpperCAmelCase									=					scheduler_class(**lowercase_							)

          UpperCAmelCase									=					[1_0_0, 8_7, 5_0, 1, 0]

          scheduler.set_timesteps(timesteps=lowercase_							)

          UpperCAmelCase									=					scheduler.timesteps

          for i, timestep in enumerate(lowercase_							):
              if i == len(lowercase_							) - 1:
                  UpperCAmelCase									=					-1
              else:
                  UpperCAmelCase									=					timesteps[i + 1]

              UpperCAmelCase									=					scheduler.previous_timestep(lowercase_							)
              UpperCAmelCase									=					prev_t.item()

              self.assertEqual(lowercase_   ,       lowercase_							)




      def     a_      (							self							)						->					Optional[Any]:
          UpperCAmelCase									=					self.scheduler_classes[0]
          UpperCAmelCase									=					self.get_scheduler_config()
          UpperCAmelCase									=					scheduler_class(**lowercase_							)

          UpperCAmelCase									=					[1_0_0, 8_7, 5_0, 5_1, 0]

          with self.assertRaises(lowercase_   ,       msg='`custom_timesteps` must be in descending order.'							):
              scheduler.set_timesteps(timesteps=lowercase_							)




      def     a_      (							self							)						->					List[Any]:
          UpperCAmelCase									=					self.scheduler_classes[0]
          UpperCAmelCase									=					self.get_scheduler_config()
          UpperCAmelCase									=					scheduler_class(**lowercase_							)

          UpperCAmelCase									=					[1_0_0, 8_7, 5_0, 1, 0]
          UpperCAmelCase									=					len(lowercase_							)

          with self.assertRaises(lowercase_   ,       msg='Can only pass one of `num_inference_steps` or `custom_timesteps`.'							):
              scheduler.set_timesteps(num_inference_steps=lowercase_   ,       timesteps=lowercase_							)




      def     a_      (							self							)						->					str:
          UpperCAmelCase									=					self.scheduler_classes[0]
          UpperCAmelCase									=					self.get_scheduler_config()
          UpperCAmelCase									=					scheduler_class(**lowercase_							)

          UpperCAmelCase									=					[scheduler.config.num_train_timesteps]

          with self.assertRaises(
              lowercase_   ,       msg='`timesteps` must start before `self.config.train_timesteps`: {scheduler.config.num_train_timesteps}}'   ,       ):
              scheduler.set_timesteps(timesteps=lowercase_							)



