


'''simple docstring'''
import unittest

from transformers import DebertaVaTokenizer, DebertaVaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin


__snake_case							   =  get_tests_dir('''fixtures/spiece.model''')
@require_sentencepiece
@require_tokenizers
class      lowercase			(							A__			,	unittest.TestCase      ):

		"""simple docstring"""

		_a									=       DebertaVaTokenizer
		_a									=       DebertaVaTokenizerFast
		_a									=       True
		_a									=       True




		def 					lowerCAmelCase__       (	self							):

							'''simple docstring'''


							super().setUp()

							# We have a SentencePiece fixture for testing
							UpperCamelCase__     :Tuple							      =				DebertaVaTokenizer(UpperCamelCase_					,     unk_token='''<unk>'''							)
							tokenizer.save_pretrained(self.tmpdirname							)




		def 					lowerCAmelCase__       (	self					,     UpperCamelCase_							):

							'''simple docstring'''


							UpperCamelCase__     :List[Any]							      =				'''this is a test'''
							UpperCamelCase__     :str							      =				'''this is a test'''
							return input_text, output_text




		def 					lowerCAmelCase__       (	self							):

							'''simple docstring'''


							UpperCamelCase__     :List[Any]							      =				'''<pad>'''
							UpperCamelCase__     :Dict							      =				0

							self.assertEqual(self.get_tokenizer()._convert_token_to_id(UpperCamelCase_							)					,     UpperCamelCase_							)
							self.assertEqual(self.get_tokenizer()._convert_id_to_token(UpperCamelCase_							)					,     UpperCamelCase_							)




		def 					lowerCAmelCase__       (	self							):

							'''simple docstring'''


							UpperCamelCase__     :Dict							      =				list(self.get_tokenizer().get_vocab().keys()							)
							self.assertEqual(vocab_keys[0]					,     '''<pad>'''							)
							self.assertEqual(vocab_keys[1]					,     '''<unk>'''							)
							self.assertEqual(vocab_keys[-1]					,     '''[PAD]'''							)
							self.assertEqual(len(UpperCamelCase_							)					,     30001							)




		def 					lowerCAmelCase__       (	self							):

							'''simple docstring'''


							self.assertEqual(self.get_tokenizer().vocab_size					,     30000							)




		def 					lowerCAmelCase__       (	self							):

							'''simple docstring'''


							UpperCamelCase__     :int							      =				''' \tHeLLo!how  \n Are yoU?  '''
							UpperCamelCase__     :Dict							      =				['''▁hello''', '''!''', '''how''', '''▁are''', '''▁you''', '''?''']
							# fmt: on

							UpperCamelCase__     :Dict							      =				DebertaVaTokenizer(UpperCamelCase_					,     do_lower_case=UpperCamelCase_							)
							UpperCamelCase__     :Tuple							      =				tokenizer.convert_ids_to_tokens(tokenizer.encode(UpperCamelCase_					,     add_special_tokens=UpperCamelCase_							)							)

							self.assertListEqual(UpperCamelCase_					,     UpperCamelCase_							)

							UpperCamelCase__     :Dict							      =				DebertaVaTokenizerFast(UpperCamelCase_					,     do_lower_case=UpperCamelCase_							)
							UpperCamelCase__     :str							      =				rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(UpperCamelCase_					,     add_special_tokens=UpperCamelCase_							)							)

							self.assertListEqual(UpperCamelCase_					,     UpperCamelCase_							)




		@unittest.skip('''There is an inconsistency between slow and fast tokenizer due to a bug in the fast one.'''							)
		def 					lowerCAmelCase__       (	self							):

							'''simple docstring'''


							pass




		@unittest.skip('''There is an inconsistency between slow and fast tokenizer due to a bug in the fast one.'''							)
		def 					lowerCAmelCase__       (	self							):

							'''simple docstring'''


							pass




		def 					lowerCAmelCase__       (	self							):

							'''simple docstring'''


							UpperCamelCase__     :Dict							      =				'''I was born in 92000, and this is falsé.'''
							UpperCamelCase__     :Any							      =				['''▁''', '''<unk>''', '''▁was''', '''▁born''', '''▁in''', '''▁9''', '''2000''', '''▁''', ''',''', '''▁and''', '''▁this''', '''▁is''', '''▁fal''', '''s''', '''<unk>''', '''▁''', '''.''', ]
							# fmt: on

							UpperCamelCase__     :Any							      =				DebertaVaTokenizer(UpperCamelCase_					,     split_by_punct=UpperCamelCase_							)
							UpperCamelCase__     :int							      =				tokenizer.convert_ids_to_tokens(tokenizer.encode(UpperCamelCase_					,     add_special_tokens=UpperCamelCase_							)							)

							self.assertListEqual(UpperCamelCase_					,     UpperCamelCase_							)

							UpperCamelCase__     :Union[str, Any]							      =				DebertaVaTokenizerFast(UpperCamelCase_					,     split_by_punct=UpperCamelCase_							)
							UpperCamelCase__     :Any							      =				rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(UpperCamelCase_					,     add_special_tokens=UpperCamelCase_							)							)

							self.assertListEqual(UpperCamelCase_					,     UpperCamelCase_							)




		def 					lowerCAmelCase__       (	self							):

							'''simple docstring'''


							UpperCamelCase__     :Optional[Any]							      =				'''I was born in 92000, and this is falsé.'''
							UpperCamelCase__     :Optional[Any]							      =				['''▁i''', '''▁was''', '''▁born''', '''▁in''', '''▁9''', '''2000''', '''▁''', ''',''', '''▁and''', '''▁this''', '''▁is''', '''▁fal''', '''s''', '''<unk>''', '''▁''', '''.''', ]
							# fmt: on

							UpperCamelCase__     :str							      =				DebertaVaTokenizer(UpperCamelCase_					,     do_lower_case=UpperCamelCase_					,     split_by_punct=UpperCamelCase_							)
							UpperCamelCase__     :Union[str, Any]							      =				tokenizer.convert_ids_to_tokens(tokenizer.encode(UpperCamelCase_					,     add_special_tokens=UpperCamelCase_							)							)
							self.assertListEqual(UpperCamelCase_					,     UpperCamelCase_							)

							UpperCamelCase__     :Dict							      =				DebertaVaTokenizerFast(UpperCamelCase_					,     do_lower_case=UpperCamelCase_					,     split_by_punct=UpperCamelCase_							)
							UpperCamelCase__     :Optional[Any]							      =				rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(UpperCamelCase_					,     add_special_tokens=UpperCamelCase_							)							)
							self.assertListEqual(UpperCamelCase_					,     UpperCamelCase_							)




		def 					lowerCAmelCase__       (	self							):

							'''simple docstring'''


							UpperCamelCase__     :Optional[int]							      =				'''I was born in 92000, and this is falsé.'''
							UpperCamelCase__     :List[Any]							      =				['''▁i''', '''▁was''', '''▁born''', '''▁in''', '''▁9''', '''2000''', ''',''', '''▁and''', '''▁this''', '''▁is''', '''▁fal''', '''s''', '''<unk>''', '''.''', ]
							# fmt: on

							UpperCamelCase__     :List[Any]							      =				DebertaVaTokenizer(UpperCamelCase_					,     do_lower_case=UpperCamelCase_					,     split_by_punct=UpperCamelCase_							)
							UpperCamelCase__     :Dict							      =				tokenizer.convert_ids_to_tokens(tokenizer.encode(UpperCamelCase_					,     add_special_tokens=UpperCamelCase_							)							)

							self.assertListEqual(UpperCamelCase_					,     UpperCamelCase_							)

							UpperCamelCase__     :List[str]							      =				DebertaVaTokenizerFast(UpperCamelCase_					,     do_lower_case=UpperCamelCase_					,     split_by_punct=UpperCamelCase_							)
							UpperCamelCase__     :Union[str, Any]							      =				rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(UpperCamelCase_					,     add_special_tokens=UpperCamelCase_							)							)

							self.assertListEqual(UpperCamelCase_					,     UpperCamelCase_							)




		def 					lowerCAmelCase__       (	self							):

							'''simple docstring'''


							UpperCamelCase__     :Any							      =				'''I was born in 92000, and this is falsé.'''
							UpperCamelCase__     :str							      =				['''▁''', '''<unk>''', '''▁was''', '''▁born''', '''▁in''', '''▁9''', '''2000''', '''▁''', ''',''', '''▁and''', '''▁this''', '''▁is''', '''▁fal''', '''s''', '''<unk>''', '''▁''', '''.''', ]
							# fmt: on

							UpperCamelCase__     :List[Any]							      =				DebertaVaTokenizer(UpperCamelCase_					,     do_lower_case=UpperCamelCase_					,     split_by_punct=UpperCamelCase_							)
							UpperCamelCase__     :Union[str, Any]							      =				tokenizer.convert_ids_to_tokens(tokenizer.encode(UpperCamelCase_					,     add_special_tokens=UpperCamelCase_							)							)

							self.assertListEqual(UpperCamelCase_					,     UpperCamelCase_							)

							UpperCamelCase__     :int							      =				DebertaVaTokenizerFast(UpperCamelCase_					,     do_lower_case=UpperCamelCase_					,     split_by_punct=UpperCamelCase_							)
							UpperCamelCase__     :Any							      =				rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(UpperCamelCase_					,     add_special_tokens=UpperCamelCase_							)							)

							self.assertListEqual(UpperCamelCase_					,     UpperCamelCase_							)




		def 					lowerCAmelCase__       (	self							):

							'''simple docstring'''


							UpperCamelCase__     :List[Any]							      =				''' \tHeLLo!how  \n Are yoU?  '''
							UpperCamelCase__     :List[str]							      =				['''▁''', '''<unk>''', '''e''', '''<unk>''', '''o''', '''!''', '''how''', '''▁''', '''<unk>''', '''re''', '''▁yo''', '''<unk>''', '''?''']
							# fmt: on

							UpperCamelCase__     :Tuple							      =				DebertaVaTokenizer(UpperCamelCase_					,     do_lower_case=UpperCamelCase_					,     split_by_punct=UpperCamelCase_							)
							UpperCamelCase__     :Optional[Any]							      =				tokenizer.convert_ids_to_tokens(tokenizer.encode(UpperCamelCase_					,     add_special_tokens=UpperCamelCase_							)							)

							self.assertListEqual(UpperCamelCase_					,     UpperCamelCase_							)

							UpperCamelCase__     :List[str]							      =				DebertaVaTokenizerFast(UpperCamelCase_					,     do_lower_case=UpperCamelCase_					,     split_by_punct=UpperCamelCase_							)
							UpperCamelCase__     :Optional[int]							      =				rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(UpperCamelCase_					,     add_special_tokens=UpperCamelCase_							)							)

							self.assertListEqual(UpperCamelCase_					,     UpperCamelCase_							)




		def 					lowerCAmelCase__       (	self							):

							'''simple docstring'''


							UpperCamelCase__     :str							      =				self.get_tokenizer()
							UpperCamelCase__     :Dict							      =				self.get_rust_tokenizer()

							UpperCamelCase__     :int							      =				'''I was born in 92000, and this is falsé.'''

							UpperCamelCase__     :List[Any]							      =				tokenizer.convert_ids_to_tokens(tokenizer.encode(UpperCamelCase_					,     add_special_tokens=UpperCamelCase_							)							)
							UpperCamelCase__     :int							      =				rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(UpperCamelCase_					,     add_special_tokens=UpperCamelCase_							)							)
							self.assertListEqual(UpperCamelCase_					,     UpperCamelCase_							)

							UpperCamelCase__     :List[str]							      =				tokenizer.encode(UpperCamelCase_					,     add_special_tokens=UpperCamelCase_							)
							UpperCamelCase__     :Union[str, Any]							      =				rust_tokenizer.encode(UpperCamelCase_					,     add_special_tokens=UpperCamelCase_							)
							self.assertListEqual(UpperCamelCase_					,     UpperCamelCase_							)

							UpperCamelCase__     :List[Any]							      =				self.get_rust_tokenizer()
							UpperCamelCase__     :Dict							      =				tokenizer.encode(UpperCamelCase_							)
							UpperCamelCase__     :Any							      =				rust_tokenizer.encode(UpperCamelCase_							)
							self.assertListEqual(UpperCamelCase_					,     UpperCamelCase_							)




		def 					lowerCAmelCase__       (	self							):

							'''simple docstring'''


							UpperCamelCase__     :List[Any]							      =				'''This is a test'''
							UpperCamelCase__     :Any							      =				[13, 1, 4398, 25, 21, 1289]
							UpperCamelCase__     :Any							      =				['''▁''', '''T''', '''his''', '''▁is''', '''▁a''', '''▁test''']
							UpperCamelCase__     :Any							      =				['''▁''', '''<unk>''', '''his''', '''▁is''', '''▁a''', '''▁test''']

							UpperCamelCase__     :Any							      =				DebertaVaTokenizer(UpperCamelCase_					,     keep_accents=UpperCamelCase_							)
							UpperCamelCase__     :Union[str, Any]							      =				DebertaVaTokenizerFast(UpperCamelCase_					,     keep_accents=UpperCamelCase_							)

							UpperCamelCase__     :Dict							      =				tokenizer.encode(UpperCamelCase_					,     add_special_tokens=UpperCamelCase_							)
							self.assertListEqual(UpperCamelCase_					,     UpperCamelCase_							)
							UpperCamelCase__     :Optional[int]							      =				tokenizer.tokenize(UpperCamelCase_							)
							self.assertListEqual(UpperCamelCase_					,     UpperCamelCase_							)
							UpperCamelCase__     :Optional[Any]							      =				tokenizer.convert_ids_to_tokens(UpperCamelCase_							)
							self.assertListEqual(UpperCamelCase_					,     UpperCamelCase_							)

							UpperCamelCase__     :Any							      =				rust_tokenizer.encode(UpperCamelCase_					,     add_special_tokens=UpperCamelCase_							)
							self.assertListEqual(UpperCamelCase_					,     UpperCamelCase_							)
							UpperCamelCase__     :List[str]							      =				rust_tokenizer.tokenize(UpperCamelCase_							)
							self.assertListEqual(UpperCamelCase_					,     UpperCamelCase_							)
							UpperCamelCase__     :str							      =				rust_tokenizer.convert_ids_to_tokens(UpperCamelCase_							)
							self.assertListEqual(UpperCamelCase_					,     UpperCamelCase_							)

							# fmt: off
							UpperCamelCase__     :Dict							      =				'''I was born in 92000, and this is falsé.'''
							UpperCamelCase__     :Optional[int]							      =				[13, 1, 23, 386, 19, 561, 3050, 15, 17, 48, 25, 8256, 18, 1, 9]
							UpperCamelCase__     :int							      =				['''▁''', '''I''', '''▁was''', '''▁born''', '''▁in''', '''▁9''', '''2000''', ''',''', '''▁and''', '''▁this''', '''▁is''', '''▁fal''', '''s''', '''é''', '''.''', ]
							UpperCamelCase__     :Optional[int]							      =				['''▁''', '''<unk>''', '''▁was''', '''▁born''', '''▁in''', '''▁9''', '''2000''', ''',''', '''▁and''', '''▁this''', '''▁is''', '''▁fal''', '''s''', '''<unk>''', '''.''', ]
							# fmt: on

							UpperCamelCase__     :Tuple							      =				tokenizer.encode(UpperCamelCase_					,     add_special_tokens=UpperCamelCase_							)
							self.assertListEqual(UpperCamelCase_					,     UpperCamelCase_							)
							UpperCamelCase__     :str							      =				tokenizer.tokenize(UpperCamelCase_							)
							self.assertListEqual(UpperCamelCase_					,     UpperCamelCase_							)
							UpperCamelCase__     :Tuple							      =				tokenizer.convert_ids_to_tokens(UpperCamelCase_							)
							self.assertListEqual(UpperCamelCase_					,     UpperCamelCase_							)

							UpperCamelCase__     :Dict							      =				rust_tokenizer.encode(UpperCamelCase_					,     add_special_tokens=UpperCamelCase_							)
							self.assertListEqual(UpperCamelCase_					,     UpperCamelCase_							)
							UpperCamelCase__     :Union[str, Any]							      =				rust_tokenizer.tokenize(UpperCamelCase_							)
							self.assertListEqual(UpperCamelCase_					,     UpperCamelCase_							)
							UpperCamelCase__     :List[Any]							      =				rust_tokenizer.convert_ids_to_tokens(UpperCamelCase_							)
							self.assertListEqual(UpperCamelCase_					,     UpperCamelCase_							)




		def 					lowerCAmelCase__       (	self							):

							'''simple docstring'''


							UpperCamelCase__     :Optional[Any]							      =				DebertaVaTokenizer(UpperCamelCase_							)

							UpperCamelCase__     :Tuple							      =				tokenizer.encode('''sequence builders'''							)
							UpperCamelCase__     :Any							      =				tokenizer.encode('''multi-sequence build'''							)

							UpperCamelCase__     :Union[str, Any]							      =				tokenizer.build_inputs_with_special_tokens(UpperCamelCase_							)
							UpperCamelCase__     :List[Any]							      =				tokenizer.build_inputs_with_special_tokens(UpperCamelCase_					,     UpperCamelCase_							)

							self.assertEqual([tokenizer.cls_token_id] + text + [tokenizer.sep_token_id]					,     UpperCamelCase_							)
							self.assertEqual(
							    [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id] + text_a + [tokenizer.sep_token_id]					,     UpperCamelCase_					,     )




		@slow
		def 					lowerCAmelCase__       (	self							):

							'''simple docstring'''


							UpperCamelCase__     :Any							      =				{'''input_ids''': [[1, 39867, 36, 19390, 486, 27, 35052, 81436, 18, 60685, 1225, 7, 35052, 81436, 18, 9367, 16899, 18, 15937, 53, 594, 773, 18, 16287, 30465, 36, 15937, 6, 41139, 38, 36979, 60763, 191, 6, 34132, 99, 6, 50538, 390, 43230, 6, 34132, 2779, 20850, 14, 699, 1072, 1194, 36, 382, 10901, 53, 7, 699, 1072, 2084, 36, 20422, 630, 53, 19, 105, 3049, 1896, 1053, 16899, 1506, 11, 37978, 4243, 7, 1237, 31869, 200, 16566, 654, 6, 35052, 81436, 7, 55630, 13593, 4, 2], [1, 26, 15011, 13, 667, 8, 1053, 18, 23611, 1237, 72356, 12820, 34, 104134, 1209, 35, 13313, 6627, 21, 202, 347, 7, 164, 2399, 11, 46, 4485, 4, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 5, 1232, 2864, 15785, 14951, 105, 5, 8581, 1250, 4, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], '''token_type_ids''': [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], '''attention_mask''': [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
							# fmt: on

							self.tokenizer_integration_test_util(
							    expected_encoding=UpperCamelCase_					,     model_name='''microsoft/deberta-v2-xlarge'''					,     revision='''ad6e42c1532ddf3a15c39246b63f5559d558b670'''					,     )



'''simple docstring'''
import contextlib
import copy
import random
from typing import Any, Dict, Iterable, Optional, Union

import numpy as np
import torch

from .utils import deprecate, is_transformers_available


if is_transformers_available():
		import transformers


def     a   (    __a     )						->			Optional[int]:



					'''simple docstring'''






					random.seed(__a     )
					np.random.seed(__a     )
					torch.manual_seed(__a     )
					torch.cuda.manual_seed_all(__a     )
					# ^^ safe to call this function even if cuda is not available







class      lowercase			:

		"""simple docstring"""

		def __init__(	self					,     UpperCamelCase_					,     UpperCamelCase_ = 0.9999					,     UpperCamelCase_ = 0.0					,     UpperCamelCase_ = 0					,     UpperCamelCase_ = False					,     UpperCamelCase_ = 1.0					,     UpperCamelCase_ = 2 / 3					,     UpperCamelCase_ = None					,     UpperCamelCase_ = None					,     **UpperCamelCase_					,     ):

							'''simple docstring'''


							if isinstance(UpperCamelCase_					,     torch.nn.Module							):
												UpperCamelCase__     :Optional[Any]							      =				(
												    '''Passing a `torch.nn.Module` to `ExponentialMovingAverage` is deprecated. '''
												    '''Please pass the parameters of the module instead.'''
												)
												deprecate(
												    '''passing a `torch.nn.Module` to `ExponentialMovingAverage`'''					,     '''1.0.0'''					,     UpperCamelCase_					,     standard_warn=UpperCamelCase_					,     )
												UpperCamelCase__     :Optional[int]							      =				parameters.parameters()

												# set use_ema_warmup to True if a torch.nn.Module is passed for backwards compatibility
												UpperCamelCase__     :str							      =				True

							if kwargs.get('''max_value'''					,     UpperCamelCase_							) is not None:
												UpperCamelCase__     :List[str]							      =				'''The `max_value` argument is deprecated. Please use `decay` instead.'''
												deprecate('''max_value'''					,     '''1.0.0'''					,     UpperCamelCase_					,     standard_warn=UpperCamelCase_							)
												UpperCamelCase__     :int							      =				kwargs['''max_value''']

							if kwargs.get('''min_value'''					,     UpperCamelCase_							) is not None:
												UpperCamelCase__     :Union[str, Any]							      =				'''The `min_value` argument is deprecated. Please use `min_decay` instead.'''
												deprecate('''min_value'''					,     '''1.0.0'''					,     UpperCamelCase_					,     standard_warn=UpperCamelCase_							)
												UpperCamelCase__     :Any							      =				kwargs['''min_value''']

							UpperCamelCase__     :Optional[int]							      =				list(UpperCamelCase_							)
							UpperCamelCase__     :Tuple							      =				[p.clone().detach() for p in parameters]

							if kwargs.get('''device'''					,     UpperCamelCase_							) is not None:
												UpperCamelCase__     :str							      =				'''The `device` argument is deprecated. Please use `to` instead.'''
												deprecate('''device'''					,     '''1.0.0'''					,     UpperCamelCase_					,     standard_warn=UpperCamelCase_							)
												self.to(device=kwargs['''device''']							)

							UpperCamelCase__     :Union[str, Any]							      =				None

							UpperCamelCase__     :List[Any]							      =				decay
							UpperCamelCase__     :List[str]							      =				min_decay
							UpperCamelCase__     :Optional[int]							      =				update_after_step
							UpperCamelCase__     :int							      =				use_ema_warmup
							UpperCamelCase__     :Any							      =				inv_gamma
							UpperCamelCase__     :Union[str, Any]							      =				power
							UpperCamelCase__     :Union[str, Any]							      =				0
							UpperCamelCase__     :Dict							      =				None  # set in `step()`

							UpperCamelCase__     :List[Any]							      =				model_cls
							UpperCamelCase__     :Optional[Any]							      =				model_config




		@classmethod
		def 					lowerCAmelCase__       (	cls					,     UpperCamelCase_					,     UpperCamelCase_							):

							'''simple docstring'''


							UpperCamelCase__      ,       UpperCamelCase__     :Tuple							      =				model_cls.load_config(UpperCamelCase_					,     return_unused_kwargs=UpperCamelCase_							)
							UpperCamelCase__     :List[str]							      =				model_cls.from_pretrained(UpperCamelCase_							)

							UpperCamelCase__     :str							      =				cls(model.parameters()					,     model_cls=UpperCamelCase_					,     model_config=model.config							)

							ema_model.load_state_dict(UpperCamelCase_							)
							return ema_model




		def 					lowerCAmelCase__       (	self					,     UpperCamelCase_							):

							'''simple docstring'''


							if self.model_cls is None:
												raise ValueError('''`save_pretrained` can only be used if `model_cls` was defined at __init__.'''							)

							if self.model_config is None:
												raise ValueError('''`save_pretrained` can only be used if `model_config` was defined at __init__.'''							)

							UpperCamelCase__     :Optional[Any]							      =				self.model_cls.from_config(self.model_config							)
							UpperCamelCase__     :Optional[int]							      =				self.state_dict()
							state_dict.pop('''shadow_params'''					,     UpperCamelCase_							)

							model.register_to_config(**UpperCamelCase_							)
							self.copy_to(model.parameters()							)
							model.save_pretrained(UpperCamelCase_							)




		def 					lowerCAmelCase__       (	self					,     UpperCamelCase_							):

							'''simple docstring'''


							UpperCamelCase__     :str							      =				max(0					,     optimization_step - self.update_after_step - 1							)

							if step <= 0:
												return 0.0

							if self.use_ema_warmup:
												UpperCamelCase__     :Dict							      =				1 - (1 + step / self.inv_gamma) ** -self.power
							else:
												UpperCamelCase__     :int							      =				(1 + step) / (10 + step)

							UpperCamelCase__     :Any							      =				min(UpperCamelCase_					,     self.decay							)
							# make sure decay is not smaller than min_decay
							UpperCamelCase__     :Dict							      =				max(UpperCamelCase_					,     self.min_decay							)
							return cur_decay_value




		@torch.no_grad()
		def 					lowerCAmelCase__       (	self					,     UpperCamelCase_							):

							'''simple docstring'''


							if isinstance(UpperCamelCase_					,     torch.nn.Module							):
												UpperCamelCase__     :Optional[Any]							      =				(
												    '''Passing a `torch.nn.Module` to `ExponentialMovingAverage.step` is deprecated. '''
												    '''Please pass the parameters of the module instead.'''
												)
												deprecate(
												    '''passing a `torch.nn.Module` to `ExponentialMovingAverage.step`'''					,     '''1.0.0'''					,     UpperCamelCase_					,     standard_warn=UpperCamelCase_					,     )
												UpperCamelCase__     :str							      =				parameters.parameters()

							UpperCamelCase__     :Dict							      =				list(UpperCamelCase_							)

							self.optimization_step += 1

							# Compute the decay factor for the exponential moving average.
							UpperCamelCase__     :Any							      =				self.get_decay(self.optimization_step							)
							UpperCamelCase__     :Tuple							      =				decay
							UpperCamelCase__     :List[Any]							      =				1 - decay

							UpperCamelCase__     :Optional[Any]							      =				contextlib.nullcontext
							if is_transformers_available() and transformers.deepspeed.is_deepspeed_zeroa_enabled():
												import deepspeed

							for s_param, param in zip(self.shadow_params					,     UpperCamelCase_							):
												if is_transformers_available() and transformers.deepspeed.is_deepspeed_zeroa_enabled():
																	UpperCamelCase__     :Dict							      =				deepspeed.zero.GatheredParameters(UpperCamelCase_					,     modifier_rank=UpperCamelCase_							)

												with context_manager():
																	if param.requires_grad:
																						s_param.sub_(one_minus_decay * (s_param - param)							)
																	else:
																						s_param.copy_(UpperCamelCase_							)




		def 					lowerCAmelCase__       (	self					,     UpperCamelCase_							):

							'''simple docstring'''


							UpperCamelCase__     :Tuple							      =				list(UpperCamelCase_							)
							for s_param, param in zip(self.shadow_params					,     UpperCamelCase_							):
												param.data.copy_(s_param.to(param.device							).data							)




		def 					lowerCAmelCase__       (	self					,     UpperCamelCase_=None					,     UpperCamelCase_=None							):

							'''simple docstring'''


							UpperCamelCase__     :Tuple							      =				[
							    p.to(device=UpperCamelCase_					,     dtype=UpperCamelCase_							) if p.is_floating_point() else p.to(device=UpperCamelCase_							)
							    for p in self.shadow_params
							]




		def 					lowerCAmelCase__       (	self							):

							'''simple docstring'''


							return {
							    "decay": self.decay,
							    "min_decay": self.min_decay,
							    "optimization_step": self.optimization_step,
							    "update_after_step": self.update_after_step,
							    "use_ema_warmup": self.use_ema_warmup,
							    "inv_gamma": self.inv_gamma,
							    "power": self.power,
							    "shadow_params": self.shadow_params,
							}




		def 					lowerCAmelCase__       (	self					,     UpperCamelCase_							):

							'''simple docstring'''


							UpperCamelCase__     :List[str]							      =				[param.detach().cpu().clone() for param in parameters]




		def 					lowerCAmelCase__       (	self					,     UpperCamelCase_							):

							'''simple docstring'''


							if self.temp_stored_params is None:
												raise RuntimeError('''This ExponentialMovingAverage has no `store()`ed weights ''' '''to `restore()`'''							)
							for c_param, param in zip(self.temp_stored_params					,     UpperCamelCase_							):
												param.data.copy_(c_param.data							)

							# Better memory-wise.
							UpperCamelCase__     :Optional[Any]							      =				None




		def 					lowerCAmelCase__       (	self					,     UpperCamelCase_							):

							'''simple docstring'''


							UpperCamelCase__     :int							      =				copy.deepcopy(UpperCamelCase_							)

							UpperCamelCase__     :Dict							      =				state_dict.get('''decay'''					,     self.decay							)
							if self.decay < 0.0 or self.decay > 1.0:
												raise ValueError('''Decay must be between 0 and 1'''							)

							UpperCamelCase__     :Union[str, Any]							      =				state_dict.get('''min_decay'''					,     self.min_decay							)
							if not isinstance(self.min_decay					,     UpperCamelCase_							):
												raise ValueError('''Invalid min_decay'''							)

							UpperCamelCase__     :Union[str, Any]							      =				state_dict.get('''optimization_step'''					,     self.optimization_step							)
							if not isinstance(self.optimization_step					,     UpperCamelCase_							):
												raise ValueError('''Invalid optimization_step'''							)

							UpperCamelCase__     :List[Any]							      =				state_dict.get('''update_after_step'''					,     self.update_after_step							)
							if not isinstance(self.update_after_step					,     UpperCamelCase_							):
												raise ValueError('''Invalid update_after_step'''							)

							UpperCamelCase__     :List[str]							      =				state_dict.get('''use_ema_warmup'''					,     self.use_ema_warmup							)
							if not isinstance(self.use_ema_warmup					,     UpperCamelCase_							):
												raise ValueError('''Invalid use_ema_warmup'''							)

							UpperCamelCase__     :Optional[int]							      =				state_dict.get('''inv_gamma'''					,     self.inv_gamma							)
							if not isinstance(self.inv_gamma					,     (float, int)							):
												raise ValueError('''Invalid inv_gamma'''							)

							UpperCamelCase__     :str							      =				state_dict.get('''power'''					,     self.power							)
							if not isinstance(self.power					,     (float, int)							):
												raise ValueError('''Invalid power'''							)

							UpperCamelCase__     :Tuple							      =				state_dict.get('''shadow_params'''					,     UpperCamelCase_							)
							if shadow_params is not None:
												UpperCamelCase__     :Dict							      =				shadow_params
												if not isinstance(self.shadow_params					,     UpperCamelCase_							):
																	raise ValueError('''shadow_params must be a list'''							)
												if not all(isinstance(UpperCamelCase_					,     torch.Tensor							) for p in self.shadow_params							):
																	raise ValueError('''shadow_params must all be Tensors'''							)