

"""simple docstring"""





import tempfile
import unittest
from pathlib import Path
from shutil import copyfile

from transformers import MaMaaaTokenizer, is_torch_available
from transformers.testing_utils import (
    get_tests_dir,
    nested_simplify,
    require_sentencepiece,
    require_tokenizers,
    require_torch,
    slow,
)
from transformers.utils import is_sentencepiece_available


if is_sentencepiece_available():
							from transformers.models.mam_aaa.tokenization_mam_aaa import VOCAB_FILES_NAMES, save_json

from ...test_tokenization_common import TokenizerTesterMixin


if is_sentencepiece_available():
							__UpperCamelCase    : List[str]				 =						get_tests_dir('''fixtures/test_sentencepiece.model''')


if is_torch_available():
							from transformers.models.mam_aaa.modeling_mam_aaa import shift_tokens_right

__UpperCamelCase    : Tuple				 =						1_2_8_0_2_2
__UpperCamelCase    : List[str]				 =						1_2_8_0_2_8







@require_sentencepiece
class 							SCREAMING_SNAKE_CASE   (						a_       ,				unittest.TestCase			):






					"""simple docstring"""



					lowercase__												=			MaMaaaTokenizer
					lowercase__												=			False
					lowercase__												=			False
					lowercase__												=			True







					def 			__lowerCAmelCase					(			self     :							List[str]						):
						super().setUp()

						lowerCAmelCase__      :		Optional[int]    							=      ['''</s>''', '''<unk>''', '''▁This''', '''▁is''', '''▁a''', '''▁t''', '''est''', '''\u0120''', '''<pad>''']
						lowerCAmelCase__      :		List[str]    							=      dict(zip(lowercase_  ,range(len(lowercase_						)						)						)						)
						lowerCAmelCase__      :		str    							=      Path(self.tmpdirname						)
						save_json(lowercase_  ,save_dir / VOCAB_FILES_NAMES['''vocab_file''']						)
						if not (save_dir / VOCAB_FILES_NAMES["spm_file"]).exists():
							copyfile(lowercase_  ,save_dir / VOCAB_FILES_NAMES['''spm_file''']						)

						lowerCAmelCase__      :		Optional[int]    							=      MaMaaaTokenizer.from_pretrained(self.tmpdirname						)
						tokenizer.save_pretrained(self.tmpdirname						)







					def 			__lowerCAmelCase					(			self     :							Tuple  ,**lowercase_     :							Any						):
						return MaMaaaTokenizer.from_pretrained(self.tmpdirname  ,**lowercase_						)







					def 			__lowerCAmelCase					(			self     :							List[str]  ,lowercase_     :							List[Any]						):
						return (
						    "This is a test",
						    "This is a test",
						)







					def 			__lowerCAmelCase					(			self     :							Tuple						):
						lowerCAmelCase__      :		List[str]    							=      '''</s>'''
						lowerCAmelCase__      :		List[Any]    							=      0

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







					def 			__lowerCAmelCase					(			self     :							Union[str, Any]						):
						lowerCAmelCase__      :		Optional[int]    							=      self.get_tokenizer()
						lowerCAmelCase__      :		List[Any]    							=      list(tokenizer.get_vocab().keys()						)

						self.assertEqual(vocab_keys[0]  ,'''</s>'''						)
						self.assertEqual(vocab_keys[1]  ,'''<unk>'''						)
						self.assertEqual(vocab_keys[-1]  ,'''<s>'''						)
						self.assertEqual(len(lowercase_						)  ,tokenizer.vocab_size + len(tokenizer.get_added_vocab()						)						)







					@unittest.skip('''Skip this test while all models are still to be uploaded.'''						)
					def 			__lowerCAmelCase					(			self     :							Tuple						):
						pass







					def 			__lowerCAmelCase					(			self     :							str						):
						lowerCAmelCase__      :		Any    							=      self.get_tokenizer()

						lowerCAmelCase__      :		Union[str, Any]    							=      tokenizer.tokenize('''This is a test'''						)
						self.assertListEqual(lowercase_  ,['''▁This''', '''▁is''', '''▁a''', '''▁t''', '''est''']						)

						self.assertListEqual(
						    tokenizer.convert_tokens_to_ids(lowercase_						)  ,[2, 3, 4, 5, 6]  ,)

						lowerCAmelCase__      :		Any    							=      tokenizer.convert_ids_to_tokens([2, 3, 4, 5, 6]						)
						self.assertListEqual(lowercase_  ,['''▁This''', '''▁is''', '''▁a''', '''▁t''', '''est''']						)

						lowerCAmelCase__      :		List[Any]    							=      tokenizer.convert_tokens_to_string(lowercase_						)
						self.assertEqual(lowercase_  ,'''This is a test'''						)







					@slow
					def 			__lowerCAmelCase					(			self     :							Dict						):
						# fmt: off
						lowerCAmelCase__      :		int    							=      {'''input_ids''': [[1_2_8_0_2_2, 1_1_0_1_0_8, 3_9_7, 1_1, 3_8_2_7_2, 2_2_4_7, 1_2_4_8_1_1, 2_8_5, 1_8_1_0_5, 1_5_8_6, 2_0_7, 7, 3_9_5_3_4, 4_4_2_8, 3_9_7, 1_0_1_9, 1_8_1_0_5, 1_5_8_6, 2_0_7, 7, 4_1_3_3_7, 1_6_7_8_6, 2_4_1, 7, 2_0_2_1_4, 1_7, 1_2_5_6_9_0, 1_0_3_9_8, 7, 4_4_3_7_8, 5_8_0_6_9, 6_8_3_4_2, 7_7_9_8, 7_3_4_3, 1_1, 2_9_9, 3_3_3_1_0, 4, 1_5_8, 3_7_3_5_0, 9_4_0_7_7, 4_5_6_9, 2_9_9, 3_3_3_1_0, 9_0, 4, 5_2_8_4_0, 2_9_0, 4, 3_1_2_7_0, 1_1_2, 2_9_9, 6_8_2, 4, 5_2_8_4_0, 3_9_9_5_3, 1_4_0_7_9, 1_9_3, 5_2_5_1_9, 9_0_8_9_4, 1_7_8_9_4, 1_2_0_6_9_7, 1_1, 4_0_4_4_5, 5_5_1, 1_7, 1_0_1_9, 5_2_5_1_9, 9_0_8_9_4, 1_7_7_5_6, 9_6_3, 1_1, 4_0_4_4_5, 4_8_0, 1_7, 9_7_9_2, 1_1_2_0, 5_1_7_3, 1_3_9_3, 6_2_4_0, 1_6_7_8_6, 2_4_1, 1_2_0_9_9_6, 2_8, 1_2_4_5, 1_3_9_3, 1_1_8_2_4_0, 1_1_1_2_3, 1_0_1_9, 9_3_6_1_2, 2_6_9_1, 1_0_6_1_8, 9_8_0_5_8, 1_2_0_4_0_9, 1_9_2_8, 2_7_9, 4, 4_0_6_8_3, 3_6_7, 1_7_8, 2_0_7, 1_0_1_9, 1_0_3, 1_0_3_1_2_1, 5_0_6, 6_5_2_9_6, 5, 2], [1_2_8_0_2_2, 2_1_2_1_7, 3_6_7, 1_1_7, 1_2_5_4_5_0, 1_2_8, 7_1_9, 7, 7_3_0_8, 4_0, 9_3_6_1_2, 1_2_6_6_9, 1_1_1_6, 1_6_7_0_4, 7_1, 1_7_7_8_5, 3_6_9_9, 1_5_5_9_2, 3_5, 1_4_4, 9_5_8_4, 2_4_1, 1_1_9_4_3, 7_1_3, 9_5_0, 7_9_9, 2_2_4_7, 8_8_4_2_7, 1_5_0, 1_4_9, 1_1_8_8_1_3, 1_2_0_7_0_6, 1_0_1_9, 1_0_6_9_0_6, 8_1_5_1_8, 2_8, 1_2_2_4, 2_2_7_9_9, 3_9_7, 5, 2, 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_2_8_0_2_2, 1_6_5_8, 1_2_3_3_1_1, 5_1_5_5, 5_5_7_8, 4_7_2_2, 2_7_9, 1_4_9_4_7, 2_3_6_6, 1_1_2_0, 1_1_9_7, 1_4, 1_3_4_8, 9_2_3_2, 5, 2, 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]], '''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, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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=lowercase_  ,model_name='''facebook/m2m100_418M'''  ,revision='''c168bae485c864188cf9aa0e4108b0b6934dc91e'''  ,)







@require_torch
@require_sentencepiece
@require_tokenizers
class 							SCREAMING_SNAKE_CASE   (						unittest.TestCase			):






					"""simple docstring"""



					lowercase__												=			"facebook/m2m100_418M"
					lowercase__												=			[
					    "In my opinion, there are two levels of response from the French government.",
					    "NSA Affair Emphasizes Complete Lack of Debate on Intelligence",
					]
					lowercase__												=			[
					    "Selon moi, il y a deux niveaux de réponse de la part du gouvernement français.",
					    "L'affaire NSA souligne l'absence totale de débat sur le renseignement",
					]

					# fmt: off
					lowercase__												=			[EN_CODE, 593, 1949, 115781, 4, 71586, 4234, 60633, 126233, 432, 123808, 15592, 1197, 117132, 120618, 5, 2]







					@classmethod
					def 			__lowerCAmelCase					(			cls     :							Union[str, Any]						):
						lowerCAmelCase__      :		MaMaaaTokenizer    							=      MaMaaaTokenizer.from_pretrained(
						    cls.checkpoint_name  ,src_lang='''en'''  ,tgt_lang='''fr'''						)
						lowerCAmelCase__      :		Union[str, Any]    							=      1
						return cls







					def 			__lowerCAmelCase					(			self     :							Union[str, Any]						):
						self.assertEqual(self.tokenizer.get_lang_id('''ar'''						)  ,1_2_8_0_0_6						)
						self.assertEqual(self.tokenizer.get_lang_id('''en'''						)  ,1_2_8_0_2_2						)
						self.assertEqual(self.tokenizer.get_lang_id('''ro'''						)  ,1_2_8_0_7_6						)
						self.assertEqual(self.tokenizer.get_lang_id('''mr'''						)  ,1_2_8_0_6_3						)







					def 			__lowerCAmelCase					(			self     :							Union[str, Any]						):
						lowerCAmelCase__      :		Optional[int]    							=      self.tokenizer.get_vocab()
						self.assertEqual(len(lowercase_						)  ,self.tokenizer.vocab_size						)
						self.assertEqual(vocab['''<unk>''']  ,3						)
						self.assertIn(self.tokenizer.get_lang_token('''en'''						)  ,lowercase_						)







					def 			__lowerCAmelCase					(			self     :							List[str]						):
						lowerCAmelCase__      :		Dict    							=      '''en'''
						lowerCAmelCase__      :		Tuple    							=      self.tokenizer.batch_encode_plus(self.src_text						).input_ids[0]
						self.assertListEqual(self.expected_src_tokens  ,lowercase_						)







					def 			__lowerCAmelCase					(			self     :							Optional[Any]						):
						self.assertIn(lowercase_  ,self.tokenizer.all_special_ids						)
						# fmt: off
						lowerCAmelCase__      :		Optional[int]    							=      [FR_CODE, 5_3_6_4, 8_2, 8_6_4_2, 4, 2_9_4, 4_7, 8, 1_4_0_2_8, 1_3_6, 3_2_8_6, 9_7_0_6, 6, 9_0_7_9_7, 6, 1_4_4_0_1_2, 1_6_2, 8_8_1_2_8, 3_0_0_6_1, 5, 2]
						# fmt: on
						lowerCAmelCase__      :		Any    							=      self.tokenizer.decode(lowercase_  ,skip_special_tokens=lowercase_						)
						lowerCAmelCase__      :		Optional[Any]    							=      self.tokenizer.decode(generated_ids[1:]  ,skip_special_tokens=lowercase_						)
						self.assertEqual(lowercase_  ,lowercase_						)
						self.assertNotIn(self.tokenizer.eos_token  ,lowercase_						)







					def 			__lowerCAmelCase					(			self     :							List[str]						):
						lowerCAmelCase__      :		List[str]    							=      tempfile.mkdtemp()
						lowerCAmelCase__      :		Dict    							=      self.tokenizer.lang_token_to_id
						self.tokenizer.save_pretrained(lowercase_						)
						lowerCAmelCase__      :		str    							=      MaMaaaTokenizer.from_pretrained(lowercase_						)
						self.assertDictEqual(new_tok.lang_token_to_id  ,lowercase_						)







					@require_torch
					def 			__lowerCAmelCase					(			self     :							Tuple						):
						lowerCAmelCase__      :		str    							=      '''en'''
						lowerCAmelCase__      :		Optional[int]    							=      '''fr'''

						lowerCAmelCase__      :		int    							=      self.tokenizer(self.src_text  ,text_target=self.tgt_text  ,padding=lowercase_  ,return_tensors='''pt'''						)

						lowerCAmelCase__      :		List[str]    							=      shift_tokens_right(
						    batch['''labels''']  ,self.tokenizer.pad_token_id  ,self.tokenizer.eos_token_id						)

						for k in batch:
							lowerCAmelCase__      :		Tuple    							=      batch[k].tolist()
						# batch = {k: v.tolist() for k,v in batch.items()}
						# fairseq batch: https://gist.github.com/sshleifer/cba08bc2109361a74ac3760a7e30e4f4
						# batch.decoder_inputs_ids[0][0] ==
						assert batch.input_ids[1][0] == EN_CODE
						assert batch.input_ids[1][-1] == 2
						assert batch.labels[1][0] == FR_CODE
						assert batch.labels[1][-1] == 2
						assert batch.decoder_input_ids[1][:2] == [2, FR_CODE]







					@require_torch
					def 			__lowerCAmelCase					(			self     :							str						):
						lowerCAmelCase__      :		List[str]    							=      '''mr'''
						self.assertListEqual(self.tokenizer.prefix_tokens  ,[self.tokenizer.get_lang_id('''mr'''						)]						)
						self.assertListEqual(self.tokenizer.suffix_tokens  ,[self.tokenizer.eos_token_id]						)

						lowerCAmelCase__      :		Tuple    							=      '''zh'''
						self.assertListEqual(self.tokenizer.prefix_tokens  ,[self.tokenizer.get_lang_id('''zh'''						)]						)
						self.assertListEqual(self.tokenizer.suffix_tokens  ,[self.tokenizer.eos_token_id]						)







					@require_torch
					def 			__lowerCAmelCase					(			self     :							List[Any]						):
						lowerCAmelCase__      :		List[str]    							=      '''mr'''
						self.tokenizer._switch_to_target_mode()
						self.assertListEqual(self.tokenizer.prefix_tokens  ,[self.tokenizer.get_lang_id('''mr'''						)]						)
						self.assertListEqual(self.tokenizer.suffix_tokens  ,[self.tokenizer.eos_token_id]						)
						self.tokenizer._switch_to_input_mode()
						self.assertListEqual(self.tokenizer.prefix_tokens  ,[self.tokenizer.get_lang_id(self.tokenizer.src_lang						)]						)

						lowerCAmelCase__      :		Dict    							=      '''zh'''
						self.tokenizer._switch_to_target_mode()
						self.assertListEqual(self.tokenizer.prefix_tokens  ,[self.tokenizer.get_lang_id('''zh'''						)]						)
						self.assertListEqual(self.tokenizer.suffix_tokens  ,[self.tokenizer.eos_token_id]						)
						self.tokenizer._switch_to_input_mode()
						self.assertListEqual(self.tokenizer.prefix_tokens  ,[self.tokenizer.get_lang_id(self.tokenizer.src_lang						)]						)







					@require_torch
					def 			__lowerCAmelCase					(			self     :							int						):
						lowerCAmelCase__      :		str    							=      self.tokenizer._build_translation_inputs('''A test'''  ,return_tensors='''pt'''  ,src_lang='''en'''  ,tgt_lang='''ar'''						)

						self.assertEqual(
						    nested_simplify(lowercase_						)  ,{
						        # en_XX, A, test, EOS
						        '''input_ids''': [[1_2_8_0_2_2, 5_8, 4_1_8_3, 2]],
						        '''attention_mask''': [[1, 1, 1, 1]],
						        # ar_AR
						        '''forced_bos_token_id''': 1_2_8_0_0_6,
						    }  ,)







"""simple docstring"""





from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices


__UpperCamelCase    : Tuple				 =						logging.get_logger(__name__)

__UpperCamelCase    : Optional[int]				 =						{
    '''google/bit-50''': '''https://huggingface.co/google/bit-50/resolve/main/config.json''',
}







class 							SCREAMING_SNAKE_CASE   (						a_       ,				a_			):






					"""simple docstring"""



					lowercase__												=			"bit"
					lowercase__												=			["preactivation", "bottleneck"]
					lowercase__												=			["SAME", "VALID"]







					def __init__(			self     :							int  ,lowercase_     :							Optional[int]=3  ,lowercase_     :							int=6_4  ,lowercase_     :							Optional[int]=[2_5_6, 5_1_2, 1_0_2_4, 2_0_4_8]  ,lowercase_     :							Union[str, Any]=[3, 4, 6, 3]  ,lowercase_     :							List[Any]="preactivation"  ,lowercase_     :							Dict="relu"  ,lowercase_     :							Dict=None  ,lowercase_     :							Optional[Any]=3_2  ,lowercase_     :							Any=0.0  ,lowercase_     :							Optional[Any]=False  ,lowercase_     :							List[Any]=3_2  ,lowercase_     :							Optional[Any]=1  ,lowercase_     :							Optional[int]=None  ,lowercase_     :							int=None  ,**lowercase_     :							List[str]  ,):
						super().__init__(**lowercase_						)
						if layer_type not in self.layer_types:
							raise ValueError(F'layer_type={layer_type} is not one of {",".join(self.layer_types						)}'						)
						if global_padding is not None:
							if global_padding.upper() in self.supported_padding:
								lowerCAmelCase__      :		Optional[Any]    							=      global_padding.upper()
							else:
								raise ValueError(F'Padding strategy {global_padding} not supported'						)
						lowerCAmelCase__      :		int    							=      num_channels
						lowerCAmelCase__      :		int    							=      embedding_size
						lowerCAmelCase__      :		Any    							=      hidden_sizes
						lowerCAmelCase__      :		int    							=      depths
						lowerCAmelCase__      :		Union[str, Any]    							=      layer_type
						lowerCAmelCase__      :		Optional[int]    							=      hidden_act
						lowerCAmelCase__      :		int    							=      global_padding
						lowerCAmelCase__      :		List[Any]    							=      num_groups
						lowerCAmelCase__      :		List[Any]    							=      drop_path_rate
						lowerCAmelCase__      :		Union[str, Any]    							=      embedding_dynamic_padding
						lowerCAmelCase__      :		int    							=      output_stride
						lowerCAmelCase__      :		Optional[Any]    							=      width_factor

						lowerCAmelCase__      :		List[str]    							=      ['''stem'''] + [F'stage{idx}' for idx in range(1  ,len(lowercase_						) + 1						)]
						lowerCAmelCase__							,lowerCAmelCase__      :		Any    							=      get_aligned_output_features_output_indices(
						    out_features=lowercase_  ,out_indices=lowercase_  ,stage_names=self.stage_names						)




