
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():
		lowercase   =	get_tests_dir('''fixtures/test_sentencepiece.model''')


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

lowercase   =	1_2_8_0_2_2
lowercase   =	1_2_8_0_2_8





@require_sentencepiece
class    __A(					UpperCAmelCase  ,		unittest.TestCase							):
					SCREAMING_SNAKE_CASE           =     MaMaaaTokenizer
					SCREAMING_SNAKE_CASE           =     False
					SCREAMING_SNAKE_CASE           =     False
					SCREAMING_SNAKE_CASE           =     True

					def  lowercase__   (						self       :  int ):
												super().setUp()

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

												lowerCamelCase_					=       MaMaaaTokenizer.from_pretrained(self.tmpdirname )
												tokenizer.save_pretrained(self.tmpdirname )

					def  lowercase__   (						self       :  List[str] ,       **__UpperCamelCase       :  Optional[int] ):
												return MaMaaaTokenizer.from_pretrained(self.tmpdirname ,       **__UpperCamelCase )

					def  lowercase__   (						self       :  Optional[int] ,       __UpperCamelCase       :  Optional[int] ):
												return (
												    "This is a test",
												    "This is a test",
												)

					def  lowercase__   (						self       :  int ):
												lowerCamelCase_					=       """</s>"""
												lowerCamelCase_					=       0

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

					def  lowercase__   (						self       :  str ):
												lowerCamelCase_					=       self.get_tokenizer()
												lowerCamelCase_					=       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(__UpperCamelCase ) ,       tokenizer.vocab_size + len(tokenizer.get_added_vocab() ) )

					@unittest.skip("""Skip this test while all models are still to be uploaded.""" )
					def  lowercase__   (						self       :  Union[str, Any] ):
												pass

					def  lowercase__   (						self       :  str ):
												lowerCamelCase_					=       self.get_tokenizer()

												lowerCamelCase_					=       tokenizer.tokenize("""This is a test""" )
												self.assertListEqual(__UpperCamelCase ,       ["""▁This""", """▁is""", """▁a""", """▁t""", """est"""] )

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

												lowerCamelCase_					=       tokenizer.convert_ids_to_tokens([2, 3, 4, 5, 6] )
												self.assertListEqual(__UpperCamelCase ,       ["""▁This""", """▁is""", """▁a""", """▁t""", """est"""] )

												lowerCamelCase_					=       tokenizer.convert_tokens_to_string(__UpperCamelCase )
												self.assertEqual(__UpperCamelCase ,       """This is a test""" )



					@slow
					def  lowercase__   (						self       :  Optional[Any] ):
												# fmt: off
												lowerCamelCase_					=       {"""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=__UpperCamelCase ,       model_name="""facebook/m2m100_418M""" ,       revision="""c168bae485c864188cf9aa0e4108b0b6934dc91e""" ,       )





@require_torch
@require_sentencepiece
@require_tokenizers
class    __A(					unittest.TestCase							):
					SCREAMING_SNAKE_CASE           =     '''facebook/m2m100_418M'''
					SCREAMING_SNAKE_CASE           =     [
					    '''In my opinion, there are two levels of response from the French government.''',
					    '''NSA Affair Emphasizes Complete Lack of Debate on Intelligence''',
					]
					SCREAMING_SNAKE_CASE           =     [
					    '''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
					SCREAMING_SNAKE_CASE           =     [EN_CODE, 5_9_3, 1_9_4_9, 1_1_5_7_8_1, 4, 7_1_5_8_6, 4_2_3_4, 6_0_6_3_3, 1_2_6_2_3_3, 4_3_2, 1_2_3_8_0_8, 1_5_5_9_2, 1_1_9_7, 1_1_7_1_3_2, 1_2_0_6_1_8, 5, 2]

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

					def  lowercase__   (						self       :  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  lowercase__   (						self       :  int ):
												lowerCamelCase_					=       self.tokenizer.get_vocab()
												self.assertEqual(len(__UpperCamelCase ) ,       self.tokenizer.vocab_size )
												self.assertEqual(vocab["""<unk>"""] ,       3 )
												self.assertIn(self.tokenizer.get_lang_token("""en""" ) ,       __UpperCamelCase )

					def  lowercase__   (						self       :  Union[str, Any] ):
												lowerCamelCase_					=       """en"""
												lowerCamelCase_					=       self.tokenizer.batch_encode_plus(self.src_text ).input_ids[0]
												self.assertListEqual(self.expected_src_tokens ,       __UpperCamelCase )

					def  lowercase__   (						self       :  Optional[int] ):
												self.assertIn(__UpperCamelCase ,       self.tokenizer.all_special_ids )
												# fmt: off
												lowerCamelCase_					=       [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_					=       self.tokenizer.decode(__UpperCamelCase ,       skip_special_tokens=__UpperCamelCase )
												lowerCamelCase_					=       self.tokenizer.decode(generated_ids[1:] ,       skip_special_tokens=__UpperCamelCase )
												self.assertEqual(__UpperCamelCase ,       __UpperCamelCase )
												self.assertNotIn(self.tokenizer.eos_token ,       __UpperCamelCase )

					def  lowercase__   (						self       :  Any ):
												lowerCamelCase_					=       tempfile.mkdtemp()
												lowerCamelCase_					=       self.tokenizer.lang_token_to_id
												self.tokenizer.save_pretrained(__UpperCamelCase )
												lowerCamelCase_					=       MaMaaaTokenizer.from_pretrained(__UpperCamelCase )
												self.assertDictEqual(new_tok.lang_token_to_id ,       __UpperCamelCase )

					@require_torch
					def  lowercase__   (						self       :  List[str] ):
												lowerCamelCase_					=       """en"""
												lowerCamelCase_					=       """fr"""

												lowerCamelCase_					=       self.tokenizer(self.src_text ,       text_target=self.tgt_text ,       padding=__UpperCamelCase ,       return_tensors="""pt""" )

												lowerCamelCase_					=       shift_tokens_right(
												    batch["""labels"""] ,       self.tokenizer.pad_token_id ,       self.tokenizer.eos_token_id )

												for k in batch:
																			lowerCamelCase_					=       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  lowercase__   (						self       :  Optional[Any] ):
												lowerCamelCase_					=       """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_					=       """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  lowercase__   (						self       :  Union[str, Any] ):
												lowerCamelCase_					=       """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_					=       """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  lowercase__   (						self       :  Any ):
												lowerCamelCase_					=       self.tokenizer._build_translation_inputs("""A test""" ,       return_tensors="""pt""" ,       src_lang="""en""" ,       tgt_lang="""ar""" )

												self.assertEqual(
												    nested_simplify(__UpperCamelCase ) ,       {
												        # 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,
												    } ,       )







from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_torch_available,
    is_vision_available,
)


lowercase   =	{
    '''configuration_blip''': [
        '''BLIP_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''BlipConfig''',
        '''BlipTextConfig''',
        '''BlipVisionConfig''',
    ],
    '''processing_blip''': ['''BlipProcessor'''],
}

try:
		if not is_vision_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowercase   =	['''BlipImageProcessor''']


try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowercase   =	[
		    '''BLIP_PRETRAINED_MODEL_ARCHIVE_LIST''',
		    '''BlipModel''',
		    '''BlipPreTrainedModel''',
		    '''BlipForConditionalGeneration''',
		    '''BlipForQuestionAnswering''',
		    '''BlipVisionModel''',
		    '''BlipTextModel''',
		    '''BlipForImageTextRetrieval''',
		]

try:
		if not is_tf_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowercase   =	[
		    '''TF_BLIP_PRETRAINED_MODEL_ARCHIVE_LIST''',
		    '''TFBlipModel''',
		    '''TFBlipPreTrainedModel''',
		    '''TFBlipForConditionalGeneration''',
		    '''TFBlipForQuestionAnswering''',
		    '''TFBlipVisionModel''',
		    '''TFBlipTextModel''',
		    '''TFBlipForImageTextRetrieval''',
		]

if TYPE_CHECKING:
		from .configuration_blip import BLIP_PRETRAINED_CONFIG_ARCHIVE_MAP, BlipConfig, BlipTextConfig, BlipVisionConfig
		from .processing_blip import BlipProcessor

		try:
				if not is_vision_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .image_processing_blip import BlipImageProcessor

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_blip import (
				    BLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
				    BlipForConditionalGeneration,
				    BlipForImageTextRetrieval,
				    BlipForQuestionAnswering,
				    BlipModel,
				    BlipPreTrainedModel,
				    BlipTextModel,
				    BlipVisionModel,
				)

		try:
				if not is_tf_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_tf_blip import (
				    TF_BLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
				    TFBlipForConditionalGeneration,
				    TFBlipForImageTextRetrieval,
				    TFBlipForQuestionAnswering,
				    TFBlipModel,
				    TFBlipPreTrainedModel,
				    TFBlipTextModel,
				    TFBlipVisionModel,
				)

else:
		import sys

		lowercase   =	_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)





