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


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

lowerCamelCase__  =					12_8022
lowerCamelCase__  =					12_8028




@require_sentencepiece
class 					_UpperCAmelCase			(     __SCREAMING_SNAKE_CASE,			unittest.TestCase  ):



 '''simple docstring'''




 __A			       =					MaMaaaTokenizer
 __A			       =					False
 __A			       =					False
 __A			       =					True







 def 		__UpperCAmelCase				(		self				:   Dict)						->	Optional[Any]:


   """simple docstring"""







   super().setUp()

   _UpperCamelCase           =    ['''</s>''', '''<unk>''', '''▁This''', '''▁is''', '''▁a''', '''▁t''', '''est''', '''\u0120''', '''<pad>''']
   _UpperCamelCase           =    dict(zip(UpperCamelCase__							, range(len(UpperCamelCase__))))
   _UpperCamelCase           =    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"])

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







 def 		__UpperCAmelCase				(		self				:   Dict							, **lowercase_				:   Optional[int])						->	Any:


   """simple docstring"""







   return MaMaaaTokenizer.from_pretrained(self.tmpdirname							, **UpperCamelCase__)







 def 		__UpperCAmelCase				(		self				:   Tuple							, lowercase_				:   Tuple)						->	str:


   """simple docstring"""







   return (
       "This is a test",
       "This is a test",
   )







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


   """simple docstring"""







   _UpperCamelCase           =    '''</s>'''
   _UpperCamelCase           =    0

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







 def 		__UpperCAmelCase				(		self				:   Dict)						->	int:


   """simple docstring"""







   _UpperCamelCase           =    self.get_tokenizer()
   _UpperCamelCase           =    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 		__UpperCAmelCase				(		self				:   str)						->	List[str]:


   """simple docstring"""







   pass







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


   """simple docstring"""







   _UpperCamelCase           =    self.get_tokenizer()

   _UpperCamelCase           =    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]							, )

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

   _UpperCamelCase           =    tokenizer.convert_tokens_to_string(UpperCamelCase__)
   self.assertEqual(UpperCamelCase__							, "This is a test")







 @slow
 def 		__UpperCAmelCase				(		self				:   Union[str, Any])						->	List[Any]:


   """simple docstring"""







   _UpperCamelCase           =    {'''input_ids''': [[128022, 110108, 397, 11, 38272, 2247, 124811, 285, 18105, 1586, 207, 7, 39534, 4428, 397, 1019, 18105, 1586, 207, 7, 41337, 16786, 241, 7, 20214, 17, 125690, 10398, 7, 44378, 58069, 68342, 7798, 7343, 11, 299, 33310, 4, 158, 37350, 94077, 4569, 299, 33310, 90, 4, 52840, 290, 4, 31270, 112, 299, 682, 4, 52840, 39953, 14079, 193, 52519, 90894, 17894, 120697, 11, 40445, 551, 17, 1019, 52519, 90894, 17756, 963, 11, 40445, 480, 17, 9792, 1120, 5173, 1393, 6240, 16786, 241, 120996, 28, 1245, 1393, 118240, 11123, 1019, 93612, 2691, 10618, 98058, 120409, 1928, 279, 4, 40683, 367, 178, 207, 1019, 103, 103121, 506, 65296, 5, 2], [128022, 21217, 367, 117, 125450, 128, 719, 7, 7308, 40, 93612, 12669, 1116, 16704, 71, 17785, 3699, 15592, 35, 144, 9584, 241, 11943, 713, 950, 799, 2247, 88427, 150, 149, 118813, 120706, 1019, 106906, 81518, 28, 1224, 22799, 397, 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], [128022, 1658, 123311, 5155, 5578, 4722, 279, 14947, 2366, 1120, 1197, 14, 1348, 9232, 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 					_UpperCAmelCase			(     unittest.TestCase  ):



 '''simple docstring'''




 __A			       =					'''facebook/m2m100_418M'''
 __A			       =					[
     '''In my opinion, there are two levels of response from the French government.''',
     '''NSA Affair Emphasizes Complete Lack of Debate on Intelligence''',
 ]
 __A			       =					[
     '''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
 __A			       =					[EN_CODE, 593, 1_949, 115_781, 4, 71_586, 4_234, 60_633, 126_233, 432, 123_808, 15_592, 1_197, 117_132, 120_618, 5, 2]







 @classmethod
 def 		__UpperCAmelCase				(		cls				:   List[Any])						->	int:


   """simple docstring"""







   _UpperCamelCase           =    MaMaaaTokenizer.from_pretrained(
       cls.checkpoint_name							, src_lang="en"							, tgt_lang="fr")
   _UpperCamelCase           =    1
   return cls







 def 		__UpperCAmelCase				(		self				:   Union[str, Any])						->	str:


   """simple docstring"""







   self.assertEqual(self.tokenizer.get_lang_id("ar")							, 128006)
   self.assertEqual(self.tokenizer.get_lang_id("en")							, 128022)
   self.assertEqual(self.tokenizer.get_lang_id("ro")							, 128076)
   self.assertEqual(self.tokenizer.get_lang_id("mr")							, 128063)







 def 		__UpperCAmelCase				(		self				:   Any)						->	Dict:


   """simple docstring"""







   _UpperCamelCase           =    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 		__UpperCAmelCase				(		self				:   Optional[Any])						->	List[Any]:


   """simple docstring"""







   _UpperCamelCase           =    '''en'''
   _UpperCamelCase           =    self.tokenizer.batch_encode_plus(self.src_text).input_ids[0]
   self.assertListEqual(self.expected_src_tokens							, UpperCamelCase__)







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


   """simple docstring"""







   self.assertIn(UpperCamelCase__							, self.tokenizer.all_special_ids)
   # fmt: off
   _UpperCamelCase           =    [FR_CODE, 5364, 82, 8642, 4, 294, 47, 8, 14028, 136, 3286, 9706, 6, 90797, 6, 144012, 162, 88128, 30061, 5, 2]
   # fmt: on
   _UpperCamelCase           =    self.tokenizer.decode(UpperCamelCase__							, skip_special_tokens=UpperCamelCase__)
   _UpperCamelCase           =    self.tokenizer.decode(generated_ids[1:]							, skip_special_tokens=UpperCamelCase__)
   self.assertEqual(UpperCamelCase__							, UpperCamelCase__)
   self.assertNotIn(self.tokenizer.eos_token							, UpperCamelCase__)







 def 		__UpperCAmelCase				(		self				:   Optional[int])						->	Tuple:


   """simple docstring"""







   _UpperCamelCase           =    tempfile.mkdtemp()
   _UpperCamelCase           =    self.tokenizer.lang_token_to_id
   self.tokenizer.save_pretrained(UpperCamelCase__)
   _UpperCamelCase           =    MaMaaaTokenizer.from_pretrained(UpperCamelCase__)
   self.assertDictEqual(new_tok.lang_token_to_id							, UpperCamelCase__)







 @require_torch
 def 		__UpperCAmelCase				(		self				:   Optional[Any])						->	Union[str, Any]:


   """simple docstring"""







   _UpperCamelCase           =    '''en'''
   _UpperCamelCase           =    '''fr'''

   _UpperCamelCase           =    self.tokenizer(self.src_text							, text_target=self.tgt_text							, padding=UpperCamelCase__							, return_tensors="pt")

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

   for k in batch:
     _UpperCamelCase           =    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 		__UpperCAmelCase				(		self				:   int)						->	Union[str, Any]:


   """simple docstring"""







   _UpperCamelCase           =    '''mr'''
   self.assertListEqual(self.tokenizer.prefix_tokens							, [self.tokenizer.get_lang_id("mr")])
   self.assertListEqual(self.tokenizer.suffix_tokens							, [self.tokenizer.eos_token_id])

   _UpperCamelCase           =    '''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 		__UpperCAmelCase				(		self				:   Union[str, Any])						->	Dict:


   """simple docstring"""







   _UpperCamelCase           =    '''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)])

   _UpperCamelCase           =    '''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 		__UpperCAmelCase				(		self				:   Tuple)						->	str:


   """simple docstring"""







   _UpperCamelCase           =    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": [[128022, 58, 4183, 2]],
           "attention_mask": [[1, 1, 1, 1]],
           # ar_AR
           "forced_bos_token_id": 128006,
       }							, )






'''simple docstring'''
from __future__ import annotations

import unittest

from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow


if is_tf_available():
						import numpy as np
						import tensorflow as tf

						from transformers import TFCamembertModel






@require_tf
@require_sentencepiece
@require_tokenizers
class 	snake_case__       (      unittest.TestCase					):







		"""simple docstring"""

		@slow
		def       lowerCAmelCase				(      self				:			Optional[Any]      )						->			Optional[Any]:






				"""simple docstring"""







				snake_case  :       Any     			=						TFCamembertModel.from_pretrained('''jplu/tf-camembert-base'''      )

				snake_case  :       List[Any]     			=						tf.convert_to_tensor(
				    [[5, 121, 11, 660, 16, 730, 2_5543, 110, 83, 6]]  ,	dtype=tf.intaa  ,	)  # J'aime le camembert !"

				snake_case  :       Any     			=						model(UpperCamelCase__      )['''last_hidden_state''']
				snake_case  :       int     			=						tf.TensorShape((1, 10, 768)      )
				self.assertEqual(output.shape  ,	UpperCamelCase__      )
				# compare the actual values for a slice.
				snake_case  :       Dict     			=						tf.convert_to_tensor(
				    [[[-0.0_254, 0.0_235, 0.1_027], [0.0_606, -0.1_811, -0.0_418], [-0.1_561, -0.1_127, 0.2_687]]]  ,	dtype=tf.floataa  ,	)
				# camembert = torch.hub.load('pytorch/fairseq', 'camembert.v0')
				# camembert.eval()
				# expected_slice = roberta.model.forward(input_ids)[0][:, :3, :3].detach()

				self.assertTrue(np.allclose(output[:, :3, :3].numpy()  ,	expected_slice.numpy()  ,	atol=1e-4      )      )


