

import shutil
import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartaaTokenizer, MBartaaTokenizerFast, is_torch_available
from transformers.testing_utils import (
    get_tests_dir,
    nested_simplify,
    require_sentencepiece,
    require_tokenizers,
    require_torch,
    slow,
)

from ...test_tokenization_common import TokenizerTesterMixin


snake_case_			  = get_tests_dir('''fixtures/test_sentencepiece.model''')

if is_torch_available():
       from transformers.models.mbart.modeling_mbart import shift_tokens_right

snake_case_			  = 250_004
snake_case_			  = 250_020


@require_sentencepiece
@require_tokenizers
class       SCREAMING_SNAKE_CASE__					(__snake_case		,       unittest.TestCase     ):
    __lowerCamelCase						:       Optional[int]														=     MBartaaTokenizer
    __lowerCamelCase						:       Optional[Any]														=     MBartaaTokenizerFast
    __lowerCamelCase						:       List[Any]														=     True
    __lowerCamelCase						:       Union[str, Any]														=     True





    def       snake_case_				(      self):
         super().setUp()

         # We have a SentencePiece fixture for testing
         lowercase__    :   Union[str, Any]      =       MBartaaTokenizer(a						,   src_lang='en_XX'						,   tgt_lang='ro_RO'						,   keep_accents=a)
         tokenizer.save_pretrained(self.tmpdirname)





    def       snake_case_				(      self):
         lowercase__    :   List[Any]      =       '<s>'
         lowercase__    :   List[Any]      =       0

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





    def       snake_case_				(      self):
         lowercase__    :   int      =       list(self.get_tokenizer().get_vocab().keys())

         self.assertEqual(vocab_keys[0]						,   '<s>')
         self.assertEqual(vocab_keys[1]						,   '<pad>')
         self.assertEqual(vocab_keys[-1]						,   '<mask>')
         self.assertEqual(len(a)						,   1054)





    def       snake_case_				(      self):
         self.assertEqual(self.get_tokenizer().vocab_size						,   1054)





    def       snake_case_				(      self):
         lowercase__    :   Union[str, Any]      =       MBartaaTokenizer(a						,   src_lang='en_XX'						,   tgt_lang='ro_RO'						,   keep_accents=a)

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

         self.assertListEqual(
             tokenizer.convert_tokens_to_ids(a)						,   [value + tokenizer.fairseq_offset for value in [285, 46, 10, 170, 382]]						,   )

         lowercase__    :   Optional[int]      =       tokenizer.tokenize('I was born in 92000, and this is falsé.')
         self.assertListEqual(
             a						,   [SPIECE_UNDERLINE + 'I', SPIECE_UNDERLINE + 'was', SPIECE_UNDERLINE + 'b', 'or', 'n', SPIECE_UNDERLINE + 'in', SPIECE_UNDERLINE + '', '9', '2', '0', '0', '0', ',', SPIECE_UNDERLINE + 'and', SPIECE_UNDERLINE + 'this', SPIECE_UNDERLINE + 'is', SPIECE_UNDERLINE + 'f', 'al', 's', 'é', '.']						,   )
         lowercase__    :   Dict      =       tokenizer.convert_tokens_to_ids(a)
         self.assertListEqual(
             a						,   [
                 value + tokenizer.fairseq_offset
                 for value in [8, 21, 84, 55, 24, 19, 7, 2, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 2, 4]
             ]						,   )

         lowercase__    :   Dict      =       tokenizer.convert_ids_to_tokens(a)
         self.assertListEqual(
             a						,   [SPIECE_UNDERLINE + 'I', SPIECE_UNDERLINE + 'was', SPIECE_UNDERLINE + 'b', 'or', 'n', SPIECE_UNDERLINE + 'in', SPIECE_UNDERLINE + '', '<unk>', '2', '0', '0', '0', ',', SPIECE_UNDERLINE + 'and', SPIECE_UNDERLINE + 'this', SPIECE_UNDERLINE + 'is', SPIECE_UNDERLINE + 'f', 'al', 's', '<unk>', '.']						,   )





    @slow
    def       snake_case_				(      self):
         # fmt: off
         lowercase__    :   List[Any]      =       {'input_ids': [[25_0004, 1_1062, 8_2772, 7, 15, 8_2772, 538, 5_1529, 237, 1_7198, 1290, 206, 9, 21_5175, 1314, 136, 1_7198, 1290, 206, 9, 5_6359, 42, 12_2009, 9, 1_6466, 16, 8_7344, 4537, 9, 4717, 7_8381, 6, 15_9958, 7, 15, 2_4480, 618, 4, 527, 2_2693, 5428, 4, 2777, 2_4480, 9874, 4, 4_3523, 594, 4, 803, 1_8392, 3_3189, 18, 4, 4_3523, 2_4447, 1_2399, 100, 2_4955, 8_3658, 9626, 14_4057, 15, 839, 2_2335, 16, 136, 2_4955, 8_3658, 8_3479, 15, 3_9102, 724, 16, 678, 645, 2789, 1328, 4589, 42, 12_2009, 11_5774, 23, 805, 1328, 4_6876, 7, 136, 5_3894, 1940, 4_2227, 4_1159, 1_7721, 823, 425, 4, 2_7512, 9_8722, 206, 136, 5531, 4970, 919, 1_7336, 5, 2], [25_0004, 2_0080, 618, 83, 8_2775, 47, 479, 9, 1517, 73, 5_3894, 333, 8_0581, 11_0117, 1_8811, 5256, 1295, 51, 15_2526, 297, 7986, 390, 12_4416, 538, 3_5431, 214, 98, 1_5044, 2_5737, 136, 7108, 4_3701, 23, 756, 13_5355, 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], [25_0004, 581, 6_3773, 11_9455, 6, 14_7797, 8_8203, 7, 645, 70, 21, 3285, 1_0269, 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]], '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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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=a						,   model_name='facebook/mbart-large-50'						,   revision='d3913889c59cd5c9e456b269c376325eabad57e2'						,   )





    def       snake_case_				(      self):
         if not self.test_slow_tokenizer:
              # as we don't have a slow version, we can't compare the outputs between slow and fast versions
              return

         lowercase__    :   Tuple      =       (self.rust_tokenizer_class, 'hf-internal-testing/tiny-random-mbart50', {})
         for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
              with self.subTest(f"""{tokenizer.__class__.__name__} ({pretrained_name})"""):
                   lowercase__    :   Optional[Any]      =       self.rust_tokenizer_class.from_pretrained(a						,   **a)
                   lowercase__    :   Optional[Any]      =       self.tokenizer_class.from_pretrained(a						,   **a)

                   lowercase__    :   Dict      =       tempfile.mkdtemp()

                   lowercase__    :   Union[str, Any]      =       tokenizer_r.save_pretrained(a)
                   lowercase__    :   str      =       tokenizer_p.save_pretrained(a)

                   # Checks it save with the same files + the tokenizer.json file for the fast one
                   self.assertTrue(any('tokenizer.json' in f for f in tokenizer_r_files))
                   lowercase__    :   List[Any]      =       tuple(f for f in tokenizer_r_files if 'tokenizer.json' not in f)
                   self.assertSequenceEqual(a						,   a)

                   # Checks everything loads correctly in the same way
                   lowercase__    :   Tuple      =       tokenizer_r.from_pretrained(a)
                   lowercase__    :   Any      =       tokenizer_p.from_pretrained(a)

                   # Check special tokens are set accordingly on Rust and Python
                   for key in tokenizer_pp.special_tokens_map:
                        self.assertTrue(hasattr(a						,   a))
                        # self.assertEqual(getattr(tokenizer_rp, key), getattr(tokenizer_pp, key))
                        # self.assertEqual(getattr(tokenizer_rp, key + "_id"), getattr(tokenizer_pp, key + "_id"))

                   shutil.rmtree(a)

                   # Save tokenizer rust, legacy_format=True
                   lowercase__    :   List[Any]      =       tempfile.mkdtemp()

                   lowercase__    :   Tuple      =       tokenizer_r.save_pretrained(a						,   legacy_format=a)
                   lowercase__    :   Optional[Any]      =       tokenizer_p.save_pretrained(a)

                   # Checks it save with the same files
                   self.assertSequenceEqual(a						,   a)

                   # Checks everything loads correctly in the same way
                   lowercase__    :   Dict      =       tokenizer_r.from_pretrained(a)
                   lowercase__    :   List[Any]      =       tokenizer_p.from_pretrained(a)

                   # Check special tokens are set accordingly on Rust and Python
                   for key in tokenizer_pp.special_tokens_map:
                        self.assertTrue(hasattr(a						,   a))

                   shutil.rmtree(a)

                   # Save tokenizer rust, legacy_format=False
                   lowercase__    :   Optional[Any]      =       tempfile.mkdtemp()

                   lowercase__    :   List[str]      =       tokenizer_r.save_pretrained(a						,   legacy_format=a)
                   lowercase__    :   str      =       tokenizer_p.save_pretrained(a)

                   # Checks it saved the tokenizer.json file
                   self.assertTrue(any('tokenizer.json' in f for f in tokenizer_r_files))

                   # Checks everything loads correctly in the same way
                   lowercase__    :   Optional[Any]      =       tokenizer_r.from_pretrained(a)
                   lowercase__    :   Tuple      =       tokenizer_p.from_pretrained(a)

                   # Check special tokens are set accordingly on Rust and Python
                   for key in tokenizer_pp.special_tokens_map:
                        self.assertTrue(hasattr(a						,   a))

                   shutil.rmtree(a)



@require_torch
@require_sentencepiece
@require_tokenizers
class       SCREAMING_SNAKE_CASE__					(unittest.TestCase     ):
    __lowerCamelCase						:       int														=     """facebook/mbart-large-50-one-to-many-mmt"""
    __lowerCamelCase						:       Optional[Any]														=     [
        """ UN Chief Says There Is No Military Solution in Syria""",
        """ Secretary-General Ban Ki-moon says his response to Russia's stepped up military support for Syria is that \"there is no military solution\" to the nearly five-year conflict and more weapons will only worsen the violence and misery for millions of people.""",
    ]
    __lowerCamelCase						:       Union[str, Any]														=     [
        """Şeful ONU declară că nu există o soluţie militară în Siria""",
        """Secretarul General Ban Ki-moon declară că răspunsul său la intensificarea sprijinului militar al Rusiei"""
        """ pentru Siria este că \"nu există o soluţie militară\" la conflictul de aproape cinci ani şi că noi arme nu vor"""
        """ face decât să înrăutăţească violenţele şi mizeria pentru milioane de oameni.""",
    ]
    __lowerCamelCase						:       Union[str, Any]														=     [EN_CODE, 8274, 12_7873, 2_5916, 7, 8622, 2071, 438, 6_7485, 53, 18_7895, 23, 5_1712, 2]





    @classmethod
    def       snake_case_				(      cls):
         lowercase__    :   MBartaaTokenizer      =       MBartaaTokenizer.from_pretrained(
             cls.checkpoint_name						,   src_lang='en_XX'						,   tgt_lang='ro_RO')
         lowercase__    :   Union[str, Any]      =       1
         return cls





    def       snake_case_				(      self):
         self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['ar_AR']						,   25_0001)
         self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['en_EN']						,   25_0004)
         self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['ro_RO']						,   25_0020)
         self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['mr_IN']						,   25_0038)





    def       snake_case_				(      self):
         lowercase__    :   List[Any]      =       self.tokenizer.batch_encode_plus(self.src_text).input_ids[0]
         self.assertListEqual(self.expected_src_tokens						,   a)





    def       snake_case_				(      self):
         self.assertIn(a						,   self.tokenizer.all_special_ids)
         lowercase__    :   Dict      =       [RO_CODE, 884, 9019, 96, 9, 916, 8_6792, 36, 1_8743, 1_5596, 5, 2]
         lowercase__    :   Any      =       self.tokenizer.decode(a						,   skip_special_tokens=a)
         lowercase__    :   Optional[int]      =       self.tokenizer.decode(generated_ids[1:]						,   skip_special_tokens=a)
         self.assertEqual(a						,   a)
         self.assertNotIn(self.tokenizer.eos_token						,   a)





    def       snake_case_				(      self):
         lowercase__    :   Any      =       ['this is gunna be a long sentence ' * 20]
         assert isinstance(src_text[0]						,   a)
         lowercase__    :   Union[str, Any]      =       10
         lowercase__    :   List[str]      =       self.tokenizer(a						,   max_length=a						,   truncation=a).input_ids[0]
         self.assertEqual(ids[0]						,   a)
         self.assertEqual(ids[-1]						,   2)
         self.assertEqual(len(a)						,   a)





    def       snake_case_				(      self):
         self.assertListEqual(self.tokenizer.convert_tokens_to_ids(['<mask>', 'ar_AR'])						,   [25_0053, 25_0001])





    def       snake_case_				(      self):
         lowercase__    :   str      =       tempfile.mkdtemp()
         lowercase__    :   List[Any]      =       self.tokenizer.fairseq_tokens_to_ids
         self.tokenizer.save_pretrained(a)
         lowercase__    :   int      =       MBartaaTokenizer.from_pretrained(a)
         self.assertDictEqual(new_tok.fairseq_tokens_to_ids						,   a)





    @require_torch
    def       snake_case_				(      self):
         lowercase__    :   str      =       self.tokenizer(self.src_text						,   text_target=self.tgt_text						,   padding=a						,   return_tensors='pt')
         lowercase__    :   List[str]      =       shift_tokens_right(batch['labels']						,   self.tokenizer.pad_token_id)

         # fairseq batch: https://gist.github.com/sshleifer/cba08bc2109361a74ac3760a7e30e4f4
         assert batch.input_ids[1][0] == EN_CODE
         assert batch.input_ids[1][-1] == 2
         assert batch.labels[1][0] == RO_CODE
         assert batch.labels[1][-1] == 2
         assert batch.decoder_input_ids[1][:2].tolist() == [2, RO_CODE]





    @require_torch
    def       snake_case_				(      self):
         lowercase__    :   Optional[int]      =       self.tokenizer(
             self.src_text						,   text_target=self.tgt_text						,   padding=a						,   truncation=a						,   max_length=len(self.expected_src_tokens)						,   return_tensors='pt'						,   )
         lowercase__    :   List[Any]      =       shift_tokens_right(batch['labels']						,   self.tokenizer.pad_token_id)

         self.assertIsInstance(a						,   a)

         self.assertEqual((2, 14)						,   batch.input_ids.shape)
         self.assertEqual((2, 14)						,   batch.attention_mask.shape)
         lowercase__    :   Dict      =       batch.input_ids.tolist()[0]
         self.assertListEqual(self.expected_src_tokens						,   a)
         self.assertEqual(2						,   batch.decoder_input_ids[0, 0])  # decoder_start_token_id
         # Test that special tokens are reset
         self.assertEqual(self.tokenizer.prefix_tokens						,   [EN_CODE])
         self.assertEqual(self.tokenizer.suffix_tokens						,   [self.tokenizer.eos_token_id])





    def       snake_case_				(      self):
         lowercase__    :   Optional[Any]      =       self.tokenizer(self.src_text						,   padding=a						,   truncation=a						,   max_length=3						,   return_tensors='pt')
         lowercase__    :   Optional[int]      =       self.tokenizer(
             text_target=self.tgt_text						,   padding=a						,   truncation=a						,   max_length=10						,   return_tensors='pt')
         lowercase__    :   List[str]      =       targets['input_ids']
         lowercase__    :   List[Any]      =       shift_tokens_right(a						,   self.tokenizer.pad_token_id)

         self.assertEqual(batch.input_ids.shape[1]						,   3)
         self.assertEqual(batch.decoder_input_ids.shape[1]						,   10)





    @require_torch
    def       snake_case_				(      self):
         lowercase__    :   Union[str, Any]      =       self.tokenizer._build_translation_inputs(
             'A test'						,   return_tensors='pt'						,   src_lang='en_XX'						,   tgt_lang='ar_AR')

         self.assertEqual(
             nested_simplify(a)						,   {
                 # en_XX, A, test, EOS
                 'input_ids': [[25_0004, 62, 3034, 2]],
                 'attention_mask': [[1, 1, 1, 1]],
                 # ar_AR
                 'forced_bos_token_id': 25_0001,
             }						,   )




import argparse
import shlex

import runhouse as rh


if __name__ == "__main__":
       # Refer to https://runhouse-docs.readthedocs-hosted.com/en/latest/api/python/cluster.html#hardware-setup for cloud access
       # setup instructions, if using on-demand hardware

       # If user passes --user <user> --host <host> --key_path <key_path> <example> <args>, fill them in as BYO cluster
       # If user passes --instance <instance> --provider <provider> <example> <args>, fill them in as on-demand cluster
       # Throw an error if user passes both BYO and on-demand cluster args
       # Otherwise, use default values
       snake_case_			  = argparse.ArgumentParser()
       parser.add_argument('''--user''', type=str, default='''ubuntu''')
       parser.add_argument('''--host''', type=str, default='''localhost''')
       parser.add_argument('''--key_path''', type=str, default=None)
       parser.add_argument('''--instance''', type=str, default='''V100:1''')
       parser.add_argument('''--provider''', type=str, default='''cheapest''')
       parser.add_argument('''--use_spot''', type=bool, default=False)
       parser.add_argument('''--example''', type=str, default='''pytorch/text-generation/run_generation.py''')
       snake_case_  ,		snake_case_			  = parser.parse_known_args()
       if args.host != "localhost":
              if args.instance != "V100:1" or args.provider != "cheapest":
                     raise ValueError('''Cannot specify both BYO and on-demand cluster args''')
              snake_case_			  = rh.cluster(
                  name='''rh-cluster''', ips=[args.host], ssh_creds={'''ssh_user''': args.user, '''ssh_private_key''': args.key_path}
              )
       else:
              snake_case_			  = rh.cluster(
                  name='''rh-cluster''', instance_type=args.instance, provider=args.provider, use_spot=args.use_spot
              )
       snake_case_			  = args.example.rsplit('''/''', 1)[0]

       # Set up remote environment
       cluster.install_packages(['''pip:./'''])  # Installs transformers from local source
       # Note transformers is copied into the home directory on the remote machine, so we can install from there
       cluster.run([F'''pip install -r transformers/examples/{example_dir}/requirements.txt'''])
       cluster.run(['''pip install torch --upgrade --extra-index-url https://download.pytorch.org/whl/cu117'''])

       # Run example. You can bypass the CLI wrapper and paste your own code here.
       cluster.run([F'''python transformers/examples/{args.example} {' '.join(shlex.quote(arg) for arg in unknown)}'''])

       # Alternatively, we can just import and run a training function (especially if there's no wrapper CLI):
       # from my_script... import train
       # reqs = ['pip:./', 'torch', 'datasets', 'accelerate', 'evaluate', 'tqdm', 'scipy', 'scikit-learn', 'tensorboard']
       # launch_train_gpu = rh.function(fn=train,
       #                                system=gpu,
       #                                reqs=reqs,
       #                                name='train_bert_glue')
       #
       # We can pass in arguments just like we would to a function:
       # launch_train_gpu(num_epochs = 3, lr = 2e-5, seed = 42, batch_size = 16
       #                  stream_logs=True)

