
import unittest

from transformers import AlbertTokenizer, AlbertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin


lowerCamelCase      =get_tests_dir("fixtures/spiece.model")




@require_sentencepiece
@require_tokenizers
class 				_lowerCamelCase (      A_	,							unittest.TestCase ):





     """simple docstring"""







     SCREAMING_SNAKE_CASE_		   =  AlbertTokenizer
     SCREAMING_SNAKE_CASE_		   =  AlbertTokenizerFast
     SCREAMING_SNAKE_CASE_		   =  True
     SCREAMING_SNAKE_CASE_		   =  True
     SCREAMING_SNAKE_CASE_		   =  True






     def    __SCREAMING_SNAKE_CASE			(							self  )  ->   str:




           """simple docstring"""







           super().setUp()

           # We have a SentencePiece fixture for testing
           UpperCamelCase__    :   Dict					=				AlbertTokenizer(__SCREAMING_SNAKE_CASE  )
           tokenizer.save_pretrained(self.tmpdirname  )






     def    __SCREAMING_SNAKE_CASE			(							self						,						__SCREAMING_SNAKE_CASE  )  ->   List[str]:




           """simple docstring"""







           UpperCamelCase__    :   Optional[Any]					=				"""this is a test"""
           UpperCamelCase__    :   str					=				"""this is a test"""
           return input_text, output_text






     def    __SCREAMING_SNAKE_CASE			(							self  )  ->   Tuple:




           """simple docstring"""







           UpperCamelCase__    :   Any					=				"""<pad>"""
           UpperCamelCase__    :   List[str]					=				0

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






     def    __SCREAMING_SNAKE_CASE			(							self  )  ->   List[Any]:




           """simple docstring"""







           UpperCamelCase__    :   int					=				list(self.get_tokenizer().get_vocab().keys()  )

           self.assertEqual(vocab_keys[0]						,						'''<pad>'''  )
           self.assertEqual(vocab_keys[1]						,						'''<unk>'''  )
           self.assertEqual(vocab_keys[-1]						,						'''▁eloquent'''  )
           self.assertEqual(len(__SCREAMING_SNAKE_CASE  )						,						3_0_0_0_0  )






     def    __SCREAMING_SNAKE_CASE			(							self  )  ->   Optional[Any]:




           """simple docstring"""







           self.assertEqual(self.get_tokenizer().vocab_size						,						3_0_0_0_0  )






     def    __SCREAMING_SNAKE_CASE			(							self  )  ->   Dict:




           """simple docstring"""







           if not self.test_rust_tokenizer:
                 return

           UpperCamelCase__    :   Union[str, Any]					=				self.get_tokenizer()
           UpperCamelCase__    :   Union[str, Any]					=				self.get_rust_tokenizer()

           UpperCamelCase__    :   str					=				"""I was born in 92000, and this is falsé."""

           UpperCamelCase__    :   Optional[Any]					=				tokenizer.tokenize(__SCREAMING_SNAKE_CASE  )
           UpperCamelCase__    :   Any					=				rust_tokenizer.tokenize(__SCREAMING_SNAKE_CASE  )
           self.assertListEqual(__SCREAMING_SNAKE_CASE						,						__SCREAMING_SNAKE_CASE  )

           UpperCamelCase__    :   Any					=				tokenizer.encode(__SCREAMING_SNAKE_CASE						,						add_special_tokens=__SCREAMING_SNAKE_CASE  )
           UpperCamelCase__    :   Optional[int]					=				rust_tokenizer.encode(__SCREAMING_SNAKE_CASE						,						add_special_tokens=__SCREAMING_SNAKE_CASE  )
           self.assertListEqual(__SCREAMING_SNAKE_CASE						,						__SCREAMING_SNAKE_CASE  )

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






     def    __SCREAMING_SNAKE_CASE			(							self  )  ->   Tuple:




           """simple docstring"""







           UpperCamelCase__    :   List[Any]					=				AlbertTokenizer(__SCREAMING_SNAKE_CASE						,						keep_accents=__SCREAMING_SNAKE_CASE  )

           UpperCamelCase__    :   Any					=				tokenizer.tokenize('''This is a test'''  )
           self.assertListEqual(__SCREAMING_SNAKE_CASE						,						['''▁this''', '''▁is''', '''▁a''', '''▁test''']  )

           self.assertListEqual(tokenizer.convert_tokens_to_ids(__SCREAMING_SNAKE_CASE  )						,						[4_8, 2_5, 2_1, 1_2_8_9]  )

           UpperCamelCase__    :   List[str]					=				tokenizer.tokenize('''I was born in 92000, and this is falsé.'''  )
           self.assertListEqual(
               __SCREAMING_SNAKE_CASE						,						['''▁i''', '''▁was''', '''▁born''', '''▁in''', '''▁9''', '''2000''', ''',''', '''▁and''', '''▁this''', '''▁is''', '''▁fal''', '''s''', '''é''', '''.''']  )
           UpperCamelCase__    :   Dict					=				tokenizer.convert_tokens_to_ids(__SCREAMING_SNAKE_CASE  )
           self.assertListEqual(__SCREAMING_SNAKE_CASE						,						[3_1, 2_3, 3_8_6, 1_9, 5_6_1, 3_0_5_0, 1_5, 1_7, 4_8, 2_5, 8_2_5_6, 1_8, 1, 9]  )

           UpperCamelCase__    :   List[Any]					=				tokenizer.convert_ids_to_tokens(__SCREAMING_SNAKE_CASE  )
           self.assertListEqual(
               __SCREAMING_SNAKE_CASE						,						['''▁i''', '''▁was''', '''▁born''', '''▁in''', '''▁9''', '''2000''', ''',''', '''▁and''', '''▁this''', '''▁is''', '''▁fal''', '''s''', '''<unk>''', '''.''']						,						)






     def    __SCREAMING_SNAKE_CASE			(							self  )  ->   Any:




           """simple docstring"""







           UpperCamelCase__    :   Any					=				AlbertTokenizer(__SCREAMING_SNAKE_CASE  )

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

           UpperCamelCase__    :   List[Any]					=				tokenizer.build_inputs_with_special_tokens(__SCREAMING_SNAKE_CASE  )
           UpperCamelCase__    :   Dict					=				tokenizer.build_inputs_with_special_tokens(__SCREAMING_SNAKE_CASE						,						__SCREAMING_SNAKE_CASE  )

           assert encoded_sentence == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id]
           assert encoded_pair == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id] + text_a + [
               tokenizer.sep_token_id
           ]






     @slow
     def    __SCREAMING_SNAKE_CASE			(							self  )  ->   int:




           """simple docstring"""







           UpperCamelCase__    :   str					=				{"""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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], """input_ids""": [[2, 2_1_9_7_0, 1_3, 5, 6_0_9_2, 1_6_7, 2_8, 7_1_0_3, 2_1_5_3, 6_7_3, 8, 7_0_2_8, 1_2_0_5_1, 1_8, 1_7, 7_1_0_3, 2_1_5_3, 6_7_3, 8, 3_5_1_5, 1_8_6_8_4, 8, 4_4_6_1, 6, 1_9_2_7, 2_9_7, 8, 1_2_0_6_0, 2_6_0_7, 1_8, 1_3, 5, 4_4_6_1, 1_5, 1_0_5_3_8, 3_8, 8, 1_3_5, 1_5, 8_2_2, 5_8, 1_5, 9_9_3, 1_0_3_6_3, 1_5, 1_4_6_0, 8_0_0_5, 4_4_6_1, 1_5, 9_9_3, 2_5_5, 2_3_2_8, 9, 9, 9, 6, 2_6, 1_1_1_2, 8_1_6, 3_2_6_0, 1_3, 5, 1_0_3, 2_3_7_7, 6, 1_7, 1_1_1_2, 8_1_6, 2_7_8_2, 1_3, 5, 1_0_3, 1_0_6_4_1, 6, 2_9, 8_4, 2_5_1_2, 2_4_3_0, 7_8_2, 1_8_6_8_4, 2_7_6_1, 1_9, 8_0_8, 2_4_3_0, 2_5_5_6, 1_7, 8_5_5, 1_4_8_0, 9_4_7_7, 4_0_9_1, 1_2_8, 1_1_7_1_2, 1_5, 7_1_0_3, 2_1_5_3, 6_7_3, 1_7, 2_4_8_8_3, 9_9_9_0, 9, 3], [2, 1_1_5_0_2, 2_5, 1_0_0_6, 2_0, 7_8_2, 8, 1_1_8_0_9, 8_5_5, 1_7_3_2, 1_9_3_9_3, 1_8_6_6_7, 3_7, 3_6_7, 2_1_0_1_8, 6_9, 1_8_5_4, 3_4, 1_1_8_6_0, 1_9_1_2_4, 2_7, 1_5_6, 2_2_5, 1_7, 1_9_3, 4_1_4_1, 1_9, 6_5, 9_1_2_4, 9, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [2, 1_4, 2_2_3_1, 8_8_6, 2_3_8_5, 1_7_6_5_9, 8_4, 1_4, 1_6_7_9_2, 1_9_5_2, 9, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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=__SCREAMING_SNAKE_CASE						,						model_name='''albert-base-v2'''						,						revision='''6b6560eaf5ff2e250b00c50f380c5389a9c2d82e'''						,						)




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
    lowerCamelCase      =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")
    lowerCamelCase   ,     lowerCamelCase      =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")
        lowerCamelCase      =rh.cluster(
            name="rh-cluster", ips=[args.host], ssh_creds={"ssh_user": args.user, "ssh_private_key": args.key_path}
        )
    else:
        lowerCamelCase      =rh.cluster(
            name="rh-cluster", instance_type=args.instance, provider=args.provider, use_spot=args.use_spot
        )
    lowerCamelCase      =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)


