


'''simple docstring'''




import unittest

from transformers import BertGenerationTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_torch, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


_a   :   int												=   '''▁'''

_a   :   List[str]												=   get_tests_dir("fixtures/test_sentencepiece.model")




@require_sentencepiece
class 			_lowercase (	_UpperCamelCase						,					unittest.TestCase							):
   _SCREAMING_SNAKE_CASE  :  Dict          =	BertGenerationTokenizer
   _SCREAMING_SNAKE_CASE  :  Optional[int]          =	False
   _SCREAMING_SNAKE_CASE  :  Any          =	True
   def a  (						self       :      Union[str, Any]      ) ->							Union[str, Any]:
        super().setUp()

        __snake_case           =						BertGenerationTokenizer(UpperCamelCase__       ,   keep_accents=UpperCamelCase__      )
        tokenizer.save_pretrained(self.tmpdirname      )
   def a  (						self       :      Any      ) ->							str:
        __snake_case           =						'<s>'
        __snake_case           =						1

        self.assertEqual(self.get_tokenizer()._convert_token_to_id(UpperCamelCase__      )       ,   UpperCamelCase__      )
        self.assertEqual(self.get_tokenizer()._convert_id_to_token(UpperCamelCase__      )       ,   UpperCamelCase__      )
   def a  (						self       :      List[Any]      ) ->							int:
        __snake_case           =						list(self.get_tokenizer().get_vocab().keys()      )

        self.assertEqual(vocab_keys[0]       ,   '<unk>'      )
        self.assertEqual(vocab_keys[1]       ,   '<s>'      )
        self.assertEqual(vocab_keys[-1]       ,   '<pad>'      )
        self.assertEqual(len(UpperCamelCase__      )       ,   1002      )
   def a  (						self       :      int      ) ->							Dict:
        self.assertEqual(self.get_tokenizer().vocab_size       ,   1000      )
   def a  (						self       :      List[Any]      ) ->							List[Any]:
        __snake_case           =						BertGenerationTokenizer(UpperCamelCase__       ,   keep_accents=UpperCamelCase__      )

        __snake_case           =						tokenizer.tokenize('This is a test'      )
        self.assertListEqual(UpperCamelCase__       ,   ['▁This', '▁is', '▁a', '▁t', 'est']      )

        self.assertListEqual(
            tokenizer.convert_tokens_to_ids(UpperCamelCase__      )       ,   [285, 46, 10, 170, 382]       ,   )

        __snake_case           =						tokenizer.tokenize('I was born in 92000, and this is falsé.'      )
        self.assertListEqual(
            UpperCamelCase__       ,   [
                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',
                '.',
            ]       ,   )
        __snake_case           =						tokenizer.convert_tokens_to_ids(UpperCamelCase__      )
        self.assertListEqual(
            UpperCamelCase__       ,   [8, 21, 84, 55, 24, 19, 7, 0, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 0, 4]       ,   )

        __snake_case           =						tokenizer.convert_ids_to_tokens(UpperCamelCase__      )
        self.assertListEqual(
            UpperCamelCase__       ,   [
                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>',
                '.',
            ]       ,   )
   @cached_property
   def a  (						self       :      Any      ) ->							str:
        return BertGenerationTokenizer.from_pretrained('google/bert_for_seq_generation_L-24_bbc_encoder'      )
   @slow
   def a  (						self       :      str      ) ->							Optional[int]:
        __snake_case           =						'Hello World!'
        __snake_case           =						[1_8536, 2260, 101]

        self.assertListEqual(UpperCamelCase__       ,   self.big_tokenizer.encode(UpperCamelCase__      )      )
   @slow
   def a  (						self       :      List[Any]      ) ->							Tuple:
        __snake_case           =						(
            'This is a very long text with a lot of weird characters, such as: . , ~ ? ( ) " [ ] ! : - . Also we will'
            ' add words that should not exsist and be tokenized to <unk>, such as saoneuhaoesuth'
        )
        __snake_case           =						[
            871,
            419,
            358,
            946,
            991,
            2521,
            452,
            358,
            1357,
            387,
            7751,
            3536,
            112,
            985,
            456,
            126,
            865,
            938,
            5400,
            5734,
            458,
            1368,
            467,
            786,
            2462,
            5246,
            1159,
            633,
            865,
            4519,
            457,
            582,
            852,
            2557,
            427,
            916,
            508,
            405,
            3_4324,
            497,
            391,
            408,
            1_1342,
            1244,
            385,
            100,
            938,
            985,
            456,
            574,
            362,
            1_2597,
            3200,
            3129,
            1172,
        ]

        self.assertListEqual(UpperCamelCase__       ,   self.big_tokenizer.encode(UpperCamelCase__      )      )
   @require_torch
   @slow
   def a  (						self       :      Optional[int]      ) ->							Union[str, Any]:
        import torch

        from transformers import BertGenerationConfig, BertGenerationEncoder

        # Build sequence
        __snake_case           =						list(self.big_tokenizer.get_vocab().keys()      )[:10]
        __snake_case           =						' '.join(UpperCamelCase__      )
        __snake_case           =						self.big_tokenizer.encode_plus(UpperCamelCase__       ,   return_tensors='pt'       ,   return_token_type_ids=UpperCamelCase__      )
        __snake_case           =						self.big_tokenizer.batch_encode_plus(
            [sequence + ' ' + sequence]       ,   return_tensors='pt'       ,   return_token_type_ids=UpperCamelCase__      )

        __snake_case           =						BertGenerationConfig()
        __snake_case           =						BertGenerationEncoder(UpperCamelCase__      )

        assert model.get_input_embeddings().weight.shape[0] >= self.big_tokenizer.vocab_size

        with torch.no_grad():
             model(**UpperCamelCase__      )
             model(**UpperCamelCase__      )





   @slow
   def a  (						self       :      Tuple      ) ->							int:
        # fmt: off
        __snake_case           =						{'input_ids': [[3_9286, 458, 3_6335, 2001, 456, 1_3073, 1_3266, 455, 113, 7746, 1741, 1_1157, 391, 1_3073, 1_3266, 455, 113, 3967, 3_5412, 113, 4936, 109, 3870, 2377, 113, 3_0084, 4_5720, 458, 134, 1_7496, 112, 503, 1_1672, 113, 118, 112, 5665, 1_3347, 3_8687, 112, 1496, 3_1389, 112, 3268, 4_7264, 134, 962, 112, 1_6377, 8035, 2_3130, 430, 1_2169, 1_5518, 2_8592, 458, 146, 4_1697, 109, 391, 1_2169, 1_5518, 1_6689, 458, 146, 4_1358, 109, 452, 726, 4034, 111, 763, 3_5412, 5082, 388, 1903, 111, 9051, 391, 2870, 4_8918, 1900, 1123, 550, 998, 112, 9586, 1_5985, 455, 391, 410, 2_2955, 3_7636, 114], [448, 1_7496, 419, 3663, 385, 763, 113, 2_7533, 2870, 3283, 1_3043, 1639, 2_4713, 523, 656, 2_4013, 1_8550, 2521, 517, 2_7014, 2_1244, 420, 1212, 1465, 391, 927, 4833, 388, 578, 1_1786, 114, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [484, 2169, 7687, 2_1932, 1_8146, 726, 363, 1_7032, 3391, 114, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], '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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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='google/bert_for_seq_generation_L-24_bbc_encoder'       ,   revision='c817d1fd1be2ffa69431227a1fe320544943d4db'       ,   )





'''simple docstring'''






_UpperCAmelCase    :     Any         =       '''0.21.0'''

from .accelerator import Accelerator
from .big_modeling import (
    cpu_offload,
    cpu_offload_with_hook,
    disk_offload,
    dispatch_model,
    init_empty_weights,
    init_on_device,
    load_checkpoint_and_dispatch,
)
from .data_loader import skip_first_batches
from .launchers import debug_launcher, notebook_launcher
from .state import PartialState
from .utils import (
    DeepSpeedPlugin,
    DistributedDataParallelKwargs,
    DistributedType,
    FullyShardedDataParallelPlugin,
    GradScalerKwargs,
    InitProcessGroupKwargs,
    find_executable_batch_size,
    infer_auto_device_map,
    is_rich_available,
    load_checkpoint_in_model,
    synchronize_rng_states,
)


if is_rich_available():
   from .utils import rich



