



import os
import unittest

from huggingface_hub.utils import are_progress_bars_disabled

import transformers.models.bart.tokenization_bart
from transformers import logging
from transformers.testing_utils import CaptureLogger, mockenv, mockenv_context
from transformers.utils.logging import disable_progress_bar, enable_progress_bar



class      _UpperCAmelCase      (							unittest.TestCase  ):




     def 		snake_case_		(					self):
         A__					=       logging.get_logger()

         # the current default level is logging.WARNING
         A__					=       logging.get_verbosity()

         logging.set_verbosity_error()
         self.assertEqual(logger.getEffectiveLevel()			,    logging.get_verbosity())

         logging.set_verbosity_warning()
         self.assertEqual(logger.getEffectiveLevel()			,    logging.get_verbosity())

         logging.set_verbosity_info()
         self.assertEqual(logger.getEffectiveLevel()			,    logging.get_verbosity())

         logging.set_verbosity_debug()
         self.assertEqual(logger.getEffectiveLevel()			,    logging.get_verbosity())

         # restore to the original level
         logging.set_verbosity(a__)




     def 		snake_case_		(					self):
         A__					=       logging.get_verbosity()

         A__					=       logging.get_logger('''transformers.models.bart.tokenization_bart''')
         A__					=       '''Testing 1, 2, 3'''

         # should be able to log warnings (if default settings weren't overridden by `pytest --log-level-all`)
         if level_origin <= logging.WARNING:
             with CaptureLogger(a__) as cl:
                 logger.warning(a__)
             self.assertEqual(cl.out			,    msg + '''\n''')

         # this is setting the level for all of `transformers.*` loggers
         logging.set_verbosity_error()

         # should not be able to log warnings
         with CaptureLogger(a__) as cl:
             logger.warning(a__)
         self.assertEqual(cl.out			,    '''''')

         # should be able to log warnings again
         logging.set_verbosity_warning()
         with CaptureLogger(a__) as cl:
             logger.warning(a__)
         self.assertEqual(cl.out			,    msg + '''\n''')

         # restore to the original level
         logging.set_verbosity(a__)




     @mockenv(TRANSFORMERS_VERBOSITY='''error''')
     def 		snake_case_		(					self):
         # reset for the env var to take effect, next time some logger call is made
         transformers.utils.logging._reset_library_root_logger()
         # this action activates the env var
         A__					=       logging.get_logger('''transformers.models.bart.tokenization_bart''')

         A__					=       os.getenv('''TRANSFORMERS_VERBOSITY'''			,    a__)
         A__					=       logging.log_levels[env_level_str]

         A__					=       logging.get_verbosity()
         self.assertEqual(
             a__			,    a__			,    F"TRANSFORMERS_VERBOSITY={env_level_str}/{env_level}, but internal verbosity is {current_level}"			,    )

         # restore to the original level
         A__					=       ''''''
         transformers.utils.logging._reset_library_root_logger()




     @mockenv(TRANSFORMERS_VERBOSITY='''super-error''')
     def 		snake_case_		(					self):
         # reset for the env var to take effect, next time some logger call is made
         transformers.utils.logging._reset_library_root_logger()
         A__					=       logging.logging.getLogger()
         with CaptureLogger(a__) as cl:
             # this action activates the env var
             logging.get_logger('''transformers.models.bart.tokenization_bart''')
         self.assertIn('''Unknown option TRANSFORMERS_VERBOSITY=super-error'''			,    cl.out)

         # no need to restore as nothing was changed




     def 		snake_case_		(					self):
         # testing `logger.warning_advice()`
         transformers.utils.logging._reset_library_root_logger()

         A__					=       logging.get_logger('''transformers.models.bart.tokenization_bart''')
         A__					=       '''Testing 1, 2, 3'''

         with mockenv_context(TRANSFORMERS_NO_ADVISORY_WARNINGS='''1'''):
             # nothing should be logged as env var disables this method
             with CaptureLogger(a__) as cl:
                 logger.warning_advice(a__)
             self.assertEqual(cl.out			,    '''''')

         with mockenv_context(TRANSFORMERS_NO_ADVISORY_WARNINGS=''''''):
             # should log normally as TRANSFORMERS_NO_ADVISORY_WARNINGS is unset
             with CaptureLogger(a__) as cl:
                 logger.warning_advice(a__)
             self.assertEqual(cl.out			,    msg + '''\n''')







def 		lowerCAmelCase__     (       )->	Union[str, Any]:
    disable_progress_bar()
    assert are_progress_bars_disabled()

    enable_progress_bar()
    assert not are_progress_bars_disabled()





from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


_lowercase    	=		logging.get_logger(__name__)

_lowercase    	=		{
    "xlm-roberta-base": "https://huggingface.co/xlm-roberta-base/resolve/main/config.json",
    "xlm-roberta-large": "https://huggingface.co/xlm-roberta-large/resolve/main/config.json",
    "xlm-roberta-large-finetuned-conll02-dutch": (
        "https://huggingface.co/xlm-roberta-large-finetuned-conll02-dutch/resolve/main/config.json"
    ),
    "xlm-roberta-large-finetuned-conll02-spanish": (
        "https://huggingface.co/xlm-roberta-large-finetuned-conll02-spanish/resolve/main/config.json"
    ),
    "xlm-roberta-large-finetuned-conll03-english": (
        "https://huggingface.co/xlm-roberta-large-finetuned-conll03-english/resolve/main/config.json"
    ),
    "xlm-roberta-large-finetuned-conll03-german": (
        "https://huggingface.co/xlm-roberta-large-finetuned-conll03-german/resolve/main/config.json"
    ),
}



class      _UpperCAmelCase      (							A__  ):
     UpperCamelCase__		     =					'''xlm-roberta'''




     def __init__(					self			,    a__=3_0_5_2_2			,    a__=7_6_8			,    a__=1_2			,    a__=1_2			,    a__=3_0_7_2			,    a__="gelu"			,    a__=0.1			,    a__=0.1			,    a__=5_1_2			,    a__=2			,    a__=0.0_2			,    a__=1e-12			,    a__=1			,    a__=0			,    a__=2			,    a__="absolute"			,    a__=True			,    a__=None			,    **a__			,    ):
         super().__init__(pad_token_id=a__			,    bos_token_id=a__			,    eos_token_id=a__			,    **a__)

         A__					=       vocab_size
         A__					=       hidden_size
         A__					=       num_hidden_layers
         A__					=       num_attention_heads
         A__					=       hidden_act
         A__					=       intermediate_size
         A__					=       hidden_dropout_prob
         A__					=       attention_probs_dropout_prob
         A__					=       max_position_embeddings
         A__					=       type_vocab_size
         A__					=       initializer_range
         A__					=       layer_norm_eps
         A__					=       position_embedding_type
         A__					=       use_cache
         A__					=       classifier_dropout







class      _UpperCAmelCase      (							A__  ):




     @property
     def 		snake_case_		(					self):
         if self.task == "multiple-choice":
             A__					=       {0: '''batch''', 1: '''choice''', 2: '''sequence'''}
         else:
             A__					=       {0: '''batch''', 1: '''sequence'''}
         return OrderedDict(
             [
                 ('''input_ids''', dynamic_axis),
                 ('''attention_mask''', dynamic_axis),
             ])
