





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 						lowerCamelCase       (unittest.TestCase      ):







							"""simple docstring"""




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





														"""simple docstring"""
														SCREAMING_SNAKE_CASE__       :      Dict     =						logging.get_logger()

														# the current default level is logging.WARNING
														SCREAMING_SNAKE_CASE__       :      Any     =						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(snake_case_						)






							def  A_     ( self     :					int						)				->			Dict:





														"""simple docstring"""
														SCREAMING_SNAKE_CASE__       :      Dict     =						logging.get_verbosity()

														SCREAMING_SNAKE_CASE__       :      str     =						logging.get_logger("transformers.models.bart.tokenization_bart"						)
														SCREAMING_SNAKE_CASE__       :      str     =						'''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(snake_case_						) as cl:
																												logger.warning(snake_case_						)
																					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(snake_case_						) as cl:
																					logger.warning(snake_case_						)
														self.assertEqual(cl.out,			""						)

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

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






							@mockenv(TRANSFORMERS_VERBOSITY="error"						)
							def  A_     ( self     :					Optional[int]						)				->			Optional[Any]:





														"""simple docstring"""
														# 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
														SCREAMING_SNAKE_CASE__       :      Optional[Any]     =						logging.get_logger("transformers.models.bart.tokenization_bart"						)

														SCREAMING_SNAKE_CASE__       :      List[str]     =						os.getenv("TRANSFORMERS_VERBOSITY",			snake_case_						)
														SCREAMING_SNAKE_CASE__       :      Union[str, Any]     =						logging.log_levels[env_level_str]

														SCREAMING_SNAKE_CASE__       :      int     =						logging.get_verbosity()
														self.assertEqual(
														    snake_case_,			snake_case_,			F'''TRANSFORMERS_VERBOSITY={env_level_str}/{env_level}, but internal verbosity is {current_level}''',			)

														# restore to the original level
														SCREAMING_SNAKE_CASE__       :      str     =						''''''
														transformers.utils.logging._reset_library_root_logger()






							@mockenv(TRANSFORMERS_VERBOSITY="super-error"						)
							def  A_     ( self     :					List[str]						)				->			Optional[int]:





														"""simple docstring"""
														# reset for the env var to take effect, next time some logger call is made
														transformers.utils.logging._reset_library_root_logger()
														SCREAMING_SNAKE_CASE__       :      Optional[int]     =						logging.logging.getLogger()
														with CaptureLogger(snake_case_						) 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  A_     ( self     :					Union[str, Any]						)				->			Any:





														"""simple docstring"""
														# testing `logger.warning_advice()`
														transformers.utils.logging._reset_library_root_logger()

														SCREAMING_SNAKE_CASE__       :      int     =						logging.get_logger("transformers.models.bart.tokenization_bart"						)
														SCREAMING_SNAKE_CASE__       :      Union[str, Any]     =						'''Testing 1, 2, 3'''

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

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




def _a (  )	->    Dict:

							'''simple docstring'''






							disable_progress_bar()
							assert are_progress_bars_disabled()

							enable_progress_bar()
							assert not are_progress_bars_disabled()













import pytest

from datasets.splits import SplitDict, SplitInfo
from datasets.utils.py_utils import asdict




@pytest.mark.parametrize(
    "split_dict"			,				[
        SplitDict(),
        SplitDict({"train": SplitInfo(name="train"			,				num_bytes=13_37			,				num_examples=42			,				dataset_name="my_dataset"       )}       ),
        SplitDict({"train": SplitInfo(name="train"			,				num_bytes=13_37			,				num_examples=42       )}       ),
        SplitDict({"train": SplitInfo()}       ),
    ]			,				)
def _a (  SCREAMING_SNAKE_CASE__      :  SplitDict       )	->    str:

							'''simple docstring'''






							SCREAMING_SNAKE_CASE__       :      Dict     =						split_dict._to_yaml_list()
							assert len(SCREAMING_SNAKE_CASE__       ) == len(SCREAMING_SNAKE_CASE__       )
							SCREAMING_SNAKE_CASE__       :      List[Any]     =						SplitDict._from_yaml_list(SCREAMING_SNAKE_CASE__       )
							for split_name, split_info in split_dict.items():
														# dataset_name field is deprecated, and is therefore not part of the YAML dump
														SCREAMING_SNAKE_CASE__       :      str     =						None
														# the split name of split_dict takes over the name of the split info object
														SCREAMING_SNAKE_CASE__       :      Union[str, Any]     =						split_name
							assert split_dict == reloaded







@pytest.mark.parametrize(
    "split_info"			,				[SplitInfo(), SplitInfo(dataset_name=SCREAMING_SNAKE_CASE__       ), SplitInfo(dataset_name="my_dataset"       )]       )
def _a (  SCREAMING_SNAKE_CASE__      :  Any       )	->    Dict:

							'''simple docstring'''






							SCREAMING_SNAKE_CASE__       :      str     =						asdict(SplitDict({"train": split_info}       )       )
							assert "dataset_name" in split_dict_asdict["train"]
							assert split_dict_asdict["train"]["dataset_name"] == split_info.dataset_name






