

"""simple docstring"""




import argparse
import logging
import sys
from unittest.mock import patch

import run_glue_deebert

from transformers.testing_utils import TestCasePlus, get_gpu_count, require_torch_non_multi_gpu, slow


logging.basicConfig(level=logging.DEBUG)

A_							:			Optional[int]											= logging.getLogger()

def 	A       (     ):




			'''simple docstring'''


			SCREAMING_SNAKE_CASE__								=      argparse.ArgumentParser()
			parser.add_argument("""-f"""    )
			SCREAMING_SNAKE_CASE__								=      parser.parse_args()
			return args.f





class    lowerCamelCase						(A__			):

			def 					SCREAMING_SNAKE_CASE				(					self				:						int       )   ->    None:
						SCREAMING_SNAKE_CASE__								=      logging.StreamHandler(sys.stdout       )
						logger.addHandler(__UpperCAmelCase       )

			def 					SCREAMING_SNAKE_CASE				(					self				:						List[str]    ,				__UpperCAmelCase				:						Optional[Any]       )   ->    List[str]:
						SCREAMING_SNAKE_CASE__								=      get_gpu_count()

						if n_gpu > 1:
									pass
									# XXX: doesn't quite work with n_gpu > 1 https://github.com/huggingface/transformers/issues/10560
									# script = f"{self.examples_dir_str}/research_projects/deebert/run_glue_deebert.py"
									# distributed_args = f"-m torch.distributed.launch --nproc_per_node={n_gpu} {script}".split()
									# cmd = [sys.executable] + distributed_args + args
									# execute_subprocess_async(cmd, env=self.get_env())
									# XXX: test the results - need to save them first into .json file
						else:
									args.insert(0    ,				"""run_glue_deebert.py"""       )
									with patch.object(__UpperCAmelCase    ,				"""argv"""    ,				__UpperCAmelCase       ):
												SCREAMING_SNAKE_CASE__								=      run_glue_deebert.main()
												for value in result.values():
															self.assertGreaterEqual(__UpperCAmelCase    ,				0.666       )





			@slow
			@require_torch_non_multi_gpu
			def 					SCREAMING_SNAKE_CASE				(					self				:						Optional[int]       )   ->    Any:
						SCREAMING_SNAKE_CASE__								=      """
            --model_type roberta
            --model_name_or_path roberta-base
            --task_name MRPC
            --do_train
            --do_eval
            --do_lower_case
            --data_dir ./tests/fixtures/tests_samples/MRPC/
            --max_seq_length 128
            --per_gpu_eval_batch_size=1
            --per_gpu_train_batch_size=8
            --learning_rate 2e-4
            --num_train_epochs 3
            --overwrite_output_dir
            --seed 42
            --output_dir ./examples/deebert/saved_models/roberta-base/MRPC/two_stage
            --plot_data_dir ./examples/deebert/results/
            --save_steps 0
            --overwrite_cache
            --eval_after_first_stage
            """.split()
						self.run_and_check(__UpperCAmelCase       )

						SCREAMING_SNAKE_CASE__								=      """
            --model_type roberta
            --model_name_or_path ./examples/deebert/saved_models/roberta-base/MRPC/two_stage
            --task_name MRPC
            --do_eval
            --do_lower_case
            --data_dir ./tests/fixtures/tests_samples/MRPC/
            --output_dir ./examples/deebert/saved_models/roberta-base/MRPC/two_stage
            --plot_data_dir ./examples/deebert/results/
            --max_seq_length 128
            --eval_each_highway
            --eval_highway
            --overwrite_cache
            --per_gpu_eval_batch_size=1
            """.split()
						self.run_and_check(__UpperCAmelCase       )

						SCREAMING_SNAKE_CASE__								=      """
            --model_type roberta
            --model_name_or_path ./examples/deebert/saved_models/roberta-base/MRPC/two_stage
            --task_name MRPC
            --do_eval
            --do_lower_case
            --data_dir ./tests/fixtures/tests_samples/MRPC/
            --output_dir ./examples/deebert/saved_models/roberta-base/MRPC/two_stage
            --plot_data_dir ./examples/deebert/results/
            --max_seq_length 128
            --early_exit_entropy 0.1
            --eval_highway
            --overwrite_cache
            --per_gpu_eval_batch_size=1
            """.split()
						self.run_and_check(__UpperCAmelCase       )





"""simple docstring"""




# Lint as: python3
# pylint: enable=line-too-long
# pylint: disable=g-import-not-at-top,g-bad-import-order,wrong-import-position

A_							:			Tuple											= "2.13.1"

import platform

import pyarrow
from packaging import version


if version.parse(platform.python_version()) < version.parse("3.7"):
						raise ImportWarning(
						    "To use `datasets`, Python>=3.7 is required, and the current version of Python doesn't match this condition."
						)

if version.parse(pyarrow.__version__).major < 8:
						raise ImportWarning(
						    "To use `datasets`, the module `pyarrow>=8.0.0` is required, and the current version of `pyarrow` doesn't match this condition.\n"
						    "If you are running this in a Google Colab, you should probably just restart the runtime to use the right version of `pyarrow`."
						)

del platform
del pyarrow
del version

from .arrow_dataset import Dataset
from .arrow_reader import ReadInstruction
from .builder import ArrowBasedBuilder, BeamBasedBuilder, BuilderConfig, DatasetBuilder, GeneratorBasedBuilder
from .combine import concatenate_datasets, interleave_datasets
from .dataset_dict import DatasetDict, IterableDatasetDict
from .download import *
from .features import *
from .fingerprint import disable_caching, enable_caching, is_caching_enabled, set_caching_enabled
from .info import DatasetInfo, MetricInfo
from .inspect import (
    get_dataset_config_info,
    get_dataset_config_names,
    get_dataset_infos,
    get_dataset_split_names,
    inspect_dataset,
    inspect_metric,
    list_datasets,
    list_metrics,
)
from .iterable_dataset import IterableDataset
from .load import load_dataset, load_dataset_builder, load_from_disk, load_metric
from .metric import Metric
from .splits import (
    NamedSplit,
    NamedSplitAll,
    Split,
    SplitBase,
    SplitDict,
    SplitGenerator,
    SplitInfo,
    SubSplitInfo,
    percent,
)
from .tasks import *
from .utils import *
from .utils import logging


# deprecated modules
from datasets import arrow_dataset as _arrow_dataset  # isort:skip
from datasets import utils as _utils  # isort:skip
from datasets.utils import download_manager as _deprecated_download_manager  # isort:skip

A_							:			Tuple											= concatenate_datasets
A_							:			List[str]											= DownloadConfig
A_							:			int											= DownloadManager
A_							:			Optional[Any]											= DownloadMode
A_							:			Optional[int]											= DownloadConfig
A_							:			List[Any]											= DownloadMode
A_							:			Any											= DownloadManager

del _arrow_dataset, _utils, _deprecated_download_manager


