"""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)

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







def 					__a   (		):






     '''simple docstring'''



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






class    a__    (   __snake_case	):


       def 	snake_case__	(     self  ):
            '''simple docstring'''



            lowercase__				 =							logging.StreamHandler(sys.stdout  )
            logger.addHandler(__UpperCamelCase  )


       def 	snake_case__	(     self,				_UpperCAmelCase  ):
            '''simple docstring'''



            lowercase__				 =							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  ):
                      lowercase__				 =							run_glue_deebert.main()
                      for value in result.values():
                           self.assertGreaterEqual(__UpperCamelCase,				0.666  )


       @slow
       @require_torch_non_multi_gpu
       def 	snake_case__	(     self  ):
            '''simple docstring'''



            lowercase__				 =							"\n            --model_type roberta\n            --model_name_or_path roberta-base\n            --task_name MRPC\n            --do_train\n            --do_eval\n            --do_lower_case\n            --data_dir ./tests/fixtures/tests_samples/MRPC/\n            --max_seq_length 128\n            --per_gpu_eval_batch_size=1\n            --per_gpu_train_batch_size=8\n            --learning_rate 2e-4\n            --num_train_epochs 3\n            --overwrite_output_dir\n            --seed 42\n            --output_dir ./examples/deebert/saved_models/roberta-base/MRPC/two_stage\n            --plot_data_dir ./examples/deebert/results/\n            --save_steps 0\n            --overwrite_cache\n            --eval_after_first_stage\n            ".split()
            self.run_and_check(__UpperCamelCase  )

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

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





"""simple docstring"""


from typing import Optional

from .. import Features, NamedSplit
from ..packaged_modules.text.text import Text
from ..utils.typing import NestedDataStructureLike, PathLike
from .abc import AbstractDatasetReader






class    a__    (   _a	):


   def __init__(     self,				_UpperCAmelCase,				_UpperCAmelCase = None,				_UpperCAmelCase = None,				_UpperCAmelCase = None,				_UpperCAmelCase = False,				_UpperCAmelCase = False,				_UpperCAmelCase = None,				**_UpperCAmelCase,				):
        '''simple docstring'''



        super().__init__(
            _UpperCAmelCase,				split=_UpperCAmelCase,				features=_UpperCAmelCase,				cache_dir=_UpperCAmelCase,				keep_in_memory=_UpperCAmelCase,				streaming=_UpperCAmelCase,				num_proc=_UpperCAmelCase,				**_UpperCAmelCase,				)
        lowercase__				 =							path_or_paths if isinstance(_UpperCAmelCase,				_UpperCAmelCase  ) else {self.split: path_or_paths}
        lowercase__				 =							Text(
            cache_dir=_UpperCAmelCase,				data_files=_UpperCAmelCase,				features=_UpperCAmelCase,				**_UpperCAmelCase,				)


   def 	snake_case__	(     self  ):
        '''simple docstring'''



        if self.streaming:
             lowercase__				 =							self.builder.as_streaming_dataset(split=self.split  )
        # Build regular (map-style) dataset
        else:
             lowercase__				 =							None
             lowercase__				 =							None
             lowercase__				 =							None
             lowercase__				 =							None

             self.builder.download_and_prepare(
                 download_config=_UpperCAmelCase,				download_mode=_UpperCAmelCase,				verification_mode=_UpperCAmelCase,				base_path=_UpperCAmelCase,				num_proc=self.num_proc,				)
             lowercase__				 =							self.builder.as_dataset(
                 split=self.split,				verification_mode=_UpperCAmelCase,				in_memory=self.keep_in_memory  )
        return dataset




