


"""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__    :							str            =					logging.getLogger()




def        UpperCAmelCase__	():




					'''simple docstring'''


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




class 			UpperCamelCase_     (			__lowercase):

	"""simple docstring"""





	def   UpperCAmelCase_				(			self      :    Tuple       )	->     int:
						__SCREAMING_SNAKE_CASE						       =    logging.StreamHandler(sys.stdout       )
						logger.addHandler(snake_case_       )




	def   UpperCAmelCase_				(			self      :    int      ,      UpperCAmelCase__      :    Any       )	->     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(snake_case_      ,      "argv"      ,      snake_case_       ):
																__SCREAMING_SNAKE_CASE						       =    run_glue_deebert.main()
																for value in result.values():
																					self.assertGreaterEqual(snake_case_      ,      0.666       )




	@slow
	@require_torch_non_multi_gpu
	def   UpperCAmelCase_				(			self      :    List[Any]       )	->     List[str]:
						__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(snake_case_       )

						__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(snake_case_       )

						__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(snake_case_       )









"""simple docstring"""







from __future__ import annotations

import requests




def        UpperCAmelCase__	(lowerCAmelCase_       ):




					'''simple docstring'''


					__SCREAMING_SNAKE_CASE						       =    f"""https://hacker-news.firebaseio.com/v0/item/{story_id}.json?print=pretty"""
					return requests.get(lowerCAmelCase_       ).json()




def        UpperCAmelCase__	(lowerCAmelCase_ = 10       ):




					'''simple docstring'''


					__SCREAMING_SNAKE_CASE						       =    "https://hacker-news.firebaseio.com/v0/topstories.json?print=pretty"
					__SCREAMING_SNAKE_CASE						       =    requests.get(lowerCAmelCase_       ).json()[:max_stories]
					return [get_hackernews_story(lowerCAmelCase_       ) for story_id in story_ids]




def        UpperCAmelCase__	(lowerCAmelCase_ = 10       ):




					'''simple docstring'''


					__SCREAMING_SNAKE_CASE						       =    hackernews_top_stories(lowerCAmelCase_       )
					return "\n".join("* [{title}]({url})".format(**lowerCAmelCase_       ) for story in stories       )


if __name__ == "__main__":
		print(hackernews_top_stories_as_markdown())
