






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)

__snake_case    :    Any         =     logging.getLogger()







def 	_UpperCamelCase   (    )  ->   str:

						"""simple docstring"""



						lowerCAmelCase__    						=						argparse.ArgumentParser()
						parser.add_argument('-f'		)
						lowerCAmelCase__    						=						parser.parse_args()
						return args.f


class     __SCREAMING_SNAKE_CASE					(   __lowercase):






						def       UpperCamelCase__      (	self   ):






												"""simple docstring"""
												lowerCAmelCase__    						=						logging.StreamHandler(sys.stdout   )
												logger.addHandler(_UpperCamelCase   )






						def       UpperCamelCase__      (	self     ,						_UpperCamelCase   ):






												"""simple docstring"""
												lowerCAmelCase__    						=						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   ):
																								lowerCAmelCase__    						=						run_glue_deebert.main()
																								for value in result.values():
																														self.assertGreaterEqual(_UpperCamelCase     ,						0.6_66   )







						@slow
						@require_torch_non_multi_gpu
						def       UpperCamelCase__      (	self   ):






												"""simple docstring"""
												lowerCAmelCase__    						=						'\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   )

												lowerCAmelCase__    						=						'\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   )

												lowerCAmelCase__    						=						'\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   )













from __future__ import annotations

__snake_case    :    Any         =     {
    """A""": ["""B""", """C""", """E"""],
    """B""": ["""A""", """D""", """E"""],
    """C""": ["""A""", """F""", """G"""],
    """D""": ["""B"""],
    """E""": ["""A""", """B""", """D"""],
    """F""": ["""C"""],
    """G""": ["""C"""],
}


class     __SCREAMING_SNAKE_CASE					:






						def __init__(	self     ,						_UpperCamelCase     ,						_UpperCamelCase   ):






												"""simple docstring"""
												lowerCAmelCase__    						=						graph
												# mapping node to its parent in resulting breadth first tree
												lowerCAmelCase__    						=						{}
												lowerCAmelCase__    						=						source_vertex






						def       UpperCamelCase__      (	self   ):






												"""simple docstring"""
												lowerCAmelCase__    						=						{self.source_vertex}
												lowerCAmelCase__    						=						None
												lowerCAmelCase__    						=						[self.source_vertex]  # first in first out queue

												while queue:
																		lowerCAmelCase__    						=						queue.pop(0   )
																		for adjacent_vertex in self.graph[vertex]:
																								if adjacent_vertex not in visited:
																														visited.add(_UpperCamelCase   )
																														lowerCAmelCase__    						=						vertex
																														queue.append(_UpperCamelCase   )







						def       UpperCamelCase__      (	self     ,						_UpperCamelCase   ):






												"""simple docstring"""
												if target_vertex == self.source_vertex:
																		return self.source_vertex

												lowerCAmelCase__    						=						self.parent.get(_UpperCamelCase   )
												if target_vertex_parent is None:
																		lowerCAmelCase__    						=						(
																		    F"No path from vertex: {self.source_vertex} to vertex: {target_vertex}"
																		)
																		raise ValueError(_UpperCamelCase   )

												return self.shortest_path(_UpperCamelCase   ) + F"->{target_vertex}"


if __name__ == "__main__":
					__snake_case    :    Optional[Any]         =     Graph(graph, """G""")
					g.breath_first_search()
					print(g.shortest_path("""D"""))
					print(g.shortest_path("""G"""))
					print(g.shortest_path("""Foo"""))





