


'''simple docstring'''



from __future__ import annotations

import matplotlib.pyplot as plt  # type: ignore
import numpy

# initial triangle of Koch snowflake
__A	=numpy.array([0, 0])
__A	=numpy.array([0.5, 0.8_6_6_0_2_5_4])
__A	=numpy.array([1, 0])
__A	=[VECTOR_1, VECTOR_2, VECTOR_3, VECTOR_1]







def     _UpperCamelCase      (		UpperCamelCase__ ,      UpperCamelCase__					):
			UpperCAmelCase__  :					Union[str, Any]        =     initial_vectors
			for _ in range(UpperCamelCase__					):
						UpperCAmelCase__  :					Dict        =     iteration_step(UpperCamelCase__					)
			return vectors







def     _UpperCamelCase      (		UpperCamelCase__					):
			UpperCAmelCase__  :					Optional[Any]        =     []
			for i, start_vector in enumerate(vectors[:-1]					):
						UpperCAmelCase__  :					Tuple        =     vectors[i + 1]
						new_vectors.append(UpperCamelCase__					)
						UpperCAmelCase__  :					Optional[Any]        =     end_vector - start_vector
						new_vectors.append(start_vector + difference_vector / 3					)
						new_vectors.append(
						    start_vector + difference_vector / 3 + rotate(difference_vector / 3 ,      6_0					)					)
						new_vectors.append(start_vector + difference_vector * 2 / 3					)
			new_vectors.append(vectors[-1]					)
			return new_vectors







def     _UpperCamelCase      (		UpperCamelCase__ ,      UpperCamelCase__					):
			UpperCAmelCase__  :					Any        =     numpy.radians(UpperCamelCase__					)
			UpperCAmelCase__   ,       UpperCAmelCase__  :					int        =     numpy.cos(UpperCamelCase__					), numpy.sin(UpperCamelCase__					)
			UpperCAmelCase__  :					Dict        =     numpy.array(((c, -s), (s, c))					)
			return numpy.dot(UpperCamelCase__ ,      UpperCamelCase__					)







def     _UpperCamelCase      (		UpperCamelCase__					):
			UpperCAmelCase__  :					Any        =     plt.gca()
			axes.set_aspect("""equal"""					)

			# matplotlib.pyplot.plot takes a list of all x-coordinates and a list of all
			# y-coordinates as inputs, which are constructed from the vector-list using
			# zip()
			UpperCAmelCase__   ,       UpperCAmelCase__  :					Tuple        =     zip(*UpperCamelCase__					)
			plt.plot(UpperCamelCase__ ,      UpperCamelCase__					)
			plt.show()


if __name__ == "__main__":
		import doctest

		doctest.testmod()

		__A	=iterate(INITIAL_VECTORS, 5)
		plot(processed_vectors)



'''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	=logging.getLogger()







def     _UpperCamelCase      (		):
			UpperCAmelCase__  :					List[Any]        =     argparse.ArgumentParser()
			parser.add_argument("""-f"""					)
			UpperCAmelCase__  :					Optional[Any]        =     parser.parse_args()
			return args.f


class 		_snake_case					(     a__	):




					def 				snake_case__						(      self):
								UpperCAmelCase__  :					Tuple        =     logging.StreamHandler(sys.stdout)
								logger.addHandler(_lowerCamelCase)




					def 				snake_case__						(      self							,							_lowerCamelCase):
								UpperCAmelCase__  :					Any        =     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(_lowerCamelCase							,							"""argv"""							,							_lowerCamelCase):
														UpperCAmelCase__  :					Union[str, Any]        =     run_glue_deebert.main()
														for value in result.values():
																	self.assertGreaterEqual(_lowerCamelCase							,							0.666)




					@slow
					@require_torch_non_multi_gpu
					def 				snake_case__						(      self):
								UpperCAmelCase__  :					List[str]        =     """
            --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(_lowerCamelCase)

								UpperCAmelCase__  :					Dict        =     """
            --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(_lowerCamelCase)

								UpperCAmelCase__  :					Any        =     """
            --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(_lowerCamelCase)