




"""simple docstring"""




import numpy as np







def      __UpperCAmelCase     ( __UpperCamelCase	,				__UpperCamelCase	,				__UpperCamelCase = 1e-12	,				__UpperCamelCase = 1_00	,				):
			assert np.shape(__UpperCamelCase	)[0] == np.shape(__UpperCamelCase	)[1]
			# Ensure proper dimensionality.
			assert np.shape(__UpperCamelCase	)[0] == np.shape(__UpperCamelCase	)[0]
			# Ensure inputs are either both complex or both real
			assert np.iscomplexobj(__UpperCamelCase	) == np.iscomplexobj(__UpperCamelCase	)
			__lowercase			:  Tuple								=       np.iscomplexobj(__UpperCamelCase	)
			if is_complex:
						# Ensure complex input_matrix is Hermitian
						assert np.array_equal(__UpperCamelCase	,				input_matrix.conj().T	)

			# Set convergence to False. Will define convergence when we exceed max_iterations
			# or when we have small changes from one iteration to next.

			__lowercase			:  Tuple								=       False
			__lowercase			:  str								=       0
			__lowercase			:  Dict								=       0
			__lowercase			:  Any								=       1e12

			while not convergence:
						# Multiple matrix by the vector.
						__lowercase			:  List[Any]								=       np.dot(__UpperCamelCase	,				__UpperCamelCase	)
						# Normalize the resulting output vector.
						__lowercase			:  Optional[int]								=       w / np.linalg.norm(__UpperCamelCase	)
						# Find rayleigh quotient
						# (faster than usual b/c we know vector is normalized already)
						__lowercase			:  int								=       vector.conj().T if is_complex else vector.T
						__lowercase			:  str								=       np.dot(__UpperCamelCase	,				np.dot(__UpperCamelCase	,				__UpperCamelCase	)	)

						# Check convergence.
						__lowercase			:  Union[str, Any]								=       np.abs(lambda_ - lambda_previous	) / lambda_
						iterations += 1

						if error <= error_tol or iterations >= max_iterations:
									__lowercase			:  Optional[int]								=       True

						__lowercase			:  Dict								=       lambda_

			if is_complex:
						__lowercase			:  Optional[Any]								=       np.real(lambda_	)

			return lambda_, vector







def      __UpperCAmelCase     ( ):
			__lowercase			:  str								=       np.array([[41, 4, 20], [4, 26, 30], [20, 30, 50]]	)
			__lowercase			:  Any								=       np.array([41, 4, 20]	)
			__lowercase			:  int								=       real_input_matrix.astype(np.complexaaa	)
			__lowercase			:  Union[str, Any]								=       np.triu(1J * complex_input_matrix	,				1	)
			complex_input_matrix += imag_matrix
			complex_input_matrix += -1 * imag_matrix.T
			__lowercase			:  Dict								=       np.array([41, 4, 20]	).astype(np.complexaaa	)

			for problem_type in ["real", "complex"]:
						if problem_type == "real":
									__lowercase			:  str								=       real_input_matrix
									__lowercase			:  Any								=       real_vector
						elif problem_type == "complex":
									__lowercase			:  Tuple								=       complex_input_matrix
									__lowercase			:  Any								=       complex_vector

						# Our implementation.
						__lowercase			,__lowercase			:  List[Any]								=       power_iteration(__UpperCamelCase	,				__UpperCamelCase	)

						# Numpy implementation.

						# Get eigenvalues and eigenvectors using built-in numpy
						# eigh (eigh used for symmetric or hermetian matrices).
						__lowercase			,__lowercase			:  List[Any]								=       np.linalg.eigh(__UpperCamelCase	)
						# Last eigenvalue is the maximum one.
						__lowercase			:  Union[str, Any]								=       eigen_values[-1]
						# Last column in this matrix is eigenvector corresponding to largest eigenvalue.
						__lowercase			:  Optional[int]								=       eigen_vectors[:, -1]

						# Check our implementation and numpy gives close answers.
						assert np.abs(eigen_value - eigen_value_max	) <= 1e-6
						# Take absolute values element wise of each eigenvector.
						# as they are only unique to a minus sign.
						assert np.linalg.norm(np.abs(__UpperCamelCase	) - np.abs(__UpperCamelCase	)	) <= 1e-6


if __name__ == "__main__":
			import doctest

			doctest.testmod()
			test_power_iteration()











"""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_							      = logging.getLogger()

def 							snake_case (  ):
			UpperCAmelCase_	:					str     	=   argparse.ArgumentParser()
			parser.add_argument("-f"		)
			UpperCAmelCase_	:					Optional[Any]     	=   parser.parse_args()
			return args.f







class      UpperCamelCase_			(__A	):





	def 	_SCREAMING_SNAKE_CASE ( self   :					str		)		->     None:
				UpperCAmelCase_	:					List[str]     	=   logging.StreamHandler(sys.stdout		)
				logger.addHandler(lowerCAmelCase_		)





	def 	_SCREAMING_SNAKE_CASE ( self   :					int      ,      lowerCAmelCase_   :					List[str]		)		->     Tuple:
				UpperCAmelCase_	:					Optional[int]     	=   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_	:					Dict     	=   run_glue_deebert.main()
										for value in result.values():
													self.assertGreaterEqual(lowerCAmelCase_      ,      0.6_6_6		)





	@slow
	@require_torch_non_multi_gpu
	def 	_SCREAMING_SNAKE_CASE ( self   :					Dict		)		->     int:
				UpperCAmelCase_	:					Tuple     	=   "\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(lowerCAmelCase_		)

				UpperCAmelCase_	:					Union[str, Any]     	=   "\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(lowerCAmelCase_		)

				UpperCAmelCase_	:					str     	=   "\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(lowerCAmelCase_		)



