
"""simple docstring"""







import unittest

from .lib import (
    Matrix,
    Vector,
    axpy,
    square_zero_matrix,
    unit_basis_vector,
    zero_vector,
)




class 			A__	(     unittest.TestCase):

		def 							__lowerCamelCase							(				self			):
			__lowerCAmelCase      :						List[Any]						      =				Vector([1, 2, 3]			)
			self.assertEqual(x.component(0			)	,		1			)
			self.assertEqual(x.component(2			)	,		3			)
			__lowerCAmelCase      :						Optional[int]						      =				Vector()

		def 							__lowerCamelCase							(				self			):
			__lowerCAmelCase      :						str						      =				Vector([0, 0, 0, 0, 0, 1]			)
			self.assertEqual(str(_SCREAMING_SNAKE_CASE			)	,		'(0,0,0,0,0,1)'			)

		def 							__lowerCamelCase							(				self			):
			__lowerCAmelCase      :						Dict						      =				Vector([1, 2, 3, 4]			)
			self.assertEqual(len(_SCREAMING_SNAKE_CASE			)	,		4			)

		def 							__lowerCamelCase							(				self			):
			__lowerCAmelCase      :						Union[str, Any]						      =				Vector([1, 2]			)
			__lowerCAmelCase      :						List[Any]						      =				Vector([1, 2, 3, 4, 5]			)
			__lowerCAmelCase      :						Optional[Any]						      =				Vector([0, 0, 0, 0, 0, 0, 0, 0, 0, 0]			)
			__lowerCAmelCase      :						Optional[int]						      =				Vector([1, -1, 1, -1, 2, -3, 4, -5]			)
			self.assertAlmostEqual(x.euclidean_length()	,		2.236	,		3			)
			self.assertAlmostEqual(y.euclidean_length()	,		7.416	,		3			)
			self.assertEqual(z.euclidean_length()	,		0			)
			self.assertAlmostEqual(w.euclidean_length()	,		7.616	,		3			)

		def 							__lowerCamelCase							(				self			):
			__lowerCAmelCase      :						Tuple						      =				Vector([1, 2, 3]			)
			__lowerCAmelCase      :						str						      =				Vector([1, 1, 1]			)
			self.assertEqual((x + y).component(0			)	,		2			)
			self.assertEqual((x + y).component(1			)	,		3			)
			self.assertEqual((x + y).component(2			)	,		4			)

		def 							__lowerCamelCase							(				self			):
			__lowerCAmelCase      :						Dict						      =				Vector([1, 2, 3]			)
			__lowerCAmelCase      :						Optional[int]						      =				Vector([1, 1, 1]			)
			self.assertEqual((x - y).component(0			)	,		0			)
			self.assertEqual((x - y).component(1			)	,		1			)
			self.assertEqual((x - y).component(2			)	,		2			)

		def 							__lowerCamelCase							(				self			):
			__lowerCAmelCase      :						Optional[int]						      =				Vector([1, 2, 3]			)
			__lowerCAmelCase      :						int						      =				Vector([2, -1, 4]			)  # for test of dot product
			__lowerCAmelCase      :						int						      =				Vector([1, -2, -1]			)
			self.assertEqual(str(x * 3.0			)	,		'(3.0,6.0,9.0)'			)
			self.assertEqual((a * b)	,		0			)

		def 							__lowerCamelCase							(				self			):
			self.assertEqual(str(zero_vector(10			)			).count('0'			)	,		10			)

		def 							__lowerCamelCase							(				self			):
			self.assertEqual(str(unit_basis_vector(3	,		1			)			)	,		'(0,1,0)'			)

		def 							__lowerCamelCase							(				self			):
			__lowerCAmelCase      :						Tuple						      =				Vector([1, 2, 3]			)
			__lowerCAmelCase      :						Tuple						      =				Vector([1, 0, 1]			)
			self.assertEqual(str(axpy(2	,		_SCREAMING_SNAKE_CASE	,		_SCREAMING_SNAKE_CASE			)			)	,		'(3,4,7)'			)

		def 							__lowerCamelCase							(				self			):
			__lowerCAmelCase      :						Tuple						      =				Vector([1, 0, 0, 0, 0, 0]			)
			__lowerCAmelCase      :						List[Any]						      =				x.copy()
			self.assertEqual(str(_SCREAMING_SNAKE_CASE			)	,		str(_SCREAMING_SNAKE_CASE			)			)

		def 							__lowerCamelCase							(				self			):
			__lowerCAmelCase      :						List[str]						      =				Vector([1, 0, 0]			)
			x.change_component(0	,		0			)
			x.change_component(1	,		1			)
			self.assertEqual(str(_SCREAMING_SNAKE_CASE			)	,		'(0,1,0)'			)

		def 							__lowerCamelCase							(				self			):
			__lowerCAmelCase      :						Optional[int]						      =				Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]	,		3	,		3			)
			self.assertEqual('|1,2,3|\n|2,4,5|\n|6,7,8|\n'	,		str(_SCREAMING_SNAKE_CASE			)			)

		def 							__lowerCamelCase							(				self			):
			__lowerCAmelCase      :						List[str]						      =				Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]	,		3	,		3			)
			__lowerCAmelCase      :						Optional[int]						      =				[[-3, -14, -10], [-5, -10, -5], [-2, -1, 0]]
			for x in range(a.height()			):
				for y in range(a.width()			):
					self.assertEqual(minors[x][y]	,		a.minor(_SCREAMING_SNAKE_CASE	,		_SCREAMING_SNAKE_CASE			)			)

		def 							__lowerCamelCase							(				self			):
			__lowerCAmelCase      :						List[Any]						      =				Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]	,		3	,		3			)
			__lowerCAmelCase      :						Optional[int]						      =				[[-3, 14, -10], [5, -10, 5], [-2, 1, 0]]
			for x in range(a.height()			):
				for y in range(a.width()			):
					self.assertEqual(cofactors[x][y]	,		a.cofactor(_SCREAMING_SNAKE_CASE	,		_SCREAMING_SNAKE_CASE			)			)

		def 							__lowerCamelCase							(				self			):
			__lowerCAmelCase      :						List[str]						      =				Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]	,		3	,		3			)
			self.assertEqual(-5	,		a.determinant()			)

		def 							__lowerCamelCase							(				self			):
			__lowerCAmelCase      :						Optional[int]						      =				Matrix([[1, 2, 3], [4, 5, 6], [7, 8, 9]]	,		3	,		3			)
			__lowerCAmelCase      :						Tuple						      =				Vector([1, 2, 3]			)
			self.assertEqual('(14,32,50)'	,		str(a * x			)			)
			self.assertEqual('|2,4,6|\n|8,10,12|\n|14,16,18|\n'	,		str(a * 2			)			)

		def 							__lowerCamelCase							(				self			):
			__lowerCAmelCase      :						int						      =				Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]	,		3	,		3			)
			a.change_component(0	,		2	,		5			)
			self.assertEqual('|1,2,5|\n|2,4,5|\n|6,7,8|\n'	,		str(_SCREAMING_SNAKE_CASE			)			)

		def 							__lowerCamelCase							(				self			):
			__lowerCAmelCase      :						List[Any]						      =				Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]	,		3	,		3			)
			self.assertEqual(7	,		a.component(2	,		1			)	,		0.01			)

		def 							__lowerCamelCase							(				self			):
			__lowerCAmelCase      :						Union[str, Any]						      =				Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]	,		3	,		3			)
			__lowerCAmelCase      :						List[str]						      =				Matrix([[1, 2, 7], [2, 4, 5], [6, 7, 10]]	,		3	,		3			)
			self.assertEqual('|2,4,10|\n|4,8,10|\n|12,14,18|\n'	,		str(a + b			)			)

		def 							__lowerCamelCase							(				self			):
			__lowerCAmelCase      :						List[str]						      =				Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]	,		3	,		3			)
			__lowerCAmelCase      :						List[Any]						      =				Matrix([[1, 2, 7], [2, 4, 5], [6, 7, 10]]	,		3	,		3			)
			self.assertEqual('|0,0,-4|\n|0,0,0|\n|0,0,-2|\n'	,		str(a - b			)			)







		def 							__lowerCamelCase							(				self			):
			self.assertEqual(
			    '|0,0,0,0,0|\n|0,0,0,0,0|\n|0,0,0,0,0|\n|0,0,0,0,0|\n|0,0,0,0,0|\n'	,		str(square_zero_matrix(5			)			)	,		)


if __name__ == "__main__":
							unittest.main()

"""simple docstring"""







import os
import tempfile
import unittest
from pathlib import Path

from transformers import AutoConfig, is_tf_available
from transformers.testing_utils import require_tf


if is_tf_available():
							import tensorflow as tf

							from transformers import TensorFlowBenchmark, TensorFlowBenchmarkArguments




@require_tf
class 			A__	(     unittest.TestCase):

		def 							__lowerCamelCase							(				self	,		_SCREAMING_SNAKE_CASE			):
			for model_result in results.values():
				for batch_size, sequence_length in zip(model_result['bs']	,		model_result['ss']			):
					__lowerCAmelCase      :						Optional[Any]						      =				model_result['result'][batch_size][sequence_length]
					self.assertIsNotNone(_SCREAMING_SNAKE_CASE			)

		def 							__lowerCamelCase							(				self			):
			__lowerCAmelCase      :						Dict						      =				'sshleifer/tiny-gpt2'
			__lowerCAmelCase      :						int						      =				TensorFlowBenchmarkArguments(
			    models=[MODEL_ID]	,		training=_SCREAMING_SNAKE_CASE	,		inference=_SCREAMING_SNAKE_CASE	,		sequence_lengths=[8]	,		batch_sizes=[1]	,		eager_mode=_SCREAMING_SNAKE_CASE	,		multi_process=_SCREAMING_SNAKE_CASE	,		)
			__lowerCAmelCase      :						Tuple						      =				TensorFlowBenchmark(_SCREAMING_SNAKE_CASE			)
			__lowerCAmelCase      :						Optional[int]						      =				benchmark.run()
			self.check_results_dict_not_empty(results.time_inference_result			)
			self.check_results_dict_not_empty(results.memory_inference_result			)

		def 							__lowerCamelCase							(				self			):
			__lowerCAmelCase      :						int						      =				'sgugger/tiny-distilbert-classification'
			__lowerCAmelCase      :						Any						      =				TensorFlowBenchmarkArguments(
			    models=[MODEL_ID]	,		training=_SCREAMING_SNAKE_CASE	,		inference=_SCREAMING_SNAKE_CASE	,		sequence_lengths=[8]	,		batch_sizes=[1]	,		multi_process=_SCREAMING_SNAKE_CASE	,		only_pretrain_model=_SCREAMING_SNAKE_CASE	,		)
			__lowerCAmelCase      :						Optional[int]						      =				TensorFlowBenchmark(_SCREAMING_SNAKE_CASE			)
			__lowerCAmelCase      :						Optional[Any]						      =				benchmark.run()
			self.check_results_dict_not_empty(results.time_inference_result			)
			self.check_results_dict_not_empty(results.memory_inference_result			)

		def 							__lowerCamelCase							(				self			):
			__lowerCAmelCase      :						Optional[int]						      =				'sshleifer/tiny-gpt2'
			__lowerCAmelCase      :						str						      =				TensorFlowBenchmarkArguments(
			    models=[MODEL_ID]	,		training=_SCREAMING_SNAKE_CASE	,		inference=_SCREAMING_SNAKE_CASE	,		sequence_lengths=[8]	,		batch_sizes=[1]	,		multi_process=_SCREAMING_SNAKE_CASE	,		)
			__lowerCAmelCase      :						List[str]						      =				TensorFlowBenchmark(_SCREAMING_SNAKE_CASE			)
			__lowerCAmelCase      :						Tuple						      =				benchmark.run()
			self.check_results_dict_not_empty(results.time_inference_result			)
			self.check_results_dict_not_empty(results.memory_inference_result			)

		def 							__lowerCamelCase							(				self			):
			__lowerCAmelCase      :						Union[str, Any]						      =				'sshleifer/tiny-gpt2'
			__lowerCAmelCase      :						int						      =				AutoConfig.from_pretrained(_SCREAMING_SNAKE_CASE			)
			__lowerCAmelCase      :						Any						      =				TensorFlowBenchmarkArguments(
			    models=[MODEL_ID]	,		training=_SCREAMING_SNAKE_CASE	,		inference=_SCREAMING_SNAKE_CASE	,		sequence_lengths=[8]	,		batch_sizes=[1]	,		eager_mode=_SCREAMING_SNAKE_CASE	,		multi_process=_SCREAMING_SNAKE_CASE	,		)
			__lowerCAmelCase      :						Dict						      =				TensorFlowBenchmark(_SCREAMING_SNAKE_CASE	,		[config]			)
			__lowerCAmelCase      :						str						      =				benchmark.run()
			self.check_results_dict_not_empty(results.time_inference_result			)
			self.check_results_dict_not_empty(results.memory_inference_result			)

		def 							__lowerCamelCase							(				self			):
			__lowerCAmelCase      :						List[Any]						      =				'sshleifer/tiny-gpt2'
			__lowerCAmelCase      :						Tuple						      =				AutoConfig.from_pretrained(_SCREAMING_SNAKE_CASE			)
			__lowerCAmelCase      :						int						      =				TensorFlowBenchmarkArguments(
			    models=[MODEL_ID]	,		training=_SCREAMING_SNAKE_CASE	,		inference=_SCREAMING_SNAKE_CASE	,		sequence_lengths=[8]	,		batch_sizes=[1]	,		multi_process=_SCREAMING_SNAKE_CASE	,		)
			__lowerCAmelCase      :						Any						      =				TensorFlowBenchmark(_SCREAMING_SNAKE_CASE	,		[config]			)
			__lowerCAmelCase      :						Dict						      =				benchmark.run()
			self.check_results_dict_not_empty(results.time_inference_result			)
			self.check_results_dict_not_empty(results.memory_inference_result			)

		def 							__lowerCamelCase							(				self			):
			__lowerCAmelCase      :						Any						      =				'sshleifer/tiny-gpt2'
			__lowerCAmelCase      :						str						      =				TensorFlowBenchmarkArguments(
			    models=[MODEL_ID]	,		training=_SCREAMING_SNAKE_CASE	,		inference=_SCREAMING_SNAKE_CASE	,		sequence_lengths=[8]	,		batch_sizes=[1]	,		multi_process=_SCREAMING_SNAKE_CASE	,		)
			__lowerCAmelCase      :						str						      =				TensorFlowBenchmark(_SCREAMING_SNAKE_CASE			)
			__lowerCAmelCase      :						List[str]						      =				benchmark.run()
			self.check_results_dict_not_empty(results.time_train_result			)
			self.check_results_dict_not_empty(results.memory_train_result			)

		def 							__lowerCamelCase							(				self			):
			__lowerCAmelCase      :						List[str]						      =				'sshleifer/tiny-gpt2'
			__lowerCAmelCase      :						Any						      =				AutoConfig.from_pretrained(_SCREAMING_SNAKE_CASE			)
			__lowerCAmelCase      :						List[str]						      =				TensorFlowBenchmarkArguments(
			    models=[MODEL_ID]	,		training=_SCREAMING_SNAKE_CASE	,		inference=_SCREAMING_SNAKE_CASE	,		sequence_lengths=[8]	,		batch_sizes=[1]	,		multi_process=_SCREAMING_SNAKE_CASE	,		)
			__lowerCAmelCase      :						List[Any]						      =				TensorFlowBenchmark(_SCREAMING_SNAKE_CASE	,		[config]			)
			__lowerCAmelCase      :						List[Any]						      =				benchmark.run()
			self.check_results_dict_not_empty(results.time_train_result			)
			self.check_results_dict_not_empty(results.memory_train_result			)

		def 							__lowerCamelCase							(				self			):
			__lowerCAmelCase      :						Optional[int]						      =				'patrickvonplaten/t5-tiny-random'
			__lowerCAmelCase      :						int						      =				AutoConfig.from_pretrained(_SCREAMING_SNAKE_CASE			)
			__lowerCAmelCase      :						List[str]						      =				TensorFlowBenchmarkArguments(
			    models=[MODEL_ID]	,		training=_SCREAMING_SNAKE_CASE	,		inference=_SCREAMING_SNAKE_CASE	,		sequence_lengths=[8]	,		batch_sizes=[1]	,		multi_process=_SCREAMING_SNAKE_CASE	,		)
			__lowerCAmelCase      :						Dict						      =				TensorFlowBenchmark(_SCREAMING_SNAKE_CASE	,		configs=[config]			)
			__lowerCAmelCase      :						Any						      =				benchmark.run()
			self.check_results_dict_not_empty(results.time_inference_result			)
			self.check_results_dict_not_empty(results.memory_inference_result			)

		@unittest.skipIf(is_tf_available() and len(tf.config.list_physical_devices('GPU'			)			) == 0	,		'Cannot do xla on CPU.'			)
		def 							__lowerCamelCase							(				self			):
			__lowerCAmelCase      :						List[str]						      =				'sshleifer/tiny-gpt2'
			__lowerCAmelCase      :						List[Any]						      =				TensorFlowBenchmarkArguments(
			    models=[MODEL_ID]	,		training=_SCREAMING_SNAKE_CASE	,		inference=_SCREAMING_SNAKE_CASE	,		sequence_lengths=[8]	,		batch_sizes=[1]	,		use_xla=_SCREAMING_SNAKE_CASE	,		multi_process=_SCREAMING_SNAKE_CASE	,		)
			__lowerCAmelCase      :						Optional[int]						      =				TensorFlowBenchmark(_SCREAMING_SNAKE_CASE			)
			__lowerCAmelCase      :						Dict						      =				benchmark.run()
			self.check_results_dict_not_empty(results.time_inference_result			)
			self.check_results_dict_not_empty(results.memory_inference_result			)

		def 							__lowerCamelCase							(				self			):
			__lowerCAmelCase      :						Optional[int]						      =				'sshleifer/tiny-gpt2'
			with tempfile.TemporaryDirectory() as tmp_dir:
				__lowerCAmelCase      :						List[str]						      =				TensorFlowBenchmarkArguments(
				    models=[MODEL_ID]	,		inference=_SCREAMING_SNAKE_CASE	,		save_to_csv=_SCREAMING_SNAKE_CASE	,		sequence_lengths=[8]	,		batch_sizes=[1]	,		inference_time_csv_file=os.path.join(_SCREAMING_SNAKE_CASE	,		'inf_time.csv'			)	,		inference_memory_csv_file=os.path.join(_SCREAMING_SNAKE_CASE	,		'inf_mem.csv'			)	,		env_info_csv_file=os.path.join(_SCREAMING_SNAKE_CASE	,		'env.csv'			)	,		multi_process=_SCREAMING_SNAKE_CASE	,		)
				__lowerCAmelCase      :						Tuple						      =				TensorFlowBenchmark(_SCREAMING_SNAKE_CASE			)
				benchmark.run()
				self.assertTrue(Path(os.path.join(_SCREAMING_SNAKE_CASE	,		'inf_time.csv'			)			).exists()			)
				self.assertTrue(Path(os.path.join(_SCREAMING_SNAKE_CASE	,		'inf_mem.csv'			)			).exists()			)
				self.assertTrue(Path(os.path.join(_SCREAMING_SNAKE_CASE	,		'env.csv'			)			).exists()			)







		def 							__lowerCamelCase							(				self			):
			__lowerCAmelCase      :						Tuple						      =				'sshleifer/tiny-gpt2'

			def _check_summary_is_not_empty(_SCREAMING_SNAKE_CASE			):
				self.assertTrue(hasattr(_SCREAMING_SNAKE_CASE	,		'sequential'			)			)
				self.assertTrue(hasattr(_SCREAMING_SNAKE_CASE	,		'cumulative'			)			)
				self.assertTrue(hasattr(_SCREAMING_SNAKE_CASE	,		'current'			)			)
				self.assertTrue(hasattr(_SCREAMING_SNAKE_CASE	,		'total'			)			)

			with tempfile.TemporaryDirectory() as tmp_dir:
				__lowerCAmelCase      :						Any						      =				TensorFlowBenchmarkArguments(
				    models=[MODEL_ID]	,		inference=_SCREAMING_SNAKE_CASE	,		sequence_lengths=[8]	,		batch_sizes=[1]	,		log_filename=os.path.join(_SCREAMING_SNAKE_CASE	,		'log.txt'			)	,		log_print=_SCREAMING_SNAKE_CASE	,		trace_memory_line_by_line=_SCREAMING_SNAKE_CASE	,		eager_mode=_SCREAMING_SNAKE_CASE	,		multi_process=_SCREAMING_SNAKE_CASE	,		)
				__lowerCAmelCase      :						Any						      =				TensorFlowBenchmark(_SCREAMING_SNAKE_CASE			)
				__lowerCAmelCase      :						int						      =				benchmark.run()
				_check_summary_is_not_empty(result.inference_summary			)
				self.assertTrue(Path(os.path.join(_SCREAMING_SNAKE_CASE	,		'log.txt'			)			).exists()			)