


import unittest

from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch

class 						__a (							unittest.TestCase     ):
		_a      :    int           =      JukeboxTokenizer
		_a      :    Optional[int]           =      {
		    'artist': 'Zac Brown Band',
		    'genres': 'Country',
		    'lyrics': 'I met a traveller from an antique land,\n        Who said "Two vast and trunkless legs of stone\n        Stand in the desert. . . . Near them, on the sand,\n        Half sunk a shattered visage lies, whose frown,\n        And wrinkled lip, and sneer of cold command,\n        Tell that its sculptor well those passions read\n        Which yet survive, stamped on these lifeless things,\n        The hand that mocked them, and the heart that fed;\n        And on the pedestal, these words appear:\n        My name is Ozymandias, King of Kings;\n        Look on my Works, ye Mighty, and despair!\n        Nothing beside remains. Round the decay\n        Of that colossal Wreck, boundless and bare\n        The lone and level sands stretch far away\n        ',
		}
		@require_torch
		def       UpperCAmelCase__							(     self		)					->			List[str]:




									"""simple docstring"""





									import torch

									_UpperCAmelCase											=     JukeboxTokenizer.from_pretrained('openai/jukebox-1b-lyrics'		)
									_UpperCAmelCase											=     tokenizer(**self.metas		)['input_ids']
									# fmt: off
									_UpperCAmelCase											=     [
									    torch.tensor([[
									        0, 0, 0, 7169, 507, 9, 76, 39, 31, 46, 76, 27,
									        76, 46, 44, 27, 48, 31, 38, 38, 31, 44, 76, 32,
									        44, 41, 39, 76, 27, 40, 76, 27, 40, 46, 35, 43,
									        47, 31, 76, 38, 27, 40, 30, 64, 78, 76, 76, 76,
									        76, 76, 76, 76, 76, 23, 34, 41, 76, 45, 27, 35,
									        30, 76, 71, 20, 49, 41, 76, 48, 27, 45, 46, 76,
									        27, 40, 30, 76, 46, 44, 47, 40, 37, 38, 31, 45,
									        45, 76, 38, 31, 33, 45, 76, 41, 32, 76, 45, 46,
									        41, 40, 31, 78, 76, 76, 76, 76, 76, 76, 76, 76,
									        19, 46, 27, 40, 30, 76, 35, 40, 76, 46, 34, 31,
									        76, 30, 31, 45, 31, 44, 46, 63, 76, 63, 76, 63,
									        76, 63, 76, 14, 31, 27, 44, 76, 46, 34, 31, 39,
									        64, 76, 41, 40, 76, 46, 34, 31, 76, 45, 27, 40,
									        30, 64, 78, 76, 76, 76, 76, 76, 76, 76, 76, 8,
									        27, 38, 32, 76, 45, 47, 40, 37, 76, 27, 76, 45,
									        34, 27, 46, 46, 31, 44, 31, 30, 76, 48, 35, 45,
									        27, 33, 31, 76, 38, 35, 31, 45, 64, 76, 49, 34,
									        41, 45, 31, 76, 32, 44, 41, 49, 40, 64, 78, 76,
									        76, 76, 76, 76, 76, 76, 76, 1, 40, 30, 76, 49,
									        44, 35, 40, 37, 38, 31, 30, 76, 38, 35, 42, 64,
									        76, 27, 40, 30, 76, 45, 40, 31, 31, 44, 76, 41,
									        32, 76, 29, 41, 38, 30, 76, 29, 41, 39, 39, 27,
									        40, 30, 64, 78, 76, 76, 76, 76, 76, 76, 76, 76,
									        20, 31, 38, 38, 76, 46, 34, 27, 46, 76, 35, 46,
									        45, 76, 45, 29, 47, 38, 42, 46, 41, 44, 76, 49,
									        31, 38, 38, 76, 46, 34, 41, 45, 31, 76, 42, 27,
									        45, 45, 35, 41, 40, 45, 76, 44, 31, 27, 30, 78,
									        76, 76, 76, 76, 76, 76, 76, 76, 23, 34, 35, 29,
									        34, 76, 51, 31, 46, 76, 45, 47, 44, 48, 35, 48,
									        31, 64, 76, 45, 46, 27, 39, 42, 31, 30, 76, 41,
									        40, 76, 46, 34, 31, 45, 31, 76, 38, 35, 32, 31,
									        38, 31, 45, 45, 76, 46, 34, 35, 40, 33, 45, 64,
									        78, 76, 76, 76, 76, 76, 76, 76, 76, 20, 34, 31,
									        76, 34, 27, 40, 30, 76, 46, 34, 27, 46, 76, 39,
									        41, 29, 37, 31, 30, 76, 46, 34, 31, 39, 64, 76,
									        27, 40, 30, 76, 46, 34, 31, 76, 34, 31, 27, 44,
									        46, 76, 46, 34, 27, 46, 76, 32, 31, 30, 66, 78,
									        76, 76, 76, 76, 76, 76, 76, 76, 1, 40, 30, 76,
									        41, 40, 76, 46, 34, 31, 76, 42, 31, 30, 31, 45,
									        46, 27, 38, 64, 76, 46, 34, 31, 45, 31, 76, 49,
									        41, 44, 30, 45, 76, 27, 42, 42, 31, 27, 44, 65,
									        78, 76, 76, 76, 76, 76, 76, 76, 76, 13, 51, 76,
									        40, 27, 39, 31, 76, 35, 45, 76, 15, 52, 51, 39,
									        27, 40, 30, 35, 27, 45, 64, 76, 11, 35, 40, 33,
									        76, 41, 32, 76, 11, 35, 40, 33, 45, 66, 78, 76,
									        76, 76, 76, 76, 76, 76, 76, 12, 41, 41, 37, 76,
									        41, 40, 76, 39, 51, 76, 23, 41, 44, 37, 45, 64,
									        76, 51, 31, 76, 13, 35, 33, 34, 46, 51, 64, 76,
									        27, 40, 30, 76, 30, 31, 45, 42, 27, 35, 44, 67,
									        78, 76, 76, 76, 76, 76, 76, 76, 76, 14, 41, 46,
									        34, 35, 40, 33, 76, 28, 31, 45, 35, 30, 31, 76,
									        44, 31, 39, 27, 35, 40, 45, 63, 76, 18, 41, 47,
									        40, 30, 76, 46, 34, 31, 76, 30, 31, 29, 27, 51,
									        78, 76, 76, 76, 76, 76, 76, 76, 76, 15, 32, 76,
									        46, 34, 27, 46, 76, 29, 41, 38, 41, 45, 45, 27,
									        38, 76, 23, 44, 31, 29, 37, 64, 76, 28, 41, 47,
									        40, 30, 38, 31, 45, 45, 76, 27, 40, 30, 76, 28,
									        27, 44, 31, 78, 76, 76, 76, 76, 76, 76, 76, 76,
									        20, 34, 31, 76, 38, 41, 40, 31, 76, 27, 40, 30,
									        76, 38, 31, 48, 31, 38, 76, 45, 27, 40, 30, 45,
									        76, 45, 46, 44, 31, 46, 29, 34, 76, 32, 27, 44,
									        76, 27, 49, 27, 51, 78, 76, 76, 76, 76, 76, 76,
									        76, 76]]		),
									    torch.tensor([[0, 0, 0, 1069, 11]]		),
									    torch.tensor([[0, 0, 0, 1069, 11]]		),
									]
									# fmt: on
									self.assertTrue(torch.allclose(tokens[0]     ,       EXPECTED_OUTPUT[0]		)		)
									self.assertTrue(torch.allclose(tokens[1]     ,       EXPECTED_OUTPUT[1]		)		)
									self.assertTrue(torch.allclose(tokens[2]     ,       EXPECTED_OUTPUT[2]		)		)






		@require_torch
		def       UpperCAmelCase__							(     self		)					->			List[Any]:




									"""simple docstring"""





									import torch

									_UpperCAmelCase											=     JukeboxTokenizer.from_pretrained('openai/jukebox-5b-lyrics'		)
									_UpperCAmelCase											=     tokenizer(**self.metas		)['input_ids']
									# fmt: off
									_UpperCAmelCase											=     [
									    torch.tensor([[
									        0, 0, 0, 1069, 11, -1, -1, -1, -1, 9, 77, 39,
									        31, 46, 77, 27, 77, 46, 44, 27, 48, 31, 38, 38,
									        31, 44, 77, 32, 44, 41, 39, 77, 27, 40, 77, 27,
									        40, 46, 35, 43, 47, 31, 77, 38, 27, 40, 30, 64,
									        79, 77, 77, 77, 77, 77, 77, 77, 77, 23, 34, 41,
									        77, 45, 27, 35, 30, 77, 72, 20, 49, 41, 77, 48,
									        27, 45, 46, 77, 27, 40, 30, 77, 46, 44, 47, 40,
									        37, 38, 31, 45, 45, 77, 38, 31, 33, 45, 77, 41,
									        32, 77, 45, 46, 41, 40, 31, 79, 77, 77, 77, 77,
									        77, 77, 77, 77, 19, 46, 27, 40, 30, 77, 35, 40,
									        77, 46, 34, 31, 77, 30, 31, 45, 31, 44, 46, 63,
									        77, 63, 77, 63, 77, 63, 77, 14, 31, 27, 44, 77,
									        46, 34, 31, 39, 64, 77, 41, 40, 77, 46, 34, 31,
									        77, 45, 27, 40, 30, 64, 79, 77, 77, 77, 77, 77,
									        77, 77, 77, 8, 27, 38, 32, 77, 45, 47, 40, 37,
									        77, 27, 77, 45, 34, 27, 46, 46, 31, 44, 31, 30,
									        77, 48, 35, 45, 27, 33, 31, 77, 38, 35, 31, 45,
									        64, 77, 49, 34, 41, 45, 31, 77, 32, 44, 41, 49,
									        40, 64, 79, 77, 77, 77, 77, 77, 77, 77, 77, 1,
									        40, 30, 77, 49, 44, 35, 40, 37, 38, 31, 30, 77,
									        38, 35, 42, 64, 77, 27, 40, 30, 77, 45, 40, 31,
									        31, 44, 77, 41, 32, 77, 29, 41, 38, 30, 77, 29,
									        41, 39, 39, 27, 40, 30, 64, 79, 77, 77, 77, 77,
									        77, 77, 77, 77, 20, 31, 38, 38, 77, 46, 34, 27,
									        46, 77, 35, 46, 45, 77, 45, 29, 47, 38, 42, 46,
									        41, 44, 77, 49, 31, 38, 38, 77, 46, 34, 41, 45,
									        31, 77, 42, 27, 45, 45, 35, 41, 40, 45, 77, 44,
									        31, 27, 30, 79, 77, 77, 77, 77, 77, 77, 77, 77,
									        23, 34, 35, 29, 34, 77, 51, 31, 46, 77, 45, 47,
									        44, 48, 35, 48, 31, 64, 77, 45, 46, 27, 39, 42,
									        31, 30, 77, 41, 40, 77, 46, 34, 31, 45, 31, 77,
									        38, 35, 32, 31, 38, 31, 45, 45, 77, 46, 34, 35,
									        40, 33, 45, 64, 79, 77, 77, 77, 77, 77, 77, 77,
									        77, 20, 34, 31, 77, 34, 27, 40, 30, 77, 46, 34,
									        27, 46, 77, 39, 41, 29, 37, 31, 30, 77, 46, 34,
									        31, 39, 64, 77, 27, 40, 30, 77, 46, 34, 31, 77,
									        34, 31, 27, 44, 46, 77, 46, 34, 27, 46, 77, 32,
									        31, 30, 66, 79, 77, 77, 77, 77, 77, 77, 77, 77,
									        1, 40, 30, 77, 41, 40, 77, 46, 34, 31, 77, 42,
									        31, 30, 31, 45, 46, 27, 38, 64, 77, 46, 34, 31,
									        45, 31, 77, 49, 41, 44, 30, 45, 77, 27, 42, 42,
									        31, 27, 44, 65, 79, 77, 77, 77, 77, 77, 77, 77,
									        77, 13, 51, 77, 40, 27, 39, 31, 77, 35, 45, 77,
									        15, 52, 51, 39, 27, 40, 30, 35, 27, 45, 64, 77,
									        11, 35, 40, 33, 77, 41, 32, 77, 11, 35, 40, 33,
									        45, 66, 79, 77, 77, 77, 77, 77, 77, 77, 77, 12,
									        41, 41, 37, 77, 41, 40, 77, 39, 51, 77, 23, 41,
									        44, 37, 45, 64, 77, 51, 31, 77, 13, 35, 33, 34,
									        46, 51, 64, 77, 27, 40, 30, 77, 30, 31, 45, 42,
									        27, 35, 44, 67, 79, 77, 77, 77, 77, 77, 77, 77,
									        77, 14, 41, 46, 34, 35, 40, 33, 77, 28, 31, 45,
									        35, 30, 31, 77, 44, 31, 39, 27, 35, 40, 45, 63,
									        77, 18, 41, 47, 40, 30, 77, 46, 34, 31, 77, 30,
									        31, 29, 27, 51, 79, 77, 77, 77, 77, 77, 77, 77,
									        77, 15, 32, 77, 46, 34, 27, 46, 77, 29, 41, 38,
									        41, 45, 45, 27, 38, 77, 23, 44, 31, 29, 37, 64,
									        77, 28, 41, 47, 40, 30, 38, 31, 45, 45, 77, 27,
									        40, 30, 77, 28, 27, 44, 31, 79, 77, 77, 77, 77,
									        77, 77, 77, 77, 20, 34, 31, 77, 38, 41, 40, 31,
									        77, 27, 40, 30, 77, 38, 31, 48, 31, 38, 77, 45,
									        27, 40, 30, 45, 77, 45, 46, 44, 31, 46, 29, 34,
									        77, 32, 27, 44, 77, 27, 49, 27, 51, 79, 77, 77,
									        77, 77, 77, 77, 77, 77]]		),
									    torch.tensor([[0, 0, 0, 1069, 11, -1, -1, -1, -1]]		),
									    torch.tensor([[0, 0, 0, 1069, 11, -1, -1, -1, -1]]		),
									]
									# fmt: on
									self.assertTrue(torch.allclose(tokens[0]     ,       EXPECTED_OUTPUT[0]		)		)
									self.assertTrue(torch.allclose(tokens[1]     ,       EXPECTED_OUTPUT[1]		)		)
									self.assertTrue(torch.allclose(tokens[2]     ,       EXPECTED_OUTPUT[2]		)		)




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       UpperCAmelCase__							(     self     ,       _SCREAMING_SNAKE_CASE		)					->			List[str]:




									"""simple docstring"""





									for model_result in results.values():
																for batch_size, sequence_length in zip(model_result['bs']     ,       model_result['ss']		):
																							_UpperCAmelCase											=     model_result['result'][batch_size][sequence_length]
																							self.assertIsNotNone(_SCREAMING_SNAKE_CASE		)
		def       UpperCAmelCase__							(     self		)					->			Optional[int]:




									"""simple docstring"""





									_UpperCAmelCase											=     'sshleifer/tiny-gpt2'
									_UpperCAmelCase											=     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     ,       )
									_UpperCAmelCase											=     TensorFlowBenchmark(_SCREAMING_SNAKE_CASE		)
									_UpperCAmelCase											=     benchmark.run()
									self.check_results_dict_not_empty(results.time_inference_result		)
									self.check_results_dict_not_empty(results.memory_inference_result		)
		def       UpperCAmelCase__							(     self		)					->			int:




									"""simple docstring"""





									_UpperCAmelCase											=     'sgugger/tiny-distilbert-classification'
									_UpperCAmelCase											=     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     ,       )
									_UpperCAmelCase											=     TensorFlowBenchmark(_SCREAMING_SNAKE_CASE		)
									_UpperCAmelCase											=     benchmark.run()
									self.check_results_dict_not_empty(results.time_inference_result		)
									self.check_results_dict_not_empty(results.memory_inference_result		)
		def       UpperCAmelCase__							(     self		)					->			List[Any]:




									"""simple docstring"""





									_UpperCAmelCase											=     'sshleifer/tiny-gpt2'
									_UpperCAmelCase											=     TensorFlowBenchmarkArguments(
									    models=[MODEL_ID]     ,       training=_SCREAMING_SNAKE_CASE     ,       inference=_SCREAMING_SNAKE_CASE     ,       sequence_lengths=[8]     ,       batch_sizes=[1]     ,       multi_process=_SCREAMING_SNAKE_CASE     ,       )
									_UpperCAmelCase											=     TensorFlowBenchmark(_SCREAMING_SNAKE_CASE		)
									_UpperCAmelCase											=     benchmark.run()
									self.check_results_dict_not_empty(results.time_inference_result		)
									self.check_results_dict_not_empty(results.memory_inference_result		)
		def       UpperCAmelCase__							(     self		)					->			List[Any]:




									"""simple docstring"""





									_UpperCAmelCase											=     'sshleifer/tiny-gpt2'
									_UpperCAmelCase											=     AutoConfig.from_pretrained(_SCREAMING_SNAKE_CASE		)
									_UpperCAmelCase											=     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     ,       )
									_UpperCAmelCase											=     TensorFlowBenchmark(_SCREAMING_SNAKE_CASE     ,       [config]		)
									_UpperCAmelCase											=     benchmark.run()
									self.check_results_dict_not_empty(results.time_inference_result		)
									self.check_results_dict_not_empty(results.memory_inference_result		)
		def       UpperCAmelCase__							(     self		)					->			List[Any]:




									"""simple docstring"""





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




									"""simple docstring"""





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




									"""simple docstring"""





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




									"""simple docstring"""





									_UpperCAmelCase											=     'patrickvonplaten/t5-tiny-random'
									_UpperCAmelCase											=     AutoConfig.from_pretrained(_SCREAMING_SNAKE_CASE		)
									_UpperCAmelCase											=     TensorFlowBenchmarkArguments(
									    models=[MODEL_ID]     ,       training=_SCREAMING_SNAKE_CASE     ,       inference=_SCREAMING_SNAKE_CASE     ,       sequence_lengths=[8]     ,       batch_sizes=[1]     ,       multi_process=_SCREAMING_SNAKE_CASE     ,       )
									_UpperCAmelCase											=     TensorFlowBenchmark(_SCREAMING_SNAKE_CASE     ,       configs=[config]		)
									_UpperCAmelCase											=     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       UpperCAmelCase__							(     self		)					->			int:




									"""simple docstring"""





									_UpperCAmelCase											=     'sshleifer/tiny-gpt2'
									_UpperCAmelCase											=     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     ,       )
									_UpperCAmelCase											=     TensorFlowBenchmark(_SCREAMING_SNAKE_CASE		)
									_UpperCAmelCase											=     benchmark.run()
									self.check_results_dict_not_empty(results.time_inference_result		)
									self.check_results_dict_not_empty(results.memory_inference_result		)
		def       UpperCAmelCase__							(     self		)					->			str:




									"""simple docstring"""





									_UpperCAmelCase											=     'sshleifer/tiny-gpt2'
									with tempfile.TemporaryDirectory() as tmp_dir:
																_UpperCAmelCase											=     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     ,       )
																_UpperCAmelCase											=     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       UpperCAmelCase__							(     self		)					->			Tuple:




									"""simple docstring"""





									_UpperCAmelCase											=     '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:
																_UpperCAmelCase											=     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     ,       )
																_UpperCAmelCase											=     TensorFlowBenchmark(_SCREAMING_SNAKE_CASE		)
																_UpperCAmelCase											=     benchmark.run()
																_check_summary_is_not_empty(result.inference_summary		)
																self.assertTrue(Path(os.path.join(_SCREAMING_SNAKE_CASE     ,       'log.txt'		)		).exists()		)
