





import dataclasses
import json
import warnings
from dataclasses import dataclass, field
from time import time
from typing import List

from ..utils import logging


UpperCAmelCase_      							=     logging.get_logger(__name__)





def 						lowerCamelCase__     (     UpperCamelCase__			:       List[str]=None       ,    UpperCamelCase__			:       str=None						)			-> Dict:



					'''simple docstring'''




					return field(default_factory=lambda: default       ,    metadata=lowerCamelCase__						)




@dataclass
class 			UpperCamelCase_		:
					lowerCAmelCase_							=	list_field(
					    default=[]							,  metadata={
					        '''help''': (
					            '''Model checkpoints to be provided to the AutoModel classes. Leave blank to benchmark the base version'''
					            ''' of all available models'''
					        )
					    }							,  )

					lowerCAmelCase_							=	list_field(
					    default=[8]							,  metadata={'''help''': '''List of batch sizes for which memory and time performance will be evaluated'''}					)

					lowerCAmelCase_							=	list_field(
					    default=[8, 32, 128, 512]							,  metadata={'''help''': '''List of sequence lengths for which memory and time performance will be evaluated'''}							,  )

					lowerCAmelCase_							=	field(
					    default=_lowerCamelCase							,  metadata={'''help''': '''Whether to benchmark inference of model. Inference can be disabled via --no-inference.'''}							,  )
					lowerCAmelCase_							=	field(
					    default=_lowerCamelCase							,  metadata={'''help''': '''Whether to run on available cuda devices. Cuda can be disabled via --no-cuda.'''}							,  )
					lowerCAmelCase_							=	field(
					    default=_lowerCamelCase							,  metadata={'''help''': '''Whether to run on available tpu devices. TPU can be disabled via --no-tpu.'''}					)
					lowerCAmelCase_							=	field(default=_lowerCamelCase							,  metadata={'''help''': '''Use FP16 to accelerate inference.'''}					)
					lowerCAmelCase_							=	field(default=_lowerCamelCase							,  metadata={'''help''': '''Benchmark training of model'''}					)
					lowerCAmelCase_							=	field(default=_lowerCamelCase							,  metadata={'''help''': '''Verbose memory tracing'''}					)
					lowerCAmelCase_							=	field(
					    default=_lowerCamelCase							,  metadata={'''help''': '''Whether to perform speed measurements. Speed measurements can be disabled via --no-speed.'''}							,  )
					lowerCAmelCase_							=	field(
					    default=_lowerCamelCase							,  metadata={
					        '''help''': '''Whether to perform memory measurements. Memory measurements can be disabled via --no-memory'''
					    }							,  )
					lowerCAmelCase_							=	field(default=_lowerCamelCase							,  metadata={'''help''': '''Trace memory line by line'''}					)
					lowerCAmelCase_							=	field(default=_lowerCamelCase							,  metadata={'''help''': '''Save result to a CSV file'''}					)
					lowerCAmelCase_							=	field(default=_lowerCamelCase							,  metadata={'''help''': '''Save all print statements in a log file'''}					)
					lowerCAmelCase_							=	field(default=_lowerCamelCase							,  metadata={'''help''': '''Whether to print environment information'''}					)
					lowerCAmelCase_							=	field(
					    default=_lowerCamelCase							,  metadata={
					        '''help''': (
					            '''Whether to use multiprocessing for memory and speed measurement. It is highly recommended to use'''
					            ''' multiprocessing for accurate CPU and GPU memory measurements. This option should only be disabled'''
					            ''' for debugging / testing and on TPU.'''
					        )
					    }							,  )
					lowerCAmelCase_							=	field(
					    default=f"inference_time_{round(time()					)}.csv"							,  metadata={'''help''': '''CSV filename used if saving time results to csv.'''}							,  )
					lowerCAmelCase_							=	field(
					    default=f"inference_memory_{round(time()					)}.csv"							,  metadata={'''help''': '''CSV filename used if saving memory results to csv.'''}							,  )
					lowerCAmelCase_							=	field(
					    default=f"train_time_{round(time()					)}.csv"							,  metadata={'''help''': '''CSV filename used if saving time results to csv for training.'''}							,  )
					lowerCAmelCase_							=	field(
					    default=f"train_memory_{round(time()					)}.csv"							,  metadata={'''help''': '''CSV filename used if saving memory results to csv for training.'''}							,  )
					lowerCAmelCase_							=	field(
					    default=f"env_info_{round(time()					)}.csv"							,  metadata={'''help''': '''CSV filename used if saving environment information.'''}							,  )
					lowerCAmelCase_							=	field(
					    default=f"log_{round(time()					)}.csv"							,  metadata={'''help''': '''Log filename used if print statements are saved in log.'''}							,  )
					lowerCAmelCase_							=	field(default=3							,  metadata={'''help''': '''Times an experiment will be run.'''}					)
					lowerCAmelCase_							=	field(
					    default=_lowerCamelCase							,  metadata={
					        '''help''': (
					            '''Instead of loading the model as defined in `config.architectures` if exists, just load the pretrain'''
					            ''' model weights.'''
					        )
					    }							,  )




					def 	lowerCAmelCase			(		self  )		->							Optional[int]:
										warnings.warn(
										    F'''The class {self.__class__} is deprecated. Hugging Face Benchmarking utils'''
										    ' are deprecated in general and it is advised to use external Benchmarking libraries '
										    ' to benchmark Transformer models.'				,						lowerCAmelCase_				,						)




					def 	lowerCAmelCase			(		self  )		->							List[Any]:
										return json.dumps(dataclasses.asdict(self  )				,						indent=2  )




					@property
					def 	lowerCAmelCase			(		self  )		->							List[str]:

										if len(self.models  ) <= 0:
															raise ValueError(
															    'Please make sure you provide at least one model name / model identifier, *e.g.* `--models'
															    ' bert-base-cased` or `args.models = [\'bert-base-cased\'].'  )
										return self.models






					@property
					def 	lowerCAmelCase			(		self  )		->							List[str]:

										if not self.multi_process:
															return False
										elif self.is_tpu:
															logger.info('Multiprocessing is currently not possible on TPU.'  )
															return False
										else:
															return True










import copy
import tempfile
import unittest

from huggingface_hub import HfFolder, delete_repo
from parameterized import parameterized
from requests.exceptions import HTTPError

from transformers import AutoConfig, GenerationConfig
from transformers.testing_utils import TOKEN, USER, is_staging_test
class 			UpperCamelCase_		(  unittest.TestCase					):




					@parameterized.expand([(None,), ('foo.json',)]  )
					def 	lowerCAmelCase			(		self				,						lowerCAmelCase_  )		->							str:
										_snake_case									=				GenerationConfig(
										    do_sample=lowerCAmelCase_				,						temperature=0.7				,						length_penalty=1.0				,						bad_words_ids=[[1, 2, 3], [4, 5]]				,						)
										with tempfile.TemporaryDirectory() as tmp_dir:
															config.save_pretrained(lowerCAmelCase_				,						config_name=lowerCAmelCase_  )
															_snake_case									=				GenerationConfig.from_pretrained(lowerCAmelCase_				,						config_name=lowerCAmelCase_  )

										# Checks parameters that were specified
										self.assertEqual(loaded_config.do_sample				,						lowerCAmelCase_  )
										self.assertEqual(loaded_config.temperature				,						0.7  )
										self.assertEqual(loaded_config.length_penalty				,						1.0  )
										self.assertEqual(loaded_config.bad_words_ids				,						[[1, 2, 3], [4, 5]]  )

										# Checks parameters that were not specified (defaults)
										self.assertEqual(loaded_config.top_k				,						50  )
										self.assertEqual(loaded_config.max_length				,						20  )
										self.assertEqual(loaded_config.max_time				,						lowerCAmelCase_  )




					def 	lowerCAmelCase			(		self  )		->							Optional[int]:
										_snake_case									=				AutoConfig.from_pretrained('gpt2'  )
										_snake_case									=				GenerationConfig.from_model_config(lowerCAmelCase_  )
										_snake_case									=				GenerationConfig()

										# The generation config has loaded a few non-default parameters from the model config
										self.assertNotEqual(lowerCAmelCase_				,						lowerCAmelCase_  )

										# One of those parameters is eos_token_id -- check if it matches
										self.assertNotEqual(generation_config_from_model.eos_token_id				,						default_generation_config.eos_token_id  )
										self.assertEqual(generation_config_from_model.eos_token_id				,						model_config.eos_token_id  )




					def 	lowerCAmelCase			(		self  )		->							Tuple:
										_snake_case									=				GenerationConfig()
										_snake_case									=				{
										    'max_new_tokens': 1024,
										    'foo': 'bar',
										}
										_snake_case									=				copy.deepcopy(lowerCAmelCase_  )
										_snake_case									=				generation_config.update(**lowerCAmelCase_  )

										# update_kwargs was not modified (no side effects)
										self.assertEqual(lowerCAmelCase_				,						lowerCAmelCase_  )

										# update_kwargs was used to update the config on valid attributes
										self.assertEqual(generation_config.max_new_tokens				,						1024  )

										# `.update()` returns a dictionary of unused kwargs
										self.assertEqual(lowerCAmelCase_				,						{'foo': 'bar'}  )




					def 	lowerCAmelCase			(		self  )		->							Optional[int]:
										_snake_case									=				GenerationConfig()
										_snake_case									=				'bar'

										with tempfile.TemporaryDirectory('test-generation-config'  ) as tmp_dir:
															generation_config.save_pretrained(lowerCAmelCase_  )

															_snake_case									=				GenerationConfig.from_pretrained(lowerCAmelCase_  )
										# update_kwargs was used to update the config on valid attributes
										self.assertEqual(new_config.foo				,						'bar'  )

										_snake_case									=				GenerationConfig.from_model_config(lowerCAmelCase_  )
										assert not hasattr(lowerCAmelCase_				,						'foo'  )  # no new kwargs should be initialized if from config






					def 	lowerCAmelCase			(		self  )		->							List[Any]:
										_snake_case									=				GenerationConfig()
										self.assertEqual(default_config.temperature				,						1.0  )
										self.assertEqual(default_config.do_sample				,						lowerCAmelCase_  )
										self.assertEqual(default_config.num_beams				,						1  )

										_snake_case									=				GenerationConfig(
										    do_sample=lowerCAmelCase_				,						temperature=0.7				,						length_penalty=1.0				,						bad_words_ids=[[1, 2, 3], [4, 5]]				,						)
										self.assertEqual(config.temperature				,						0.7  )
										self.assertEqual(config.do_sample				,						lowerCAmelCase_  )
										self.assertEqual(config.num_beams				,						1  )

										with tempfile.TemporaryDirectory() as tmp_dir:
															config.save_pretrained(lowerCAmelCase_  )
															_snake_case									=				GenerationConfig.from_pretrained(lowerCAmelCase_				,						temperature=1.0  )

										self.assertEqual(loaded_config.temperature				,						1.0  )
										self.assertEqual(loaded_config.do_sample				,						lowerCAmelCase_  )
										self.assertEqual(loaded_config.num_beams				,						1  )  # default value





@is_staging_test
class 			UpperCamelCase_		(  unittest.TestCase					):




					@classmethod
					def 	lowerCAmelCase			(		cls  )		->							List[str]:
										_snake_case									=				TOKEN
										HfFolder.save_token(lowerCAmelCase_  )




					@classmethod
					def 	lowerCAmelCase			(		cls  )		->							Union[str, Any]:
										try:
															delete_repo(token=cls._token				,						repo_id='test-generation-config'  )
										except HTTPError:
															pass

										try:
															delete_repo(token=cls._token				,						repo_id='valid_org/test-generation-config-org'  )
										except HTTPError:
															pass




					def 	lowerCAmelCase			(		self  )		->							int:
										_snake_case									=				GenerationConfig(
										    do_sample=lowerCAmelCase_				,						temperature=0.7				,						length_penalty=1.0				,						)
										config.push_to_hub('test-generation-config'				,						use_auth_token=self._token  )

										_snake_case									=				GenerationConfig.from_pretrained(F'''{USER}/test-generation-config'''  )
										for k, v in config.to_dict().items():
															if k != "transformers_version":
																				self.assertEqual(lowerCAmelCase_				,						getattr(lowerCAmelCase_				,						lowerCAmelCase_  )  )

        # Reset repo
										delete_repo(token=self._token				,						repo_id='test-generation-config'  )

										# Push to hub via save_pretrained
										with tempfile.TemporaryDirectory() as tmp_dir:
															config.save_pretrained(
															    lowerCAmelCase_				,						repo_id='test-generation-config'				,						push_to_hub=lowerCAmelCase_				,						use_auth_token=self._token  )

										_snake_case									=				GenerationConfig.from_pretrained(F'''{USER}/test-generation-config'''  )
										for k, v in config.to_dict().items():
															if k != "transformers_version":
																				self.assertEqual(lowerCAmelCase_				,						getattr(lowerCAmelCase_				,						lowerCAmelCase_  )  )






					def 	lowerCAmelCase			(		self  )		->							List[str]:
										_snake_case									=				GenerationConfig(
										    do_sample=lowerCAmelCase_				,						temperature=0.7				,						length_penalty=1.0				,						)
										config.push_to_hub('valid_org/test-generation-config-org'				,						use_auth_token=self._token  )

										_snake_case									=				GenerationConfig.from_pretrained('valid_org/test-generation-config-org'  )
										for k, v in config.to_dict().items():
															if k != "transformers_version":
																				self.assertEqual(lowerCAmelCase_				,						getattr(lowerCAmelCase_				,						lowerCAmelCase_  )  )

        # Reset repo
										delete_repo(token=self._token				,						repo_id='valid_org/test-generation-config-org'  )

										# Push to hub via save_pretrained
										with tempfile.TemporaryDirectory() as tmp_dir:
															config.save_pretrained(
															    lowerCAmelCase_				,						repo_id='valid_org/test-generation-config-org'				,						push_to_hub=lowerCAmelCase_				,						use_auth_token=self._token  )

										_snake_case									=				GenerationConfig.from_pretrained('valid_org/test-generation-config-org'  )
										for k, v in config.to_dict().items():
															if k != "transformers_version":
																				self.assertEqual(lowerCAmelCase_				,						getattr(lowerCAmelCase_				,						lowerCAmelCase_  )  )



