
"""simple docstring"""





import csv
from collections import defaultdict
from dataclasses import dataclass, field
from typing import List, Optional

import matplotlib.pyplot as plt
import numpy as np
from matplotlib.ticker import ScalarFormatter

from transformers import HfArgumentParser



def 				lowerCamelCase__		(      __snake_case=None,					__snake_case=None     )							->		List[Any]:


					"""simple docstring"""





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






@dataclass
class    _UpperCAmelCase:
		lowercase__      =				field(
		    metadata={'help': 'The csv file to plot.'}				,					)
		lowercase__      =				field(
		    default=lowerCamelCase				,					metadata={'help': 'Whether to plot along batch size or sequence length. Defaults to sequence length.'}				,					)
		lowercase__      =				field(
		    default=lowerCamelCase				,					metadata={'help': 'Whether the csv file has time results or memory results. Defaults to memory results.'}				,					)
		lowercase__      =				field(
		    default=lowerCamelCase				,					metadata={'help': 'Disable logarithmic scale when plotting'}				,					)
		lowercase__      =				field(
		    default=lowerCamelCase				,					metadata={
		        'help': 'Whether the csv file has training results or inference results. Defaults to inference results.'
		    }				,					)
		lowercase__      =				field(
		    default=lowerCamelCase				,					metadata={'help': 'Filename under which the plot will be saved. If unused no plot is saved.'}				,					)
		lowercase__      =				list_field(
		    default=lowerCamelCase				,					metadata={'help': 'List of model names that are used instead of the ones in the csv file.'}     )





def 				lowerCamelCase__		(      __snake_case     )							->		Union[str, Any]:


					"""simple docstring"""





					try:
										int(__snake_case     )
										return True
					except ValueError:
										return False



def 				lowerCamelCase__		(      __snake_case     )							->		int:


					"""simple docstring"""





					try:
										float(__snake_case     )
										return True
					except ValueError:
										return False






class    _UpperCAmelCase:



		def __init__( self    ,		__a)	->	Dict:






							'''simple docstring'''
							_UpperCamelCase										=  args
							_UpperCamelCase										=  defaultdict(lambda: {"bsz": [], "seq_len": [], "result": {}})

							with open(self.args.csv_file    ,		newline='''''') as csv_file:
												_UpperCamelCase										=  csv.DictReader(__a)
												for row in reader:
																	_UpperCamelCase										=  row['''model''']
																	self.result_dict[model_name]["bsz"].append(int(row['''batch_size''']))
																	self.result_dict[model_name]["seq_len"].append(int(row['''sequence_length''']))
																	if can_convert_to_int(row['''result''']):
																						# value is not None
																						_UpperCamelCase										=  int(row['''result'''])
																	elif can_convert_to_float(row['''result''']):
																						# value is not None
																						_UpperCamelCase										=  float(row['''result'''])




		def 						UpperCAmelCase							( self)	->	str:






							'''simple docstring'''
							_UpperCamelCase			,  _UpperCamelCase										=  plt.subplots()
							_UpperCamelCase										=  '''Time usage''' if self.args.is_time else '''Memory usage'''
							_UpperCamelCase										=  title_str + ''' for training''' if self.args.is_train else title_str + ''' for inference'''

							if not self.args.no_log_scale:
												# set logarithm scales
												ax.set_xscale('''log''')
												ax.set_yscale('''log''')

							for axis in [ax.xaxis, ax.yaxis]:
												axis.set_major_formatter(ScalarFormatter())

							for model_name_idx, model_name in enumerate(self.result_dict.keys()):
												_UpperCamelCase										=  sorted(set(self.result_dict[model_name]['''bsz''']))
												_UpperCamelCase										=  sorted(set(self.result_dict[model_name]['''seq_len''']))
												_UpperCamelCase										=  self.result_dict[model_name]['''result''']

												((_UpperCamelCase)			,  (_UpperCamelCase))										=  (
												    (batch_sizes, sequence_lengths) if self.args.plot_along_batch else (sequence_lengths, batch_sizes)
												)

												_UpperCamelCase										=  (
												    model_name if self.args.short_model_names is None else self.args.short_model_names[model_name_idx]
												)

												for inner_loop_value in inner_loop_array:
																	if self.args.plot_along_batch:
																						_UpperCamelCase										=  np.asarray(
																						    [results[(x, inner_loop_value)] for x in x_axis_array if (x, inner_loop_value) in results]    ,		dtype=__a    ,		)
																	else:
																						_UpperCamelCase										=  np.asarray(
																						    [results[(inner_loop_value, x)] for x in x_axis_array if (inner_loop_value, x) in results]    ,		dtype=np.floataa    ,		)

																	((_UpperCamelCase)			,  (_UpperCamelCase))										=  (
																	    ('''batch_size''', '''len''') if self.args.plot_along_batch else ('''in #tokens''', '''bsz''')
																	)

																	_UpperCamelCase										=  np.asarray(__a    ,		__a)[: len(__a)]
																	plt.scatter(
																	    __a    ,		__a    ,		label=F'''{label_model_name} - {inner_loop_label}: {inner_loop_value}''')
																	plt.plot(__a    ,		__a    ,		'''--''')

												title_str += F''' {label_model_name} vs.'''

							_UpperCamelCase										=  title_str[:-4]
							_UpperCamelCase										=  '''Time in s''' if self.args.is_time else '''Memory in MB'''

							# plot
							plt.title(__a)
							plt.xlabel(__a)
							plt.ylabel(__a)
							plt.legend()

							if self.args.figure_png_file is not None:
												plt.savefig(self.args.figure_png_file)
							else:
												plt.show()





def 				lowerCamelCase__		(      )							->		List[str]:


					"""simple docstring"""





					_UpperCamelCase										=  HfArgumentParser(__snake_case     )
					_UpperCamelCase										=  parser.parse_args_into_dataclasses()[0]
					_UpperCamelCase										=  Plot(args=__snake_case     )
					plot.plot()


if __name__ == "__main__":
				main()








"""simple docstring"""





import importlib
import json
import os
import sys
import tempfile
import unittest
from pathlib import Path

import transformers
import transformers.models.auto
from transformers.models.auto.configuration_auto import CONFIG_MAPPING, AutoConfig
from transformers.models.bert.configuration_bert import BertConfig
from transformers.models.roberta.configuration_roberta import RobertaConfig
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, get_tests_dir


sys.path.append(str(Path(__file__).parent.parent.parent.parent / """utils"""))

from test_module.custom_configuration import CustomConfig  # noqa E402


_a														=		get_tests_dir("""fixtures/dummy-config.json""")






class    _UpperCAmelCase(   unittest.TestCase     ):



		def 						UpperCAmelCase							( self)	->	str:






							'''simple docstring'''
							_UpperCamelCase										=  0



		def 						UpperCAmelCase							( self)	->	List[str]:






							'''simple docstring'''
							self.assertIsNotNone(transformers.models.auto.__spec__)
							self.assertIsNotNone(importlib.util.find_spec('''transformers.models.auto'''))



		def 						UpperCAmelCase							( self)	->	str:






							'''simple docstring'''
							_UpperCamelCase										=  AutoConfig.from_pretrained('''bert-base-uncased''')
							self.assertIsInstance(__a    ,		__a)



		def 						UpperCAmelCase							( self)	->	Tuple:






							'''simple docstring'''
							_UpperCamelCase										=  AutoConfig.from_pretrained(__a)
							self.assertIsInstance(__a    ,		__a)



		def 						UpperCAmelCase							( self)	->	Optional[Any]:






							'''simple docstring'''
							_UpperCamelCase										=  AutoConfig.from_pretrained(__a)
							self.assertIsInstance(__a    ,		__a)



		def 						UpperCAmelCase							( self)	->	Union[str, Any]:






							'''simple docstring'''
							_UpperCamelCase										=  AutoConfig.for_model('''roberta''')
							self.assertIsInstance(__a    ,		__a)



		def 						UpperCAmelCase							( self)	->	Dict:






							'''simple docstring'''
							with tempfile.TemporaryDirectory() as tmp_dir:
												# This model name contains bert and roberta, but roberta ends up being picked.
												_UpperCamelCase										=  os.path.join(__a    ,		'''fake-roberta''')
												os.makedirs(__a    ,		exist_ok=__a)
												with open(os.path.join(__a    ,		'''config.json''')    ,		'''w''') as f:
																	f.write(json.dumps({}))
												_UpperCamelCase										=  AutoConfig.from_pretrained(__a)
												self.assertEqual(type(__a)    ,		__a)



		def 						UpperCAmelCase							( self)	->	Tuple:






							'''simple docstring'''
							try:
												AutoConfig.register('''custom'''    ,		__a)
												# Wrong model type will raise an error
												with self.assertRaises(__a):
																	AutoConfig.register('''model'''    ,		__a)
												# Trying to register something existing in the Transformers library will raise an error
												with self.assertRaises(__a):
																	AutoConfig.register('''bert'''    ,		__a)

												# Now that the config is registered, it can be used as any other config with the auto-API
												_UpperCamelCase										=  CustomConfig()
												with tempfile.TemporaryDirectory() as tmp_dir:
																	config.save_pretrained(__a)
																	_UpperCamelCase										=  AutoConfig.from_pretrained(__a)
																	self.assertIsInstance(__a    ,		__a)

							finally:
												if "custom" in CONFIG_MAPPING._extra_content:
																	del CONFIG_MAPPING._extra_content["custom"]



		def 						UpperCAmelCase							( self)	->	List[Any]:






							'''simple docstring'''
							with self.assertRaisesRegex(
							    __a    ,		'''bert-base is not a local folder and is not a valid model identifier'''):
												_UpperCamelCase										=  AutoConfig.from_pretrained('''bert-base''')



		def 						UpperCAmelCase							( self)	->	List[Any]:






							'''simple docstring'''
							with self.assertRaisesRegex(
							    __a    ,		R'''aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)'''):
												_UpperCamelCase										=  AutoConfig.from_pretrained(__a    ,		revision='''aaaaaa''')



		def 						UpperCAmelCase							( self)	->	Optional[Any]:






							'''simple docstring'''
							with self.assertRaisesRegex(
							    __a    ,		'''hf-internal-testing/no-config-test-repo does not appear to have a file named config.json.'''    ,		):
												_UpperCamelCase										=  AutoConfig.from_pretrained('''hf-internal-testing/no-config-test-repo''')



		def 						UpperCAmelCase							( self)	->	int:






							'''simple docstring'''
							# If remote code is not set, we will time out when asking whether to load the model.
							with self.assertRaises(__a):
												_UpperCamelCase										=  AutoConfig.from_pretrained('''hf-internal-testing/test_dynamic_model''')
							# If remote code is disabled, we can't load this config.
							with self.assertRaises(__a):
												_UpperCamelCase										=  AutoConfig.from_pretrained('''hf-internal-testing/test_dynamic_model'''    ,		trust_remote_code=__a)

							_UpperCamelCase										=  AutoConfig.from_pretrained('''hf-internal-testing/test_dynamic_model'''    ,		trust_remote_code=__a)
							self.assertEqual(config.__class__.__name__    ,		'''NewModelConfig''')

							# Test config can be reloaded.
							with tempfile.TemporaryDirectory() as tmp_dir:
												config.save_pretrained(__a)
												_UpperCamelCase										=  AutoConfig.from_pretrained(__a    ,		trust_remote_code=__a)
							self.assertEqual(reloaded_config.__class__.__name__    ,		'''NewModelConfig''')




		def 						UpperCAmelCase							( self)	->	Any:






							'''simple docstring'''






							class    _UpperCAmelCase(   lowerCamelCase     ):
									lowercase__      =				'new-model'

							try:
												AutoConfig.register('''new-model'''    ,		__a)
												# If remote code is not set, the default is to use local
												_UpperCamelCase										=  AutoConfig.from_pretrained('''hf-internal-testing/test_dynamic_model''')
												self.assertEqual(config.__class__.__name__    ,		'''NewModelConfigLocal''')

												# If remote code is disabled, we load the local one.
												_UpperCamelCase										=  AutoConfig.from_pretrained('''hf-internal-testing/test_dynamic_model'''    ,		trust_remote_code=__a)
												self.assertEqual(config.__class__.__name__    ,		'''NewModelConfigLocal''')

												# If remote is enabled, we load from the Hub
												_UpperCamelCase										=  AutoConfig.from_pretrained('''hf-internal-testing/test_dynamic_model'''    ,		trust_remote_code=__a)
												self.assertEqual(config.__class__.__name__    ,		'''NewModelConfig''')

							finally:
												if "new-model" in CONFIG_MAPPING._extra_content:
																	del CONFIG_MAPPING._extra_content["new-model"]






