import pickle
import shutil
import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, XLMRobertaTokenizer, XLMRobertaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


A__           =							get_tests_dir("""fixtures/test_sentencepiece.model""")
@require_sentencepiece
@require_tokenizers
class   _lowerCAmelCase		(     __SCREAMING_SNAKE_CASE      ,   unittest.TestCase				):
							_UpperCAmelCase						    =     XLMRobertaTokenizer
							_UpperCAmelCase						    =     XLMRobertaTokenizerFast
							_UpperCAmelCase						    =     True
							_UpperCAmelCase						    =     True







							def 				snake_case  (				self     :    int		):
										super().setUp()

										# We have a SentencePiece fixture for testing
										lowerCamelCase						:List[Any]						  =     XLMRobertaTokenizer(__snake_case	,					keep_accents=__snake_case		)
										tokenizer.save_pretrained(self.tmpdirname		)







							def 				snake_case  (				self     :    Dict		):
										lowerCamelCase						:List[str]						  =     '''<pad>'''
										lowerCamelCase						:Optional[int]						  =     1

										self.assertEqual(self.get_tokenizer()._convert_token_to_id(__snake_case		)	,					__snake_case		)
										self.assertEqual(self.get_tokenizer()._convert_id_to_token(__snake_case		)	,					__snake_case		)







							def 				snake_case  (				self     :    int		):
										lowerCamelCase						:int						  =     list(self.get_tokenizer().get_vocab().keys()		)

										self.assertEqual(vocab_keys[0]	,					'''<s>'''		)
										self.assertEqual(vocab_keys[1]	,					'''<pad>'''		)
										self.assertEqual(vocab_keys[-1]	,					'''<mask>'''		)
										self.assertEqual(len(__snake_case		)	,					1002		)







							def 				snake_case  (				self     :    str		):
										self.assertEqual(self.get_tokenizer().vocab_size	,					1002		)







							def 				snake_case  (				self     :    Tuple		):
										lowerCamelCase						:str						  =     XLMRobertaTokenizer(__snake_case	,					keep_accents=__snake_case		)

										lowerCamelCase						:int						  =     tokenizer.tokenize('''This is a test'''		)
										self.assertListEqual(__snake_case	,					['''▁This''', '''▁is''', '''▁a''', '''▁t''', '''est''']		)

										self.assertListEqual(
										    tokenizer.convert_tokens_to_ids(__snake_case		)	,					[value + tokenizer.fairseq_offset for value in [285, 46, 10, 170, 382]]	,					)

										lowerCamelCase						:str						  =     tokenizer.tokenize('''I was born in 92000, and this is falsé.'''		)
										self.assertListEqual(
										    __snake_case	,					[
										        SPIECE_UNDERLINE + '''I''',
										        SPIECE_UNDERLINE + '''was''',
										        SPIECE_UNDERLINE + '''b''',
										        '''or''',
										        '''n''',
										        SPIECE_UNDERLINE + '''in''',
										        SPIECE_UNDERLINE + '''''',
										        '''9''',
										        '''2''',
										        '''0''',
										        '''0''',
										        '''0''',
										        ''',''',
										        SPIECE_UNDERLINE + '''and''',
										        SPIECE_UNDERLINE + '''this''',
										        SPIECE_UNDERLINE + '''is''',
										        SPIECE_UNDERLINE + '''f''',
										        '''al''',
										        '''s''',
										        '''é''',
										        '''.''',
										    ]	,					)
										lowerCamelCase						:Tuple						  =     tokenizer.convert_tokens_to_ids(__snake_case		)
										self.assertListEqual(
										    __snake_case	,					[
										        value + tokenizer.fairseq_offset
										        for value in [8, 21, 84, 55, 24, 19, 7, 2, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 2, 4]
										        #                                       ^ unk: 2 + 1 = 3                  unk: 2 + 1 = 3 ^
										    ]	,					)

										lowerCamelCase						:Any						  =     tokenizer.convert_ids_to_tokens(__snake_case		)
										self.assertListEqual(
										    __snake_case	,					[
										        SPIECE_UNDERLINE + '''I''',
										        SPIECE_UNDERLINE + '''was''',
										        SPIECE_UNDERLINE + '''b''',
										        '''or''',
										        '''n''',
										        SPIECE_UNDERLINE + '''in''',
										        SPIECE_UNDERLINE + '''''',
										        '''<unk>''',
										        '''2''',
										        '''0''',
										        '''0''',
										        '''0''',
										        ''',''',
										        SPIECE_UNDERLINE + '''and''',
										        SPIECE_UNDERLINE + '''this''',
										        SPIECE_UNDERLINE + '''is''',
										        SPIECE_UNDERLINE + '''f''',
										        '''al''',
										        '''s''',
										        '''<unk>''',
										        '''.''',
										    ]	,					)







							def 				snake_case  (				self     :    str		):
										if not self.test_slow_tokenizer:
													# as we don't have a slow version, we can't compare the outputs between slow and fast versions
													return

										lowerCamelCase						:int						  =     (self.rust_tokenizer_class, '''hf-internal-testing/tiny-xlm-roberta''', {})
										for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
													with self.subTest(F"{tokenizer.__class__.__name__} ({pretrained_name})"		):
																lowerCamelCase						:List[str]						  =     self.rust_tokenizer_class.from_pretrained(__snake_case	,					**__snake_case		)
																lowerCamelCase						:int						  =     self.tokenizer_class.from_pretrained(__snake_case	,					**__snake_case		)

																lowerCamelCase						:Optional[int]						  =     tempfile.mkdtemp()

																lowerCamelCase						:List[Any]						  =     tokenizer_r.save_pretrained(__snake_case		)
																lowerCamelCase						:List[str]						  =     tokenizer_p.save_pretrained(__snake_case		)

																# Checks it save with the same files + the tokenizer.json file for the fast one
																self.assertTrue(any('''tokenizer.json''' in f for f in tokenizer_r_files		)		)
																lowerCamelCase						:Any						  =     tuple(f for f in tokenizer_r_files if '''tokenizer.json''' not in f		)
																self.assertSequenceEqual(__snake_case	,					__snake_case		)

																# Checks everything loads correctly in the same way
																lowerCamelCase						:Dict						  =     tokenizer_r.from_pretrained(__snake_case		)
																lowerCamelCase						:Optional[Any]						  =     tokenizer_p.from_pretrained(__snake_case		)

																# Check special tokens are set accordingly on Rust and Python
																for key in tokenizer_pp.special_tokens_map:
																			self.assertTrue(hasattr(__snake_case	,					__snake_case		)		)
																			# self.assertEqual(getattr(tokenizer_rp, key), getattr(tokenizer_pp, key))
																			# self.assertEqual(getattr(tokenizer_rp, key + "_id"), getattr(tokenizer_pp, key + "_id"))

																shutil.rmtree(__snake_case		)

																# Save tokenizer rust, legacy_format=True
																lowerCamelCase						:List[str]						  =     tempfile.mkdtemp()

																lowerCamelCase						:Optional[Any]						  =     tokenizer_r.save_pretrained(__snake_case	,					legacy_format=__snake_case		)
																lowerCamelCase						:Any						  =     tokenizer_p.save_pretrained(__snake_case		)

																# Checks it save with the same files
																self.assertSequenceEqual(__snake_case	,					__snake_case		)

																# Checks everything loads correctly in the same way
																lowerCamelCase						:Any						  =     tokenizer_r.from_pretrained(__snake_case		)
																lowerCamelCase						:Optional[int]						  =     tokenizer_p.from_pretrained(__snake_case		)

																# Check special tokens are set accordingly on Rust and Python
																for key in tokenizer_pp.special_tokens_map:
																			self.assertTrue(hasattr(__snake_case	,					__snake_case		)		)

																shutil.rmtree(__snake_case		)

																# Save tokenizer rust, legacy_format=False
																lowerCamelCase						:Dict						  =     tempfile.mkdtemp()

																lowerCamelCase						:Optional[int]						  =     tokenizer_r.save_pretrained(__snake_case	,					legacy_format=__snake_case		)
																lowerCamelCase						:Optional[int]						  =     tokenizer_p.save_pretrained(__snake_case		)

																# Checks it saved the tokenizer.json file
																self.assertTrue(any('''tokenizer.json''' in f for f in tokenizer_r_files		)		)

																# Checks everything loads correctly in the same way
																lowerCamelCase						:Tuple						  =     tokenizer_r.from_pretrained(__snake_case		)
																lowerCamelCase						:str						  =     tokenizer_p.from_pretrained(__snake_case		)

																# Check special tokens are set accordingly on Rust and Python
																for key in tokenizer_pp.special_tokens_map:
																			self.assertTrue(hasattr(__snake_case	,					__snake_case		)		)

																shutil.rmtree(__snake_case		)







							@cached_property
							def 				snake_case  (				self     :    Optional[Any]		):
										return XLMRobertaTokenizer.from_pretrained('''xlm-roberta-base'''		)







							def 				snake_case  (				self     :    Optional[int]		):
										with tempfile.NamedTemporaryFile() as f:
													shutil.copyfile(__snake_case	,					f.name		)
													lowerCamelCase						:Optional[int]						  =     XLMRobertaTokenizer(f.name	,					keep_accents=__snake_case		)
													lowerCamelCase						:Any						  =     pickle.dumps(__snake_case		)
										pickle.loads(__snake_case		)







							def 				snake_case  (				self     :    Optional[Any]		):
										if not self.test_rust_tokenizer:
													return

										lowerCamelCase						:Optional[Any]						  =     self.get_tokenizer()
										lowerCamelCase						:Tuple						  =     self.get_rust_tokenizer()

										lowerCamelCase						:List[str]						  =     '''I was born in 92000, and this is falsé.'''

										lowerCamelCase						:Any						  =     tokenizer.tokenize(__snake_case		)
										lowerCamelCase						:Any						  =     rust_tokenizer.tokenize(__snake_case		)
										self.assertListEqual(__snake_case	,					__snake_case		)

										lowerCamelCase						:List[str]						  =     tokenizer.encode(__snake_case	,					add_special_tokens=__snake_case		)
										lowerCamelCase						:Dict						  =     rust_tokenizer.encode(__snake_case	,					add_special_tokens=__snake_case		)
										self.assertListEqual(__snake_case	,					__snake_case		)

										lowerCamelCase						:Optional[Any]						  =     self.get_rust_tokenizer()
										lowerCamelCase						:List[str]						  =     tokenizer.encode(__snake_case		)
										lowerCamelCase						:Dict						  =     rust_tokenizer.encode(__snake_case		)
										self.assertListEqual(__snake_case	,					__snake_case		)







							@slow
							def 				snake_case  (				self     :    List[Any]		):
										lowerCamelCase						:Tuple						  =     '''Hello World!'''
										lowerCamelCase						:Dict						  =     [0, 35378, 6661, 38, 2]
										# xlmr = torch.hub.load('pytorch/fairseq', 'xlmr.base')  # xlmr.large has same tokenizer
										# xlmr.eval()
										# xlmr.encode(symbols)

										self.assertListEqual(__snake_case	,					self.big_tokenizer.encode(__snake_case		)		)







							@slow
							def 				snake_case  (				self     :    Optional[Any]		):
										lowerCamelCase						:Any						  =     (
										    '''This is a very long text with a lot of weird characters, such as: . , ~ ? ( ) " [ ] ! : - . Also we will'''
										    ''' add words that should not exsist and be tokenized to <unk>, such as saoneuhaoesuth'''
										)
										lowerCamelCase						:Optional[int]						  =     [
										    0,
										    3293,
										    83,
										    10,
										    4552,
										    4989,
										    7986,
										    678,
										    10,
										    5915,
										    111,
										    179459,
										    124850,
										    4,
										    6044,
										    237,
										    12,
										    6,
										    5,
										    6,
										    4,
										    6780,
										    705,
										    15,
										    1388,
										    44,
										    378,
										    10114,
										    711,
										    152,
										    20,
										    6,
										    5,
										    22376,
										    642,
										    1221,
										    15190,
										    34153,
										    450,
										    5608,
										    959,
										    1119,
										    57702,
										    136,
										    186,
										    47,
										    1098,
										    29367,
										    47,
										    # 4426, # What fairseq tokenizes from "<unk>": "_<"
										    # 3678, # What fairseq tokenizes from "<unk>": "unk"
										    # 2740, # What fairseq tokenizes from "<unk>": ">"
										    3,  # What we tokenize from "<unk>": "<unk>"
										    6,  # Residue from the tokenization: an extra sentencepiece underline
										    4,
										    6044,
										    237,
										    6284,
										    50901,
										    528,
										    31,
										    90,
										    34,
										    927,
										    2,
										]
										# xlmr = torch.hub.load('pytorch/fairseq', 'xlmr.base')  # xlmr.large has same tokenizer
										# xlmr.eval()
										# xlmr.encode(symbols)

										self.assertListEqual(__snake_case	,					self.big_tokenizer.encode(__snake_case		)		)







							@slow
							def 				snake_case  (				self     :    str		):
										# fmt: off
										lowerCamelCase						:Any						  =     {'''input_ids''': [[0, 11062, 82772, 7, 15, 82772, 538, 51529, 237, 17198, 1290, 206, 9, 215175, 1314, 136, 17198, 1290, 206, 9, 56359, 42, 122009, 9, 16466, 16, 87344, 4537, 9, 4717, 78381, 6, 159958, 7, 15, 24480, 618, 4, 527, 22693, 5428, 4, 2777, 24480, 9874, 4, 43523, 594, 4, 803, 18392, 33189, 18, 4, 43523, 24447, 12399, 100, 24955, 83658, 9626, 144057, 15, 839, 22335, 16, 136, 24955, 83658, 83479, 15, 39102, 724, 16, 678, 645, 2789, 1328, 4589, 42, 122009, 115774, 23, 805, 1328, 46876, 7, 136, 53894, 1940, 42227, 41159, 17721, 823, 425, 4, 27512, 98722, 206, 136, 5531, 4970, 919, 17336, 5, 2], [0, 20080, 618, 83, 82775, 47, 479, 9, 1517, 73, 53894, 333, 80581, 110117, 18811, 5256, 1295, 51, 152526, 297, 7986, 390, 124416, 538, 35431, 214, 98, 15044, 25737, 136, 7108, 43701, 23, 756, 135355, 7, 5, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [0, 581, 63773, 119455, 6, 147797, 88203, 7, 645, 70, 21, 3285, 10269, 5, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]], '''attention_mask''': [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
										# fmt: on

										self.tokenizer_integration_test_util(
										    expected_encoding=__snake_case	,					model_name='''xlm-roberta-base'''	,					revision='''d9d8a8ea5eb94b1c6654ae9249df7793cd2933d3'''	,					)




import ast
import os
import re
import shutil
import tempfile
import unittest
from unittest import mock

import torch

from accelerate.test_utils.examples import compare_against_test
from accelerate.test_utils.testing import TempDirTestCase, require_trackers, run_command, slow
from accelerate.utils import write_basic_config


# DataLoaders built from `test_samples/MRPC` for quick testing
# Should mock `{script_name}.get_dataloaders` via:
# @mock.patch("{script_name}.get_dataloaders", mocked_dataloaders)

A__           =							[
    """cross_validation.py""",
    """gradient_accumulation.py""",
    """local_sgd.py""",
    """multi_process_metrics.py""",
    """memory.py""",
    """automatic_gradient_accumulation.py""",
    """fsdp_with_peak_mem_tracking.py""",
    """deepspeed_with_config_support.py""",
    """megatron_lm_gpt_pretraining.py""",
]
class   _lowerCAmelCase		(     unittest.TestCase				):







							def 				snake_case  (				self     :    Any	,					__snake_case     :    str	,					__snake_case     :    bool	,					__snake_case     :    str = None	,					__snake_case     :    list = None		):
										lowerCamelCase						:Tuple						  =     None
										lowerCamelCase						:Tuple						  =     os.path.abspath(os.path.join('''examples'''	,					'''by_feature'''		)		)
										lowerCamelCase						:Optional[int]						  =     os.path.abspath('''examples'''		)
										for item in os.listdir(__snake_case		):
													if item not in EXCLUDE_EXAMPLES:
																lowerCamelCase						:Optional[int]						  =     os.path.join(__snake_case	,					__snake_case		)
																if os.path.isfile(__snake_case		) and ".py" in item_path:
																			with self.subTest(
																			    tested_script=__snake_case	,					feature_script=__snake_case	,					tested_section='''main()''' if parser_only else '''training_function()'''	,					):
																						lowerCamelCase						:Union[str, Any]						  =     compare_against_test(
																						    os.path.join(__snake_case	,					__snake_case		)	,					__snake_case	,					__snake_case	,					__snake_case		)
																						lowerCamelCase						:int						  =     '''\n'''.join(__snake_case		)
																						if special_strings is not None:
																									for string in special_strings:
																												lowerCamelCase						:int						  =     diff.replace(__snake_case	,					''''''		)
																						self.assertEqual(__snake_case	,					''''''		)







							def 				snake_case  (				self     :    Dict		):
										self.one_complete_example('''complete_nlp_example.py'''	,					__snake_case		)
										self.one_complete_example('''complete_nlp_example.py'''	,					__snake_case		)







							def 				snake_case  (				self     :    Optional[Any]		):
										lowerCamelCase						:Union[str, Any]						  =     os.path.abspath(os.path.join('''examples'''	,					'''cv_example.py'''		)		)
										lowerCamelCase						:Optional[int]						  =     [
										    ''' ''' * 16 + '''{\n\n''',
										    ''' ''' * 20 + '''"accuracy": eval_metric["accuracy"],\n\n''',
										    ''' ''' * 20 + '''"f1": eval_metric["f1"],\n\n''',
										    ''' ''' * 20 + '''"train_loss": total_loss.item() / len(train_dataloader),\n\n''',
										    ''' ''' * 20 + '''"epoch": epoch,\n\n''',
										    ''' ''' * 16 + '''},\n\n''',
										    ''' ''' * 16 + '''step=epoch,\n''',
										    ''' ''' * 12,
										    ''' ''' * 8 + '''for step, batch in enumerate(active_dataloader):\n''',
										]
										self.one_complete_example('''complete_cv_example.py'''	,					__snake_case	,					__snake_case	,					__snake_case		)
										self.one_complete_example('''complete_cv_example.py'''	,					__snake_case	,					__snake_case	,					__snake_case		)


@mock.patch.dict(os.environ      ,   {'TESTING_MOCKED_DATALOADERS': '1'}				)
class   _lowerCAmelCase		(     __SCREAMING_SNAKE_CASE				):
							_UpperCAmelCase						    =     False







							@classmethod
							def 				snake_case  (				cls     :    Optional[Any]		):
										super().setUpClass()
										lowerCamelCase						:Any						  =     tempfile.mkdtemp()
										lowerCamelCase						:Optional[int]						  =     os.path.join(cls._tmpdir	,					'''default_config.yml'''		)

										write_basic_config(save_location=cls.configPath		)
										lowerCamelCase						:List[str]						  =     ['''accelerate''', '''launch''', '''--config_file''', cls.configPath]







							@classmethod
							def 				snake_case  (				cls     :    Dict		):
										super().tearDownClass()
										shutil.rmtree(cls._tmpdir		)







							def 				snake_case  (				self     :    int		):
										lowerCamelCase						:Any						  =     F"\n        examples/by_feature/checkpointing.py\n        --checkpointing_steps epoch\n        --output_dir {self.tmpdir}\n        ".split()
										run_command(self._launch_args + testargs		)
										self.assertTrue(os.path.exists(os.path.join(self.tmpdir	,					'''epoch_0'''		)		)		)







							def 				snake_case  (				self     :    List[Any]		):
										lowerCamelCase						:Tuple						  =     F"\n        examples/by_feature/checkpointing.py\n        --checkpointing_steps 1\n        --output_dir {self.tmpdir}\n        ".split()
										lowerCamelCase						:List[Any]						  =     run_command(self._launch_args + testargs		)
										self.assertTrue(os.path.exists(os.path.join(self.tmpdir	,					'''step_2'''		)		)		)







							def 				snake_case  (				self     :    List[str]		):
										lowerCamelCase						:Dict						  =     F"\n        examples/by_feature/checkpointing.py\n        --resume_from_checkpoint {os.path.join(self.tmpdir	,					'epoch_0'		)}\n        ".split()
										lowerCamelCase						:Dict						  =     run_command(self._launch_args + testargs	,					return_stdout=__snake_case		)
										self.assertNotIn('''epoch 0:'''	,					__snake_case		)
										self.assertIn('''epoch 1:'''	,					__snake_case		)







							def 				snake_case  (				self     :    str		):
										lowerCamelCase						:List[Any]						  =     F"\n        examples/by_feature/checkpointing.py\n        --resume_from_checkpoint {os.path.join(self.tmpdir	,					'step_2'		)}\n        ".split()
										lowerCamelCase						:Optional[int]						  =     run_command(self._launch_args + testargs	,					return_stdout=__snake_case		)
										if torch.cuda.is_available():
													lowerCamelCase						:Union[str, Any]						  =     torch.cuda.device_count()
										else:
													lowerCamelCase						:Dict						  =     1
										if num_processes > 1:
													self.assertNotIn('''epoch 0:'''	,					__snake_case		)
													self.assertIn('''epoch 1:'''	,					__snake_case		)
										else:
													self.assertIn('''epoch 0:'''	,					__snake_case		)
													self.assertIn('''epoch 1:'''	,					__snake_case		)







							@slow
							def 				snake_case  (				self     :    Any		):
										lowerCamelCase						:Tuple						  =     '''
        examples/by_feature/cross_validation.py
        --num_folds 2
        '''.split()
										with mock.patch.dict(os.environ	,					{'''TESTING_MOCKED_DATALOADERS''': '''0'''}		):
													lowerCamelCase						:Dict						  =     run_command(self._launch_args + testargs	,					return_stdout=__snake_case		)
													lowerCamelCase						:Tuple						  =     re.findall('''({.+})'''	,					__snake_case		)
													lowerCamelCase						:Optional[Any]						  =     [r for r in results if '''accuracy''' in r][-1]
													lowerCamelCase						:List[str]						  =     ast.literal_eval(__snake_case		)
													self.assertGreaterEqual(results['''accuracy''']	,					0.7_5		)







							def 				snake_case  (				self     :    int		):
										lowerCamelCase						:Dict						  =     ['''examples/by_feature/multi_process_metrics.py''']
										run_command(self._launch_args + testargs		)







							@require_trackers
							@mock.patch.dict(os.environ	,					{'''WANDB_MODE''': '''offline'''}		)
							def 				snake_case  (				self     :    Any		):
										with tempfile.TemporaryDirectory() as tmpdir:
													lowerCamelCase						:Tuple						  =     F"\n            examples/by_feature/tracking.py\n            --with_tracking\n            --project_dir {tmpdir}\n            ".split()
													run_command(self._launch_args + testargs		)
													self.assertTrue(os.path.exists(os.path.join(__snake_case	,					'''tracking'''		)		)		)







							def 				snake_case  (				self     :    Tuple		):
										lowerCamelCase						:Tuple						  =     ['''examples/by_feature/gradient_accumulation.py''']
										run_command(self._launch_args + testargs		)







							def 				snake_case  (				self     :    Optional[Any]		):
										lowerCamelCase						:int						  =     ['''examples/by_feature/local_sgd.py''']
										run_command(self._launch_args + testargs		)



