

"""simple docstring"""





import argparse
import json
import logging
import os
import sys
from unittest import skip
from unittest.mock import patch

import tensorflow as tf

from transformers.testing_utils import TestCasePlus, get_gpu_count, slow


_SCREAMING_SNAKE_CASE							:	int										=			[
    os.path.join(os.path.dirname(__file__), dirname)
    for dirname in [
        """text-generation""",
        """text-classification""",
        """token-classification""",
        """language-modeling""",
        """multiple-choice""",
        """question-answering""",
        """summarization""",
        """translation""",
        """image-classification""",
    ]
]
sys.path.extend(SRC_DIRS)


if SRC_DIRS is not None:
				import run_clm
				import run_image_classification
				import run_mlm
				import run_ner
				import run_qa as run_squad
				import run_summarization
				import run_swag
				import run_text_classification
				import run_translation


logging.basicConfig(level=logging.DEBUG)

_SCREAMING_SNAKE_CASE							:	Any										=			logging.getLogger()



def 							_lowerCAmelCase   (    ):


					'''simple docstring'''






					UpperCamelCase__		:     Any								=argparse.ArgumentParser()
					parser.add_argument('''-f'''					)
					UpperCamelCase__		:     Tuple								=parser.parse_args()
					return args.f



def 							_lowerCAmelCase   (    UpperCAmelCase  :				List[Any]					):


					'''simple docstring'''






					UpperCamelCase__		:     str								={}
					UpperCamelCase__		:     Dict								=os.path.join(UpperCAmelCase   ,				'''all_results.json'''					)
					if os.path.exists(UpperCAmelCase					):
										with open(UpperCAmelCase   ,				'''r'''					) as f:
															UpperCamelCase__		:     str								=json.load(UpperCAmelCase					)
					else:
										raise ValueError(F'''can\'t find {path}'''					)
					return results



def 							_lowerCAmelCase   (    ):


					'''simple docstring'''






					return bool(tf.config.list_physical_devices('''GPU'''					)					)


_SCREAMING_SNAKE_CASE							:	Tuple										=			logging.StreamHandler(sys.stdout)
logger.addHandler(stream_handler)







class      __a (   snake_case__     ):

			"""simple docstring"""

			@skip('''Skipping until shape inference for to_tf_dataset PR is merged.'''    )
			def  _lowerCAmelCase      (				self  :       str    ):
								UpperCamelCase__		:     str								=self.get_auto_remove_tmp_dir()
								UpperCamelCase__		:     Any								=f'''
            run_text_classification.py
            --model_name_or_path distilbert-base-uncased
            --output_dir {tmp_dir}
            --overwrite_output_dir
            --train_file ./tests/fixtures/tests_samples/MRPC/train.csv
            --validation_file ./tests/fixtures/tests_samples/MRPC/dev.csv
            --do_train
            --do_eval
            --per_device_train_batch_size=2
            --per_device_eval_batch_size=1
            --learning_rate=1e-4
            --max_steps=10
            --warmup_steps=2
            --seed=42
            --max_seq_length=128
            '''.split()

								if is_cuda_available():
													testargs.append('''--fp16'''    )

								with patch.object(lowercase_    ,	'''argv'''    ,	lowercase_    ):
													run_text_classification.main()
													# Reset the mixed precision policy so we don't break other tests
													tf.keras.mixed_precision.set_global_policy('''float32'''    )
													UpperCamelCase__		:     int								=get_results(lowercase_    )
													self.assertGreaterEqual(result['''eval_accuracy''']    ,	0.7_5    )






			def  _lowerCAmelCase      (				self  :       str    ):
								UpperCamelCase__		:     str								=self.get_auto_remove_tmp_dir()
								UpperCamelCase__		:     List[str]								=f'''
            run_clm.py
            --model_name_or_path distilgpt2
            --train_file ./tests/fixtures/sample_text.txt
            --validation_file ./tests/fixtures/sample_text.txt
            --do_train
            --do_eval
            --block_size 128
            --per_device_train_batch_size 2
            --per_device_eval_batch_size 1
            --num_train_epochs 2
            --output_dir {tmp_dir}
            --overwrite_output_dir
            '''.split()

								if len(tf.config.list_physical_devices('''GPU'''    )    ) > 1:
													# Skipping because there are not enough batches to train the model + would need a drop_last to work.
													return

								with patch.object(lowercase_    ,	'''argv'''    ,	lowercase_    ):
													run_clm.main()
													UpperCamelCase__		:     Any								=get_results(lowercase_    )
													self.assertLess(result['''eval_perplexity''']    ,	100    )






			def  _lowerCAmelCase      (				self  :       int    ):
								UpperCamelCase__		:     Tuple								=self.get_auto_remove_tmp_dir()
								UpperCamelCase__		:     Union[str, Any]								=f'''
            run_mlm.py
            --model_name_or_path distilroberta-base
            --train_file ./tests/fixtures/sample_text.txt
            --validation_file ./tests/fixtures/sample_text.txt
            --max_seq_length 64
            --output_dir {tmp_dir}
            --overwrite_output_dir
            --do_train
            --do_eval
            --prediction_loss_only
            --num_train_epochs=1
            --learning_rate=1e-4
        '''.split()

								with patch.object(lowercase_    ,	'''argv'''    ,	lowercase_    ):
													run_mlm.main()
													UpperCamelCase__		:     Union[str, Any]								=get_results(lowercase_    )
													self.assertLess(result['''eval_perplexity''']    ,	42    )






			def  _lowerCAmelCase      (				self  :       Any    ):
								# with so little data distributed training needs more epochs to get the score on par with 0/1 gpu
								UpperCamelCase__		:     Any								=7 if get_gpu_count() > 1 else 2

								UpperCamelCase__		:     Tuple								=self.get_auto_remove_tmp_dir()
								UpperCamelCase__		:     str								=f'''
            run_ner.py
            --model_name_or_path bert-base-uncased
            --train_file tests/fixtures/tests_samples/conll/sample.json
            --validation_file tests/fixtures/tests_samples/conll/sample.json
            --output_dir {tmp_dir}
            --overwrite_output_dir
            --do_train
            --do_eval
            --warmup_steps=2
            --learning_rate=2e-4
            --per_device_train_batch_size=2
            --per_device_eval_batch_size=2
            --num_train_epochs={epochs}
            --seed 7
        '''.split()

								with patch.object(lowercase_    ,	'''argv'''    ,	lowercase_    ):
													run_ner.main()
													UpperCamelCase__		:     Tuple								=get_results(lowercase_    )
													self.assertGreaterEqual(result['''accuracy''']    ,	0.7_5    )






			def  _lowerCAmelCase      (				self  :       Dict    ):
								UpperCamelCase__		:     Dict								=self.get_auto_remove_tmp_dir()
								UpperCamelCase__		:     Optional[int]								=f'''
            run_qa.py
            --model_name_or_path bert-base-uncased
            --version_2_with_negative
            --train_file tests/fixtures/tests_samples/SQUAD/sample.json
            --validation_file tests/fixtures/tests_samples/SQUAD/sample.json
            --output_dir {tmp_dir}
            --overwrite_output_dir
            --max_steps=10
            --warmup_steps=2
            --do_train
            --do_eval
            --learning_rate=2e-4
            --per_device_train_batch_size=2
            --per_device_eval_batch_size=1
        '''.split()

								with patch.object(lowercase_    ,	'''argv'''    ,	lowercase_    ):
													run_squad.main()
													UpperCamelCase__		:     Optional[Any]								=get_results(lowercase_    )
													self.assertGreaterEqual(result['''f1''']    ,	30    )
													self.assertGreaterEqual(result['''exact''']    ,	30    )






			def  _lowerCAmelCase      (				self  :       Dict    ):
								UpperCamelCase__		:     Union[str, Any]								=self.get_auto_remove_tmp_dir()
								UpperCamelCase__		:     Any								=f'''
            run_swag.py
            --model_name_or_path bert-base-uncased
            --train_file tests/fixtures/tests_samples/swag/sample.json
            --validation_file tests/fixtures/tests_samples/swag/sample.json
            --output_dir {tmp_dir}
            --overwrite_output_dir
            --max_steps=20
            --warmup_steps=2
            --do_train
            --do_eval
            --learning_rate=2e-4
            --per_device_train_batch_size=2
            --per_device_eval_batch_size=1
        '''.split()

								with patch.object(lowercase_    ,	'''argv'''    ,	lowercase_    ):
													run_swag.main()
													UpperCamelCase__		:     Any								=get_results(lowercase_    )
													self.assertGreaterEqual(result['''val_accuracy''']    ,	0.8    )






			@slow
			def  _lowerCAmelCase      (				self  :       str    ):
								UpperCamelCase__		:     int								=self.get_auto_remove_tmp_dir()
								UpperCamelCase__		:     Dict								=f'''
            run_summarization.py
            --model_name_or_path t5-small
            --train_file tests/fixtures/tests_samples/xsum/sample.json
            --validation_file tests/fixtures/tests_samples/xsum/sample.json
            --output_dir {tmp_dir}
            --overwrite_output_dir
            --max_steps=50
            --warmup_steps=8
            --do_train
            --do_eval
            --learning_rate=2e-4
            --per_device_train_batch_size=2
            --per_device_eval_batch_size=1
        '''.split()

								with patch.object(lowercase_    ,	'''argv'''    ,	lowercase_    ):
													run_summarization.main()
													UpperCamelCase__		:     Union[str, Any]								=get_results(lowercase_    )
													self.assertGreaterEqual(result['''rouge1''']    ,	10    )
													self.assertGreaterEqual(result['''rouge2''']    ,	2    )
													self.assertGreaterEqual(result['''rougeL''']    ,	7    )
													self.assertGreaterEqual(result['''rougeLsum''']    ,	7    )






			@slow
			def  _lowerCAmelCase      (				self  :       Union[str, Any]    ):
								UpperCamelCase__		:     Any								=self.get_auto_remove_tmp_dir()
								UpperCamelCase__		:     Any								=f'''
            run_translation.py
            --model_name_or_path Rocketknight1/student_marian_en_ro_6_1
            --source_lang en
            --target_lang ro
            --train_file tests/fixtures/tests_samples/wmt16/sample.json
            --validation_file tests/fixtures/tests_samples/wmt16/sample.json
            --output_dir {tmp_dir}
            --overwrite_output_dir
            --warmup_steps=8
            --do_train
            --do_eval
            --learning_rate=3e-3
            --num_train_epochs 12
            --per_device_train_batch_size=2
            --per_device_eval_batch_size=1
            --source_lang en_XX
            --target_lang ro_RO
        '''.split()

								with patch.object(lowercase_    ,	'''argv'''    ,	lowercase_    ):
													run_translation.main()
													UpperCamelCase__		:     Any								=get_results(lowercase_    )
													self.assertGreaterEqual(result['''bleu''']    ,	30    )






			def  _lowerCAmelCase      (				self  :       int    ):
								UpperCamelCase__		:     int								=self.get_auto_remove_tmp_dir()
								UpperCamelCase__		:     Tuple								=f'''
            run_image_classification.py
            --dataset_name hf-internal-testing/cats_vs_dogs_sample
            --model_name_or_path microsoft/resnet-18
            --do_train
            --do_eval
            --learning_rate 1e-4
            --per_device_train_batch_size 2
            --per_device_eval_batch_size 1
            --output_dir {tmp_dir}
            --overwrite_output_dir
            --dataloader_num_workers 16
            --num_train_epochs 2
            --train_val_split 0.1
            --seed 42
            --ignore_mismatched_sizes True
            '''.split()

								with patch.object(lowercase_    ,	'''argv'''    ,	lowercase_    ):
													run_image_classification.main()
													UpperCamelCase__		:     Optional[Any]								=get_results(lowercase_    )
													self.assertGreaterEqual(result['''accuracy''']    ,	0.7    )





"""simple docstring"""





import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_mpnet import MPNetTokenizer


_SCREAMING_SNAKE_CASE							:	Union[str, Any]										=			logging.get_logger(__name__)

_SCREAMING_SNAKE_CASE							:	Union[str, Any]										=			{"""vocab_file""": """vocab.txt""", """tokenizer_file""": """tokenizer.json"""}

_SCREAMING_SNAKE_CASE							:	List[Any]										=			{
    """vocab_file""": {
        """microsoft/mpnet-base""": """https://huggingface.co/microsoft/mpnet-base/resolve/main/vocab.txt""",
    },
    """tokenizer_file""": {
        """microsoft/mpnet-base""": """https://huggingface.co/microsoft/mpnet-base/resolve/main/tokenizer.json""",
    },
}

_SCREAMING_SNAKE_CASE							:	List[Any]										=			{
    """microsoft/mpnet-base""": 5_1_2,
}

_SCREAMING_SNAKE_CASE							:	Optional[int]										=			{
    """microsoft/mpnet-base""": {"""do_lower_case""": True},
}

class      __a (   snake_case__     ):

			"""simple docstring"""

			SCREAMING_SNAKE_CASE_      =    VOCAB_FILES_NAMES
			SCREAMING_SNAKE_CASE_      =    PRETRAINED_VOCAB_FILES_MAP
			SCREAMING_SNAKE_CASE_      =    PRETRAINED_INIT_CONFIGURATION
			SCREAMING_SNAKE_CASE_      =    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			SCREAMING_SNAKE_CASE_      =    MPNetTokenizer
			SCREAMING_SNAKE_CASE_      =    ['input_ids', 'attention_mask']






			def __init__(				self  :       List[str]    ,	lowercase_  :       List[Any]=None    ,	lowercase_  :       Optional[int]=None    ,	lowercase_  :       Optional[int]=True    ,	lowercase_  :       str="<s>"    ,	lowercase_  :       str="</s>"    ,	lowercase_  :       List[Any]="</s>"    ,	lowercase_  :       Tuple="<s>"    ,	lowercase_  :       Any="[UNK]"    ,	lowercase_  :       Dict="<pad>"    ,	lowercase_  :       Optional[Any]="<mask>"    ,	lowercase_  :       List[str]=True    ,	lowercase_  :       Optional[Any]=None    ,	**lowercase_  :       Dict    ,	):
								super().__init__(
								    lowercase_    ,	tokenizer_file=lowercase_    ,	do_lower_case=lowercase_    ,	bos_token=lowercase_    ,	eos_token=lowercase_    ,	sep_token=lowercase_    ,	cls_token=lowercase_    ,	unk_token=lowercase_    ,	pad_token=lowercase_    ,	mask_token=lowercase_    ,	tokenize_chinese_chars=lowercase_    ,	strip_accents=lowercase_    ,	**lowercase_    ,	)

								UpperCamelCase__		:     List[str]								=json.loads(self.backend_tokenizer.normalizer.__getstate__()    )
								if (
								    pre_tok_state.get('''lowercase'''    ,	lowercase_    ) != do_lower_case
								    or pre_tok_state.get('''strip_accents'''    ,	lowercase_    ) != strip_accents
								):
													UpperCamelCase__		:     int								=getattr(lowercase_    ,	pre_tok_state.pop('''type'''    )    )
													UpperCamelCase__		:     List[Any]								=do_lower_case
													UpperCamelCase__		:     Optional[Any]								=strip_accents
													UpperCamelCase__		:     Optional[int]								=pre_tok_class(**lowercase_    )

								UpperCamelCase__		:     Tuple								=do_lower_case






			@property
			def  _lowerCAmelCase      (				self  :       List[str]    ):
								if self._mask_token is None:
													if self.verbose:
																		logger.error('''Using mask_token, but it is not set yet.'''    )
													return None
								return str(self._mask_token    )






			@mask_token.setter
			def  _lowerCAmelCase      (				self  :       int    ,	lowercase_  :       str    ):
								UpperCamelCase__		:     int								=AddedToken(lowercase_    ,	lstrip=lowercase_    ,	rstrip=lowercase_    ) if isinstance(lowercase_    ,	lowercase_    ) else value
								UpperCamelCase__		:     str								=value






			def  _lowerCAmelCase      (				self  :       Tuple    ,	lowercase_  :       Any    ,	lowercase_  :       Tuple=None    ):
								UpperCamelCase__		:     int								=[self.bos_token_id] + token_ids_a + [self.eos_token_id]
								if token_ids_a is None:
													return output

								return output + [self.eos_token_id] + token_ids_a + [self.eos_token_id]






			def  _lowerCAmelCase      (				self  :       List[str]    ,	lowercase_  :       List[int]    ,	lowercase_  :       Optional[List[int]] = None    ):
								UpperCamelCase__		:     str								=[self.sep_token_id]
								UpperCamelCase__		:     List[str]								=[self.cls_token_id]

								if token_ids_a is None:
													return len(cls + token_ids_a + sep    ) * [0]
								return len(cls + token_ids_a + sep + sep + token_ids_a + sep    ) * [0]






			def  _lowerCAmelCase      (				self  :       str    ,	lowercase_  :       str    ,	lowercase_  :       Optional[str] = None    ):
								UpperCamelCase__		:     List[Any]								=self._tokenizer.model.save(lowercase_    ,	name=lowercase_    )
								return tuple(lowercase_    )


