
'''simple docstring'''
import argparse
import json
import logging
import os
import sys
from unittest.mock import patch

from transformers.testing_utils import TestCasePlus, get_gpu_count, slow


lowercase__						       =      [
    os.path.join(os.path.dirname(__file__), dirname)
    for dirname in [
        "text-classification",
        "language-modeling",
        "summarization",
        "token-classification",
        "question-answering",
    ]
]
sys.path.extend(SRC_DIRS)


if SRC_DIRS is not None:
						import run_clm_flax
						import run_flax_glue
						import run_flax_ner
						import run_mlm_flax
						import run_qa
						import run_summarization_flax
						import run_ta_mlm_flax


logging.basicConfig(level=logging.DEBUG)

lowercase__						       =      logging.getLogger()




def    _UpperCamelCase						(       )  ->							List[Any]:


		'''simple docstring'''


		snake_case  :       List[Any]     			=						argparse.ArgumentParser()
		parser.add_argument('''-f'''			)
		snake_case  :       int     			=						parser.parse_args()
		return args.f




def    _UpperCamelCase						(       SCREAMING_SNAKE_CASE__ ,       SCREAMING_SNAKE_CASE__="eval"			)  ->							Union[str, Any]:


		'''simple docstring'''


		snake_case  :       Optional[Any]     			=						os.path.join(SCREAMING_SNAKE_CASE__ ,       F'{split}_results.json'			)
		if os.path.exists(SCREAMING_SNAKE_CASE__			):
				with open(SCREAMING_SNAKE_CASE__ ,       '''r'''			) as f:
						return json.load(SCREAMING_SNAKE_CASE__			)
		raise ValueError(F'can\'t find {path}'			)


lowercase__						       =      logging.StreamHandler(sys.stdout)
logger.addHandler(stream_handler)






class 	snake_case__       (      __SCREAMING_SNAKE_CASE					):







		"""simple docstring"""

		def       lowerCAmelCase				(      self				:			Tuple      )						->			Any:






				"""simple docstring"""







				snake_case  :       Tuple     			=						self.get_auto_remove_tmp_dir()
				snake_case  :       Union[str, Any]     			=						f'\n            run_glue.py\n            --model_name_or_path distilbert-base-uncased\n            --output_dir {tmp_dir}\n            --train_file ./tests/fixtures/tests_samples/MRPC/train.csv\n            --validation_file ./tests/fixtures/tests_samples/MRPC/dev.csv\n            --per_device_train_batch_size=2\n            --per_device_eval_batch_size=1\n            --learning_rate=1e-4\n            --eval_steps=2\n            --warmup_steps=2\n            --seed=42\n            --max_seq_length=128\n            '.split()

				with patch.object(UpperCamelCase__  ,	'''argv'''  ,	UpperCamelCase__      ):
						run_flax_glue.main()
						snake_case  :       List[Any]     			=						get_results(UpperCamelCase__      )
						self.assertGreaterEqual(result['''eval_accuracy''']  ,	0.75      )



		@slow
		def       lowerCAmelCase				(      self				:			Any      )						->			Dict:






				"""simple docstring"""







				snake_case  :       Dict     			=						self.get_auto_remove_tmp_dir()
				snake_case  :       Dict     			=						f'\n            run_clm_flax.py\n            --model_name_or_path distilgpt2\n            --train_file ./tests/fixtures/sample_text.txt\n            --validation_file ./tests/fixtures/sample_text.txt\n            --do_train\n            --do_eval\n            --block_size 128\n            --per_device_train_batch_size 4\n            --per_device_eval_batch_size 4\n            --num_train_epochs 2\n            --logging_steps 2 --eval_steps 2\n            --output_dir {tmp_dir}\n            --overwrite_output_dir\n            '.split()

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



		@slow
		def       lowerCAmelCase				(      self				:			Any      )						->			Dict:






				"""simple docstring"""







				snake_case  :       Tuple     			=						self.get_auto_remove_tmp_dir()
				snake_case  :       Any     			=						f'\n            run_summarization.py\n            --model_name_or_path t5-small\n            --train_file tests/fixtures/tests_samples/xsum/sample.json\n            --validation_file tests/fixtures/tests_samples/xsum/sample.json\n            --test_file tests/fixtures/tests_samples/xsum/sample.json\n            --output_dir {tmp_dir}\n            --overwrite_output_dir\n            --num_train_epochs=3\n            --warmup_steps=8\n            --do_train\n            --do_eval\n            --do_predict\n            --learning_rate=2e-4\n            --per_device_train_batch_size=2\n            --per_device_eval_batch_size=1\n            --predict_with_generate\n        '.split()

				with patch.object(UpperCamelCase__  ,	'''argv'''  ,	UpperCamelCase__      ):
						run_summarization_flax.main()
						snake_case  :       int     			=						get_results(UpperCamelCase__  ,	split='''test'''      )
						self.assertGreaterEqual(result['''test_rouge1''']  ,	10      )
						self.assertGreaterEqual(result['''test_rouge2''']  ,	2      )
						self.assertGreaterEqual(result['''test_rougeL''']  ,	7      )
						self.assertGreaterEqual(result['''test_rougeLsum''']  ,	7      )



		@slow
		def       lowerCAmelCase				(      self				:			Dict      )						->			Tuple:






				"""simple docstring"""







				snake_case  :       Optional[int]     			=						self.get_auto_remove_tmp_dir()
				snake_case  :       str     			=						f'\n            run_mlm.py\n            --model_name_or_path distilroberta-base\n            --train_file ./tests/fixtures/sample_text.txt\n            --validation_file ./tests/fixtures/sample_text.txt\n            --output_dir {tmp_dir}\n            --overwrite_output_dir\n            --max_seq_length 128\n            --per_device_train_batch_size 4\n            --per_device_eval_batch_size 4\n            --logging_steps 2 --eval_steps 2\n            --do_train\n            --do_eval\n            --num_train_epochs=1\n        '.split()

				with patch.object(UpperCamelCase__  ,	'''argv'''  ,	UpperCamelCase__      ):
						run_mlm_flax.main()
						snake_case  :       Tuple     			=						get_results(UpperCamelCase__      )
						self.assertLess(result['''eval_perplexity''']  ,	42      )



		@slow
		def       lowerCAmelCase				(      self				:			Union[str, Any]      )						->			Optional[Any]:






				"""simple docstring"""







				snake_case  :       Optional[int]     			=						self.get_auto_remove_tmp_dir()
				snake_case  :       Any     			=						f'\n            run_t5_mlm_flax.py\n            --model_name_or_path t5-small\n            --train_file ./tests/fixtures/sample_text.txt\n            --validation_file ./tests/fixtures/sample_text.txt\n            --do_train\n            --do_eval\n            --max_seq_length 128\n            --per_device_train_batch_size 4\n            --per_device_eval_batch_size 4\n            --num_train_epochs 2\n            --logging_steps 2 --eval_steps 2\n            --output_dir {tmp_dir}\n            --overwrite_output_dir\n            '.split()

				with patch.object(UpperCamelCase__  ,	'''argv'''  ,	UpperCamelCase__      ):
						run_ta_mlm_flax.main()
						snake_case  :       List[Any]     			=						get_results(UpperCamelCase__      )
						self.assertGreaterEqual(result['''eval_accuracy''']  ,	0.42      )



		@slow
		def       lowerCAmelCase				(      self				:			Optional[int]      )						->			Tuple:






				"""simple docstring"""







				snake_case  :       Optional[int]     			=						7 if get_gpu_count() > 1 else 2

				snake_case  :       List[Any]     			=						self.get_auto_remove_tmp_dir()
				snake_case  :       Optional[int]     			=						f'\n            run_flax_ner.py\n            --model_name_or_path bert-base-uncased\n            --train_file tests/fixtures/tests_samples/conll/sample.json\n            --validation_file tests/fixtures/tests_samples/conll/sample.json\n            --output_dir {tmp_dir}\n            --overwrite_output_dir\n            --do_train\n            --do_eval\n            --warmup_steps=2\n            --learning_rate=2e-4\n            --logging_steps 2 --eval_steps 2\n            --per_device_train_batch_size=2\n            --per_device_eval_batch_size=2\n            --num_train_epochs={epochs}\n            --seed 7\n        '.split()

				with patch.object(UpperCamelCase__  ,	'''argv'''  ,	UpperCamelCase__      ):
						run_flax_ner.main()
						snake_case  :       int     			=						get_results(UpperCamelCase__      )
						self.assertGreaterEqual(result['''eval_accuracy''']  ,	0.75      )
						self.assertGreaterEqual(result['''eval_f1''']  ,	0.3      )



		@slow
		def       lowerCAmelCase				(      self				:			Optional[int]      )						->			str:






				"""simple docstring"""







				snake_case  :       List[Any]     			=						self.get_auto_remove_tmp_dir()
				snake_case  :       Dict     			=						f'\n            run_qa.py\n            --model_name_or_path bert-base-uncased\n            --version_2_with_negative\n            --train_file tests/fixtures/tests_samples/SQUAD/sample.json\n            --validation_file tests/fixtures/tests_samples/SQUAD/sample.json\n            --output_dir {tmp_dir}\n            --overwrite_output_dir\n            --num_train_epochs=3\n            --warmup_steps=2\n            --do_train\n            --do_eval\n            --logging_steps 2 --eval_steps 2\n            --learning_rate=2e-4\n            --per_device_train_batch_size=2\n            --per_device_eval_batch_size=1\n        '.split()

				with patch.object(UpperCamelCase__  ,	'''argv'''  ,	UpperCamelCase__      ):
						run_qa.main()
						snake_case  :       Union[str, Any]     			=						get_results(UpperCamelCase__      )
						self.assertGreaterEqual(result['''eval_f1''']  ,	30      )
						self.assertGreaterEqual(result['''eval_exact''']  ,	30      )




'''simple docstring'''
from .data_collator import (
    DataCollatorForLanguageModeling,
    DataCollatorForPermutationLanguageModeling,
    DataCollatorForSeqaSeq,
    DataCollatorForSOP,
    DataCollatorForTokenClassification,
    DataCollatorForWholeWordMask,
    DataCollatorWithPadding,
    DefaultDataCollator,
    default_data_collator,
)
from .metrics import glue_compute_metrics, xnli_compute_metrics
from .processors import (
    DataProcessor,
    InputExample,
    InputFeatures,
    SingleSentenceClassificationProcessor,
    SquadExample,
    SquadFeatures,
    SquadVaProcessor,
    SquadVaProcessor,
    glue_convert_examples_to_features,
    glue_output_modes,
    glue_processors,
    glue_tasks_num_labels,
    squad_convert_examples_to_features,
    xnli_output_modes,
    xnli_processors,
    xnli_tasks_num_labels,
)


