





'''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


A__				:   Optional[int]      =[
    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)

A__				:   List[Any]      =logging.getLogger()
def    UpperCamelCase__      (		):





      """simple docstring"""


      _lowerCAmelCase							     =							argparse.ArgumentParser()
      parser.add_argument("""-f"""  )
      _lowerCAmelCase							     =							parser.parse_args()
      return args.f
def    UpperCamelCase__      (		lowerCAmelCase							,	lowerCAmelCase="eval"  ):





      """simple docstring"""


      _lowerCAmelCase							     =							os.path.join(lowerCAmelCase							,	f"{split}_results.json"  )
      if os.path.exists(lowerCAmelCase  ):
            with open(lowerCAmelCase							,	"""r"""  ) as f:
                  return json.load(lowerCAmelCase  )
      raise ValueError(f"can't find {path}"  )


A__				:   int      =logging.StreamHandler(sys.stdout)
logger.addHandler(stream_handler)





class  UpperCAmelCase     (			snake_case_   ):




      def 				lowercase__    (			self			: List[str]  )				->      Optional[int]:
            _lowerCAmelCase							     =							self.get_auto_remove_tmp_dir()
            _lowerCAmelCase							     =							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(__snake_case			,			"""argv"""			,			__snake_case  ):
                  run_flax_glue.main()
                  _lowerCAmelCase							     =							get_results(__snake_case  )
                  self.assertGreaterEqual(result["""eval_accuracy"""]			,			0.75  )




      @slow
      def 				lowercase__    (			self			: Tuple  )				->      Any:
            _lowerCAmelCase							     =							self.get_auto_remove_tmp_dir()
            _lowerCAmelCase							     =							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(__snake_case			,			"""argv"""			,			__snake_case  ):
                  run_clm_flax.main()
                  _lowerCAmelCase							     =							get_results(__snake_case  )
                  self.assertLess(result["""eval_perplexity"""]			,			1_00  )




      @slow
      def 				lowercase__    (			self			: Union[str, Any]  )				->      str:
            _lowerCAmelCase							     =							self.get_auto_remove_tmp_dir()
            _lowerCAmelCase							     =							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(__snake_case			,			"""argv"""			,			__snake_case  ):
                  run_summarization_flax.main()
                  _lowerCAmelCase							     =							get_results(__snake_case			,			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 				lowercase__    (			self			: Optional[int]  )				->      List[Any]:
            _lowerCAmelCase							     =							self.get_auto_remove_tmp_dir()
            _lowerCAmelCase							     =							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(__snake_case			,			"""argv"""			,			__snake_case  ):
                  run_mlm_flax.main()
                  _lowerCAmelCase							     =							get_results(__snake_case  )
                  self.assertLess(result["""eval_perplexity"""]			,			42  )




      @slow
      def 				lowercase__    (			self			: List[Any]  )				->      Optional[Any]:
            _lowerCAmelCase							     =							self.get_auto_remove_tmp_dir()
            _lowerCAmelCase							     =							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(__snake_case			,			"""argv"""			,			__snake_case  ):
                  run_ta_mlm_flax.main()
                  _lowerCAmelCase							     =							get_results(__snake_case  )
                  self.assertGreaterEqual(result["""eval_accuracy"""]			,			0.42  )




      @slow
      def 				lowercase__    (			self			: Optional[Any]  )				->      Tuple:
            # with so little data distributed training needs more epochs to get the score on par with 0/1 gpu
            _lowerCAmelCase							     =							7 if get_gpu_count() > 1 else 2

            _lowerCAmelCase							     =							self.get_auto_remove_tmp_dir()
            _lowerCAmelCase							     =							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(__snake_case			,			"""argv"""			,			__snake_case  ):
                  run_flax_ner.main()
                  _lowerCAmelCase							     =							get_results(__snake_case  )
                  self.assertGreaterEqual(result["""eval_accuracy"""]			,			0.75  )
                  self.assertGreaterEqual(result["""eval_f1"""]			,			0.3  )




      @slow
      def 				lowercase__    (			self			: List[str]  )				->      Union[str, Any]:
            _lowerCAmelCase							     =							self.get_auto_remove_tmp_dir()
            _lowerCAmelCase							     =							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(__snake_case			,			"""argv"""			,			__snake_case  ):
                  run_qa.main()
                  _lowerCAmelCase							     =							get_results(__snake_case  )
                  self.assertGreaterEqual(result["""eval_f1"""]			,			30  )
                  self.assertGreaterEqual(result["""eval_exact"""]			,			30  )














import warnings

from ...utils import logging
from .image_processing_imagegpt import ImageGPTImageProcessor


__UpperCAmelCase								=						logging.get_logger(__name__)



class   lowerCamelCase      (_snake_case			):







		'''simple docstring'''



		def __init__(							self				,		*_UpperCamelCase				,		**_UpperCamelCase   )	->							None:
							warnings.warn(
							    'The class ImageGPTFeatureExtractor is deprecated and will be removed in version 5 of Transformers.'
							    ' Please use ImageGPTImageProcessor instead.'				,		_UpperCamelCase				,		)
							super().__init__(*_UpperCamelCase				,		**_UpperCamelCase   )






