





'''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  )













'''simple docstring'''




import os

import pytest
import yaml

from datasets.features.features import Features, Value
from datasets.info import DatasetInfo, DatasetInfosDict
@pytest.mark.parametrize(
    "files"			,     [
        ["full:README.md", "dataset_infos.json"],
        ["empty:README.md", "dataset_infos.json"],
        ["dataset_infos.json"],
        ["full:README.md"],
    ]			,     )
def 	UpperCAmelCase_							(					__lowercase							:      Any			,     __lowercase							:      int       )		->       int:


     '''simple docstring'''



     _UpperCAmelCase     							=   tmp_path_factory.mktemp("dset_infos_dir"       )
     if "full:README.md" in files:
          with open(dataset_infos_dir / "README.md"			,     "w"       ) as f:
               f.write("---\ndataset_info:\n  dataset_size: 42\n---"       )
     if "empty:README.md" in files:
          with open(dataset_infos_dir / "README.md"			,     "w"       ) as f:
               f.write(""       )
    # we want to support dataset_infos.json for backward compatibility
     if "dataset_infos.json" in files:
          with open(dataset_infos_dir / "dataset_infos.json"			,     "w"       ) as f:
               f.write("{\"default\": {\"dataset_size\": 42}}"       )
     _UpperCAmelCase     							=   DatasetInfosDict.from_directory(__lowercase       )
     assert dataset_infos
     assert dataset_infos["default"].dataset_size == 42
@pytest.mark.parametrize(
    "dataset_info"			,     [
        DatasetInfo(),
        DatasetInfo(
            description="foo"			,     features=Features({"a": Value("int32"       )}       )			,     builder_name="builder"			,     config_name="config"			,     version="1.0.0"			,     splits=[{"name": "train"}]			,     download_size=42			,     ),
    ]			,     )
def 	UpperCAmelCase_							(					__lowercase							:      Tuple			,     __lowercase							:      DatasetInfo       )		->       Any:


     '''simple docstring'''



     _UpperCAmelCase     							=   str(__lowercase       )
     dataset_info.write_to_directory(__lowercase       )
     _UpperCAmelCase     							=   DatasetInfo.from_directory(__lowercase       )
     assert dataset_info == reloaded
     assert os.path.exists(os.path.join(__lowercase			,     "dataset_info.json"       )       )
def 	UpperCAmelCase_							(					)		->       Optional[Any]:


     '''simple docstring'''



     _UpperCAmelCase     							=   DatasetInfo(
         description="foo"			,     citation="bar"			,     homepage="https://foo.bar"			,     license="CC0"			,     features=Features({"a": Value("int32"       )}       )			,     post_processed={}			,     supervised_keys=()			,     task_templates=[]			,     builder_name="builder"			,     config_name="config"			,     version="1.0.0"			,     splits=[{"name": "train", "num_examples": 42}]			,     download_checksums={}			,     download_size=1337			,     post_processing_size=442			,     dataset_size=1234			,     size_in_bytes=1337 + 442 + 1234			,     )
     _UpperCAmelCase     							=   dataset_info._to_yaml_dict()
     assert sorted(__lowercase       ) == sorted(DatasetInfo._INCLUDED_INFO_IN_YAML       )
     for key in DatasetInfo._INCLUDED_INFO_IN_YAML:
          assert key in dataset_info_yaml_dict
          assert isinstance(dataset_info_yaml_dict[key]			,     (list, dict, int, str)       )
     _UpperCAmelCase     							=   yaml.safe_dump(__lowercase       )
     _UpperCAmelCase     							=   yaml.safe_load(__lowercase       )
     assert dataset_info_yaml_dict == reloaded
def 	UpperCAmelCase_							(					)		->       Optional[int]:


     '''simple docstring'''



     _UpperCAmelCase     							=   DatasetInfo()
     _UpperCAmelCase     							=   dataset_info._to_yaml_dict()
     assert dataset_info_yaml_dict == {}






@pytest.mark.parametrize(
    "dataset_infos_dict"			,     [
        DatasetInfosDict(),
        DatasetInfosDict({"default": DatasetInfo()}       ),
        DatasetInfosDict({"my_config_name": DatasetInfo()}       ),
        DatasetInfosDict(
            {
                "default": DatasetInfo(
                    description="foo"			,     features=Features({"a": Value("int32"       )}       )			,     builder_name="builder"			,     config_name="config"			,     version="1.0.0"			,     splits=[{"name": "train"}]			,     download_size=42			,     )
            }       ),
        DatasetInfosDict(
            {
                "v1": DatasetInfo(dataset_size=42       ),
                "v2": DatasetInfo(dataset_size=1337       ),
            }       ),
    ]			,     )
def 	UpperCAmelCase_							(					__lowercase							:      int			,     __lowercase							:      DatasetInfosDict       )		->       Dict:


     '''simple docstring'''



     _UpperCAmelCase     							=   str(__lowercase       )
     dataset_infos_dict.write_to_directory(__lowercase       )
     _UpperCAmelCase     							=   DatasetInfosDict.from_directory(__lowercase       )

     # the config_name of the dataset_infos_dict take over the attribute
     for config_name, dataset_info in dataset_infos_dict.items():
          _UpperCAmelCase     							=   config_name
          # the yaml representation doesn't include fields like description or citation
          # so we just test that we can recover what we can from the yaml
          _UpperCAmelCase     							=   DatasetInfo._from_yaml_dict(dataset_info._to_yaml_dict()       )
     assert dataset_infos_dict == reloaded

     if dataset_infos_dict:
          assert os.path.exists(os.path.join(__lowercase			,     "README.md"       )       )




