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


__lowerCamelCase			: str							   =		[
    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)

__lowerCamelCase			: Tuple							   =		logging.getLogger()



def 	__SCREAMING_SNAKE_CASE  (					)							->					Optional[Any]:







  """simple docstring"""





  SCREAMING_SNAKE_CASE__										=      argparse.ArgumentParser()
  parser.add_argument("""-f"""	)
  SCREAMING_SNAKE_CASE__										=      parser.parse_args()
  return args.f



def 	__SCREAMING_SNAKE_CASE  (					__UpperCamelCase    :       Optional[int] ,     __UpperCamelCase    :       Dict="eval"	)							->					Optional[Any]:







  """simple docstring"""





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


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







class __snake_case				(						lowerCamelCase_		):




   def 	__a						(    self			:				Dict      ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__										=      self.get_auto_remove_tmp_dir()
     SCREAMING_SNAKE_CASE__										=      f"""
            run_glue.py
            --model_name_or_path distilbert-base-uncased
            --output_dir {tmp_dir}
            --train_file ./tests/fixtures/tests_samples/MRPC/train.csv
            --validation_file ./tests/fixtures/tests_samples/MRPC/dev.csv
            --per_device_train_batch_size=2
            --per_device_eval_batch_size=1
            --learning_rate=1e-4
            --eval_steps=2
            --warmup_steps=2
            --seed=42
            --max_seq_length=128
            """.split()

     with patch.object(_lowercase       ,	"""argv"""       ,	_lowercase      ):
       run_flax_glue.main()
       SCREAMING_SNAKE_CASE__										=      get_results(_lowercase      )
       self.assertGreaterEqual(result["""eval_accuracy"""]       ,	0.75      )




   @slow
   def 	__a						(    self			:				List[Any]      ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__										=      self.get_auto_remove_tmp_dir()
     SCREAMING_SNAKE_CASE__										=      f"""
            run_clm_flax.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 4
            --per_device_eval_batch_size 4
            --num_train_epochs 2
            --logging_steps 2 --eval_steps 2
            --output_dir {tmp_dir}
            --overwrite_output_dir
            """.split()

     with patch.object(_lowercase       ,	"""argv"""       ,	_lowercase      ):
       run_clm_flax.main()
       SCREAMING_SNAKE_CASE__										=      get_results(_lowercase      )
       self.assertLess(result["""eval_perplexity"""]       ,	1_00      )




   @slow
   def 	__a						(    self			:				Optional[int]      ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__										=      self.get_auto_remove_tmp_dir()
     SCREAMING_SNAKE_CASE__										=      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
            --test_file tests/fixtures/tests_samples/xsum/sample.json
            --output_dir {tmp_dir}
            --overwrite_output_dir
            --num_train_epochs=3
            --warmup_steps=8
            --do_train
            --do_eval
            --do_predict
            --learning_rate=2e-4
            --per_device_train_batch_size=2
            --per_device_eval_batch_size=1
            --predict_with_generate
        """.split()

     with patch.object(_lowercase       ,	"""argv"""       ,	_lowercase      ):
       run_summarization_flax.main()
       SCREAMING_SNAKE_CASE__										=      get_results(_lowercase       ,	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 	__a						(    self			:				Optional[Any]      ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__										=      self.get_auto_remove_tmp_dir()
     SCREAMING_SNAKE_CASE__										=      f"""
            run_mlm.py
            --model_name_or_path distilroberta-base
            --train_file ./tests/fixtures/sample_text.txt
            --validation_file ./tests/fixtures/sample_text.txt
            --output_dir {tmp_dir}
            --overwrite_output_dir
            --max_seq_length 128
            --per_device_train_batch_size 4
            --per_device_eval_batch_size 4
            --logging_steps 2 --eval_steps 2
            --do_train
            --do_eval
            --num_train_epochs=1
        """.split()

     with patch.object(_lowercase       ,	"""argv"""       ,	_lowercase      ):
       run_mlm_flax.main()
       SCREAMING_SNAKE_CASE__										=      get_results(_lowercase      )
       self.assertLess(result["""eval_perplexity"""]       ,	42      )




   @slow
   def 	__a						(    self			:				int      ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__										=      self.get_auto_remove_tmp_dir()
     SCREAMING_SNAKE_CASE__										=      f"""
            run_t5_mlm_flax.py
            --model_name_or_path t5-small
            --train_file ./tests/fixtures/sample_text.txt
            --validation_file ./tests/fixtures/sample_text.txt
            --do_train
            --do_eval
            --max_seq_length 128
            --per_device_train_batch_size 4
            --per_device_eval_batch_size 4
            --num_train_epochs 2
            --logging_steps 2 --eval_steps 2
            --output_dir {tmp_dir}
            --overwrite_output_dir
            """.split()

     with patch.object(_lowercase       ,	"""argv"""       ,	_lowercase      ):
       run_ta_mlm_flax.main()
       SCREAMING_SNAKE_CASE__										=      get_results(_lowercase      )
       self.assertGreaterEqual(result["""eval_accuracy"""]       ,	0.42      )




   @slow
   def 	__a						(    self			:				Dict      ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__										=      7 if get_gpu_count() > 1 else 2

     SCREAMING_SNAKE_CASE__										=      self.get_auto_remove_tmp_dir()
     SCREAMING_SNAKE_CASE__										=      f"""
            run_flax_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
            --logging_steps 2 --eval_steps 2
            --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_flax_ner.main()
       SCREAMING_SNAKE_CASE__										=      get_results(_lowercase      )
       self.assertGreaterEqual(result["""eval_accuracy"""]       ,	0.75      )
       self.assertGreaterEqual(result["""eval_f1"""]       ,	0.3      )




   @slow
   def 	__a						(    self			:				Dict      ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__										=      self.get_auto_remove_tmp_dir()
     SCREAMING_SNAKE_CASE__										=      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
            --num_train_epochs=3
            --warmup_steps=2
            --do_train
            --do_eval
            --logging_steps 2 --eval_steps 2
            --learning_rate=2e-4
            --per_device_train_batch_size=2
            --per_device_eval_batch_size=1
        """.split()

     with patch.object(_lowercase       ,	"""argv"""       ,	_lowercase      ):
       run_qa.main()
       SCREAMING_SNAKE_CASE__										=      get_results(_lowercase      )
       self.assertGreaterEqual(result["""eval_f1"""]       ,	30      )
       self.assertGreaterEqual(result["""eval_exact"""]       ,	30      )

# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run

import sys
import warnings
from os.path import abspath, dirname, join


# allow having multiple repository checkouts and not needing to remember to rerun
# 'pip install -e .[dev]' when switching between checkouts and running tests.
__lowerCamelCase			: Any							   =		abspath(join(dirname(dirname(__file__)), '''src'''))
sys.path.insert(1, git_repo_path)

# silence FutureWarning warnings in tests since often we can't act on them until
# they become normal warnings - i.e. the tests still need to test the current functionality
warnings.simplefilter(action='''ignore''', category=FutureWarning)



def 	__SCREAMING_SNAKE_CASE  (					__UpperCamelCase    :       Optional[int]	)							->					Any:







  """simple docstring"""





  from diffusers.utils.testing_utils import pytest_addoption_shared

  pytest_addoption_shared(__UpperCamelCase	)






def 	__SCREAMING_SNAKE_CASE  (					__UpperCamelCase    :       Dict	)							->					Optional[Any]:







  """simple docstring"""





  from diffusers.utils.testing_utils import pytest_terminal_summary_main

  SCREAMING_SNAKE_CASE__										=      terminalreporter.config.getoption("""--make-reports"""	)
  if make_reports:
    pytest_terminal_summary_main(__UpperCamelCase ,     id=__UpperCamelCase	)
