
'''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			:				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)

lowercase			:				Tuple    		=			logging.getLogger()







def 		lowerCAmelCase_				(   ):




    '''simple docstring'''



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







def 		lowerCAmelCase_				(   snake_case__		,				snake_case__="eval"						):




    '''simple docstring'''



    A       :   str					=						os.path.join(snake_case__		,				F'{split}_results.json'						)
    if os.path.exists(snake_case__						):
        with open(snake_case__		,				'''r'''						) as f:
            return json.load(snake_case__						)
    raise ValueError(F'can\'t find {path}'						)


lowercase			:				str    		=			logging.StreamHandler(sys.stdout)
logger.addHandler(stream_handler)







class  A				(							__snake_case						):





     def 				__lowerCAmelCase							(							self	) ->				Optional[Any]:






         """simple docstring"""






         A       :   List[Any]					=						self.get_auto_remove_tmp_dir()
         A       :   int					=						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(SCREAMING_SNAKE_CASE						,			'''argv'''						,			SCREAMING_SNAKE_CASE	):
             run_flax_glue.main()
             A       :   Any					=						get_results(SCREAMING_SNAKE_CASE	)
             self.assertGreaterEqual(result['''eval_accuracy''']						,			0.75	)





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






         """simple docstring"""






         A       :   str					=						self.get_auto_remove_tmp_dir()
         A       :   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(SCREAMING_SNAKE_CASE						,			'''argv'''						,			SCREAMING_SNAKE_CASE	):
             run_clm_flax.main()
             A       :   Optional[Any]					=						get_results(SCREAMING_SNAKE_CASE	)
             self.assertLess(result['''eval_perplexity''']						,			100	)





     @slow
     def 				__lowerCAmelCase							(							self	) ->				Any:






         """simple docstring"""






         A       :   int					=						self.get_auto_remove_tmp_dir()
         A       :   Optional[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(SCREAMING_SNAKE_CASE						,			'''argv'''						,			SCREAMING_SNAKE_CASE	):
             run_summarization_flax.main()
             A       :   Any					=						get_results(SCREAMING_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 				__lowerCAmelCase							(							self	) ->				Union[str, Any]:






         """simple docstring"""






         A       :   int					=						self.get_auto_remove_tmp_dir()
         A       :   Optional[int]					=						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(SCREAMING_SNAKE_CASE						,			'''argv'''						,			SCREAMING_SNAKE_CASE	):
             run_mlm_flax.main()
             A       :   str					=						get_results(SCREAMING_SNAKE_CASE	)
             self.assertLess(result['''eval_perplexity''']						,			42	)





     @slow
     def 				__lowerCAmelCase							(							self	) ->				Optional[Any]:






         """simple docstring"""






         A       :   Optional[Any]					=						self.get_auto_remove_tmp_dir()
         A       :   List[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(SCREAMING_SNAKE_CASE						,			'''argv'''						,			SCREAMING_SNAKE_CASE	):
             run_ta_mlm_flax.main()
             A       :   Optional[Any]					=						get_results(SCREAMING_SNAKE_CASE	)
             self.assertGreaterEqual(result['''eval_accuracy''']						,			0.42	)





     @slow
     def 				__lowerCAmelCase							(							self	) ->				str:






         """simple docstring"""






         A       :   List[str]					=						7 if get_gpu_count() > 1 else 2

         A       :   Optional[int]					=						self.get_auto_remove_tmp_dir()
         A       :   Tuple					=						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(SCREAMING_SNAKE_CASE						,			'''argv'''						,			SCREAMING_SNAKE_CASE	):
             run_flax_ner.main()
             A       :   str					=						get_results(SCREAMING_SNAKE_CASE	)
             self.assertGreaterEqual(result['''eval_accuracy''']						,			0.75	)
             self.assertGreaterEqual(result['''eval_f1''']						,			0.3	)





     @slow
     def 				__lowerCAmelCase							(							self	) ->				Dict:






         """simple docstring"""






         A       :   Any					=						self.get_auto_remove_tmp_dir()
         A       :   List[str]					=						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(SCREAMING_SNAKE_CASE						,			'''argv'''						,			SCREAMING_SNAKE_CASE	):
             run_qa.main()
             A       :   List[Any]					=						get_results(SCREAMING_SNAKE_CASE	)
             self.assertGreaterEqual(result['''eval_f1''']						,			30	)
             self.assertGreaterEqual(result['''eval_exact''']						,			30	)






'''simple docstring'''




from dataclasses import dataclass
from typing import List, Optional, Union

import numpy as np
import PIL

from ...utils import BaseOutput, OptionalDependencyNotAvailable, is_torch_available, is_transformers_available
from .timesteps import (
    fastaa_timesteps,
    smartaa_timesteps,
    smartaa_timesteps,
    smartaaa_timesteps,
    smartaaa_timesteps,
    superaa_timesteps,
    superaa_timesteps,
    superaaa_timesteps,
)





@dataclass
class  A				(							__snake_case						):
     __magic_name__						=		42
     __magic_name__						=		42
     __magic_name__						=		42


try:
      if not (is_transformers_available() and is_torch_available()):
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      from ...utils.dummy_torch_and_transformers_objects import *  # noqa F403
else:
      from .pipeline_if import IFPipeline
      from .pipeline_if_imgaimg import IFImgaImgPipeline
      from .pipeline_if_imgaimg_superresolution import IFImgaImgSuperResolutionPipeline
      from .pipeline_if_inpainting import IFInpaintingPipeline
      from .pipeline_if_inpainting_superresolution import IFInpaintingSuperResolutionPipeline
      from .pipeline_if_superresolution import IFSuperResolutionPipeline
      from .safety_checker import IFSafetyChecker
      from .watermark import IFWatermarker




