





'''simple docstring'''
import os

import pytest
from attr import dataclass


a__							:							Any ='''us-east-1'''  # defaults region

@dataclass
class      snake_case     :




 """simple docstring"""



 SCREAMING_SNAKE_CASE_	:					str
 SCREAMING_SNAKE_CASE_	:					Tuple					="arn:aws:iam::558105141721:role/sagemaker_execution_role"
 SCREAMING_SNAKE_CASE_	:					str					={
     "task_name": "mnli",
     "per_device_train_batch_size": 16,
     "per_device_eval_batch_size": 16,
     "do_train": True,
     "do_eval": True,
     "do_predict": True,
     "output_dir": "/opt/ml/model",
     "overwrite_output_dir": True,
     "max_steps": 500,
     "save_steps": 5500,
 }
 SCREAMING_SNAKE_CASE_	:					Optional[Any]					={**hyperparameters, "max_steps": 1000}






 @property
 def        _lowerCamelCase					(       self       :							Dict	):
        if self.framework == "pytorch":
               return [
                   {"Name": "train_runtime", "Regex": r"train_runtime.*=\D*(.*?)$"},
                   {"Name": "eval_accuracy", "Regex": r"eval_accuracy.*=\D*(.*?)$"},
                   {"Name": "eval_loss", "Regex": r"eval_loss.*=\D*(.*?)$"},
               ]
        else:
               return [
                   {"Name": "train_runtime", "Regex": r"train_runtime.*=\D*(.*?)$"},
                   {"Name": "eval_accuracy", "Regex": r"loss.*=\D*(.*?)]?$"},
                   {"Name": "eval_loss", "Regex": r"sparse_categorical_accuracy.*=\D*(.*?)]?$"},
               ]






 @property
 def        _lowerCamelCase					(       self       :							List[Any]	):
        return f'''{self.framework}-transfromers-test'''






 @property
 def        _lowerCamelCase					(       self       :							Optional[Any]	):
        return f'''./tests/sagemaker/scripts/{self.framework}'''






 @property
 def        _lowerCamelCase					(       self       :							Any	):
        if self.framework == "pytorch":
               return "763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-pytorch-training:1.7.1-transformers4.6.1-gpu-py36-cu110-ubuntu18.04"
        else:
               return "763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-tensorflow-training:2.4.1-transformers4.6.1-gpu-py37-cu110-ubuntu18.04"






@pytest.fixture(scope='class'     )
def 				lowercase__   (   __lowercase						:  Dict     ) ->      Optional[Any]:



       """simple docstring"""






       __UpperCamelCase       =  SageMakerTestEnvironment(framework=request.cls.framework     )







'''simple docstring'''
from ...utils import (
    OptionalDependencyNotAvailable,
    is_torch_available,
    is_transformers_available,
    is_transformers_version,
)


try:
    if not (is_transformers_available() and is_torch_available() and is_transformers_version('''>=''', '''4.25.0''')):
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    from ...utils.dummy_torch_and_transformers_objects import (
        VersatileDiffusionDualGuidedPipeline,
        VersatileDiffusionImageVariationPipeline,
        VersatileDiffusionPipeline,
        VersatileDiffusionTextToImagePipeline,
    )
else:
    from .modeling_text_unet import UNetFlatConditionModel
    from .pipeline_versatile_diffusion import VersatileDiffusionPipeline
    from .pipeline_versatile_diffusion_dual_guided import VersatileDiffusionDualGuidedPipeline
    from .pipeline_versatile_diffusion_image_variation import VersatileDiffusionImageVariationPipeline
    from .pipeline_versatile_diffusion_text_to_image import VersatileDiffusionTextToImagePipeline
