


'''simple docstring'''
import argparse

from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection

from diffusers import UnCLIPImageVariationPipeline, UnCLIPPipeline


if __name__ == "__main__":
		__snake_case							      =     argparse.ArgumentParser()

		parser.add_argument('''--dump_path''', default=None, type=str, required=True, help='''Path to the output model.''')

		parser.add_argument(
		    '''--txt2img_unclip''',
		    default='''kakaobrain/karlo-v1-alpha''',
		    type=str,
		    required=False,
		    help='''The pretrained txt2img unclip.''',
		)

		__snake_case							      =     parser.parse_args()

		__snake_case							      =     UnCLIPPipeline.from_pretrained(args.txtaimg_unclip)

		__snake_case							      =     CLIPImageProcessor()
		__snake_case							      =     CLIPVisionModelWithProjection.from_pretrained('''openai/clip-vit-large-patch14''')

		__snake_case							      =     UnCLIPImageVariationPipeline(
		    decoder=txtaimg.decoder,
		    text_encoder=txtaimg.text_encoder,
		    tokenizer=txtaimg.tokenizer,
		    text_proj=txtaimg.text_proj,
		    feature_extractor=feature_extractor,
		    image_encoder=image_encoder,
		    super_res_first=txtaimg.super_res_first,
		    super_res_last=txtaimg.super_res_last,
		    decoder_scheduler=txtaimg.decoder_scheduler,
		    super_res_scheduler=txtaimg.super_res_scheduler,
		)

		imgaimg.save_pretrained(args.dump_path)



'''simple docstring'''
import unittest
from dataclasses import dataclass

import pytest

from accelerate.commands.config.config_args import SageMakerConfig
from accelerate.utils import ComputeEnvironment
from accelerate.utils.launch import _convert_nargs_to_dict
@dataclass
class    lowercase	(							A__					):

		"""simple docstring"""

		_a     =				ComputeEnvironment.AMAZON_SAGEMAKER
		_a     =				True
		_a     =				'ml.p3.2xlarge'
		_a     =				'accelerate_sagemaker_execution_role'
		_a     =				'hf-sm'
		_a     =				'us-east-1'
		_a     =				1
		_a     =				'accelerate-sagemaker-1'
		_a     =				'1.6'
		_a     =				'4.4'
		_a     =				'train.py'
		_a     =				[
		    '--model_name_or_path',
		    'bert',
		    '--do_train',
		    'False',
		    '--epochs',
		    '3',
		    '--learning_rate',
		    '5e-5',
		    '--max_steps',
		    '50.5',
		]
		_a     =				[
		    '--model_name_or_path',
		    'bert',
		    '--do_train',
		    '--do_test',
		    'False',
		    '--do_predict',
		    '--epochs',
		    '3',
		    '--learning_rate',
		    '5e-5',
		    '--max_steps',
		    '50.5',
		]



class    lowercase	(							unittest.TestCase					):

		"""simple docstring"""

		def     lowerCAmelCase__				(		self							):

							'''simple docstring'''


							UpperCamelCase__   :Union[str, Any]												= _convert_nargs_to_dict(MockLaunchConfig.success_training_script_args							)
							assert isinstance(converted_args['''model_name_or_path''']    ,   UpperCamelCase_							)
							assert isinstance(converted_args['''do_train''']    ,   UpperCamelCase_							)
							assert isinstance(converted_args['''epochs''']    ,   UpperCamelCase_							)
							assert isinstance(converted_args['''learning_rate''']    ,   UpperCamelCase_							)
							assert isinstance(converted_args['''max_steps''']    ,   UpperCamelCase_							)

							with pytest.raises(UpperCamelCase_							):
												_convert_nargs_to_dict(MockLaunchConfig.fail_training_script_args							)