
"""simple docstring"""


import os

from apache_beam.io.filesystems import FileSystems
from apache_beam.pipeline import Pipeline

from .logging import get_logger


__A					=			2 << 20  # 2mb
__A					=			get_logger(__name__)







class 						lowerCamelCase__   (   __magic_name__							):





			'''simple docstring'''



			def    _lowerCAmelCase						(				self    )					->	Optional[Any]:
				_lowerCAmelCase								=self._options.get_all_options().get("""runner"""    )
				return runner in [None, "DirectRunner", "PortableRunner"]







def        _lowerCamelCase(__UpperCamelCase       ,					__UpperCamelCase       ,					__UpperCamelCase=False			)							->					Dict:
	_lowerCAmelCase								=FileSystems
	if fs.exists(__UpperCamelCase			):
		if force_upload:
			logger.info(F'''Remote path already exist: {remote_file_path}. Overwriting it as force_upload=True.'''			)
		else:
			logger.info(F'''Remote path already exist: {remote_file_path}. Skipping it as force_upload=False.'''			)
			return
	with fs.create(__UpperCamelCase			) as remote_file:
		with open(__UpperCamelCase       ,					"""rb"""			) as local_file:
			_lowerCAmelCase								=local_file.read(__UpperCamelCase			)
			while chunk:
				remote_file.write(__UpperCamelCase			)
				_lowerCAmelCase								=local_file.read(__UpperCamelCase			)



def        _lowerCamelCase(__UpperCamelCase       ,					__UpperCamelCase       ,					__UpperCamelCase=False			)							->					int:
	_lowerCAmelCase								=FileSystems
	if os.path.exists(__UpperCamelCase			):
		if force_download:
			logger.info(F'''Local path already exist: {remote_file_path}. Overwriting it as force_upload=True.'''			)
		else:
			logger.info(F'''Local path already exist: {remote_file_path}. Skipping it as force_upload=False.'''			)
			return
	with fs.open(__UpperCamelCase			) as remote_file:
		with open(__UpperCamelCase       ,					"""wb"""			) as local_file:
			_lowerCAmelCase								=remote_file.read(__UpperCamelCase			)
			while chunk:
				local_file.write(__UpperCamelCase			)
				_lowerCAmelCase								=remote_file.read(__UpperCamelCase			)





"""simple docstring"""


import unittest

import numpy as np
import PIL
import torch

from diffusers.image_processor import VaeImageProcessor







class 						lowerCamelCase__   (   unittest.TestCase							):





			'''simple docstring'''



			@property
			def    _lowerCAmelCase						(				self    )					->	List[str]:
				_lowerCAmelCase								=1
				_lowerCAmelCase								=3
				_lowerCAmelCase								=8
				_lowerCAmelCase								=8

				_lowerCAmelCase								=torch.rand((batch_size, num_channels, height, width)    )

				return sample



			def    _lowerCAmelCase						(				self	,	__UpperCAmelCase    )					->	Any:
				if isinstance(image[0]	,	PIL.Image.Image    ):
					return np.stack([np.array(__UpperCAmelCase    ) for i in image]	,	axis=0    )
				elif isinstance(__UpperCAmelCase	,	torch.Tensor    ):
					return image.cpu().numpy().transpose(0	,	2	,	3	,	1    )
				return image



			def    _lowerCAmelCase						(				self    )					->	Tuple:
				_lowerCAmelCase								=VaeImageProcessor(do_resize=__UpperCAmelCase	,	do_normalize=__UpperCAmelCase    )

				_lowerCAmelCase								=self.dummy_sample
				_lowerCAmelCase								=self.to_np(__UpperCAmelCase    )

				for output_type in ["pt", "np", "pil"]:
					_lowerCAmelCase								=image_processor.postprocess(
					    image_processor.preprocess(__UpperCAmelCase    )	,	output_type=__UpperCAmelCase	,	)
					_lowerCAmelCase								=self.to_np(__UpperCAmelCase    )
					_lowerCAmelCase								=(input_np * 2_55).round() if output_type == """pil""" else input_np
					assert (
					    np.abs(in_np - out_np    ).max() < 1e-6
					), f'''decoded output does not match input for output_type {output_type}'''



			def    _lowerCAmelCase						(				self    )					->	Union[str, Any]:
				_lowerCAmelCase								=VaeImageProcessor(do_resize=__UpperCAmelCase	,	do_normalize=__UpperCAmelCase    )
				_lowerCAmelCase								=self.dummy_sample.cpu().numpy().transpose(0	,	2	,	3	,	1    )

				for output_type in ["pt", "np", "pil"]:
					_lowerCAmelCase								=image_processor.postprocess(image_processor.preprocess(__UpperCAmelCase    )	,	output_type=__UpperCAmelCase    )

					_lowerCAmelCase								=self.to_np(__UpperCAmelCase    )
					_lowerCAmelCase								=(input_np * 2_55).round() if output_type == """pil""" else input_np
					assert (
					    np.abs(in_np - out_np    ).max() < 1e-6
					), f'''decoded output does not match input for output_type {output_type}'''



			def    _lowerCAmelCase						(				self    )					->	List[str]:
				_lowerCAmelCase								=VaeImageProcessor(do_resize=__UpperCAmelCase	,	do_normalize=__UpperCAmelCase    )

				_lowerCAmelCase								=self.dummy_sample.cpu().numpy().transpose(0	,	2	,	3	,	1    )
				_lowerCAmelCase								=image_processor.numpy_to_pil(__UpperCAmelCase    )

				for output_type in ["pt", "np", "pil"]:
					_lowerCAmelCase								=image_processor.postprocess(image_processor.preprocess(__UpperCAmelCase    )	,	output_type=__UpperCAmelCase    )
					for i, o in zip(__UpperCAmelCase	,	__UpperCAmelCase    ):
						_lowerCAmelCase								=np.array(__UpperCAmelCase    )
						_lowerCAmelCase								=self.to_np(__UpperCAmelCase    ) if output_type == """pil""" else (self.to_np(__UpperCAmelCase    ) * 2_55).round()
						assert (
						    np.abs(in_np - out_np    ).max() < 1e-6
						), f'''decoded output does not match input for output_type {output_type}'''



			def    _lowerCAmelCase						(				self    )					->	Tuple:
				_lowerCAmelCase								=VaeImageProcessor(do_resize=__UpperCAmelCase	,	do_normalize=__UpperCAmelCase    )

				_lowerCAmelCase								=self.dummy_sample
				_lowerCAmelCase								=input_pt_ad.squeeze(0    )

				_lowerCAmelCase								=image_processor.postprocess(
				    image_processor.preprocess(__UpperCAmelCase    )	,	output_type="""np"""	,	)
				_lowerCAmelCase								=image_processor.postprocess(
				    image_processor.preprocess(__UpperCAmelCase    )	,	output_type="""np"""	,	)

				_lowerCAmelCase								=self.to_np(self.dummy_sample    )
				_lowerCAmelCase								=input_np_ad.squeeze(0    )

				_lowerCAmelCase								=image_processor.postprocess(
				    image_processor.preprocess(__UpperCAmelCase    )	,	output_type="""np"""	,	)
				_lowerCAmelCase								=image_processor.postprocess(
				    image_processor.preprocess(__UpperCAmelCase    )	,	output_type="""np"""	,	)

				assert np.abs(out_pt_ad - out_pt_ad    ).max() < 1e-6
				assert np.abs(out_np_ad - out_np_ad    ).max() < 1e-6



			def    _lowerCAmelCase						(				self    )					->	Optional[Any]:
				_lowerCAmelCase								=VaeImageProcessor(do_resize=__UpperCAmelCase	,	do_normalize=__UpperCAmelCase    )

				_lowerCAmelCase								=self.dummy_sample
				_lowerCAmelCase								=list(__UpperCAmelCase    )

				_lowerCAmelCase								=image_processor.postprocess(
				    image_processor.preprocess(__UpperCAmelCase    )	,	output_type="""np"""	,	)

				_lowerCAmelCase								=image_processor.postprocess(
				    image_processor.preprocess(__UpperCAmelCase    )	,	output_type="""np"""	,	)

				_lowerCAmelCase								=self.to_np(self.dummy_sample    )
				list(__UpperCAmelCase    )

				_lowerCAmelCase								=image_processor.postprocess(
				    image_processor.preprocess(__UpperCAmelCase    )	,	output_type="""np"""	,	)

				_lowerCAmelCase								=image_processor.postprocess(
				    image_processor.preprocess(__UpperCAmelCase    )	,	output_type="""np"""	,	)

				assert np.abs(out_pt_ad - out_pt_list    ).max() < 1e-6
				assert np.abs(out_np_ad - out_np_list    ).max() < 1e-6



