"""simple docstring"""







import unittest

import numpy as np
import torch

from diffusers import DDIMPipeline, DDIMScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, slow, torch_device

from ..pipeline_params import UNCONDITIONAL_IMAGE_GENERATION_BATCH_PARAMS, UNCONDITIONAL_IMAGE_GENERATION_PARAMS
from ..test_pipelines_common import PipelineTesterMixin


enable_full_determinism()



class  _lowerCamelCase			(__lowerCamelCase						,							unittest.TestCase     ):
				_snake_case     =  DDIMPipeline
				_snake_case     =  UNCONDITIONAL_IMAGE_GENERATION_PARAMS
				_snake_case     =  PipelineTesterMixin.required_optional_params - {
				    "num_images_per_prompt",
				    "latents",
				    "callback",
				    "callback_steps",
				}
				_snake_case     =  UNCONDITIONAL_IMAGE_GENERATION_BATCH_PARAMS
				_snake_case     =  False







				def 							__UpperCAmelCase					( self    :       Any						):

					"""simple docstring"""






					torch.manual_seed(0						)
					_lowercase :    Dict							=							UNetaDModel(
					    block_out_channels=(3_2, 6_4)			,					layers_per_block=2			,					sample_size=3_2			,					in_channels=3			,					out_channels=3			,					down_block_types=('DownBlock2D', 'AttnDownBlock2D')			,					up_block_types=('AttnUpBlock2D', 'UpBlock2D')			,					)
					_lowercase :    Dict							=							DDIMScheduler()
					_lowercase :    Optional[int]							=							{'unet': unet, 'scheduler': scheduler}
					return components







				def 							__UpperCAmelCase					( self    :       str			,					lowerCamelCase_    :       List[str]			,					lowerCamelCase_    :       Tuple=0						):

					"""simple docstring"""






					if str(lowerCamelCase_						).startswith('mps'						):
						_lowercase :    Tuple							=							torch.manual_seed(lowerCamelCase_						)
					else:
						_lowercase :    Dict							=							torch.Generator(device=lowerCamelCase_						).manual_seed(lowerCamelCase_						)
					_lowercase :    Optional[int]							=							{
					    'batch_size': 1,
					    'generator': generator,
					    'num_inference_steps': 2,
					    'output_type': 'numpy',
					}
					return inputs







				def 							__UpperCAmelCase					( self    :       Any						):

					"""simple docstring"""






					_lowercase :    str							=							'cpu'

					_lowercase :    Optional[int]							=							self.get_dummy_components()
					_lowercase :    Any							=							self.pipeline_class(**lowerCamelCase_						)
					pipe.to(lowerCamelCase_						)
					pipe.set_progress_bar_config(disable=lowerCamelCase_						)

					_lowercase :    Any							=							self.get_dummy_inputs(lowerCamelCase_						)
					_lowercase :    Optional[int]							=							pipe(**lowerCamelCase_						).images
					_lowercase :    Tuple							=							image[0, -3:, -3:, -1]

					self.assertEqual(image.shape			,					(1, 3_2, 3_2, 3)						)
					_lowercase :    Union[str, Any]							=							np.array(
					    [1.0_00E00, 5.7_17E-01, 4.7_17E-01, 1.0_00E00, 0.0_00E00, 1.0_00E00, 3.0_00E-04, 0.0_00E00, 9.0_00E-04]						)
					_lowercase :    List[str]							=							np.abs(image_slice.flatten() - expected_slice						).max()
					self.assertLessEqual(lowerCamelCase_			,					1E-3						)







				def 							__UpperCAmelCase					( self    :       Optional[Any]						):

					"""simple docstring"""






					super().test_dict_tuple_outputs_equivalent(expected_max_difference=3E-3						)







				def 							__UpperCAmelCase					( self    :       Any						):

					"""simple docstring"""






					super().test_save_load_local(expected_max_difference=3E-3						)







				def 							__UpperCAmelCase					( self    :       List[str]						):

					"""simple docstring"""






					super().test_save_load_optional_components(expected_max_difference=3E-3						)







				def 							__UpperCAmelCase					( self    :       Dict						):

					"""simple docstring"""






					super().test_inference_batch_single_identical(expected_max_diff=3E-3						)



@slow
@require_torch_gpu
class  _lowerCamelCase			(unittest.TestCase     ):







				def 							__UpperCAmelCase					( self    :       Union[str, Any]						):

					"""simple docstring"""






					_lowercase :    Any							=							'google/ddpm-cifar10-32'

					_lowercase :    int							=							UNetaDModel.from_pretrained(lowerCamelCase_						)
					_lowercase :    Optional[Any]							=							DDIMScheduler()

					_lowercase :    Dict							=							DDIMPipeline(unet=lowerCamelCase_			,					scheduler=lowerCamelCase_						)
					ddim.to(lowerCamelCase_						)
					ddim.set_progress_bar_config(disable=lowerCamelCase_						)

					_lowercase :    Dict							=							torch.manual_seed(0						)
					_lowercase :    Optional[Any]							=							ddim(generator=lowerCamelCase_			,					eta=0.0			,					output_type='numpy'						).images

					_lowercase :    Union[str, Any]							=							image[0, -3:, -3:, -1]

					assert image.shape == (1, 3_2, 3_2, 3)
					_lowercase :    Optional[int]							=							np.array([0.1723, 0.1617, 0.1600, 0.1626, 0.1497, 0.1513, 0.1505, 0.1442, 0.1453]						)

					assert np.abs(image_slice.flatten() - expected_slice						).max() < 1E-2







				def 							__UpperCAmelCase					( self    :       Optional[int]						):

					"""simple docstring"""






					_lowercase :    Any							=							'google/ddpm-ema-bedroom-256'

					_lowercase :    int							=							UNetaDModel.from_pretrained(lowerCamelCase_						)
					_lowercase :    List[str]							=							DDIMScheduler.from_pretrained(lowerCamelCase_						)

					_lowercase :    int							=							DDIMPipeline(unet=lowerCamelCase_			,					scheduler=lowerCamelCase_						)
					ddpm.to(lowerCamelCase_						)
					ddpm.set_progress_bar_config(disable=lowerCamelCase_						)

					_lowercase :    List[str]							=							torch.manual_seed(0						)
					_lowercase :    List[str]							=							ddpm(generator=lowerCamelCase_			,					output_type='numpy'						).images

					_lowercase :    Optional[int]							=							image[0, -3:, -3:, -1]

					assert image.shape == (1, 2_5_6, 2_5_6, 3)
					_lowercase :    Any							=							np.array([0.0060, 0.0201, 0.0344, 0.0024, 0.0018, 0.0002, 0.0022, 0.0000, 0.0069]						)

					assert np.abs(image_slice.flatten() - expected_slice						).max() < 1E-2
"""simple docstring"""







import os
from typing import Optional

import fsspec
from fsspec.archive import AbstractArchiveFileSystem
from fsspec.utils import DEFAULT_BLOCK_SIZE



class  _lowerCamelCase			(__lowerCamelCase     ):
				_snake_case     =  ""
				_snake_case     =  (
				    None  # protocol passed in prefix to the url. ex: "gzip", for gzip://file.txt::http://foo.bar/file.txt.gz
				)
				_snake_case     =  None  # compression type in fsspec. ex: "gzip"
				_snake_case     =  None  # extension of the filename to strip. ex: "".gz" to get file.txt from file.txt.gz







				def __init__( self    :       str			,					lowerCamelCase_    :       str = ""			,					lowerCamelCase_    :       Optional[str] = None			,					lowerCamelCase_    :       Optional[dict] = None			,					**lowerCamelCase_    :       List[str]						):

					"""simple docstring"""






					super().__init__(self			,					**lowerCamelCase_						)
					# always open as "rb" since fsspec can then use the TextIOWrapper to make it work for "r" mode
					_lowercase :    Union[str, Any]							=							fsspec.open(
					    lowerCamelCase_			,					mode='rb'			,					protocol=lowerCamelCase_			,					compression=self.compression			,					client_kwargs={
					        'requote_redirect_url': False,  # see https://github.com/huggingface/datasets/pull/5459
					        'trust_env': True,  # Enable reading proxy env variables.
					        **(target_options or {}).pop('client_kwargs'			,					{}						),  # To avoid issues if it was already passed.
					    }			,					**(target_options or {})			,					)
					_lowercase :    str							=							os.path.basename(self.file.path.split('::'						)[0]						)
					_lowercase :    Optional[int]							=							(
					    self.compressed_name[: self.compressed_name.rindex('.'						)]
					    if '.' in self.compressed_name
					    else self.compressed_name
					)
					_lowercase :    str							=							None







				@classmethod
				def 							__UpperCAmelCase					( cls    :       int			,					lowerCamelCase_    :       List[str]						):

					"""simple docstring"""






					return super()._strip_protocol(lowerCamelCase_						).lstrip('/'						)







				def 							__UpperCAmelCase					( self    :       Optional[Any]						):

					"""simple docstring"""






					if self.dir_cache is None:
						_lowercase :    Tuple							=							{**self.file.fs.info(self.file.path						), 'name': self.uncompressed_name}
						_lowercase :    int							=							{f['name']: f}







				def 							__UpperCAmelCase					( self    :       List[str]			,					lowerCamelCase_    :       str						):

					"""simple docstring"""






					return self.file.open().read()







				def 							__UpperCAmelCase					( self    :       Dict			,					lowerCamelCase_    :       str			,					lowerCamelCase_    :       str = "rb"			,					lowerCamelCase_    :       str=None			,					lowerCamelCase_    :       str=True			,					lowerCamelCase_    :       Union[str, Any]=None			,					**lowerCamelCase_    :       Optional[int]			,					):

					"""simple docstring"""






					_lowercase :    Union[str, Any]							=							self._strip_protocol(lowerCamelCase_						)
					if mode != "rb":
						raise ValueError(F'''Tried to read with mode {mode} on file {self.file.path} opened with mode \'rb\''''						)
					return self.file.open()



class  _lowerCamelCase			(__lowerCamelCase     ):
				_snake_case     =  "bz2"
				_snake_case     =  "bz2"
				_snake_case     =  ".bz2"



class  _lowerCamelCase			(__lowerCamelCase     ):
				_snake_case     =  "gzip"
				_snake_case     =  "gzip"
				_snake_case     =  ".gz"



class  _lowerCamelCase			(__lowerCamelCase     ):
				_snake_case     =  "lz4"
				_snake_case     =  "lz4"
				_snake_case     =  ".lz4"



class  _lowerCamelCase			(__lowerCamelCase     ):
				_snake_case     =  "xz"
				_snake_case     =  "xz"
				_snake_case     =  ".xz"



class  _lowerCamelCase			(__lowerCamelCase     ):
				_snake_case     =  "zstd"
				_snake_case     =  "zstd"
				_snake_case     =  ".zst"







				def __init__( self    :       Union[str, Any]			,					lowerCamelCase_    :       str			,					lowerCamelCase_    :       str = "rb"			,					lowerCamelCase_    :       Optional[str] = None			,					lowerCamelCase_    :       Optional[dict] = None			,					lowerCamelCase_    :       int = DEFAULT_BLOCK_SIZE			,					**lowerCamelCase_    :       int			,					):

					"""simple docstring"""






					super().__init__(
					    fo=lowerCamelCase_			,					mode=lowerCamelCase_			,					target_protocol=lowerCamelCase_			,					target_options=lowerCamelCase_			,					block_size=lowerCamelCase_			,					**lowerCamelCase_			,					)
					# We need to wrap the zstd decompressor to avoid this error in fsspec==2021.7.0 and zstandard==0.15.2:
					#
					# File "/Users/user/.virtualenvs/hf-datasets/lib/python3.7/site-packages/fsspec/core.py", line 145, in open
					#     out.close = close
					# AttributeError: 'zstd.ZstdDecompressionReader' object attribute 'close' is read-only
					#
					# see https://github.com/intake/filesystem_spec/issues/725
					_lowercase :    Any							=							self.file.__enter__



					class  _lowerCamelCase			:







									def __init__( self    :       Any			,					lowerCamelCase_    :       List[Any]						):

										"""simple docstring"""






										_lowercase :    Tuple							=							file_







									def __enter__( self    :       str						):

										"""simple docstring"""






										self._file.__enter__()
										return self







									def __exit__( self    :       Union[str, Any]			,					*lowerCamelCase_    :       Optional[Any]			,					**lowerCamelCase_    :       Union[str, Any]						):

										"""simple docstring"""






										self._file.__exit__(*lowerCamelCase_			,					**lowerCamelCase_						)







									def __iter__( self    :       Optional[int]						):

										"""simple docstring"""






										return iter(self._file						)







									def 							__UpperCAmelCase					( self    :       int						):

										"""simple docstring"""






										return next(self._file						)







									def __getattr__( self    :       List[str]			,					lowerCamelCase_    :       str						):

										"""simple docstring"""






										return getattr(self._file			,					lowerCamelCase_						)

					def fixed_enter(*lowerCamelCase_    :       List[Any]			,					**lowerCamelCase_    :       int						):
						return WrappedFile(_enter(*lowerCamelCase_			,					**lowerCamelCase_						)						)

					_lowercase :    Optional[int]							=							fixed_enter



