

import os
from typing import Optional

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



class  __lowerCAmelCase	(      _a					):
			lowerCamelCase_					:					List[Any]	      =				''''''
			lowerCamelCase_					:					str	      =				(
			    None  # protocol passed in prefix to the url. ex: "gzip", for gzip://file.txt::http://foo.bar/file.txt.gz
			)
			lowerCamelCase_					:					str	      =				None  # compression type in fsspec. ex: "gzip"
			lowerCamelCase_					:					str	      =				None  # extension of the filename to strip. ex: "".gz" to get file.txt from file.txt.gz






			def __init__(self ,							__magic_name__ = "" ,							__magic_name__ = None ,							__magic_name__ = None ,							**__magic_name__   )					->       List[Any]:


							'''simple docstring'''



							super().__init__(self ,							**__magic_name__   )
							# always open as "rb" since fsspec can then use the TextIOWrapper to make it work for "r" mode
							snake_case_						:   Dict           =  fsspec.open(
							    __magic_name__ ,							mode='''rb''' ,							protocol=__magic_name__ ,							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 {}) ,							)
							snake_case_						:   Optional[int]           =  os.path.basename(self.file.path.split('''::'''   )[0]   )
							snake_case_						:   Tuple           =  (
							    self.compressed_name[: self.compressed_name.rindex('''.'''   )]
							    if '''.''' in self.compressed_name
							    else self.compressed_name
							)
							snake_case_						:   Optional[int]           =  None






			@classmethod
			def       lowerCamelCase  (cls ,							__magic_name__   )					->       int:


							'''simple docstring'''



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






			def       lowerCamelCase  (self   )					->       Dict:


							'''simple docstring'''



							if self.dir_cache is None:
											snake_case_						:   Optional[Any]           =  {**self.file.fs.info(self.file.path   ), '''name''': self.uncompressed_name}
											snake_case_						:   str           =  {f['''name''']: f}






			def       lowerCamelCase  (self ,							__magic_name__   )					->       List[str]:


							'''simple docstring'''



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






			def       lowerCamelCase  (self ,							__magic_name__ ,							__magic_name__ = "rb" ,							__magic_name__=None ,							__magic_name__=True ,							__magic_name__=None ,							**__magic_name__ ,							)					->       Tuple:


							'''simple docstring'''



							snake_case_						:   Union[str, Any]           =  self._strip_protocol(__magic_name__   )
							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	(      _a					):
			lowerCamelCase_					:					List[str]	      =				'''bz2'''
			lowerCamelCase_					:					Optional[int]	      =				'''bz2'''
			lowerCamelCase_					:					Optional[Any]	      =				'''.bz2'''




class  __lowerCAmelCase	(      _a					):
			lowerCamelCase_					:					Union[str, Any]	      =				'''gzip'''
			lowerCamelCase_					:					Any	      =				'''gzip'''
			lowerCamelCase_					:					Optional[int]	      =				'''.gz'''




class  __lowerCAmelCase	(      _a					):
			lowerCamelCase_					:					Tuple	      =				'''lz4'''
			lowerCamelCase_					:					List[str]	      =				'''lz4'''
			lowerCamelCase_					:					str	      =				'''.lz4'''




class  __lowerCAmelCase	(      _a					):
			lowerCamelCase_					:					List[Any]	      =				'''xz'''
			lowerCamelCase_					:					Union[str, Any]	      =				'''xz'''
			lowerCamelCase_					:					str	      =				'''.xz'''




class  __lowerCAmelCase	(      _a					):
			lowerCamelCase_					:					List[str]	      =				'''zstd'''
			lowerCamelCase_					:					Optional[int]	      =				'''zstd'''
			lowerCamelCase_					:					str	      =				'''.zst'''






			def __init__(self ,							__magic_name__ ,							__magic_name__ = "rb" ,							__magic_name__ = None ,							__magic_name__ = None ,							__magic_name__ = DEFAULT_BLOCK_SIZE ,							**__magic_name__ ,							)					->       str:


							'''simple docstring'''



							super().__init__(
							    fo=__magic_name__ ,							mode=__magic_name__ ,							target_protocol=__magic_name__ ,							target_options=__magic_name__ ,							block_size=__magic_name__ ,							**__magic_name__ ,							)
							# 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
							snake_case_						:   Tuple           =  self.file.__enter__



							class  __lowerCAmelCase	:






										def __init__(self ,							__magic_name__   )					->       List[str]:


														'''simple docstring'''



														snake_case_						:   int           =  file_






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


														'''simple docstring'''



														self._file.__enter__()
														return self






										def __exit__(self ,							*__magic_name__ ,							**__magic_name__   )					->       str:


														'''simple docstring'''



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






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


														'''simple docstring'''



														return iter(self._file   )






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


														'''simple docstring'''



														return next(self._file   )






										def __getattr__(self ,							__magic_name__   )					->       Tuple:


														'''simple docstring'''



														return getattr(self._file ,							__magic_name__   )

							def fixed_enter(*__magic_name__ ,							**__magic_name__   ):
											return WrappedFile(_enter(*__magic_name__ ,							**__magic_name__   )   )

							snake_case_						:   str           =  fixed_enter







import unittest

import numpy as np
import torch

from diffusers import PNDMPipeline, PNDMScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device


enable_full_determinism()



class  __lowerCAmelCase	(      unittest.TestCase					):






			@property
			def       lowerCamelCase  (self   )					->       Union[str, Any]:


							'''simple docstring'''



							torch.manual_seed(0   )
							snake_case_						:   int           =  UNetaDModel(
							    block_out_channels=(32, 64) ,							layers_per_block=2 ,							sample_size=32 ,							in_channels=3 ,							out_channels=3 ,							down_block_types=('''DownBlock2D''', '''AttnDownBlock2D''') ,							up_block_types=('''AttnUpBlock2D''', '''UpBlock2D''') ,							)
							return model






			def       lowerCamelCase  (self   )					->       Dict:


							'''simple docstring'''



							snake_case_						:   Any           =  self.dummy_uncond_unet
							snake_case_						:   Optional[Any]           =  PNDMScheduler()

							snake_case_						:   Optional[Any]           =  PNDMPipeline(unet=__magic_name__ ,							scheduler=__magic_name__   )
							pndm.to(__magic_name__   )
							pndm.set_progress_bar_config(disable=__magic_name__   )

							snake_case_						:   str           =  torch.manual_seed(0   )
							snake_case_						:   Dict           =  pndm(generator=__magic_name__ ,							num_inference_steps=20 ,							output_type='''numpy'''   ).images

							snake_case_						:   str           =  torch.manual_seed(0   )
							snake_case_						:   str           =  pndm(generator=__magic_name__ ,							num_inference_steps=20 ,							output_type='''numpy''' ,							return_dict=__magic_name__   )[0]

							snake_case_						:   Any           =  image[0, -3:, -3:, -1]
							snake_case_						:   str           =  image_from_tuple[0, -3:, -3:, -1]

							assert image.shape == (1, 32, 32, 3)
							snake_case_						:   str           =  np.array([1.0, 1.0, 0.0, 1.0, 0.0, 1.0, 0.0, 0.0, 0.0]   )

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




@slow
@require_torch
class  __lowerCAmelCase	(      unittest.TestCase					):






			def       lowerCamelCase  (self   )					->       Any:


							'''simple docstring'''



							snake_case_						:   Tuple           =  '''google/ddpm-cifar10-32'''

							snake_case_						:   Tuple           =  UNetaDModel.from_pretrained(__magic_name__   )
							snake_case_						:   Optional[Any]           =  PNDMScheduler()

							snake_case_						:   Any           =  PNDMPipeline(unet=__magic_name__ ,							scheduler=__magic_name__   )
							pndm.to(__magic_name__   )
							pndm.set_progress_bar_config(disable=__magic_name__   )
							snake_case_						:   int           =  torch.manual_seed(0   )
							snake_case_						:   Tuple           =  pndm(generator=__magic_name__ ,							output_type='''numpy'''   ).images

							snake_case_						:   List[str]           =  image[0, -3:, -3:, -1]

							assert image.shape == (1, 32, 32, 3)
							snake_case_						:   str           =  np.array([0.1_564, 0.14_645, 0.1_406, 0.14_715, 0.12_425, 0.14_045, 0.13_115, 0.12_175, 0.125]   )

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