



'''simple docstring'''
import unittest

import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel

from diffusers import DDIMScheduler, LDMPipeline, UNetaDModel, VQModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device


enable_full_determinism()






class 							lowercase__	(							unittest.TestCase   ):





	@property
	def 	UpperCamelCase_  ( self					:				int ):







							'''simple docstring'''
							torch.manual_seed(0 )
							_UpperCamelCase					:		Any 				=   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





	@property
	def 	UpperCamelCase_  ( self					:				List[Any] ):







							'''simple docstring'''
							torch.manual_seed(0 )
							_UpperCamelCase					:		Union[str, Any] 				=   VQModel(
							    block_out_channels=[32, 64] ,in_channels=3 ,out_channels=3 ,down_block_types=['DownEncoderBlock2D', 'DownEncoderBlock2D'] ,up_block_types=['UpDecoderBlock2D', 'UpDecoderBlock2D'] ,latent_channels=3 ,)
							return model





	@property
	def 	UpperCamelCase_  ( self					:				Optional[Any] ):







							'''simple docstring'''
							torch.manual_seed(0 )
							_UpperCamelCase					:		Dict 				=   CLIPTextConfig(
							    bos_token_id=0 ,eos_token_id=2 ,hidden_size=32 ,intermediate_size=37 ,layer_norm_eps=1E-05 ,num_attention_heads=4 ,num_hidden_layers=5 ,pad_token_id=1 ,vocab_size=1000 ,)
							return CLIPTextModel(lowerCamelCase__ )





	def 	UpperCamelCase_  ( self					:				Optional[Any] ):







							'''simple docstring'''
							_UpperCamelCase					:		str 				=   self.dummy_uncond_unet
							_UpperCamelCase					:		Optional[int] 				=   DDIMScheduler()
							_UpperCamelCase					:		str 				=   self.dummy_vq_model

							_UpperCamelCase					:		Any 				=   LDMPipeline(unet=lowerCamelCase__ ,vqvae=lowerCamelCase__ ,scheduler=lowerCamelCase__ )
							ldm.to(lowerCamelCase__ )
							ldm.set_progress_bar_config(disable=lowerCamelCase__ )

							_UpperCamelCase					:		int 				=   torch.manual_seed(0 )
							_UpperCamelCase					:		List[str] 				=   ldm(generator=lowerCamelCase__ ,num_inference_steps=2 ,output_type='numpy' ).images

							_UpperCamelCase					:		Any 				=   torch.manual_seed(0 )
							_UpperCamelCase					:		Any 				=   ldm(generator=lowerCamelCase__ ,num_inference_steps=2 ,output_type='numpy' ,return_dict=lowerCamelCase__ )[0]

							_UpperCamelCase					:		Tuple 				=   image[0, -3:, -3:, -1]
							_UpperCamelCase					:		Optional[int] 				=   image_from_tuple[0, -3:, -3:, -1]

							assert image.shape == (1, 64, 64, 3)
							_UpperCamelCase					:		int 				=   np.array([0.8_5_1_2, 0.8_1_8, 0.6_4_1_1, 0.6_8_0_8, 0.4_4_6_5, 0.5_6_1_8, 0.4_6, 0.6_2_3_1, 0.5_1_7_2] )
							_UpperCamelCase					:		Union[str, Any] 				=   1E-2 if torch_device != 'mps' else 3E-2

							assert np.abs(image_slice.flatten() - expected_slice ).max() < tolerance
							assert np.abs(image_from_tuple_slice.flatten() - expected_slice ).max() < tolerance






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





	def 	UpperCamelCase_  ( self					:				Optional[int] ):







							'''simple docstring'''
							_UpperCamelCase					:		List[str] 				=   LDMPipeline.from_pretrained('CompVis/ldm-celebahq-256' )
							ldm.to(lowerCamelCase__ )
							ldm.set_progress_bar_config(disable=lowerCamelCase__ )

							_UpperCamelCase					:		Union[str, Any] 				=   torch.manual_seed(0 )
							_UpperCamelCase					:		Optional[int] 				=   ldm(generator=lowerCamelCase__ ,num_inference_steps=5 ,output_type='numpy' ).images

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

							assert image.shape == (1, 256, 256, 3)
							_UpperCamelCase					:		Any 				=   np.array([0.4_3_9_9, 0.4_4_9_7_5, 0.4_6_8_2_5, 0.4_7_4, 0.4_3_5_9, 0.4_5_8_1, 0.4_5_0_9_5, 0.4_3_4_1, 0.4_4_4_7] )
							_UpperCamelCase					:		List[Any] 				=   1E-2 if torch_device != 'mps' else 3E-2

							assert np.abs(image_slice.flatten() - expected_slice ).max() < tolerance









import importlib
import shutil
import threading
import warnings
from typing import List

import fsspec
import fsspec.asyn

from . import compression
from .hffilesystem import HfFileSystem


SCREAMING_SNAKE_CASE_						   =       importlib.util.find_spec("""s3fs""") is not None

if _has_safs:
      from .safilesystem import SaFileSystem  # noqa: F401

SCREAMING_SNAKE_CASE_						   =       [
    compression.BzaFileSystem,
    compression.GzipFileSystem,
    compression.LzaFileSystem,
    compression.XzFileSystem,
    compression.ZstdFileSystem,
]

# Register custom filesystems
for fs_class in COMPRESSION_FILESYSTEMS + [HfFileSystem]:
      if fs_class.protocol in fsspec.registry and fsspec.registry[fs_class.protocol] is not fs_class:
            warnings.warn(F'''A filesystem protocol was already set for {fs_class.protocol} and will be overwritten.''')
      fsspec.register_implementation(fs_class.protocol, fs_class, clobber=True)



def    __lowercase   (      _SCREAMING_SNAKE_CASE	) ->   str:


      '''simple docstring'''


      if "://" in dataset_path:
            SCREAMING_SNAKE_CASE		=						dataset_path.split("""://"""	)[1]
      return dataset_path



def    __lowercase   (      _SCREAMING_SNAKE_CASE	) ->   bool:


      '''simple docstring'''


      if fs is not None and fs.protocol != "file":
            return True
      else:
            return False



def    __lowercase   (      _SCREAMING_SNAKE_CASE ,						_SCREAMING_SNAKE_CASE ,						_SCREAMING_SNAKE_CASE	) ->   Dict:


      '''simple docstring'''


      SCREAMING_SNAKE_CASE		=						not is_remote_filesystem(_SCREAMING_SNAKE_CASE	)
      if is_local:
            # LocalFileSystem.mv does copy + rm, it is more efficient to simply move a local directory
            shutil.move(fs._strip_protocol(_SCREAMING_SNAKE_CASE	) ,						fs._strip_protocol(_SCREAMING_SNAKE_CASE	)	)
      else:
            fs.mv(_SCREAMING_SNAKE_CASE ,						_SCREAMING_SNAKE_CASE ,						recursive=_SCREAMING_SNAKE_CASE	)



def    __lowercase   (      ) ->   None:


      '''simple docstring'''


      if hasattr(fsspec.asyn ,						"""reset_lock"""	):
            # for future fsspec>2022.05.0
            fsspec.asyn.reset_lock()
      else:
            SCREAMING_SNAKE_CASE		=						None
            SCREAMING_SNAKE_CASE		=						None
            SCREAMING_SNAKE_CASE		=						threading.Lock()


