






import torch
from torch import nn

from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class  _UpperCAmelCase   (			A__						,A__      ):

				"""simple docstring"""




				@register_to_config
				def __init__(	self		:       List[str],    *,
				    lowerCamelCase		:       int = 4,    lowerCamelCase		:       int = 768,    lowerCamelCase		:       int,    lowerCamelCase		:       Tuple,    ):

								'''simple docstring'''
								super().__init__()

								lowercase__  					=     nn.Parameter(torch.zeros(lowerCamelCase    )    )

								# parameters for additional clip time embeddings
								lowercase__  					=     nn.Linear(lowerCamelCase,    lowerCamelCase    )
								lowercase__  					=     nn.Linear(lowerCamelCase,    lowerCamelCase    )

								# parameters for encoder hidden states
								lowercase__  					=     clip_extra_context_tokens
								lowercase__  					=     nn.Linear(
								    lowerCamelCase,    self.clip_extra_context_tokens * cross_attention_dim    )
								lowercase__  					=     nn.Linear(lowerCamelCase,    lowerCamelCase    )
								lowercase__  					=     nn.LayerNorm(lowerCamelCase    )




				def 							lowercase__  (	self		:       Any,    *, lowerCamelCase		:       Tuple,    lowerCamelCase		:       List[str],    lowerCamelCase		:       Tuple,    lowerCamelCase		:       Dict    ):

								'''simple docstring'''
								if do_classifier_free_guidance:
												# Add the classifier free guidance embeddings to the image embeddings
												lowercase__  					=     image_embeddings.shape[0]
												lowercase__  					=     self.learned_classifier_free_guidance_embeddings.unsqueeze(0    )
												lowercase__  					=     classifier_free_guidance_embeddings.expand(
												    lowerCamelCase,    -1    )
												lowercase__  					=     torch.cat([classifier_free_guidance_embeddings, image_embeddings],    dim=0    )

								# The image embeddings batch size and the text embeddings batch size are equal
								assert image_embeddings.shape[0] == prompt_embeds.shape[0]

								lowercase__  					=     prompt_embeds.shape[0]

								# "Specifically, we modify the architecture described in Nichol et al. (2021) by projecting and
								# adding CLIP embeddings to the existing timestep embedding, ...
								lowercase__  					=     self.embedding_proj(lowerCamelCase    )
								lowercase__  					=     self.clip_image_embeddings_project_to_time_embeddings(lowerCamelCase    )
								lowercase__  					=     time_projected_image_embeddings + time_projected_prompt_embeds

								# ... and by projecting CLIP embeddings into four
								# extra tokens of context that are concatenated to the sequence of outputs from the GLIDE text encoder"
								lowercase__  					=     self.clip_extra_context_tokens_proj(lowerCamelCase    )
								lowercase__  					=     clip_extra_context_tokens.reshape(lowerCamelCase,    -1,    self.clip_extra_context_tokens    )
								lowercase__  					=     clip_extra_context_tokens.permute(0,    2,    1    )

								lowercase__  					=     self.encoder_hidden_states_proj(lowerCamelCase    )
								lowercase__  					=     self.text_encoder_hidden_states_norm(lowerCamelCase    )
								lowercase__  					=     torch.cat([clip_extra_context_tokens, text_encoder_hidden_states],    dim=1    )

								return text_encoder_hidden_states, additive_clip_time_embeddings












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

import fsspec
import fsspec.asyn

from . import compression
from .hffilesystem import HfFileSystem


A__      :     int       =					importlib.util.find_spec('s3fs') is not None

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

A__      :     List[compression.BaseCompressedFileFileSystem]       =					[
    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     a     (		lowerCamelCase_							):






				'''simple docstring'''
				if "://" in dataset_path:
								lowercase__  					=     dataset_path.split('''://'''							)[1]
				return dataset_path






def     a     (		lowerCamelCase_							):






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






def     a     (		lowerCamelCase_						,  lowerCamelCase_						,  lowerCamelCase_							):






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






def     a     (		):






				'''simple docstring'''
				if hasattr(fsspec.asyn						,  '''reset_lock'''							):
								# for future fsspec>2022.05.0
								fsspec.asyn.reset_lock()
				else:
								lowercase__  					=     None
								lowercase__  					=     None
								lowercase__  					=     threading.Lock()




