

'''simple docstring'''

import torch
from torch import nn

from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin


class 	lowerCAmelCase  (   A ,      A ):







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







            """simple docstring"""







            super().__init__()

            __lowercase      		=nn.Parameter(torch.zeros(__lowercase   )   )

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

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







       def       snake_case (				self      :			Dict    ,   *, __lowercase      :			int    ,   __lowercase      :			int    ,   __lowercase      :			Any    ,   __lowercase      :			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(
                     __lowercase    ,   -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(__lowercase   )
            __lowercase      		=self.clip_image_embeddings_project_to_time_embeddings(__lowercase   )
            __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(__lowercase   )
            __lowercase      		=clip_extra_context_tokens.reshape(__lowercase    ,   -1    ,   self.clip_extra_context_tokens   )
            __lowercase      		=clip_extra_context_tokens.permute(0    ,   2    ,   1   )

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

            return text_encoder_hidden_states, additive_clip_time_embeddings





'''simple docstring'''

import os
from collections.abc import Iterator

def 					__UpperCamelCase				(						lowercase__    :	str = "."			):






     '''simple docstring'''





     for dir_path, dir_names, filenames in os.walk(lowercase__			):
          __lowercase      		=[d for d in dir_names if d != 'scripts' and d[0] not in '._']
          for filename in filenames:
               if filename == "__init__.py":
                    continue
               if os.path.splitext(lowercase__			)[1] in (".py", ".ipynb"):
                    yield os.path.join(lowercase__,       lowercase__			).lstrip('./'			)

def 					__UpperCamelCase				(						lowercase__    :	Optional[Any]			):






     '''simple docstring'''





     return F'''{i * "  "}*''' if i else "\n##"

def 					__UpperCamelCase				(						lowercase__    :	str,       lowercase__    :	str			):






     '''simple docstring'''





     __lowercase      		=old_path.split(os.sep			)
     for i, new_part in enumerate(new_path.split(os.sep			)			):
          if (i + 1 > len(lowercase__			) or old_parts[i] != new_part) and new_part:
               print(F'''{md_prefix(lowercase__			)} {new_part.replace("_",       " "			).title()}'''			)
     return new_path

def 					__UpperCamelCase				(						lowercase__    :	str = "."			):






     '''simple docstring'''





     __lowercase      		=''
     for filepath in sorted(good_file_paths(lowercase__			)			):
          __lowercase		,  __lowercase      		=os.path.split(lowercase__			)
          if filepath != old_path:
               __lowercase      		=print_path(lowercase__,       lowercase__			)
          __lowercase      		=(filepath.count(os.sep			) + 1) if filepath else 0
          __lowercase      		=F'''{filepath}/{filename}'''.replace(' ',       '%20'			)
          __lowercase      		=os.path.splitext(filename.replace('_',       ' '			).title()			)[0]
          print(F'''{md_prefix(lowercase__			)} [{filename}]({url})'''			)


if __name__ == "__main__":
       print_directory_md('''.''')


