



'''simple docstring'''





import torch
from torch import nn
from transformers import CLIPPreTrainedModel, CLIPVisionModel

from ...models.attention import BasicTransformerBlock
from ...utils import logging


__a  			=						logging.get_logger(__name__)  # pylint: disable=invalid-name







class        UpperCAmelCase_			(			_a      ):
    """simple docstring"""







    def __init__(       self   :	Optional[Any]					,	snake_case_   :	Optional[Any]					,	snake_case_   :	str=768		):
          super().__init__(__UpperCAmelCase		)
          snake_case__    :       List[Any]       		= proj_size

          snake_case__    :       Union[str, Any]       		= CLIPVisionModel(__UpperCAmelCase		)
          snake_case__    :       Tuple       		= PaintByExampleMapper(__UpperCAmelCase		)
          snake_case__    :       int       		= nn.LayerNorm(config.hidden_size		)
          snake_case__    :       int       		= nn.Linear(config.hidden_size					,	self.proj_size		)

          # uncondition for scaling
          snake_case__    :       int       		= nn.Parameter(torch.randn((1, 1, self.proj_size)		)		)




    def lowerCamelCase			(       self   :	List[Any]					,	snake_case_   :	List[Any]					,	snake_case_   :	Optional[Any]=False		):
          snake_case__    :       Any       		= self.model(pixel_values=__UpperCAmelCase		)
          snake_case__    :       Union[str, Any]       		= clip_output.pooler_output
          snake_case__    :       Optional[Any]       		= self.mapper(latent_states[:, None]		)
          snake_case__    :       Dict       		= self.final_layer_norm(__UpperCAmelCase		)
          snake_case__    :       Dict       		= self.proj_out(__UpperCAmelCase		)
          if return_uncond_vector:
                return latent_states, self.uncond_vector

          return latent_states







class        UpperCAmelCase_			(			nn.Module      ):
    """simple docstring"""







    def __init__(       self   :	List[Any]					,	snake_case_   :	Union[str, Any]		):
          super().__init__()
          snake_case__    :       Tuple       		= (config.num_hidden_layers + 1) // 5
          snake_case__    :       Optional[Any]       		= config.hidden_size
          snake_case__    :       Optional[int]       		= 1
          snake_case__    :       str       		= nn.ModuleList(
              [
                  BasicTransformerBlock(__UpperCAmelCase					,	__UpperCAmelCase					,	__UpperCAmelCase					,	activation_fn="""gelu"""					,	attention_bias=__UpperCAmelCase		)
                  for _ in range(__UpperCAmelCase		)
              ]		)




    def lowerCamelCase			(       self   :	Tuple					,	snake_case_   :	List[str]		):



          for block in self.blocks:
                snake_case__    :       Tuple       		= block(__UpperCAmelCase		)

          return hidden_states





# this script reports modified .py files under the desired list of top-level sub-dirs passed as a list of arguments, e.g.:
#   python ./utils/get_modified_files.py utils src tests examples
#
# it uses git to find the forking point and which files were modified - i.e. files not under git won't be considered
# since the output of this script is fed into Makefile commands it doesn't print a newline after the results

import re
import subprocess
import sys


lowerCamelCase		       =      subprocess.check_output("""git merge-base main HEAD""".split()).decode("""utf-8""")
lowerCamelCase		       =      subprocess.check_output(F'git diff --name-only {fork_point_sha}'.split()).decode("""utf-8""").split()

lowerCamelCase		       =      """|""".join(sys.argv[1:])
lowerCamelCase		       =      re.compile(RF'^({joined_dirs}).*?\.py$')

lowerCamelCase		       =      [x for x in modified_files if regex.match(x)]
print(""" """.join(relevant_modified_files), end="""""")


