



'''simple docstring'''


import argparse
import os
import re


lowercase							       =			'''src/diffusers'''

# Pattern that looks at the indentation in a line.
lowercase							       =			re.compile(R'''^(\s*)\S''')
# Pattern that matches `"key":" and puts `key` in group 0.
lowercase							       =			re.compile(R'''^\s*"([^"]+)":''')
# Pattern that matches `_import_structure["key"]` and puts `key` in group 0.
lowercase							       =			re.compile(R'''^\s*_import_structure\["([^"]+)"\]''')
# Pattern that matches `"key",` and puts `key` in group 0.
lowercase							       =			re.compile(R'''^\s*"([^"]+)",\s*$''')
# Pattern that matches any `[stuff]` and puts `stuff` in group 0.
lowercase							       =			re.compile(R'''\[([^\]]+)\]''')






def  UpperCAmelCase_       (		lowercase__       ):


     '''simple docstring'''







     a_       		=_re_indent.search(lowercase__       )
     return "" if search is None else search.groups()[0]






def  UpperCAmelCase_       (		lowercase__       ,	lowercase__=""       ,	lowercase__=None       ,	lowercase__=None       ):


     '''simple docstring'''







     a_       		=0
     a_       		=code.split("\n"       )
     if start_prompt is not None:
          while not lines[index].startswith(lowercase__       ):
               index += 1
          a_       		=["\n".join(lines[:index]       )]
     else:
          a_       		=[]

     # We split into blocks until we get to the `end_prompt` (or the end of the block).
     a_       		=[lines[index]]
     index += 1
     while index < len(lowercase__       ) and (end_prompt is None or not lines[index].startswith(lowercase__       )):
          if len(lines[index]       ) > 0 and get_indent(lines[index]       ) == indent_level:
               if len(lowercase__       ) > 0 and get_indent(current_block[-1]       ).startswith(indent_level + " "       ):
                    current_block.append(lines[index]       )
                    blocks.append("\n".join(lowercase__       )       )
                    if index < len(lowercase__       ) - 1:
                         a_       		=[lines[index + 1]]
                         index += 1
                    else:
                         a_       		=[]
               else:
                    blocks.append("\n".join(lowercase__       )       )
                    a_       		=[lines[index]]
          else:
               current_block.append(lines[index]       )
          index += 1

     # Adds current block if it's nonempty.
     if len(lowercase__       ) > 0:
          blocks.append("\n".join(lowercase__       )       )

     # Add final block after end_prompt if provided.
     if end_prompt is not None and index < len(lowercase__       ):
          blocks.append("\n".join(lines[index:]       )       )

     return blocks






def  UpperCAmelCase_       (		lowercase__       ):


     '''simple docstring'''







     def _inner(lowercase__       ):
          return key(lowercase__       ).lower().replace("_"       ,	""       )

     return _inner






def  UpperCAmelCase_       (		lowercase__       ,	lowercase__=None       ):


     '''simple docstring'''







     def noop(lowercase__       ):
          return x

     if key is None:
          a_       		=noop
     # Constants are all uppercase, they go first.
     a_       		=[obj for obj in objects if key(lowercase__       ).isupper()]
     # Classes are not all uppercase but start with a capital, they go second.
     a_       		=[obj for obj in objects if key(lowercase__       )[0].isupper() and not key(lowercase__       ).isupper()]
     # Functions begin with a lowercase, they go last.
     a_       		=[obj for obj in objects if not key(lowercase__       )[0].isupper()]

     a_       		=ignore_underscore(lowercase__       )
     return sorted(lowercase__       ,	key=lowercase__       ) + sorted(lowercase__       ,	key=lowercase__       ) + sorted(lowercase__       ,	key=lowercase__       )






def  UpperCAmelCase_       (		lowercase__       ):


     '''simple docstring'''







     def _replace(lowercase__       ):
          a_       		=match.groups()[0]
          if "," not in imports:
               return F"""[{imports}]"""
          a_       		=[part.strip().replace("\""       ,	""       ) for part in imports.split(","       )]
          # We will have a final empty element if the line finished with a comma.
          if len(keys[-1]       ) == 0:
               a_       		=keys[:-1]
          return "[" + ", ".join([F"""\"{k}\"""" for k in sort_objects(lowercase__       )]       ) + "]"

     a_       		=import_statement.split("\n"       )
     if len(lowercase__       ) > 3:
          # Here we have to sort internal imports that are on several lines (one per name):
          # key: [
          #     "object1",
          #     "object2",
          #     ...
          # ]

          # We may have to ignore one or two lines on each side.
          a_       		=2 if lines[1].strip() == "[" else 1
          a_       		=[(i, _re_strip_line.search(lowercase__       ).groups()[0]) for i, line in enumerate(lines[idx:-idx]       )]
          a_       		=sort_objects(lowercase__       ,	key=lambda lowercase__       : x[1]       )
          a_       		=[lines[x[0] + idx] for x in sorted_indices]
          return "\n".join(lines[:idx] + sorted_lines + lines[-idx:]       )
     elif len(lowercase__       ) == 3:
          # Here we have to sort internal imports that are on one separate line:
          # key: [
          #     "object1", "object2", ...
          # ]
          if _re_bracket_content.search(lines[1]       ) is not None:
               a_       		=_re_bracket_content.sub(_replace       ,	lines[1]       )
          else:
               a_       		=[part.strip().replace("\""       ,	""       ) for part in lines[1].split(","       )]
               # We will have a final empty element if the line finished with a comma.
               if len(keys[-1]       ) == 0:
                    a_       		=keys[:-1]
               a_       		=get_indent(lines[1]       ) + ", ".join([F"""\"{k}\"""" for k in sort_objects(lowercase__       )]       )
          return "\n".join(lowercase__       )
     else:
          # Finally we have to deal with imports fitting on one line
          a_       		=_re_bracket_content.sub(_replace       ,	lowercase__       )
          return import_statement






def  UpperCAmelCase_       (		lowercase__       ,	lowercase__=True       ):


     '''simple docstring'''







     with open(lowercase__       ,	"r"       ) as f:
          a_       		=f.read()

     if "_import_structure" not in code:
          return

     # Blocks of indent level 0
     a_       		=split_code_in_indented_blocks(
         lowercase__       ,	start_prompt="_import_structure = {"       ,	end_prompt="if TYPE_CHECKING:"       )

     # We ignore block 0 (everything until start_prompt) and the last block (everything after end_prompt).
     for block_idx in range(1       ,	len(lowercase__       ) - 1       ):
          # Check if the block contains some `_import_structure`s thingy to sort.
          a_       		=main_blocks[block_idx]
          a_       		=block.split("\n"       )

          # Get to the start of the imports.
          a_       		=0
          while line_idx < len(lowercase__       ) and "_import_structure" not in block_lines[line_idx]:
               # Skip dummy import blocks
               if "import dummy" in block_lines[line_idx]:
                    a_       		=len(lowercase__       )
               else:
                    line_idx += 1
          if line_idx >= len(lowercase__       ):
               continue

          # Ignore beginning and last line: they don't contain anything.
          a_       		="\n".join(block_lines[line_idx:-1]       )
          a_       		=get_indent(block_lines[1]       )
          # Slit the internal block into blocks of indent level 1.
          a_       		=split_code_in_indented_blocks(lowercase__       ,	indent_level=lowercase__       )
          # We have two categories of import key: list or _import_structure[key].append/extend
          a_       		=_re_direct_key if "_import_structure" in block_lines[0] else _re_indirect_key
          # Grab the keys, but there is a trap: some lines are empty or just comments.
          a_       		=[(pattern.search(lowercase__       ).groups()[0] if pattern.search(lowercase__       ) is not None else None) for b in internal_blocks]
          # We only sort the lines with a key.
          a_       		=[(i, key) for i, key in enumerate(lowercase__       ) if key is not None]
          a_       		=[x[0] for x in sorted(lowercase__       ,	key=lambda lowercase__       : x[1]       )]

          # We reorder the blocks by leaving empty lines/comments as they were and reorder the rest.
          a_       		=0
          a_       		=[]
          for i in range(len(lowercase__       )       ):
               if keys[i] is None:
                    reordered_blocks.append(internal_blocks[i]       )
               else:
                    a_       		=sort_objects_in_import(internal_blocks[sorted_indices[count]]       )
                    reordered_blocks.append(lowercase__       )
                    count += 1

        # And we put our main block back together with its first and last line.
          a_       		="\n".join(block_lines[:line_idx] + reordered_blocks + [block_lines[-1]]       )

     if code != "\n".join(lowercase__       ):
          if check_only:
               return True
          else:
               print(F"""Overwriting {file}."""       )
               with open(lowercase__       ,	"w"       ) as f:
                    f.write("\n".join(lowercase__       )       )






def  UpperCAmelCase_       (		lowercase__=True       ):


     '''simple docstring'''







     a_       		=[]
     for root, _, files in os.walk(lowercase__       ):
          if "__init__.py" in files:
               a_       		=sort_imports(os.path.join(lowercase__       ,	"__init__.py"       )       ,	check_only=lowercase__       )
               if result:
                    a_       		=[os.path.join(lowercase__       ,	"__init__.py"       )]
     if len(lowercase__       ) > 0:
          raise ValueError(F"""Would overwrite {len(lowercase__       )} files, run `make style`."""       )


if __name__ == "__main__":
  lowercase							       =			argparse.ArgumentParser()
  parser.add_argument('''--check_only''', action='''store_true''', help='''Whether to only check or fix style.''')
  lowercase							       =			parser.parse_args()

  sort_imports_in_all_inits(check_only=args.check_only)







'''simple docstring'''


import unittest
from typing import Tuple

import torch

from diffusers.utils import floats_tensor, randn_tensor, torch_all_close, torch_device
from diffusers.utils.testing_utils import require_torch







@require_torch
class 	UpperCAmelCase	:


 '''simple docstring'''




 @property
 def       lowercase_  (   self) ->      Any:



      """simple docstring"""







      return self.get_dummy_input()




 @property
 def       lowercase_  (   self) ->      List[str]:



      """simple docstring"""







      if self.block_type == "down":
           return (4, 3_2, 1_6, 1_6)
      elif self.block_type == "mid":
           return (4, 3_2, 3_2, 3_2)
      elif self.block_type == "up":
           return (4, 3_2, 6_4, 6_4)

      raise ValueError(f"""'{self.block_type}' is not a supported block_type. Set it to 'up', 'mid', or 'down'.""")




 def       lowercase_  (   self							,  lowerCAmelCase_=True							,  lowerCAmelCase_=False							,  lowerCAmelCase_=False							,  lowerCAmelCase_=False							,  ) ->      Dict:



      """simple docstring"""







      a_       		=4
      a_       		=3_2
      a_       		=(3_2, 3_2)

      a_       		=torch.manual_seed(0)
      a_       		=torch.device(lowerCAmelCase_)
      a_       		=(batch_size, num_channels) + sizes
      a_       		=randn_tensor(lowerCAmelCase_							,  generator=lowerCAmelCase_							,  device=lowerCAmelCase_)
      a_       		={"hidden_states": hidden_states}

      if include_temb:
           a_       		=1_2_8
           a_       		=randn_tensor((batch_size, temb_channels)							,  generator=lowerCAmelCase_							,  device=lowerCAmelCase_)

      if include_res_hidden_states_tuple:
           a_       		=torch.manual_seed(1)
           a_       		=(randn_tensor(lowerCAmelCase_							,  generator=lowerCAmelCase_							,  device=lowerCAmelCase_),)

      if include_encoder_hidden_states:
           a_       		=floats_tensor((batch_size, 3_2, 3_2)).to(lowerCAmelCase_)

      if include_skip_sample:
           a_       		=randn_tensor(((batch_size, 3) + sizes)							,  generator=lowerCAmelCase_							,  device=lowerCAmelCase_)

      return dummy_input




 def       lowercase_  (   self) ->      Optional[int]:



      """simple docstring"""







      a_       		={
          "in_channels": 3_2,
          "out_channels": 3_2,
          "temb_channels": 1_2_8,
      }
      if self.block_type == "up":
           a_       		=3_2

      if self.block_type == "mid":
           init_dict.pop("out_channels")

      a_       		=self.dummy_input
      return init_dict, inputs_dict




 def       lowercase_  (   self							,  lowerCAmelCase_) ->      Dict:



      """simple docstring"""







      a_		,						a_       		=self.prepare_init_args_and_inputs_for_common()
      a_       		=self.block_class(**lowerCAmelCase_)
      unet_block.to(lowerCAmelCase_)
      unet_block.eval()

      with torch.no_grad():
           a_       		=unet_block(**lowerCAmelCase_)

      if isinstance(lowerCAmelCase_							,  lowerCAmelCase_):
           a_       		=output[0]

      self.assertEqual(output.shape							,  self.output_shape)

      a_       		=output[0, -1, -3:, -3:]
      a_       		=torch.tensor(lowerCAmelCase_).to(lowerCAmelCase_)
      assert torch_all_close(output_slice.flatten()							,  lowerCAmelCase_							,  atol=5e-3)




 @unittest.skipIf(torch_device == "mps"							,  "Training is not supported in mps")
 def       lowercase_  (   self) ->      Optional[Any]:



      """simple docstring"""







      a_		,						a_       		=self.prepare_init_args_and_inputs_for_common()
      a_       		=self.block_class(**lowerCAmelCase_)
      model.to(lowerCAmelCase_)
      model.train()
      a_       		=model(**lowerCAmelCase_)

      if isinstance(lowerCAmelCase_							,  lowerCAmelCase_):
           a_       		=output[0]

      a_       		=torch.device(lowerCAmelCase_)
      a_       		=randn_tensor(output.shape							,  device=lowerCAmelCase_)
      a_       		=torch.nn.functional.mse_loss(lowerCAmelCase_							,  lowerCAmelCase_)
      loss.backward()


