





import argparse
import glob
import importlib.util
import os
import re

import black
from doc_builder.style_doc import style_docstrings_in_code


# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_copies.py
_snake_case           =			"""src/diffusers"""
_snake_case           =			"""."""


# This is to make sure the diffusers module imported is the one in the repo.
_snake_case           =			importlib.util.spec_from_file_location(
    """diffusers""",
    os.path.join(DIFFUSERS_PATH, """__init__.py"""),
    submodule_search_locations=[DIFFUSERS_PATH],
)
_snake_case           =			spec.loader.load_module()


def _A       (   __magic_name__  , __magic_name__	):
   return line.startswith(lowerCAmelCase__	) or len(lowerCAmelCase__	) <= 1 or re.search(R"^\s*\)(\s*->.*:|:)\s*$"  , lowerCAmelCase__	) is not None


def _A       (   __magic_name__	):
   lowercase__			       =  object_name.split("."	)
   lowercase__			       =  0

   # First let's find the module where our object lives.
   lowercase__			       =  parts[i]
   while i < len(lowerCAmelCase__	) and not os.path.isfile(os.path.join(lowerCAmelCase__  , f'''{module}.py'''	)	):
      i += 1
      if i < len(lowerCAmelCase__	):
         lowercase__			       =  os.path.join(lowerCAmelCase__  , parts[i]	)
   if i >= len(lowerCAmelCase__	):
      raise ValueError(f'''`object_name` should begin with the name of a module of diffusers but got {object_name}.'''	)

   with open(os.path.join(lowerCAmelCase__  , f'''{module}.py'''	)  , "r"  , encoding="utf-8"  , newline="\n"	) as f:
      lowercase__			       =  f.readlines()

   # Now let's find the class / func in the code!
   lowercase__			       =  ''''''
   lowercase__			       =  0
   for name in parts[i + 1 :]:
      while (
          line_index < len(lowerCAmelCase__	) and re.search(Rf'''^{indent}(class|def)\s+{name}(\(|\:)'''  , lines[line_index]	) is None
      ):
         line_index += 1
      indent += "    "
      line_index += 1

   if line_index >= len(lowerCAmelCase__	):
      raise ValueError(f''' {object_name} does not match any function or class in {module}.'''	)

   # We found the beginning of the class / func, now let's find the end (when the indent diminishes).
   lowercase__			       =  line_index
   while line_index < len(lowerCAmelCase__	) and _should_continue(lines[line_index]  , lowerCAmelCase__	):
      line_index += 1
   # Clean up empty lines at the end (if any).
   while len(lines[line_index - 1]	) <= 1:
      line_index -= 1

   lowercase__			       =  lines[start_index:line_index]
   return "".join(lowerCAmelCase__	)


_snake_case           =			re.compile(R"""^(\s*)#\s*Copied from\s+diffusers\.(\S+\.\S+)\s*($|\S.*$)""")
_snake_case           =			re.compile(R"""^\s*(\S+)->(\S+)(\s+.*|$)""")
_snake_case           =			re.compile(R"""<FILL\s+[^>]*>""")


def _A       (   __magic_name__	):
   lowercase__			       =  code.split("\n"	)
   lowercase__			       =  0
   while idx < len(lowerCAmelCase__	) and len(lines[idx]	) == 0:
      idx += 1
   if idx < len(lowerCAmelCase__	):
      return re.search(R"^(\s*)\S"  , lines[idx]	).groups()[0]
   return ""


def _A       (   __magic_name__	):
   lowercase__			       =  len(get_indent(lowerCAmelCase__	)	) > 0
   if has_indent:
      lowercase__			       =  f'''class Bla:\n{code}'''
   lowercase__			       =  black.Mode(target_versions={black.TargetVersion.PYaa}  , line_length=119  , preview=lowerCAmelCase__	)
   lowercase__			       =  black.format_str(lowerCAmelCase__  , mode=lowerCAmelCase__	)
   lowercase__			       =  style_docstrings_in_code(lowerCAmelCase__	)
   return result[len("class Bla:\n"	) :] if has_indent else result


def _A       (   __magic_name__  , __magic_name__=False	):
   with open(lowerCAmelCase__  , "r"  , encoding="utf-8"  , newline="\n"	) as f:
      lowercase__			       =  f.readlines()
   lowercase__			       =  []
   lowercase__			       =  0
   # Not a for loop cause `lines` is going to change (if `overwrite=True`).
   while line_index < len(lowerCAmelCase__	):
      lowercase__			       =  _re_copy_warning.search(lines[line_index]	)
      if search is None:
         line_index += 1
         continue

      # There is some copied code here, let's retrieve the original.
      lowercase__			       =  search.groups()
      lowercase__			       =  find_code_in_diffusers(lowerCAmelCase__	)
      lowercase__			       =  get_indent(lowerCAmelCase__	)

      lowercase__			       =  line_index + 1 if indent == theoretical_indent else line_index + 2
      lowercase__			       =  theoretical_indent
      lowercase__			       =  start_index

      # Loop to check the observed code, stop when indentation diminishes or if we see a End copy comment.
      lowercase__			       =  True
      while line_index < len(lowerCAmelCase__	) and should_continue:
         line_index += 1
         if line_index >= len(lowerCAmelCase__	):
            break
         lowercase__			       =  lines[line_index]
         lowercase__			       =  _should_continue(lowerCAmelCase__  , lowerCAmelCase__	) and re.search(f'''^{indent}# End copy'''  , lowerCAmelCase__	) is None
      # Clean up empty lines at the end (if any).
      while len(lines[line_index - 1]	) <= 1:
         line_index -= 1

      lowercase__			       =  lines[start_index:line_index]
      lowercase__			       =  ''''''.join(lowerCAmelCase__	)

      # Remove any nested `Copied from` comments to avoid circular copies
      lowercase__			       =  [line for line in theoretical_code.split("\n"	) if _re_copy_warning.search(lowerCAmelCase__	) is None]
      lowercase__			       =  '''\n'''.join(lowerCAmelCase__	)

      # Before comparing, use the `replace_pattern` on the original code.
      if len(lowerCAmelCase__	) > 0:
         lowercase__			       =  replace_pattern.replace("with"  , ""	).split(","	)
         lowercase__			       =  [_re_replace_pattern.search(lowerCAmelCase__	) for p in patterns]
         for pattern in patterns:
            if pattern is None:
               continue
            lowercase__			       =  pattern.groups()
            lowercase__			       =  re.sub(lowerCAmelCase__  , lowerCAmelCase__  , lowerCAmelCase__	)
            if option.strip() == "all-casing":
               lowercase__			       =  re.sub(obja.lower()  , obja.lower()  , lowerCAmelCase__	)
               lowercase__			       =  re.sub(obja.upper()  , obja.upper()  , lowerCAmelCase__	)

                      # Blackify after replacement. To be able to do that, we need the header (class or function definition)
                      # from the previous line
         lowercase__			       =  blackify(lines[start_index - 1] + theoretical_code	)
         lowercase__			       =  theoretical_code[len(lines[start_index - 1]	) :]

      # Test for a diff and act accordingly.
      if observed_code != theoretical_code:
         diffs.append([object_name, start_index]	)
         if overwrite:
            lowercase__			       =  lines[:start_index] + [theoretical_code] + lines[line_index:]
            lowercase__			       =  start_index + 1

   if overwrite and len(lowerCAmelCase__	) > 0:
      # Warn the user a file has been modified.
      print(f'''Detected changes, rewriting {filename}.'''	)
      with open(lowerCAmelCase__  , "w"  , encoding="utf-8"  , newline="\n"	) as f:
         f.writelines(lowerCAmelCase__	)
   return diffs


def _A       (   __magic_name__ = False	):
   lowercase__			       =  glob.glob(os.path.join(lowerCAmelCase__  , "**/*.py"	)  , recursive=lowerCAmelCase__	)
   lowercase__			       =  []
   for filename in all_files:
      lowercase__			       =  is_copy_consistent(lowerCAmelCase__  , lowerCAmelCase__	)
      diffs += [f'''- {filename}: copy does not match {d[0]} at line {d[1]}''' for d in new_diffs]
   if not overwrite and len(lowerCAmelCase__	) > 0:
      lowercase__			       =  '''\n'''.join(lowerCAmelCase__	)
      raise Exception(
          "Found the following copy inconsistencies:\n"
          + diff
          + "\nRun `make fix-copies` or `python utils/check_copies.py --fix_and_overwrite` to fix them."	)


if __name__ == "__main__":
  _snake_case           =			argparse.ArgumentParser()
  parser.add_argument("""--fix_and_overwrite""", action="""store_true""", help="""Whether to fix inconsistencies.""")
  _snake_case           =			parser.parse_args()

  check_copies(args.fix_and_overwrite)












import math
from typing import List, Optional, Tuple, Union

import numpy as np
import torch

from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils import SchedulerMixin, SchedulerOutput





class  lowerCAmelCase							(       lowercase_							,							lowercase_ ):
  __lowerCamelCase		=      1







  @register_to_config
  def __init__(      self  :Dict   ,							_lowercase  :int = 10_00   ,							_lowercase  :Optional[Union[np.ndarray, List[float]]] = None ):






     '''simple docstring'''





     self.set_timesteps(_lowercase )

     # standard deviation of the initial noise distribution
     lowercase__			       =  1.0

     # For now we only support F-PNDM, i.e. the runge-kutta method
     # For more information on the algorithm please take a look at the paper: https://arxiv.org/pdf/2202.09778.pdf
     # mainly at formula (9), (12), (13) and the Algorithm 2.
     lowercase__			       =  4

     # running values
     lowercase__			       =  []







  def   UpperCAmelCase					(      self  :str   ,							_lowercase  :int   ,							_lowercase  :Union[str, torch.device] = None ):






     '''simple docstring'''





     lowercase__			       =  num_inference_steps
     lowercase__			       =  torch.linspace(1   ,							0   ,							num_inference_steps + 1 )[:-1]
     lowercase__			       =  torch.cat([steps, torch.tensor([0.0] )] )

     if self.config.trained_betas is not None:
        lowercase__			       =  torch.tensor(self.config.trained_betas   ,							dtype=torch.floataa )
     else:
        lowercase__			       =  torch.sin(steps * math.pi / 2 ) ** 2

     lowercase__			       =  (1.0 - self.betas**2) ** 0.5

     lowercase__			       =  (torch.atana(self.betas   ,							self.alphas ) / math.pi * 2)[:-1]
     lowercase__			       =  timesteps.to(_lowercase )

     lowercase__			       =  []







  def   UpperCAmelCase					(      self  :Optional[int]   ,							_lowercase  :torch.FloatTensor   ,							_lowercase  :int   ,							_lowercase  :torch.FloatTensor   ,							_lowercase  :bool = True   ,							):






     '''simple docstring'''





     if self.num_inference_steps is None:
        raise ValueError(
            "Number of inference steps is 'None', you need to run 'set_timesteps' after creating the scheduler" )

     lowercase__			       =  (self.timesteps == timestep).nonzero().item()
     lowercase__			       =  timestep_index + 1

     lowercase__			       =  sample * self.betas[timestep_index] + model_output * self.alphas[timestep_index]
     self.ets.append(_lowercase )

     if len(self.ets ) == 1:
        lowercase__			       =  self.ets[-1]
     elif len(self.ets ) == 2:
        lowercase__			       =  (3 * self.ets[-1] - self.ets[-2]) / 2
     elif len(self.ets ) == 3:
        lowercase__			       =  (23 * self.ets[-1] - 16 * self.ets[-2] + 5 * self.ets[-3]) / 12
     else:
        lowercase__			       =  (1 / 24) * (55 * self.ets[-1] - 59 * self.ets[-2] + 37 * self.ets[-3] - 9 * self.ets[-4])

     lowercase__			       =  self._get_prev_sample(_lowercase   ,							_lowercase   ,							_lowercase   ,							_lowercase )

     if not return_dict:
        return (prev_sample,)

     return SchedulerOutput(prev_sample=_lowercase )







  def   UpperCAmelCase					(      self  :Any   ,							_lowercase  :torch.FloatTensor   ,							*_lowercase  :int   ,							**_lowercase  :int ):






     '''simple docstring'''





     return sample







  def   UpperCAmelCase					(      self  :str   ,							_lowercase  :Tuple   ,							_lowercase  :int   ,							_lowercase  :Optional[Any]   ,							_lowercase  :List[str] ):






     '''simple docstring'''





     lowercase__			       =  self.alphas[timestep_index]
     lowercase__			       =  self.betas[timestep_index]

     lowercase__			       =  self.alphas[prev_timestep_index]
     lowercase__			       =  self.betas[prev_timestep_index]

     lowercase__			       =  (sample - sigma * ets) / max(_lowercase   ,							1e-8 )
     lowercase__			       =  next_alpha * pred + ets * next_sigma

     return prev_sample







  def __len__(      self  :Union[str, Any] ):






     '''simple docstring'''





     return self.config.num_train_timesteps






