
import argparse

import intel_extension_for_pytorch as ipex
import torch

from diffusers import DPMSolverMultistepScheduler, StableDiffusionPipeline


UpperCAmelCase       =					argparse.ArgumentParser('''Stable Diffusion script with intel optimization''', add_help=False)
parser.add_argument('''--dpm''', action='''store_true''', help='''Enable DPMSolver or not''')
parser.add_argument('''--steps''', default=None, type=int, help='''Num inference steps''')
UpperCAmelCase       =					parser.parse_args()


UpperCAmelCase       =					'''cpu'''
UpperCAmelCase       =					'''a lovely <dicoo> in red dress and hat, in the snowly and brightly night, with many brighly buildings'''

UpperCAmelCase       =					'''path-to-your-trained-model'''
UpperCAmelCase       =					StableDiffusionPipeline.from_pretrained(model_id)
if args.dpm:
	UpperCAmelCase       =					DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)
UpperCAmelCase       =					pipe.to(device)

# to channels last
UpperCAmelCase       =					pipe.unet.to(memory_format=torch.channels_last)
UpperCAmelCase       =					pipe.vae.to(memory_format=torch.channels_last)
UpperCAmelCase       =					pipe.text_encoder.to(memory_format=torch.channels_last)
if pipe.requires_safety_checker:
	UpperCAmelCase       =					pipe.safety_checker.to(memory_format=torch.channels_last)

# optimize with ipex
UpperCAmelCase       =					torch.randn(2, 4, 64, 64)
UpperCAmelCase       =					torch.rand(1) * 999
UpperCAmelCase       =					torch.randn(2, 77, 768)
UpperCAmelCase       =					(sample, timestep, encoder_hidden_status)
try:
	UpperCAmelCase       =					ipex.optimize(pipe.unet.eval(), dtype=torch.bfloataa, inplace=True, sample_input=input_example)
except Exception:
	UpperCAmelCase       =					ipex.optimize(pipe.unet.eval(), dtype=torch.bfloataa, inplace=True)
UpperCAmelCase       =					ipex.optimize(pipe.vae.eval(), dtype=torch.bfloataa, inplace=True)
UpperCAmelCase       =					ipex.optimize(pipe.text_encoder.eval(), dtype=torch.bfloataa, inplace=True)
if pipe.requires_safety_checker:
	UpperCAmelCase       =					ipex.optimize(pipe.safety_checker.eval(), dtype=torch.bfloataa, inplace=True)

# compute
UpperCAmelCase       =					666
UpperCAmelCase       =					torch.Generator(device).manual_seed(seed)
UpperCAmelCase       =					{'''generator''': generator}
if args.steps is not None:
	UpperCAmelCase       =					args.steps

with torch.cpu.amp.autocast(enabled=True, dtype=torch.bfloataa):
	UpperCAmelCase       =					pipe(prompt, **generate_kwargs).images[0]

# save image
image.save('''generated.png''')







import argparse
import json
import os
import time
import zipfile

from get_ci_error_statistics import download_artifact, get_artifacts_links

from transformers import logging


_lowerCamelCase      :						int							=  logging.get_logger(__name__)







def SCREAMING_SNAKE_CASE							(			lowercase_					,							lowercase_		)  ->			Dict:



       """simple docstring"""

       A__ 					=       set()
       A__ 					=       []

       def parse_line(lowercase_		):
              for line in fp:
                     if isinstance(lowercase_					,							lowercase_		):
                            A__ 					=       line.decode('''UTF-8'''		)
                     if "warnings summary (final)" in line:
                            continue
                     # This means we are outside the body of a warning
                     elif not line.startswith(''' '''		):
                            # process a single warning and move it to `selected_warnings`.
                            if len(lowercase_		) > 0:
                                   A__ 					=       '''\n'''.join(lowercase_		)
                                   # Only keep the warnings specified in `targets`
                                   if any(f""": {x}: """ in warning for x in targets		):
                                          selected_warnings.add(lowercase_		)
                                   buffer.clear()
                            continue
                     else:
                            A__ 					=       line.strip()
                            buffer.append(lowercase_		)

       if from_gh:
              for filename in os.listdir(lowercase_		):
                     A__ 					=       os.path.join(lowercase_					,							lowercase_		)
                     if not os.path.isdir(lowercase_		):
                            # read the file
                            if filename != "warnings.txt":
                                   continue
                            with open(lowercase_		) as fp:
                                   parse_line(lowercase_		)
       else:
              try:
                     with zipfile.ZipFile(lowercase_		) as z:
                            for filename in z.namelist():
                                   if not os.path.isdir(lowercase_		):
                                          # read the file
                                          if filename != "warnings.txt":
                                                 continue
                                          with z.open(lowercase_		) as fp:
                                                 parse_line(lowercase_		)
              except Exception:
                     logger.warning(
                         f"""{artifact_path} is either an invalid zip file or something else wrong. This file is skipped."""		)

       return selected_warnings







def SCREAMING_SNAKE_CASE							(			lowercase_					,							lowercase_		)  ->			str:



       """simple docstring"""

       A__ 					=       set()

       A__ 					=       [os.path.join(lowercase_					,							lowercase_		) for p in os.listdir(lowercase_		) if (p.endswith('''.zip'''		) or from_gh)]
       for p in paths:
              selected_warnings.update(extract_warnings_from_single_artifact(lowercase_					,							lowercase_		)		)

       return selected_warnings


if __name__ == "__main__":







  def SCREAMING_SNAKE_CASE							(			lowercase_		)  ->			int:



         """simple docstring"""

         return values.split(''','''		)

  _lowerCamelCase      :						int							=  argparse.ArgumentParser()
  # Required parameters
  parser.add_argument("""--workflow_run_id""", type=str, required=True, help="""A GitHub Actions workflow run id.""")
  parser.add_argument(
      """--output_dir""",
      type=str,
      required=True,
      help="""Where to store the downloaded artifacts and other result files.""",
  )
  parser.add_argument("""--token""", default=None, type=str, help="""A token that has actions:read permission.""")
  # optional parameters
  parser.add_argument(
      """--targets""",
      default="""DeprecationWarning,UserWarning,FutureWarning""",
      type=list_str,
      help="""Comma-separated list of target warning(s) which we want to extract.""",
  )
  parser.add_argument(
      """--from_gh""",
      action="""store_true""",
      help="""If running from a GitHub action workflow and collecting warnings from its artifacts.""",
  )

  _lowerCamelCase      :						List[Any]							=  parser.parse_args()

  _lowerCamelCase      :						List[str]							=  args.from_gh
  if from_gh:
    # The artifacts have to be downloaded using `actions/download-artifact@v3`
    pass
  else:
    os.makedirs(args.output_dir, exist_ok=True)

    # get download links
    _lowerCamelCase      :						Any							=  get_artifacts_links(args.workflow_run_id, token=args.token)
    with open(os.path.join(args.output_dir, """artifacts.json"""), """w""", encoding="""UTF-8""") as fp:
      json.dump(artifacts, fp, ensure_ascii=False, indent=4)

    # download artifacts
    for idx, (name, url) in enumerate(artifacts.items()):
      print(name)
      print(url)
      print("""=""" * 80)
      download_artifact(name, url, args.output_dir, args.token)
      # Be gentle to GitHub
      time.sleep(1)

    # extract warnings from artifacts
  _lowerCamelCase      :						Any							=  extract_warnings(args.output_dir, args.targets)
  _lowerCamelCase      :						Optional[Any]							=  sorted(selected_warnings)
  with open(os.path.join(args.output_dir, """selected_warnings.json"""), """w""", encoding="""UTF-8""") as fp:
    json.dump(selected_warnings, fp, ensure_ascii=False, indent=4)


