
'''simple docstring'''

import argparse
import math
import os

import torch
from neural_compressor.utils.pytorch import load
from PIL import Image
from transformers import CLIPTextModel, CLIPTokenizer

from diffusers import AutoencoderKL, StableDiffusionPipeline, UNetaDConditionModel






def 	_snake_case						(      ):
  """simple docstring"""







  a_      :	List[str]      =							argparse.ArgumentParser()
  parser.add_argument(
      """-m"""     ,		"""--pretrained_model_name_or_path"""     ,		type=A_     ,		default=A_     ,		required=A_     ,		help="""Path to pretrained model or model identifier from huggingface.co/models."""     ,		)
  parser.add_argument(
      """-c"""     ,		"""--caption"""     ,		type=A_     ,		default="""robotic cat with wings"""     ,		help="""Text used to generate images."""     ,		)
  parser.add_argument(
      """-n"""     ,		"""--images_num"""     ,		type=A_     ,		default=4     ,		help="""How much images to generate."""     ,		)
  parser.add_argument(
      """-s"""     ,		"""--seed"""     ,		type=A_     ,		default=42     ,		help="""Seed for random process."""     ,		)
  parser.add_argument(
      """-ci"""     ,		"""--cuda_id"""     ,		type=A_     ,		default=0     ,		help="""cuda_id."""     ,		)
  a_      :	Any      =							parser.parse_args()
  return args






def 	_snake_case						(      A_       :    Optional[int]     ,		A_       :    Dict     ,		A_       :    Any   ):
  """simple docstring"""







  if not len(A_   ) == rows * cols:
    raise ValueError("""The specified number of rows and columns are not correct."""   )

  a_      , a_      :	Union[str, Any]      =							imgs[0].size
  a_      :	str      =							Image.new("""RGB"""     ,		size=(cols * w, rows * h)   )
  a_      , a_      :	Tuple      =							grid.size

  for i, img in enumerate(A_   ):
    grid.paste(A_     ,		box=(i % cols * w, i // cols * h)   )
  return grid






def 	_snake_case						(      A_       :    int     ,		A_       :    Dict="robotic cat with wings"     ,		A_       :    Any=7.5     ,		A_       :    List[Any]=50     ,		A_       :    Optional[Any]=1     ,		A_       :    Dict=42     ,		):
  """simple docstring"""







  a_      :	Optional[Any]      =							torch.Generator(pipeline.device   ).manual_seed(A_   )
  a_      :	Union[str, Any]      =							pipeline(
      A_     ,		guidance_scale=A_     ,		num_inference_steps=A_     ,		generator=A_     ,		num_images_per_prompt=A_     ,		).images
  a_      :	Optional[int]      =							int(math.sqrt(A_   )   )
  a_      :	List[str]      =							image_grid(A_     ,		rows=_rows     ,		cols=num_images_per_prompt // _rows   )
  return grid, images


__snake_case:  Optional[Any]								=			parse_args()
# Load models and create wrapper for stable diffusion
__snake_case:  List[Any]								=			CLIPTokenizer.from_pretrained(args.pretrained_model_name_or_path, subfolder="tokenizer")
__snake_case:  Optional[int]								=			CLIPTextModel.from_pretrained(args.pretrained_model_name_or_path, subfolder="text_encoder")
__snake_case:  List[str]								=			AutoencoderKL.from_pretrained(args.pretrained_model_name_or_path, subfolder="vae")
__snake_case:  Optional[int]								=			UNetaDConditionModel.from_pretrained(args.pretrained_model_name_or_path, subfolder="unet")

__snake_case:  List[Any]								=			StableDiffusionPipeline.from_pretrained(
    args.pretrained_model_name_or_path, text_encoder=text_encoder, vae=vae, unet=unet, tokenizer=tokenizer
)
__snake_case:  Optional[int]								=			lambda images, clip_input: (images, False)
if os.path.exists(os.path.join(args.pretrained_model_name_or_path, "best_model.pt")):
    __snake_case:  str								=			load(args.pretrained_model_name_or_path, model=unet)
    unet.eval()
    setattr(pipeline, "unet", unet)
else:
    __snake_case:  Dict								=			unet.to(torch.device("cuda", args.cuda_id))
__snake_case:  Optional[int]								=			pipeline.to(unet.device)
__snake_case							,__snake_case:  Any								=			generate_images(pipeline, prompt=args.caption, num_images_per_prompt=args.images_num, seed=args.seed)
grid.save(os.path.join(args.pretrained_model_name_or_path, "{}.png".format("_".join(args.caption.split()))))
__snake_case:  Optional[int]								=			os.path.join(args.pretrained_model_name_or_path, "_".join(args.caption.split()))
os.makedirs(dirname, exist_ok=True)
for idx, image in enumerate(images):
    image.save(os.path.join(dirname, "{}.png".format(idx + 1)))




'''simple docstring'''

from datasets.utils.patching import _PatchedModuleObj, patch_submodule

from . import _test_patching






def 	_snake_case						(      ):
  """simple docstring"""







  import os as original_os
  from os import path as original_path
  from os import rename as original_rename
  from os.path import dirname as original_dirname
  from os.path import join as original_join

  assert _test_patching.os is original_os
  assert _test_patching.path is original_path
  assert _test_patching.join is original_join

  assert _test_patching.renamed_os is original_os
  assert _test_patching.renamed_path is original_path
  assert _test_patching.renamed_join is original_join

  a_      :	List[str]      =							"""__test_patch_submodule_mock__"""
  with patch_submodule(_test_patching     ,		"""os.path.join"""     ,		A_   ):
    # Every way to access os.path.join must be patched, and the rest must stay untouched

    # check os.path.join
    assert isinstance(_test_patching.os     ,		_PatchedModuleObj   )
    assert isinstance(_test_patching.os.path     ,		_PatchedModuleObj   )
    assert _test_patching.os.path.join is mock

    # check path.join
    assert isinstance(_test_patching.path     ,		_PatchedModuleObj   )
    assert _test_patching.path.join is mock

    # check join
    assert _test_patching.join is mock

    # check that the other attributes are untouched
    assert _test_patching.os.rename is original_rename
    assert _test_patching.path.dirname is original_dirname
    assert _test_patching.os.path.dirname is original_dirname

    # Even renamed modules or objects must be patched

    # check renamed_os.path.join
    assert isinstance(_test_patching.renamed_os     ,		_PatchedModuleObj   )
    assert isinstance(_test_patching.renamed_os.path     ,		_PatchedModuleObj   )
    assert _test_patching.renamed_os.path.join is mock

    # check renamed_path.join
    assert isinstance(_test_patching.renamed_path     ,		_PatchedModuleObj   )
    assert _test_patching.renamed_path.join is mock

    # check renamed_join
    assert _test_patching.renamed_join is mock

    # check that the other attributes are untouched
    assert _test_patching.renamed_os.rename is original_rename
    assert _test_patching.renamed_path.dirname is original_dirname
    assert _test_patching.renamed_os.path.dirname is original_dirname

  # check that everthing is back to normal when the patch is over

  assert _test_patching.os is original_os
  assert _test_patching.path is original_path
  assert _test_patching.join is original_join

  assert _test_patching.renamed_os is original_os
  assert _test_patching.renamed_path is original_path
  assert _test_patching.renamed_join is original_join






def 	_snake_case						(      ):
  """simple docstring"""







  assert _test_patching.open is open

  a_      :	Tuple      =							"""__test_patch_submodule_builtin_mock__"""
  # _test_patching has "open" in its globals
  assert _test_patching.open is open
  with patch_submodule(_test_patching     ,		"""open"""     ,		A_   ):
    assert _test_patching.open is mock

  # check that everthing is back to normal when the patch is over

  assert _test_patching.open is open






def 	_snake_case						(      ):
  """simple docstring"""







  a_      :	Any      =							"""__test_patch_submodule_missing_mock__"""
  with patch_submodule(_test_patching     ,		"""pandas.read_csv"""     ,		A_   ):
    pass






def 	_snake_case						(      ):
  """simple docstring"""







  a_      :	int      =							"""__test_patch_submodule_missing_builtin_mock__"""
  # _test_patching doesn't have "len" in its globals
  assert getattr(_test_patching     ,		"""len"""     ,		A_   ) is None
  with patch_submodule(_test_patching     ,		"""len"""     ,		A_   ):
    assert _test_patching.len is mock
  assert _test_patching.len is len






def 	_snake_case						(      ):
  """simple docstring"""







  a_      :	List[str]      =							"""__test_patch_submodule_start_and_stop_mock__"""
  a_      :	int      =							patch_submodule(_test_patching     ,		"""open"""     ,		A_   )
  assert _test_patching.open is open
  patch.start()
  assert _test_patching.open is mock
  patch.stop()
  assert _test_patching.open is open






def 	_snake_case						(      ):
  """simple docstring"""







  from os import rename as original_rename
  from os.path import dirname as original_dirname
  from os.path import join as original_join

  a_      :	Any      =							"""__test_patch_submodule_successive_join__"""
  a_      :	Optional[Any]      =							"""__test_patch_submodule_successive_dirname__"""
  a_      :	Optional[int]      =							"""__test_patch_submodule_successive_rename__"""
  assert _test_patching.os.path.join is original_join
  assert _test_patching.os.path.dirname is original_dirname
  assert _test_patching.os.rename is original_rename

  with patch_submodule(_test_patching     ,		"""os.path.join"""     ,		A_   ):
    with patch_submodule(_test_patching     ,		"""os.rename"""     ,		A_   ):
      with patch_submodule(_test_patching     ,		"""os.path.dirname"""     ,		A_   ):
        assert _test_patching.os.path.join is mock_join
        assert _test_patching.os.path.dirname is mock_dirname
        assert _test_patching.os.rename is mock_rename

    # try another order
  with patch_submodule(_test_patching     ,		"""os.rename"""     ,		A_   ):
    with patch_submodule(_test_patching     ,		"""os.path.join"""     ,		A_   ):
      with patch_submodule(_test_patching     ,		"""os.path.dirname"""     ,		A_   ):
        assert _test_patching.os.path.join is mock_join
        assert _test_patching.os.path.dirname is mock_dirname
        assert _test_patching.os.rename is mock_rename

  assert _test_patching.os.path.join is original_join
  assert _test_patching.os.path.dirname is original_dirname
  assert _test_patching.os.rename is original_rename






def 	_snake_case						(      ):
  """simple docstring"""







  a_      :	Optional[int]      =							"""__test_patch_submodule_doesnt_exist_mock__"""
  with patch_submodule(_test_patching     ,		"""__module_that_doesn_exist__.__attribute_that_doesn_exist__"""     ,		A_   ):
    pass
  with patch_submodule(_test_patching     ,		"""os.__attribute_that_doesn_exist__"""     ,		A_   ):
    pass


