





import argparse
import os
import re

import packaging.version


__UpperCAmelCase       :   Any				       =							"examples/"
__UpperCAmelCase       :   str				       =							{
    "examples": (re.compile(R"^check_min_version\(\"[^\"]+\"\)\s*$", re.MULTILINE), "check_min_version(\"VERSION\")\n"),
    "init": (re.compile(R"^__version__\s+=\s+\"([^\"]+)\"\s*$", re.MULTILINE), "__version__ = \"VERSION\"\n"),
    "setup": (re.compile(R"^(\s*)version\s*=\s*\"[^\"]+\",", re.MULTILINE), R"\1version=\"VERSION\","),
    "doc": (re.compile(R"^(\s*)release\s*=\s*\"[^\"]+\"$", re.MULTILINE), "release = \"VERSION\"\n"),
}
__UpperCAmelCase       :   str				       =							{
    "init": "src/transformers/__init__.py",
    "setup": "setup.py",
}
__UpperCAmelCase       :   List[Any]				       =							"README.md"







def 			A__							(    SCREAMING_SNAKE_CASE__					,					SCREAMING_SNAKE_CASE__					,					SCREAMING_SNAKE_CASE__)   ->    Union[str, Any]:
  with open(SCREAMING_SNAKE_CASE__					,					"""r"""					,					encoding="""utf-8"""					,					newline="""\n""") as f:
    __snake_case:						Optional[int]   =						f.read()
  __snake_case  ,   __snake_case:						str   =						REPLACE_PATTERNS[pattern]
  __snake_case:						List[str]   =						replace.replace("""VERSION"""					,					SCREAMING_SNAKE_CASE__)
  __snake_case:						Any   =						re_pattern.sub(SCREAMING_SNAKE_CASE__					,					SCREAMING_SNAKE_CASE__)
  with open(SCREAMING_SNAKE_CASE__					,					"""w"""					,					encoding="""utf-8"""					,					newline="""\n""") as f:
    f.write(SCREAMING_SNAKE_CASE__)







def 			A__							(    SCREAMING_SNAKE_CASE__)   ->    int:
  for folder, directories, fnames in os.walk(SCREAMING_SNAKE_CASE__):
    # Removing some of the folders with non-actively maintained examples from the walk
    if "research_projects" in directories:
      directories.remove("""research_projects""")
    if "legacy" in directories:
      directories.remove("""legacy""")
    for fname in fnames:
      if fname.endswith(""".py"""):
        update_version_in_file(os.path.join(SCREAMING_SNAKE_CASE__					,					SCREAMING_SNAKE_CASE__)					,					SCREAMING_SNAKE_CASE__					,					pattern="""examples""")







def 			A__							(    SCREAMING_SNAKE_CASE__					,					SCREAMING_SNAKE_CASE__=False)   ->    List[str]:
  for pattern, fname in REPLACE_FILES.items():
    update_version_in_file(SCREAMING_SNAKE_CASE__					,					SCREAMING_SNAKE_CASE__					,					SCREAMING_SNAKE_CASE__)
  if not patch:
    update_version_in_examples(SCREAMING_SNAKE_CASE__)







def 			A__							(    )   ->    List[str]:
  __snake_case:						str   =						"""🤗 Transformers currently provides the following architectures"""
  __snake_case:						str   =						"""1. Want to contribute a new model?"""
  with open(SCREAMING_SNAKE_CASE__					,					"""r"""					,					encoding="""utf-8"""					,					newline="""\n""") as f:
    __snake_case:						Dict   =						f.readlines()

  # Find the start of the list.
  __snake_case:						List[Any]   =						0
  while not lines[start_index].startswith(_start_prompt):
    start_index += 1
  start_index += 1

  __snake_case:						List[str]   =						start_index
  # Update the lines in the model list.
  while not lines[index].startswith(_end_prompt):
    if lines[index].startswith("""1."""):
      __snake_case:						Tuple   =						lines[index].replace(
          """https://huggingface.co/docs/transformers/main/model_doc"""					,					"""https://huggingface.co/docs/transformers/model_doc"""					,					)
    index += 1

  with open(SCREAMING_SNAKE_CASE__					,					"""w"""					,					encoding="""utf-8"""					,					newline="""\n""") as f:
    f.writelines(SCREAMING_SNAKE_CASE__)







def 			A__							(    )   ->    List[str]:
  with open(REPLACE_FILES["""init"""]					,					"""r""") as f:
    __snake_case:						str   =						f.read()
  __snake_case:						str   =						REPLACE_PATTERNS["""init"""][0].search(SCREAMING_SNAKE_CASE__).groups()[0]
  return packaging.version.parse(SCREAMING_SNAKE_CASE__)







def 			A__							(    SCREAMING_SNAKE_CASE__=False)   ->    Optional[Any]:
  __snake_case:						Dict   =						get_version()
  if patch and default_version.is_devrelease:
    raise ValueError("""Can't create a patch version from the dev branch, checkout a released version!""")
  if default_version.is_devrelease:
    __snake_case:						Union[str, Any]   =						default_version.base_version
  elif patch:
    __snake_case:						List[str]   =						F'''{default_version.major}.{default_version.minor}.{default_version.micro + 1}'''
  else:
    __snake_case:						Dict   =						F'''{default_version.major}.{default_version.minor + 1}.0'''

  # Now let's ask nicely if that's the right one.
  __snake_case:						int   =						input(F'''Which version are you releasing? [{default_version}]''')
  if len(SCREAMING_SNAKE_CASE__) == 0:
    __snake_case:						Optional[Any]   =						default_version

  print(F'''Updating version to {version}.''')
  global_version_update(SCREAMING_SNAKE_CASE__					,					patch=SCREAMING_SNAKE_CASE__)
  if not patch:
    print("""Cleaning main README, don't forget to run `make fix-copies`.""")
    clean_main_ref_in_model_list()







def 			A__							(    )   ->    int:
  __snake_case:						Dict   =						get_version()
  __snake_case:						Dict   =						F'''{current_version.major}.{current_version.minor + 1}.0.dev0'''
  __snake_case:						Tuple   =						current_version.base_version

  # Check with the user we got that right.
  __snake_case:						Dict   =						input(F'''Which version are we developing now? [{dev_version}]''')
  if len(SCREAMING_SNAKE_CASE__) == 0:
    __snake_case:						List[str]   =						dev_version

  print(F'''Updating version to {version}.''')
  global_version_update(SCREAMING_SNAKE_CASE__)
  print("""Cleaning main README, don't forget to run `make fix-copies`.""")
  clean_main_ref_in_model_list()


if __name__ == "__main__":
      __UpperCAmelCase       :   int				       =							argparse.ArgumentParser()
      parser.add_argument("--post_release", action="store_true", help="Whether this is pre or post release.")
      parser.add_argument("--patch", action="store_true", help="Whether or not this is a patch release.")
      __UpperCAmelCase       :   Optional[int]				       =							parser.parse_args()
      if not args.post_release:
            pre_release_work(patch=args.patch)
      elif args.patch:
            print("Nothing to do after a patch :-)")
      else:
            post_release_work()













import gc
import unittest

from parameterized import parameterized

from diffusers import FlaxUNetaDConditionModel
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import load_hf_numpy, require_flax, slow


if is_flax_available():
      import jax
      import jax.numpy as jnp







@slow
@require_flax
class     __snake_case       (							unittest.TestCase			):





       '''simple docstring'''







       def 							UpperCAmelCase__ (  self :    Any							,				A :    Dict							,				A :    Any		):
         return f'''gaussian_noise_s={seed}_shape={'_'.join([str(A		) for s in shape]		)}.npy'''




       def 							UpperCAmelCase__ (  self :    Optional[Any]		):
         # clean up the VRAM after each test
         super().tearDown()
         gc.collect()




       def 							UpperCAmelCase__ (  self :    Optional[Any]							,				A :    Optional[int]=0							,				A :    Tuple=(4, 4, 64, 64)							,				A :    Tuple=False		):
         __snake_case:						Dict   =						jnp.bfloataa if fpaa else jnp.floataa
         __snake_case:						str   =						jnp.array(load_hf_numpy(self.get_file_format(A							,				A		)		)							,				dtype=A		)
         return image




       def 							UpperCAmelCase__ (  self :    Union[str, Any]							,				A :    Any=False							,				A :    Optional[Any]="CompVis/stable-diffusion-v1-4"		):
         __snake_case:						List[Any]   =						jnp.bfloataa if fpaa else jnp.floataa
         __snake_case:						Union[str, Any]   =						"""bf16""" if fpaa else None

         __snake_case  ,   __snake_case:						Optional[int]   =						FlaxUNetaDConditionModel.from_pretrained(
             A							,				subfolder="""unet"""							,				dtype=A							,				revision=A		)
         return model, params




       def 							UpperCAmelCase__ (  self :    Tuple							,				A :    Tuple=0							,				A :    str=(4, 77, 768)							,				A :    List[str]=False		):
         __snake_case:						Any   =						jnp.bfloataa if fpaa else jnp.floataa
         __snake_case:						Dict   =						jnp.array(load_hf_numpy(self.get_file_format(A							,				A		)		)							,				dtype=A		)
         return hidden_states




       @parameterized.expand(
           [
               # fmt: off
               [83, 4, [-0.2323, -0.1304, 0.0813, -0.3093, -0.0919, -0.1571, -0.1125, -0.5806]],
               [17, 0.55, [-0.0831, -0.2443, 0.0901, -0.0919, 0.3396, 0.0103, -0.3743, 0.0701]],
               [8, 0.89, [-0.4863, 0.0859, 0.0875, -0.1658, 0.9199, -0.0114, 0.4839, 0.4639]],
               [3, 1_000, [-0.5649, 0.2402, -0.5518, 0.1248, 1.1328, -0.2443, -0.0325, -1.0078]],
               # fmt: on
           ]		)
       def 							UpperCAmelCase__ (  self :    Optional[Any]							,				A :    Optional[Any]							,				A :    str							,				A :    Any		):
         __snake_case  ,   __snake_case:						Union[str, Any]   =						self.get_unet_model(model_id="""CompVis/stable-diffusion-v1-4"""							,				fpaa=A		)
         __snake_case:						Tuple   =						self.get_latents(A							,				fpaa=A		)
         __snake_case:						int   =						self.get_encoder_hidden_states(A							,				fpaa=A		)

         __snake_case:						List[Any]   =						model.apply(
             {"""params""": params}							,				A							,				jnp.array(A							,				dtype=jnp.intaa		)							,				encoder_hidden_states=A							,				).sample

         assert sample.shape == latents.shape

         __snake_case:						str   =						jnp.asarray(jax.device_get((sample[-1, -2:, -2:, :2].flatten())		)							,				dtype=jnp.floataa		)
         __snake_case:						Optional[int]   =						jnp.array(A							,				dtype=jnp.floataa		)

         # Found torch (float16) and flax (bfloat16) outputs to be within this tolerance, in the same hardware
         assert jnp.allclose(A							,				A							,				atol=1E-2		)






       @parameterized.expand(
           [
               # fmt: off
               [83, 4, [0.1514, 0.0807, 0.1624, 0.1016, -0.1896, 0.0263, 0.0677, 0.2310]],
               [17, 0.55, [0.1164, -0.0216, 0.0170, 0.1589, -0.3120, 0.1005, -0.0581, -0.1458]],
               [8, 0.89, [-0.1758, -0.0169, 0.1004, -0.1411, 0.1312, 0.1103, -0.1996, 0.2139]],
               [3, 1_000, [0.1214, 0.0352, -0.0731, -0.1562, -0.0994, -0.0906, -0.2340, -0.0539]],
               # fmt: on
           ]		)
       def 							UpperCAmelCase__ (  self :    Optional[Any]							,				A :    int							,				A :    Tuple							,				A :    List[str]		):
         __snake_case  ,   __snake_case:						Union[str, Any]   =						self.get_unet_model(model_id="""stabilityai/stable-diffusion-2"""							,				fpaa=A		)
         __snake_case:						Optional[int]   =						self.get_latents(A							,				shape=(4, 4, 96, 96)							,				fpaa=A		)
         __snake_case:						str   =						self.get_encoder_hidden_states(A							,				shape=(4, 77, 1_024)							,				fpaa=A		)

         __snake_case:						str   =						model.apply(
             {"""params""": params}							,				A							,				jnp.array(A							,				dtype=jnp.intaa		)							,				encoder_hidden_states=A							,				).sample

         assert sample.shape == latents.shape

         __snake_case:						Dict   =						jnp.asarray(jax.device_get((sample[-1, -2:, -2:, :2].flatten())		)							,				dtype=jnp.floataa		)
         __snake_case:						Any   =						jnp.array(A							,				dtype=jnp.floataa		)

         # Found torch (float16) and flax (bfloat16) outputs to be within this tolerance, on the same hardware
         assert jnp.allclose(A							,				A							,				atol=1E-2		)






