



'''simple docstring'''






import json
import os

import torch

from diffusers import UNetaDModel


os.makedirs('hub/hopper-medium-v2/unet/hor32', exist_ok=True)
os.makedirs('hub/hopper-medium-v2/unet/hor128', exist_ok=True)

os.makedirs('hub/hopper-medium-v2/value_function', exist_ok=True)
def 				lowerCamelCase__	(						_A    ):
  if hor == 128:
    a						: int					       =					('DownResnetBlock1D', 'DownResnetBlock1D', 'DownResnetBlock1D')
    a						: List[str]					       =					(32, 128, 256)
    a						: Dict					       =					('UpResnetBlock1D', 'UpResnetBlock1D')

  elif hor == 32:
    a						: int					       =					('DownResnetBlock1D', 'DownResnetBlock1D', 'DownResnetBlock1D', 'DownResnetBlock1D')
    a						: Any					       =					(32, 64, 128, 256)
    a						: Dict					       =					('UpResnetBlock1D', 'UpResnetBlock1D', 'UpResnetBlock1D')
  a						: int					       =					torch.load(f"""/Users/bglickenhaus/Documents/diffuser/temporal_unet-hopper-mediumv2-hor{hor}.torch"""    )
  a						: Optional[Any]					       =					model.state_dict()
  a						: Any					       =					{
      'down_block_types': down_block_types,
      'block_out_channels': block_out_channels,
      'up_block_types': up_block_types,
      'layers_per_block': 1,
      'use_timestep_embedding': True,
      'out_block_type': 'OutConv1DBlock',
      'norm_num_groups': 8,
      'downsample_each_block': False,
      'in_channels': 14,
      'out_channels': 14,
      'extra_in_channels': 0,
      'time_embedding_type': 'positional',
      'flip_sin_to_cos': False,
      'freq_shift': 1,
      'sample_size': 6_5536,
      'mid_block_type': 'MidResTemporalBlock1D',
      'act_fn': 'mish',
  }
  a						: str					       =					UNetaDModel(**_A    )
  print(f"""length of state dict: {len(state_dict.keys()    )}"""    )
  print(f"""length of value function dict: {len(hf_value_function.state_dict().keys()    )}"""    )
  a						: List[str]					       =					dict(zip(model.state_dict().keys()			,      hf_value_function.state_dict().keys()    )    )
  for k, v in mapping.items():
    a						: List[str]					       =					state_dict.pop(_A    )
  hf_value_function.load_state_dict(_A    )

  torch.save(hf_value_function.state_dict()			,      f"""hub/hopper-medium-v2/unet/hor{hor}/diffusion_pytorch_model.bin"""    )
  with open(f"""hub/hopper-medium-v2/unet/hor{hor}/config.json"""			,      'w'    ) as f:
    json.dump(_A			,      _A    )
def 				lowerCamelCase__	(						):
  a						: str					       =					{
      'in_channels': 14,
      'down_block_types': ('DownResnetBlock1D', 'DownResnetBlock1D', 'DownResnetBlock1D', 'DownResnetBlock1D'),
      'up_block_types': (),
      'out_block_type': 'ValueFunction',
      'mid_block_type': 'ValueFunctionMidBlock1D',
      'block_out_channels': (32, 64, 128, 256),
      'layers_per_block': 1,
      'downsample_each_block': True,
      'sample_size': 6_5536,
      'out_channels': 14,
      'extra_in_channels': 0,
      'time_embedding_type': 'positional',
      'use_timestep_embedding': True,
      'flip_sin_to_cos': False,
      'freq_shift': 1,
      'norm_num_groups': 8,
      'act_fn': 'mish',
  }

  a						: Optional[int]					       =					torch.load('/Users/bglickenhaus/Documents/diffuser/value_function-hopper-mediumv2-hor32.torch'    )
  a						: str					       =					model
  a						: Dict					       =					UNetaDModel(**_A    )
  print(f"""length of state dict: {len(state_dict.keys()    )}"""    )
  print(f"""length of value function dict: {len(hf_value_function.state_dict().keys()    )}"""    )

  a						: Union[str, Any]					       =					dict(zip(state_dict.keys()			,      hf_value_function.state_dict().keys()    )    )
  for k, v in mapping.items():
    a						: int					       =					state_dict.pop(_A    )

  hf_value_function.load_state_dict(_A    )

  torch.save(hf_value_function.state_dict()			,      'hub/hopper-medium-v2/value_function/diffusion_pytorch_model.bin'    )
  with open('hub/hopper-medium-v2/value_function/config.json'			,      'w'    ) as f:
    json.dump(_A			,      _A    )


if __name__ == "__main__":
     unet(3_2)
     # unet(128)
     value_function()




'''simple docstring'''






import argparse
import os
import re

import packaging.version


lowerCAmelCase: List[str]							=						'examples/'
lowerCAmelCase: List[Any]							=						{
    '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'),
}
lowerCAmelCase: str							=						{
    'init': 'src/transformers/__init__.py',
    'setup': 'setup.py',
}
lowerCAmelCase: str							=						'README.md'
def 				lowerCamelCase__	(						_A			,      _A			,      _A    ):
  with open(_A			,      'r'			,      encoding='utf-8'			,      newline='\n'    ) as f:
    a						: Tuple					       =					f.read()
  a       ,     a						: Tuple					       =					REPLACE_PATTERNS[pattern]
  a						: Dict					       =					replace.replace('VERSION'			,      _A    )
  a						: Dict					       =					re_pattern.sub(_A			,      _A    )
  with open(_A			,      'w'			,      encoding='utf-8'			,      newline='\n'    ) as f:
    f.write(_A    )
def 				lowerCamelCase__	(						_A    ):
  for folder, directories, fnames in os.walk(_A    ):
    # 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(_A			,      _A    )			,      _A			,      pattern='examples'    )
def 				lowerCamelCase__	(						_A			,      _A=False    ):
  for pattern, fname in REPLACE_FILES.items():
    update_version_in_file(_A			,      _A			,      _A    )
  if not patch:
    update_version_in_examples(_A    )
def 				lowerCamelCase__	(						):
  a						: Tuple					       =					'🤗 Transformers currently provides the following architectures'
  a						: Any					       =					'1. Want to contribute a new model?'
  with open(_A			,      'r'			,      encoding='utf-8'			,      newline='\n'    ) as f:
    a						: Tuple					       =					f.readlines()

  # Find the start of the list.
  a						: Optional[int]					       =					0
  while not lines[start_index].startswith(_start_prompt    ):
    start_index += 1
  start_index += 1

  a						: Optional[int]					       =					start_index
  # Update the lines in the model list.
  while not lines[index].startswith(_end_prompt    ):
    if lines[index].startswith('1.'    ):
      a						: List[Any]					       =					lines[index].replace(
          'https://huggingface.co/docs/transformers/main/model_doc'			,      'https://huggingface.co/docs/transformers/model_doc'			,      )
    index += 1

  with open(_A			,      'w'			,      encoding='utf-8'			,      newline='\n'    ) as f:
    f.writelines(_A    )
def 				lowerCamelCase__	(						):
  with open(REPLACE_FILES['init']			,      'r'    ) as f:
    a						: Union[str, Any]					       =					f.read()
  a						: Tuple					       =					REPLACE_PATTERNS['init'][0].search(_A    ).groups()[0]
  return packaging.version.parse(_A    )
def 				lowerCamelCase__	(						_A=False    ):
  a						: int					       =					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:
    a						: Any					       =					default_version.base_version
  elif patch:
    a						: Dict					       =					f"""{default_version.major}.{default_version.minor}.{default_version.micro + 1}"""
  else:
    a						: Union[str, Any]					       =					f"""{default_version.major}.{default_version.minor + 1}.0"""

  # Now let's ask nicely if that's the right one.
  a						: List[Any]					       =					input(f"""Which version are you releasing? [{default_version}]"""    )
  if len(_A    ) == 0:
    a						: Union[str, Any]					       =					default_version

  print(f"""Updating version to {version}."""    )
  global_version_update(_A			,      patch=_A    )
  if not patch:
    print('Cleaning main README, don\'t forget to run `make fix-copies`.'    )
    clean_main_ref_in_model_list()
def 				lowerCamelCase__	(						):
  a						: int					       =					get_version()
  a						: Any					       =					f"""{current_version.major}.{current_version.minor + 1}.0.dev0"""
  a						: int					       =					current_version.base_version

  # Check with the user we got that right.
  a						: Tuple					       =					input(f"""Which version are we developing now? [{dev_version}]"""    )
  if len(_A    ) == 0:
    a						: Optional[int]					       =					dev_version

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


if __name__ == "__main__":
     lowerCAmelCase: Tuple							=						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.')
     lowerCAmelCase: Optional[Any]							=						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()