




"""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 		_snake_case	(   _snake_case				:   int				)       ->   Any:






      '''simple docstring'''


      if hor == 1_28:
            _A     =  ('DownResnetBlock1D', 'DownResnetBlock1D', 'DownResnetBlock1D')
            _A     =  (32, 1_28, 2_56)
            _A     =  ('UpResnetBlock1D', 'UpResnetBlock1D')

      elif hor == 32:
            _A     =  ('DownResnetBlock1D', 'DownResnetBlock1D', 'DownResnetBlock1D', 'DownResnetBlock1D')
            _A     =  (32, 64, 1_28, 2_56)
            _A     =  ('UpResnetBlock1D', 'UpResnetBlock1D', 'UpResnetBlock1D')
      _A     =  torch.load(F'''/Users/bglickenhaus/Documents/diffuser/temporal_unet-hopper-mediumv2-hor{hor}.torch'''				)
      _A     =  model.state_dict()
      _A     =  {
          '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_55_36,
          'mid_block_type': 'MidResTemporalBlock1D',
          'act_fn': 'mish',
      }
      _A     =  UNetaDModel(**_snake_case				)
      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     =  dict(zip(model.state_dict().keys()							,    hf_value_function.state_dict().keys()				)				)
      for k, v in mapping.items():
            _A     =  state_dict.pop(_snake_case				)
      hf_value_function.load_state_dict(_snake_case				)

      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(_snake_case							,    _snake_case				)






def 		_snake_case	(   )       ->   List[str]:






      '''simple docstring'''


      _A     =  {
          '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, 1_28, 2_56),
          'layers_per_block': 1,
          'downsample_each_block': True,
          'sample_size': 6_55_36,
          '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     =  torch.load('/Users/bglickenhaus/Documents/diffuser/value_function-hopper-mediumv2-hor32.torch'				)
      _A     =  model
      _A     =  UNetaDModel(**_snake_case				)
      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     =  dict(zip(state_dict.keys()							,    hf_value_function.state_dict().keys()				)				)
      for k, v in mapping.items():
            _A     =  state_dict.pop(_snake_case				)

      hf_value_function.load_state_dict(_snake_case				)

      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(_snake_case							,    _snake_case				)


if __name__ == "__main__":
       unet(32)
       # unet(128)
       value_function()







"""simple docstring"""

import argparse


a							      =     '''docs/source/_static/js/custom.js'''






def 		_snake_case	(   _snake_case				:   Dict				)       ->   Any:






      '''simple docstring'''


      with open(_snake_case							,    encoding='utf-8'							,    newline='\n'				) as f:
            _A     =  f.readlines()
      _A     =  0

      # First let's put the right version
      while not lines[index].startswith('const stableVersion ='				):
            index += 1
      _A     =  F'''const stableVersion = "v{version}"\n'''

      # Then update the dictionary
      while not lines[index].startswith('const versionMapping = {'				):
            index += 1

      # We go until the end
      while not lines[index].startswith('}'				):
            index += 1
      # We add the new version at the end
      lines[index - 1] += F'''    "v{version}": "v{version}",\n'''

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


if __name__ == "__main__":
       a							      =     argparse.ArgumentParser()
       parser.add_argument('''--version''', help='''Release version.''')
       a							      =     parser.parse_args()
       update_custom_js(args.version)

