AttributeError: 'Sequential' object has no attribute 'model'

[SnowWindSaveYou]

Hi, use the models download from link in notebook is fine, but when i try to use the model trained from pytorch-CycleGAN-and-pix2pix, it will shows this error:

Traceback (most recent call last):
  File "test.py", line 56, in <module>
    netG = load_model('./models/facades_label2photo/test_G.pth')

  File "test.py", line 47, in load_model
    __patch_instance_norm_state_dict(state_dict, net_g, key.split('.') )

  File "test.py", line 36, in __patch_instance_norm_state_dict
    __patch_instance_norm_state_dict(state_dict, getattr(module, key), keys, i + 1)

  File "test.py", line 36, in __patch_instance_norm_state_dict
    __patch_instance_norm_state_dict(state_dict, getattr(module, key), keys, i + 1)

  File "/Users/.../miniconda3/lib/python3.6/site-packages/torch/nn/modules/module.py", line 532, in __getattr__

type(self).__name__, name))
AttributeError: 'Sequential' object has no attribute 'model' 

After debug, i see the keys of them is different

Models download from link in jupyter have very clear structure like['model','1','something']
But in the model of my-self is a lot of like ['model','model','1','model','3','something']

Compare:

Keys must have

 Missing key(s) in state_dict: "model.1.weight", "model.1.bias", "model.2.running_mean", 
"model.2.running_var", "model.4.weight", "model.4.bias", "model.5.running_mean", 
"model.5.running_var", "model.7.weight", "model.7.bias", "model.8.running_mean", 
"model.8.running_var", "model.10.conv_block.1.weight", "model.10.conv_block.1.bias", 
"model.10.conv_block.2.running_mean", "model.10.conv_block.2.running_var", 
"model.10.conv_block.5.weight", "model.10.conv_block.5.bias", "model.10.conv_block.6.running_mean", "model.10.conv_block.6.running_var", "model.11.conv_block.1.weight", "model.11.conv_block.1.bias", "model.11.conv_block.2.running_mean", "model.11.conv_block.2.running_var", "model.11.conv_block.5.weight", "model.11.conv_block.5.bias", "model.11.conv_block.6.running_mean", "model.11.conv_block.6.running_var", "model.12.conv_block.1.weight", "model.12.conv_block.1.bias", "model.12.conv_block.2.running_mean", "model.12.conv_block.2.running_var", "model.12.conv_block.5.weight", "model.12.conv_block.5.bias", "model.12.conv_block.6.running_mean", "model.12.conv_block.6.running_var", "model.13.conv_block.1.weight", "model.13.conv_block.1.bias", "model.13.conv_block.2.running_mean", "model.13.conv_block.2.running_var", "model.13.conv_block.5.weight", "model.13.conv_block.5.bias", "model.13.conv_block.6.running_mean", "model.13.conv_block.6.running_var", "model.14.conv_block.1.weight", "model.14.conv_block.1.bias", "model.14.conv_block.2.running_mean", "model.14.conv_block.2.running_var", "model.14.conv_block.5.weight", "model.14.conv_block.5.bias", "model.14.conv_block.6.running_mean", "model.14.conv_block.6.running_var", "model.15.conv_block.1.weight", "model.15.conv_block.1.bias", "model.15.conv_block.2.running_mean", "model.15.conv_block.2.running_var", "model.15.conv_block.5.weight", "model.15.conv_block.5.bias", "model.15.conv_block.6.running_mean", "model.15.conv_block.6.running_var", "model.16.conv_block.1.weight", "model.16.conv_block.1.bias", "model.16.conv_block.2.running_mean", "model.16.conv_block.2.running_var", "model.16.conv_block.5.weight", "model.16.conv_block.5.bias", "model.16.conv_block.6.running_mean", "model.16.conv_block.6.running_var", "model.17.conv_block.1.weight", "model.17.conv_block.1.bias", 
"model.17.conv_block.2.running_mean", "model.17.conv_block.2.running_var", 
"model.17.conv_block.5.weight", "model.17.conv_block.5.bias", "model.17.conv_block.6.running_mean", 
"model.17.conv_block.6.running_var", "model.18.conv_block.1.weight", "model.18.conv_block.1.bias", 
"model.18.conv_block.2.running_mean", "model.18.conv_block.2.running_var", 
"model.18.conv_block.5.weight", "model.18.conv_block.5.bias", "model.18.conv_block.6.running_mean",
 "model.18.conv_block.6.running_var", "model.19.weight", "model.19.bias", "model.20.running_mean", 
"model.20.running_var", "model.22.weight", "model.22.bias", "model.23.running_mean", 
"model.23.running_var", "model.26.weight", "model.26.bias".

My one

Unexpected key(s) in state_dict: "model.model.0.weight", "model.model.1.model.1.weight", 
"model.model.1.model.2.weight", "model.model.1.model.2.bias", 
"model.model.1.model.2.running_mean", "model.model.1.model.2.running_var", 
"model.model.1.model.3.model.1.weight", "model.model.1.model.3.model.2.weight",
 "model.model.1.model.3.model.2.bias", "model.model.1.model.3.model.2.running_mean", 
"model.model.1.model.3.model.2.running_var", "model.model.1.model.3.model.3.model.1.weight", 
"model.model.1.model.3.model.3.model.2.weight", "model.model.1.model.3.model.3.model.2.bias", 
"model.model.1.model.3.model.3.model.2.running_mean", 
"model.model.1.model.3.model.3.model.2.running_var", 
"model.model.1.model.3.model.3.model.3.model.1.weight", 
"model.model.1.model.3.model.3.model.3.model.2.weight", 
"model.model.1.model.3.model.3.model.3.model.2.bias", 
"model.model.1.model.3.model.3.model.3.model.2.running_mean", "model.model.1.model.3.model.3.model.3.model.2.running_var", "model.model.1.model.3.model.3.model.3.model.3.model.1.weight", "model.model.1.model.3.model.3.model.3.model.3.model.2.weight", "model.model.1.model.3.model.3.model.3.model.3.model.2.bias", "model.model.1.model.3.model.3.model.3.model.3.model.2.running_mean", "model.model.1.model.3.model.3.model.3.model.3.model.2.running_var", "model.model.1.model.3.model.3.model.3.model.3.model.3.model.1.weight", "model.model.1.model.3.model.3.model.3.model.3.model.3.model.2.weight", "model.model.1.model.3.model.3.model.3.model.3.model.3.model.2.bias", "model.model.1.model.3.model.3.model.3.model.3.model.3.model.2.running_mean", "model.model.1.model.3.model.3.model.3.model.3.model.3.model.2.running_var", "model.model.1.model.3.model.3.model.3.model.3.model.3.model.3.model.1.weight", "model.model.1.model.3.model.3.model.3.model.3.model.3.model.3.model.3.weight", "model.model.1.model.3.model.3.model.3.model.3.model.3.model.3.model.4.weight", "model.model.1.model.3.model.3.model.3.model.3.model.3.model.3.model.4.bias", "model.model.1.model.3.model.3.model.3.model.3.model.3.model.3.model.4.running_mean", "model.model.1.model.3.model.3.model.3.model.3.model.3.model.3.model.4.running_var", "model.model.1.model.3.model.3.model.3.model.3.model.3.model.3.model.4.num_batches_tracked", "model.model.1.model.3.model.3.model.3.model.3.model.3.model.5.weight", "model.model.1.model.3.model.3.model.3.model.3.model.3.model.6.weight", "model.model.1.model.3.model.3.model.3.model.3.model.3.model.6.bias", "model.model.1.model.3.model.3.model.3.model.3.model.3.model.6.running_mean", "model.model.1.model.3.model.3.model.3.model.3.model.3.model.6.running_var", "model.model.1.model.3.model.3.model.3.model.3.model.3.model.6.num_batches_tracked", "model.model.1.model.3.model.3.model.3.model.3.model.5.weight", "model.model.1.model.3.model.3.model.3.model.3.model.6.weight", "model.model.1.model.3.model.3.model.3.model.3.model.6.bias", "model.model.1.model.3.model.3.model.3.model.3.model.6.running_mean", "model.model.1.model.3.model.3.model.3.model.3.model.6.running_var", "model.model.1.model.3.model.3.model.3.model.3.model.6.num_batches_tracked", "model.model.1.model.3.model.3.model.3.model.5.weight", "model.model.1.model.3.model.3.model.3.model.6.weight", "model.model.1.model.3.model.3.model.3.model.6.bias", "model.model.1.model.3.model.3.model.3.model.6.running_mean", "model.model.1.model.3.model.3.model.3.model.6.running_var", "model.model.1.model.3.model.3.model.3.model.6.num_batches_tracked", "model.model.1.model.3.model.3.model.5.weight", "model.model.1.model.3.model.3.model.6.weight", "model.model.1.model.3.model.3.model.6.bias", "model.model.1.model.3.model.3.model.6.running_mean", "model.model.1.model.3.model.3.model.6.running_var", "model.model.1.model.3.model.3.model.6.num_batches_tracked", 
"model.model.1.model.3.model.5.weight", "model.model.1.model.3.model.6.weight", 
"model.model.1.model.3.model.6.bias", "model.model.1.model.3.model.6.running_mean", 
"model.model.1.model.3.model.6.running_var", 
"model.model.1.model.3.model.6.num_batches_tracked", "model.model.1.model.5.weight", 
"model.model.1.model.6.weight", "model.model.1.model.6.bias", 
"model.model.1.model.6.running_mean", "model.model.1.model.6.running_var", 
"model.model.1.model.6.num_batches_tracked", "model.model.3.weight", "model.model.3.bias".

[SnowWindSaveYou]

Found problem...
because my one is actually pix2pix model

Because i can run the model download from link, and they have same name, i suddenly not discover this difference (:з」∠)

[junjy007]

:) Will have more models available soon. Jun

…

On 3 Sep 2018, at 2:53 pm, SnowWind ***@***.***> wrote: Found problem... because my one is actually pix2pix model Because i can run the model download from link, and they have same name, i suddenly not discover this difference (:з」∠) — You are receiving this because you are subscribed to this thread. Reply to this email directly, view it on GitHub <#1 (comment)>, or mute the thread <https://github.com/notifications/unsubscribe-auth/AIAJOBAYT3u-FmNsyy7g7Qhmxz0P1MgQks5uXNHpgaJpZM4WW597>.