Lora interrogator fixes

[A2va]

This fixes some problems in the lora interrogator. However I'm facing an stacktrace error when I run the script, I don't know how to resolve it so I will leave here:

Traceback (most recent call last):
  File "D:\GitHub\sd-scripts\networks\lora_interrogator.py", line 137, in <module>
    interrogate(args)
  File "D:\GitHub\sd-scripts\networks\lora_interrogator.py", line 95, in interrogate
    lora_embs = get_all_embeddings(text_encoder)
  File "D:\GitHub\sd-scripts\networks\lora_interrogator.py", line 76, in get_all_embeddings
    encoder_hidden_states = text_encoder(batch)[0]
  File "D:\compiler\Python\lib\site-packages\torch\nn\modules\module.py", line 1194, in _call_impl
  File "D:\compiler\Python\lib\site-packages\transformers\models\clip\modeling_clip.py", line 816, in forward
    return self.text_model(
  File "D:\compiler\Python\lib\site-packages\torch\nn\modules\module.py", line 1194, in _call_impl
    return forward_call(*input, **kwargs)
  File "D:\compiler\Python\lib\site-packages\transformers\models\clip\modeling_clip.py", line 725, in forward
    encoder_outputs = self.encoder(
  File "D:\compiler\Python\lib\site-packages\torch\nn\modules\module.py", line 1194, in _call_impl
    return forward_call(*input, **kwargs)
  File "D:\compiler\Python\lib\site-packages\transformers\models\clip\modeling_clip.py", line 654, in forward
    layer_outputs = encoder_layer(
  File "D:\compiler\Python\lib\site-packages\torch\nn\modules\module.py", line 1194, in _call_impl
    return forward_call(*input, **kwargs)
  File "D:\compiler\Python\lib\site-packages\transformers\models\clip\modeling_clip.py", line 383, in forward
    hidden_states, attn_weights = self.self_attn(
  File "D:\compiler\Python\lib\site-packages\torch\nn\modules\module.py", line 1194, in _call_impl
    return forward_call(*input, **kwargs)
  File "D:\compiler\Python\lib\site-packages\transformers\models\clip\modeling_clip.py", line 272, in forward
    query_states = self.q_proj(hidden_states) * self.scale
  File "D:\compiler\Python\lib\site-packages\torch\nn\modules\module.py", line 1194, in _call_impl
    return forward_call(*input, **kwargs)
  File "D:\GitHub\sd-scripts\networks\lora.py", line 105, in forward
    return self.org_forward(x) + self.lora_up(self.lora_down(x)) * self.multiplier * self.scale
  File "D:\compiler\Python\lib\site-packages\torch\nn\modules\module.py", line 1194, in _call_impl
    return forward_call(*input, **kwargs)
  File "D:\compiler\Python\lib\site-packages\torch\nn\modules\linear.py", line 114, in forward
    return F.linear(input, self.weight, self.bias)
RuntimeError: expected scalar type Half but found Float

[kohya-ss]

Thank you for this! I didn't tested after the last update of the utils. I will check the error.

[heyalexchoi]

I get an error running these changes. looks like train_util.load_target_model expects a argparse.Namespace with pretrained_model_name_or_path attribute.

File "/home/alexchoi/sd-scripts/./networks/lora_interrogator.py", line 22, in interrogate
    text_encoder, vae, unet, _ = train_util.load_target_model(args, args.sd_model, DEVICE)
  File "/home/alexchoi/anaconda3/envs/sd-scripts/lib/python3.10/site-packages/library/train_util.py", line 2784, in load_target_model
    name_or_path = args.pretrained_model_name_or_path
AttributeError: 'Namespace' object has no attribute 'pretrained_model_name_or_path'

[heyalexchoi]

this fixes issues for me

#423

[A2va]

Your fix in the new PR is already included in mine.

[kohya-ss]

I've merged! I restored --sd_model argument for the backward compatibility, and fixed some additional bugs.

[A2va]

Thanks ! What was the fix with the stacktrace ?

[kohya-ss]

It seems to be required to set dtype explicitly. However, I'm not sure why it work before 😅