SKDDJ
commented
8 months ago Hi. I'm getting this very long warning message when I run
edit_cli.py. I'm running this on a Google Compute Engine VM with an Nvidia T4 16 GB:
python edit_cli.py --resolution 384 --input ../examples/image-1.jpg --output ../examples/blue.jpg --edit "dye her hair blue"Loading model from checkpoints/instruct-pix2pix-00-22000.ckpt Global Step: 22000 LatentDiffusion: Running in eps-prediction mode DiffusionWrapper has 859.53 M params. Keeping EMAs of 688. making attention of type 'vanilla' with 512 in_channels Working with z of shape (1, 4, 32, 32) = 4096 dimensions. making attention of type 'vanilla' with 512 in_channels Some weights of the model checkpoint at openai/clip-vit-large-patch14 were not used when initializing CLIPTextModel: ['vision_model.encoder.layers.14.self_attn.v_proj.bias', 'vision_model.encoder.layers.20.self_attn.q_proj.bias', 'vision_model.encoder.layers.4.self_attn.v_proj.bias', 'vision_model.encoder.layers.19.layer_norm2.weight', 'vision_model.encoder.layers.14.self_attn.k_proj.weight', 'vision_model.encoder.layers.18.layer_norm2.weight', 'vision_model.encoder.layers.19.layer_norm1.bias', 'vision_model.encoder.layers.17.layer_norm1.bias', 'vision_model.encoder.layers.1.self_attn.k_proj.weight', 'vision_model.encoder.layers.23.self_attn.out_proj.weight', 'vision_model.encoder.layers.1.layer_norm2.bias', 'vision_model.encoder.layers.15.self_attn.q_proj.weight', 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'vision_model.encoder.layers.11.self_attn.v_proj.weight', 'vision_model.encoder.layers.3.self_attn.v_proj.weight', 'vision_model.encoder.layers.2.mlp.fc2.bias', 'vision_model.encoder.layers.8.layer_norm1.weight', 'vision_model.encoder.layers.9.mlp.fc2.weight', 'vision_model.encoder.layers.7.mlp.fc1.bias', 'vision_model.encoder.layers.5.layer_norm2.bias', 'vision_model.encoder.layers.0.layer_norm2.bias', 'vision_model.encoder.layers.9.layer_norm2.bias', 'vision_model.encoder.layers.1.mlp.fc2.weight', 'vision_model.encoder.layers.22.self_attn.out_proj.bias', 'vision_model.encoder.layers.16.layer_norm1.weight', 'vision_model.encoder.layers.10.layer_norm1.weight', 'vision_model.encoder.layers.15.self_attn.k_proj.weight', 'vision_model.encoder.layers.15.layer_norm2.weight'] - This IS expected if you are initializing CLIPTextModel from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model). - This IS NOT expected if you are initializing CLIPTextModel from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).I'm getting a decent output and I've seen other people complain about this warning as well so I'm assuming it's somewhat expected. But I still wonder:
- What exactly does this mean in simple terms?
- More importantly, does this have any implications on quality of the resulting image?
Thanks.
I think it caused by the CLIP model consists of two components: a text encoder and an image encoder. However, in your implementation, you are only using the CLIP text encoder to convert the text into embeddings. As a result, you may encounter warnings indicating that some parts of CLIP are not being utilized, specifically the image encoder.
This will not affect the final result.
umutyazgan
Hi. I'm getting this very long warning message when I run
edit_cli.py. I'm running this on a Google Compute Engine VM with an Nvidia T4 16 GB:python edit_cli.py --resolution 384 --input ../examples/image-1.jpg --output ../examples/blue.jpg --edit "dye her hair blue"I'm getting a decent output and I've seen other people complain about this warning as well so I'm assuming it's somewhat expected. But I still wonder:
Thanks.