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mingyuan-zhang / FineMoGen

[NeurIPS 2023] FineMoGen: Fine-Grained Spatio-Temporal Motion Generation and Editing
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Error loading model checkpoint weights #3

Open connorzl opened 9 months ago

connorzl commented 9 months ago

Hi, after following the setup instructions, I tested the model by running the following command:

PYTHONPATH=".":$PYTHONPATH python tools/visualize.py configs/finemogen/finemogen_t2m.py logs/finemogen/finemogen_t2m/latest.pth --text "a person is running quickly" --motion_length 120 --out "test.gif"

I received the following warnings below:

warnings.warn( load checkpoint from local path: logs/finemogen/finemogen_t2m/latest.pth The model and loaded state dict do not match exactly

missing keys in source state_dict: model.clip.positional_embedding, model.clip.text_projection, model.clip.logit_scale, model.clip.visual.class_embedding, model.clip.visual.positional_embedding, model.clip.visual.proj, model.clip.visual.conv1.weight, model.clip.visual.ln_pre.weight, model.clip.visual.ln_pre.bias, model.clip.visual.transformer.resblocks.0.attn.in_proj_weight, model.clip.visual.transformer.resblocks.0.attn.in_proj_bias, model.clip.visual.transformer.resblocks.0.attn.out_proj.weight, model.clip.visual.transformer.resblocks.0.attn.out_proj.bias, model.clip.visual.transformer.resblocks.0.ln_1.weight, model.clip.visual.transformer.resblocks.0.ln_1.bias, model.clip.visual.transformer.resblocks.0.mlp.c_fc.weight, model.clip.visual.transformer.resblocks.0.mlp.c_fc.bias, model.clip.visual.transformer.resblocks.0.mlp.c_proj.weight, model.clip.visual.transformer.resblocks.0.mlp.c_proj.bias, model.clip.visual.transformer.resblocks.0.ln_2.weight, model.clip.visual.transformer.resblocks.0.ln_2.bias, model.clip.visual.transformer.resblocks.1.attn.in_proj_weight, model.clip.visual.transformer.resblocks.1.attn.in_proj_bias, model.clip.visual.transformer.resblocks.1.attn.out_proj.weight, model.clip.visual.transformer.resblocks.1.attn.out_proj.bias, model.clip.visual.transformer.resblocks.1.ln_1.weight, model.clip.visual.transformer.resblocks.1.ln_1.bias, model.clip.visual.transformer.resblocks.1.mlp.c_fc.weight, model.clip.visual.transformer.resblocks.1.mlp.c_fc.bias, model.clip.visual.transformer.resblocks.1.mlp.c_proj.weight, model.clip.visual.transformer.resblocks.1.mlp.c_proj.bias, model.clip.visual.transformer.resblocks.1.ln_2.weight, model.clip.visual.transformer.resblocks.1.ln_2.bias, model.clip.visual.transformer.resblocks.2.attn.in_proj_weight, model.clip.visual.transformer.resblocks.2.attn.in_proj_bias, model.clip.visual.transformer.resblocks.2.attn.out_proj.weight, model.clip.visual.transformer.resblocks.2.attn.out_proj.bias, model.clip.visual.transformer.resblocks.2.ln_1.weight, model.clip.visual.transformer.resblocks.2.ln_1.bias, model.clip.visual.transformer.resblocks.2.mlp.c_fc.weight, model.clip.visual.transformer.resblocks.2.mlp.c_fc.bias, model.clip.visual.transformer.resblocks.2.mlp.c_proj.weight, model.clip.visual.transformer.resblocks.2.mlp.c_proj.bias, model.clip.visual.transformer.resblocks.2.ln_2.weight, model.clip.visual.transformer.resblocks.2.ln_2.bias, model.clip.visual.transformer.resblocks.3.attn.in_proj_weight, model.clip.visual.transformer.resblocks.3.attn.in_proj_bias, model.clip.visual.transformer.resblocks.3.attn.out_proj.weight, model.clip.visual.transformer.resblocks.3.attn.out_proj.bias, model.clip.visual.transformer.resblocks.3.ln_1.weight, model.clip.visual.transformer.resblocks.3.ln_1.bias, model.clip.visual.transformer.resblocks.3.mlp.c_fc.weight, model.clip.visual.transformer.resblocks.3.mlp.c_fc.bias, 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model.clip.transformer.resblocks.6.attn.out_proj.bias, model.clip.transformer.resblocks.6.ln_1.weight, model.clip.transformer.resblocks.6.ln_1.bias, model.clip.transformer.resblocks.6.mlp.c_fc.weight, model.clip.transformer.resblocks.6.mlp.c_fc.bias, model.clip.transformer.resblocks.6.mlp.c_proj.weight, model.clip.transformer.resblocks.6.mlp.c_proj.bias, model.clip.transformer.resblocks.6.ln_2.weight, model.clip.transformer.resblocks.6.ln_2.bias, model.clip.transformer.resblocks.7.attn.in_proj_weight, model.clip.transformer.resblocks.7.attn.in_proj_bias, model.clip.transformer.resblocks.7.attn.out_proj.weight, model.clip.transformer.resblocks.7.attn.out_proj.bias, model.clip.transformer.resblocks.7.ln_1.weight, model.clip.transformer.resblocks.7.ln_1.bias, model.clip.transformer.resblocks.7.mlp.c_fc.weight, model.clip.transformer.resblocks.7.mlp.c_fc.bias, model.clip.transformer.resblocks.7.mlp.c_proj.weight, model.clip.transformer.resblocks.7.mlp.c_proj.bias, model.clip.transformer.resblocks.7.ln_2.weight, model.clip.transformer.resblocks.7.ln_2.bias, model.clip.transformer.resblocks.8.attn.in_proj_weight, model.clip.transformer.resblocks.8.attn.in_proj_bias, model.clip.transformer.resblocks.8.attn.out_proj.weight, model.clip.transformer.resblocks.8.attn.out_proj.bias, model.clip.transformer.resblocks.8.ln_1.weight, model.clip.transformer.resblocks.8.ln_1.bias, model.clip.transformer.resblocks.8.mlp.c_fc.weight, model.clip.transformer.resblocks.8.mlp.c_fc.bias, model.clip.transformer.resblocks.8.mlp.c_proj.weight, model.clip.transformer.resblocks.8.mlp.c_proj.bias, model.clip.transformer.resblocks.8.ln_2.weight, model.clip.transformer.resblocks.8.ln_2.bias, model.clip.transformer.resblocks.9.attn.in_proj_weight, model.clip.transformer.resblocks.9.attn.in_proj_bias, model.clip.transformer.resblocks.9.attn.out_proj.weight, model.clip.transformer.resblocks.9.attn.out_proj.bias, model.clip.transformer.resblocks.9.ln_1.weight, model.clip.transformer.resblocks.9.ln_1.bias, model.clip.transformer.resblocks.9.mlp.c_fc.weight, model.clip.transformer.resblocks.9.mlp.c_fc.bias, model.clip.transformer.resblocks.9.mlp.c_proj.weight, model.clip.transformer.resblocks.9.mlp.c_proj.bias, model.clip.transformer.resblocks.9.ln_2.weight, model.clip.transformer.resblocks.9.ln_2.bias, model.clip.transformer.resblocks.10.attn.in_proj_weight, model.clip.transformer.resblocks.10.attn.in_proj_bias, model.clip.transformer.resblocks.10.attn.out_proj.weight, model.clip.transformer.resblocks.10.attn.out_proj.bias, model.clip.transformer.resblocks.10.ln_1.weight, model.clip.transformer.resblocks.10.ln_1.bias, model.clip.transformer.resblocks.10.mlp.c_fc.weight, model.clip.transformer.resblocks.10.mlp.c_fc.bias, model.clip.transformer.resblocks.10.mlp.c_proj.weight, model.clip.transformer.resblocks.10.mlp.c_proj.bias, model.clip.transformer.resblocks.10.ln_2.weight, model.clip.transformer.resblocks.10.ln_2.bias, model.clip.transformer.resblocks.11.attn.in_proj_weight, model.clip.transformer.resblocks.11.attn.in_proj_bias, model.clip.transformer.resblocks.11.attn.out_proj.weight, model.clip.transformer.resblocks.11.attn.out_proj.bias, model.clip.transformer.resblocks.11.ln_1.weight, model.clip.transformer.resblocks.11.ln_1.bias, model.clip.transformer.resblocks.11.mlp.c_fc.weight, model.clip.transformer.resblocks.11.mlp.c_fc.bias, model.clip.transformer.resblocks.11.mlp.c_proj.weight, model.clip.transformer.resblocks.11.mlp.c_proj.bias, model.clip.transformer.resblocks.11.ln_2.weight, model.clip.transformer.resblocks.11.ln_2.bias, model.clip.token_embedding.weight, model.clip.ln_final.weight, model.clip.ln_final.bias

I also had to comment out the following lines to get the command to run, otherwise I would get plotting errors.

However, the output seems to be a blank gif with a text caption. test

Sarah816 commented 7 months ago

Hi @connorzl ! I faced the same problem when testing the model. Have you solved the problem? Many thanks.

mingyuan-zhang commented 6 months ago

Hi, after following the setup instructions, I tested the model by running the following command:

PYTHONPATH=".":$PYTHONPATH python tools/visualize.py configs/finemogen/finemogen_t2m.py logs/finemogen/finemogen_t2m/latest.pth --text "a person is running quickly" --motion_length 120 --out "test.gif"

I received the following warnings below:

warnings.warn( load checkpoint from local path: logs/finemogen/finemogen_t2m/latest.pth The model and loaded state dict do not match exactly

missing keys in source state_dict: model.clip.positional_embedding, model.clip.text_projection, model.clip.logit_scale, model.clip.visual.class_embedding, model.clip.visual.positional_embedding, model.clip.visual.proj, model.clip.visual.conv1.weight, model.clip.visual.ln_pre.weight, model.clip.visual.ln_pre.bias, model.clip.visual.transformer.resblocks.0.attn.in_proj_weight, model.clip.visual.transformer.resblocks.0.attn.in_proj_bias, model.clip.visual.transformer.resblocks.0.attn.out_proj.weight, model.clip.visual.transformer.resblocks.0.attn.out_proj.bias, model.clip.visual.transformer.resblocks.0.ln_1.weight, model.clip.visual.transformer.resblocks.0.ln_1.bias, model.clip.visual.transformer.resblocks.0.mlp.c_fc.weight, model.clip.visual.transformer.resblocks.0.mlp.c_fc.bias, model.clip.visual.transformer.resblocks.0.mlp.c_proj.weight, model.clip.visual.transformer.resblocks.0.mlp.c_proj.bias, model.clip.visual.transformer.resblocks.0.ln_2.weight, model.clip.visual.transformer.resblocks.0.ln_2.bias, model.clip.visual.transformer.resblocks.1.attn.in_proj_weight, model.clip.visual.transformer.resblocks.1.attn.in_proj_bias, model.clip.visual.transformer.resblocks.1.attn.out_proj.weight, model.clip.visual.transformer.resblocks.1.attn.out_proj.bias, model.clip.visual.transformer.resblocks.1.ln_1.weight, model.clip.visual.transformer.resblocks.1.ln_1.bias, model.clip.visual.transformer.resblocks.1.mlp.c_fc.weight, model.clip.visual.transformer.resblocks.1.mlp.c_fc.bias, model.clip.visual.transformer.resblocks.1.mlp.c_proj.weight, model.clip.visual.transformer.resblocks.1.mlp.c_proj.bias, model.clip.visual.transformer.resblocks.1.ln_2.weight, model.clip.visual.transformer.resblocks.1.ln_2.bias, model.clip.visual.transformer.resblocks.2.attn.in_proj_weight, model.clip.visual.transformer.resblocks.2.attn.in_proj_bias, model.clip.visual.transformer.resblocks.2.attn.out_proj.weight, 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I also had to comment out the following lines to get the command to run, otherwise I would get plotting errors.

However, the output seems to be a blank gif with a text caption. test test

You can ignore this warning. In the current implementation, we don't store the frozen CLIP weights during training to reduce the size of checkpoint file. Therefore, during loading state_dict, pytorch can not find the corresponding weights. Instead, we will load this part of weights during initialization.

May I know your detailed log of the plotting error? It seems that you can not remove these two lines.

mingyuan-zhang commented 6 months ago

Hi @connorzl ! I faced the same problem when testing the model. Have you solved the problem? Many thanks.

You can ignore this warning. In the current implementation, we don't store the frozen CLIP weights during training to reduce the size of checkpoint file. Therefore, during loading state_dict, pytorch can not find the corresponding weights. Instead, we will load this part of weights during initialization.

Run542968 commented 5 months ago

Hi @connorzl ! I faced the same problem when testing the model. Have you solved the problem? Many thanks.

Hi, this issue come from the version of matplotlib, you can 'pip install matplotlib==3.4.3'. I have solved by this way.