DALLE2-pytorch
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Inference with a pretrained model
Hiya, is there a simple inference script that uses a specific checkpoint to load a fully trained model and generate images?
It is not clear how to use this repo without finetuning the model.
^^
I am trying to write simple scripts with DiffusionPriorNetwork
and DiffusionPrior
class, and load the pretrained model from huggingface.
I do the code below as the params in conditioned-prior / vit-l-14 / aesthetic / prior_config.json
:
clip = OpenAIClipAdapter("ViT-L/14")
prior_network = DiffusionPriorNetwork(
dim = 768,
depth = 12,
dim_head = 64,
heads = 12
)
diffusion_prior = DiffusionPrior(
net = prior_network,
clip = clip,
timesteps = 1000,
cond_drop_prob = 0.1
)
when loading the checkpoints with diffusion_prior.load_state_dict(torch.load(prior_path, map_location='cpu'))
I got the error below:
RuntimeError: Error(s) in loading state_dict for DiffusionPrior:
Missing key(s) in state_dict: "net.to_time_embeds.0.1.net.0.0.weight", "net.to_time_embeds.0.1.net.0.0.bias", "net.to_time_embeds.0.1.net.1.0.weight", "net.to_time_embeds.0.1.net.1.0.bias", "net.to_time_embeds.0.1.net.2.weight", "net.to_time_embeds.0.1.net.2.bias", "net.causal_transformer.layers.0.0.norm.gamma", "net.causal_transformer.layers.0.0.norm.beta", "net.causal_transformer.layers.0.0.to_out.1.gamma", "net.causal_transformer.layers.0.0.to_out.1.beta", "net.causal_transformer.layers.0.1.0.gamma", "net.causal_transformer.layers.0.1.0.beta", "net.causal_transformer.layers.1.0.norm.gamma", "net.causal_transformer.layers.1.0.norm.beta", "net.causal_transformer.layers.1.0.to_out.1.gamma", "net.causal_transformer.layers.1.0.to_out.1.beta", "net.causal_transformer.layers.1.1.0.gamma", "net.causal_transformer.layers.1.1.0.beta", "net.causal_transformer.layers.2.0.norm.gamma", "net.causal_transformer.layers.2.0.norm.beta", "net.causal_transformer.layers.2.0.to_out.1.gamma", "net.causal_transformer.layers.2.0.to_out.1.beta", "net.causal_transformer.layers.2.1.0.gamma", "net.causal_transformer.layers.2.1.0.beta", "net.causal_transformer.layers.3.0.norm.gamma", "net.causal_transformer.layers.3.0.norm.beta", "net.causal_transformer.layers.3.0.to_out.1.gamma", "net.causal_transformer.layers.3.0.to_out.1.beta", "net.causal_transformer.layers.3.1.0.gamma", "net.causal_transformer.layers.3.1.0.beta", "net.causal_transformer.layers.4.0.norm.gamma", "net.causal_transformer.layers.4.0.norm.beta", "net.causal_transformer.layers.4.0.to_out.1.gamma", "net.causal_transformer.layers.4.0.to_out.1.beta", "net.causal_transformer.layers.4.1.0.gamma", "net.causal_transformer.layers.4.1.0.beta", "net.causal_transformer.layers.5.0.norm.gamma", "net.causal_transformer.layers.5.0.norm.beta", "net.causal_transformer.layers.5.0.to_out.1.gamma", "net.causal_transformer.layers.5.0.to_out.1.beta", "net.causal_transformer.layers.5.1.0.gamma", "net.causal_transformer.layers.5.1.0.beta", "net.causal_transformer.layers.6.0.norm.gamma", "net.causal_transformer.layers.6.0.norm.beta", "net.causal_transformer.layers.6.0.to_out.1.gamma", "net.causal_transformer.layers.6.0.to_out.1.beta", "net.causal_transformer.layers.6.1.0.gamma", "net.causal_transformer.layers.6.1.0.beta", "net.causal_transformer.layers.7.0.norm.gamma", "net.causal_transformer.layers.7.0.norm.beta", "net.causal_transformer.layers.7.0.to_out.1.gamma", "net.causal_transformer.layers.7.0.to_out.1.beta", "net.causal_transformer.layers.7.1.0.gamma", "net.causal_transformer.layers.7.1.0.beta", "net.causal_transformer.layers.8.0.norm.gamma", "net.causal_transformer.layers.8.0.norm.beta", "net.causal_transformer.layers.8.0.to_out.1.gamma", "net.causal_transformer.layers.8.0.to_out.1.beta", "net.causal_transformer.layers.8.1.0.gamma", "net.causal_transformer.layers.8.1.0.beta", "net.causal_transformer.layers.9.0.norm.gamma", "net.causal_transformer.layers.9.0.norm.beta", "net.causal_transformer.layers.9.0.to_out.1.gamma", "net.causal_transformer.layers.9.0.to_out.1.beta", "net.causal_transformer.layers.9.1.0.gamma", "net.causal_transformer.layers.9.1.0.beta", "net.causal_transformer.layers.10.0.norm.gamma", "net.causal_transformer.layers.10.0.norm.beta", "net.causal_transformer.layers.10.0.to_out.1.gamma", "net.causal_transformer.layers.10.0.to_out.1.beta", "net.causal_transformer.layers.10.1.0.gamma", "net.causal_transformer.layers.10.1.0.beta", "net.causal_transformer.layers.11.0.norm.gamma", "net.causal_transformer.layers.11.0.norm.beta", "net.causal_transformer.layers.11.0.to_out.1.gamma", "net.causal_transformer.layers.11.0.to_out.1.beta", "net.causal_transformer.layers.11.1.0.gamma", "net.causal_transformer.layers.11.1.0.beta", "net.causal_transformer.norm.gamma", "net.causal_transformer.norm.beta".
Unexpected key(s) in state_dict: "net.to_time_embeds.0.weight", "net.causal_transformer.layers.0.0.norm.g", "net.causal_transformer.layers.0.0.to_out.1.g", "net.causal_transformer.layers.0.1.0.g", "net.causal_transformer.layers.0.1.3.g", "net.causal_transformer.layers.1.0.norm.g", "net.causal_transformer.layers.1.0.to_out.1.g", "net.causal_transformer.layers.1.1.0.g", "net.causal_transformer.layers.1.1.3.g", "net.causal_transformer.layers.2.0.norm.g", "net.causal_transformer.layers.2.0.to_out.1.g", "net.causal_transformer.layers.2.1.0.g", "net.causal_transformer.layers.2.1.3.g", "net.causal_transformer.layers.3.0.norm.g", "net.causal_transformer.layers.3.0.to_out.1.g", "net.causal_transformer.layers.3.1.0.g", "net.causal_transformer.layers.3.1.3.g", "net.causal_transformer.layers.4.0.norm.g", "net.causal_transformer.layers.4.0.to_out.1.g", "net.causal_transformer.layers.4.1.0.g", "net.causal_transformer.layers.4.1.3.g", "net.causal_transformer.layers.5.0.norm.g", "net.causal_transformer.layers.5.0.to_out.1.g", "net.causal_transformer.layers.5.1.0.g", "net.causal_transformer.layers.5.1.3.g", "net.causal_transformer.layers.6.0.norm.g", "net.causal_transformer.layers.6.0.to_out.1.g", "net.causal_transformer.layers.6.1.0.g", "net.causal_transformer.layers.6.1.3.g", "net.causal_transformer.layers.7.0.norm.g", "net.causal_transformer.layers.7.0.to_out.1.g", "net.causal_transformer.layers.7.1.0.g", "net.causal_transformer.layers.7.1.3.g", "net.causal_transformer.layers.8.0.norm.g", "net.causal_transformer.layers.8.0.to_out.1.g", "net.causal_transformer.layers.8.1.0.g", "net.causal_transformer.layers.8.1.3.g", "net.causal_transformer.layers.9.0.norm.g", "net.causal_transformer.layers.9.0.to_out.1.g", "net.causal_transformer.layers.9.1.0.g", "net.causal_transformer.layers.9.1.3.g", "net.causal_transformer.layers.10.0.norm.g", "net.causal_transformer.layers.10.0.to_out.1.g", "net.causal_transformer.layers.10.1.0.g", "net.causal_transformer.layers.10.1.3.g", "net.causal_transformer.layers.11.0.norm.g", "net.causal_transformer.layers.11.0.to_out.1.g", "net.causal_transformer.layers.11.1.0.g", "net.causal_transformer.layers.11.1.3.g", "net.causal_transformer.norm.g".
does anyone have some idea?
I am trying to write simple scripts with
DiffusionPriorNetwork
andDiffusionPrior
class, and load the pretrained model from huggingface.I do the code below as the params in
conditioned-prior / vit-l-14 / aesthetic / prior_config.json
:clip = OpenAIClipAdapter("ViT-L/14") prior_network = DiffusionPriorNetwork( dim = 768, depth = 12, dim_head = 64, heads = 12 ) diffusion_prior = DiffusionPrior( net = prior_network, clip = clip, timesteps = 1000, cond_drop_prob = 0.1 )
when loading the checkpoints with
diffusion_prior.load_state_dict(torch.load(prior_path, map_location='cpu'))
I got the error below:
RuntimeError: Error(s) in loading state_dict for DiffusionPrior: Missing key(s) in state_dict: "net.to_time_embeds.0.1.net.0.0.weight", "net.to_time_embeds.0.1.net.0.0.bias", "net.to_time_embeds.0.1.net.1.0.weight", "net.to_time_embeds.0.1.net.1.0.bias", "net.to_time_embeds.0.1.net.2.weight", "net.to_time_embeds.0.1.net.2.bias", "net.causal_transformer.layers.0.0.norm.gamma", "net.causal_transformer.layers.0.0.norm.beta", "net.causal_transformer.layers.0.0.to_out.1.gamma", "net.causal_transformer.layers.0.0.to_out.1.beta", "net.causal_transformer.layers.0.1.0.gamma", "net.causal_transformer.layers.0.1.0.beta", "net.causal_transformer.layers.1.0.norm.gamma", "net.causal_transformer.layers.1.0.norm.beta", "net.causal_transformer.layers.1.0.to_out.1.gamma", "net.causal_transformer.layers.1.0.to_out.1.beta", "net.causal_transformer.layers.1.1.0.gamma", "net.causal_transformer.layers.1.1.0.beta", "net.causal_transformer.layers.2.0.norm.gamma", "net.causal_transformer.layers.2.0.norm.beta", "net.causal_transformer.layers.2.0.to_out.1.gamma", "net.causal_transformer.layers.2.0.to_out.1.beta", "net.causal_transformer.layers.2.1.0.gamma", "net.causal_transformer.layers.2.1.0.beta", "net.causal_transformer.layers.3.0.norm.gamma", "net.causal_transformer.layers.3.0.norm.beta", "net.causal_transformer.layers.3.0.to_out.1.gamma", "net.causal_transformer.layers.3.0.to_out.1.beta", "net.causal_transformer.layers.3.1.0.gamma", "net.causal_transformer.layers.3.1.0.beta", "net.causal_transformer.layers.4.0.norm.gamma", "net.causal_transformer.layers.4.0.norm.beta", "net.causal_transformer.layers.4.0.to_out.1.gamma", "net.causal_transformer.layers.4.0.to_out.1.beta", "net.causal_transformer.layers.4.1.0.gamma", "net.causal_transformer.layers.4.1.0.beta", "net.causal_transformer.layers.5.0.norm.gamma", "net.causal_transformer.layers.5.0.norm.beta", "net.causal_transformer.layers.5.0.to_out.1.gamma", "net.causal_transformer.layers.5.0.to_out.1.beta", "net.causal_transformer.layers.5.1.0.gamma", "net.causal_transformer.layers.5.1.0.beta", "net.causal_transformer.layers.6.0.norm.gamma", "net.causal_transformer.layers.6.0.norm.beta", "net.causal_transformer.layers.6.0.to_out.1.gamma", "net.causal_transformer.layers.6.0.to_out.1.beta", "net.causal_transformer.layers.6.1.0.gamma", "net.causal_transformer.layers.6.1.0.beta", "net.causal_transformer.layers.7.0.norm.gamma", "net.causal_transformer.layers.7.0.norm.beta", "net.causal_transformer.layers.7.0.to_out.1.gamma", "net.causal_transformer.layers.7.0.to_out.1.beta", "net.causal_transformer.layers.7.1.0.gamma", "net.causal_transformer.layers.7.1.0.beta", "net.causal_transformer.layers.8.0.norm.gamma", "net.causal_transformer.layers.8.0.norm.beta", "net.causal_transformer.layers.8.0.to_out.1.gamma", "net.causal_transformer.layers.8.0.to_out.1.beta", "net.causal_transformer.layers.8.1.0.gamma", "net.causal_transformer.layers.8.1.0.beta", "net.causal_transformer.layers.9.0.norm.gamma", "net.causal_transformer.layers.9.0.norm.beta", "net.causal_transformer.layers.9.0.to_out.1.gamma", "net.causal_transformer.layers.9.0.to_out.1.beta", "net.causal_transformer.layers.9.1.0.gamma", "net.causal_transformer.layers.9.1.0.beta", "net.causal_transformer.layers.10.0.norm.gamma", "net.causal_transformer.layers.10.0.norm.beta", "net.causal_transformer.layers.10.0.to_out.1.gamma", "net.causal_transformer.layers.10.0.to_out.1.beta", "net.causal_transformer.layers.10.1.0.gamma", "net.causal_transformer.layers.10.1.0.beta", "net.causal_transformer.layers.11.0.norm.gamma", "net.causal_transformer.layers.11.0.norm.beta", "net.causal_transformer.layers.11.0.to_out.1.gamma", "net.causal_transformer.layers.11.0.to_out.1.beta", "net.causal_transformer.layers.11.1.0.gamma", "net.causal_transformer.layers.11.1.0.beta", "net.causal_transformer.norm.gamma", "net.causal_transformer.norm.beta". Unexpected key(s) in state_dict: "net.to_time_embeds.0.weight", "net.causal_transformer.layers.0.0.norm.g", "net.causal_transformer.layers.0.0.to_out.1.g", "net.causal_transformer.layers.0.1.0.g", "net.causal_transformer.layers.0.1.3.g", "net.causal_transformer.layers.1.0.norm.g", "net.causal_transformer.layers.1.0.to_out.1.g", "net.causal_transformer.layers.1.1.0.g", "net.causal_transformer.layers.1.1.3.g", "net.causal_transformer.layers.2.0.norm.g", "net.causal_transformer.layers.2.0.to_out.1.g", "net.causal_transformer.layers.2.1.0.g", "net.causal_transformer.layers.2.1.3.g", "net.causal_transformer.layers.3.0.norm.g", "net.causal_transformer.layers.3.0.to_out.1.g", "net.causal_transformer.layers.3.1.0.g", "net.causal_transformer.layers.3.1.3.g", "net.causal_transformer.layers.4.0.norm.g", "net.causal_transformer.layers.4.0.to_out.1.g", "net.causal_transformer.layers.4.1.0.g", "net.causal_transformer.layers.4.1.3.g", "net.causal_transformer.layers.5.0.norm.g", "net.causal_transformer.layers.5.0.to_out.1.g", "net.causal_transformer.layers.5.1.0.g", "net.causal_transformer.layers.5.1.3.g", "net.causal_transformer.layers.6.0.norm.g", "net.causal_transformer.layers.6.0.to_out.1.g", "net.causal_transformer.layers.6.1.0.g", "net.causal_transformer.layers.6.1.3.g", "net.causal_transformer.layers.7.0.norm.g", "net.causal_transformer.layers.7.0.to_out.1.g", "net.causal_transformer.layers.7.1.0.g", "net.causal_transformer.layers.7.1.3.g", "net.causal_transformer.layers.8.0.norm.g", "net.causal_transformer.layers.8.0.to_out.1.g", "net.causal_transformer.layers.8.1.0.g", "net.causal_transformer.layers.8.1.3.g", "net.causal_transformer.layers.9.0.norm.g", "net.causal_transformer.layers.9.0.to_out.1.g", "net.causal_transformer.layers.9.1.0.g", "net.causal_transformer.layers.9.1.3.g", "net.causal_transformer.layers.10.0.norm.g", "net.causal_transformer.layers.10.0.to_out.1.g", "net.causal_transformer.layers.10.1.0.g", "net.causal_transformer.layers.10.1.3.g", "net.causal_transformer.layers.11.0.norm.g", "net.causal_transformer.layers.11.0.to_out.1.g", "net.causal_transformer.layers.11.1.0.g", "net.causal_transformer.layers.11.1.3.g", "net.causal_transformer.norm.g".
does anyone have some idea?
same problem with me, i am finding solution now
you can try set strict to false, maybe is ok
#282
See my response here. This may help you too.