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0161e74 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 | from src.models.scGPT.model import TransformerModel
from src.models.perturbation.model import Model as FlowModel
from src.models.perturbation.model import TimedTransformer
from src.models.origin.model import model as OriginModel
import torch
def instantiate_model(model_type: str, **kwargs):
if model_type == 'origin':
if kwargs['fusion_method'] == 'differential_transformer':
layers = 8
elif kwargs['fusion_method'] == 'differential_perceiver':
layers = 4
else:
layers = 8
d_model = kwargs.get('d_model', 512)
ntoken = kwargs.get('ntoken', 6000)
d_hid = int(4.0 * d_model)
return OriginModel(
ntoken=ntoken,
d_model=d_model,
d_hid=d_hid,
nlayers=layers,
fusion_method=kwargs['fusion_method'],
perturbation_function=kwargs['perturbation_function'],
mask_path=kwargs['mask_path'],
)
else:
raise ValueError(f"Invalid model type: {model_type}")
if __name__ == "__main__":
model = instantiate_model("punet128")
x = torch.randn(32, 128, 128)
t = torch.randn(32)
out = model( x,t)
print(out.shape) |