This project is an implementation of the Generative Adversarial Network proposed in our CVPR 2017 paper - DeLiGAN : Generative Adversarial Networks for Diverse and Limited Data. DeLiGAN is a simple but effective modification of the GAN framework and aims to improve performance on datasets which are diverse yet small in size.
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TypeError: ('An update must have the same type as the original shared variable (shared_var=W, shared_var.type=GpuArrayType<None>(float32, (False, True, False, False)), update_val=Elemwise{sub,no_inplace}.0, update_val.type=TensorType(float32, 4D)).', 'If the difference is related to the broadcast pattern, you can call the tensor.unbroadcast(var, axis_to_unbroadcast[, ...]) function to remove broadcastable dimensions.') #7
I got this error when I run the code in the folder sketches,but I can't find the solution to this error.