Model and guide event_dims disagree at site 'module$$$out.weight': 0 vs 1

Issue Description

I want to implement the Making Your Neural Network Say “I Don’t Know” — Bayesian NNs using Pyro and PyTorch but when i run it , i got error. ValueError: Model and guide event_dims disagree at site 'module$$$out.weight': 0 vs 1 i copy its module and guide here

def model(x_data, y_data):
    
    fc1w_prior = Normal(loc=torch.zeros_like(net.fc1.weight), scale=torch.ones_like(net.fc1.weight))
    fc1b_prior = Normal(loc=torch.zeros_like(net.fc1.bias), scale=torch.ones_like(net.fc1.bias))
    
    outw_prior = Normal(loc=torch.zeros_like(net.out.weight), scale=torch.ones_like(net.out.weight))
    outb_prior = Normal(loc=torch.zeros_like(net.out.bias), scale=torch.ones_like(net.out.bias))
    
    priors = {'fc1.weight': fc1w_prior, 'fc1.bias': fc1b_prior,  'out.weight': outw_prior, 'out.bias': outb_prior}
    print(priors['out.weight'])
    # lift module parameters to random variables sampled from the priors
    lifted_module = pyro.random_module("module", net, priors)
    # sample a regressor (which also samples w and b)
    lifted_reg_model = lifted_module()
    
    lhat = log_softmax(lifted_reg_model(x_data))
    
    pyro.sample("obs", Categorical(logits=lhat), obs=y_data)

def guide(x_data, y_data):

    # First layer weight distribution priors
    fc1w_mu = torch.randn_like(net.fc1.weight)
    fc1w_sigma = torch.randn_like(net.fc1.weight)
    fc1w_mu_param = pyro.param("fc1w_mu", fc1w_mu)
    fc1w_sigma_param = softplus(pyro.param("fc1w_sigma", fc1w_sigma))
    fc1w_prior = Normal(loc=fc1w_mu_param, scale=fc1w_sigma_param)
    # First layer bias distribution priors
    fc1b_mu = torch.randn_like(net.fc1.bias)
    fc1b_sigma = torch.randn_like(net.fc1.bias)
    fc1b_mu_param = pyro.param("fc1b_mu", fc1b_mu)
    fc1b_sigma_param = softplus(pyro.param("fc1b_sigma", fc1b_sigma))
    fc1b_prior = Normal(loc=fc1b_mu_param, scale=fc1b_sigma_param)
    # Output layer weight distribution priors
    outw_mu = torch.randn_like(net.out.weight)
    outw_sigma = torch.randn_like(net.out.weight)
    outw_mu_param = pyro.param("outw_mu", outw_mu)
    outw_sigma_param = softplus(pyro.param("outw_sigma", outw_sigma))
    outw_prior = Normal(loc=outw_mu_param, scale=outw_sigma_param).independent(1)
    # outw_prior = Normal(loc=outw_mu_param, scale=outw_sigma_param)
    # Output layer bias distribution priors
    outb_mu = torch.randn_like(net.out.bias)
    outb_sigma = torch.randn_like(net.out.bias)
    outb_mu_param = pyro.param("outb_mu", outb_mu)
    outb_sigma_param = softplus(pyro.param("outb_sigma", outb_sigma))
    outb_prior = Normal(loc=outb_mu_param, scale=outb_sigma_param)
    priors = {'fc1.weight': fc1w_prior, 'fc1.bias': fc1b_prior, 'out.weight': outw_prior, 'out.bias': outb_prior}
    print(priors['out.weight'])
    
    lifted_module = pyro.random_module("module", net, priors)
    
    return lifted_module()

how can i resolve this problem? i tried to add .to_event()after the variables (such as fc1w_prior) but it cause more errors

Environment

• ubuntu python 3.8.8
• PyTorch 1.8.1+cu102
• Pyro version: 1.6.0

Hope for some help . thanks a lot !!

[arm-on]

I had the same issue and was not able to fix it by manually setting the event dimensions. When trying to run the code, I recommend installing an earlier version of pyro (ex: !pip3 install pyro-ppl==1.4.0) in the notebook instead as a temporary fix. I am still trying to figure out how to fix it.

Hi I eventually fixed the code by installing the previous versions of all of the necessary packages. Here is my code: https://github.com/arm-on/interpretable-image-classification/blob/main/bayesian-nn/MNIST_Bayesian_Training.ipynb

[tgeller08]

I had the same issue and was not able to fix it by manually setting the event dimensions. When trying to run the code, I recommend installing an earlier version of pyro (ex: !pip3 install pyro-ppl==1.4.0) in the notebook instead as a temporary fix. I am still trying to figure out how to fix it.