import torch


def mean_activations(tensor):
    """Computes mean of activation maps tensor."""
    # squeeze to remove batch dimension
    return torch.mean(tensor.detach().cpu(), dim=1).squeeze(dim=0)


def load_weights(model, weights):
    """Loads the weights of only the layers present in the given model."""
    pretrained_dict = torch.load(weights, map_location='cpu')
    model_dict = model.state_dict()
    pretrained_dict = {k: v for k,
                       v in pretrained_dict.items() if k in model_dict}
    model_dict.update(pretrained_dict)
    model.load_state_dict(model_dict)