ValueError: Per sample gradient is not initialized. Not updated in backward pass? about opacus HOT 4 OPEN

def set_submodel(self, ind, strategy=None):
    self.ind = ind

    assert ind <= 3

    if strategy is None:
        strategy = self.strategy
    print(strategy, ind, self.dataset)

    if strategy == 'progressive':
        modules = []
        for i in range(ind + 1):
            modules.append(self.module_splits[i])
        self.enc = nn.Sequential(*modules)
        self.head = self.head_splits[ind]

        for param in self.parameters():
            param.requires_grad = False

        for module in self.enc:
            for param in module.parameters():
                param.requires_grad = True
        for param in self.head.parameters():
            param.requires_grad = True

    elif strategy == 'baseline':
        modules = []
        for i in range(len(self.module_splits)):
            modules.append(self.module_splits[i])
        self.enc = nn.Sequential(*modules)
        self.head = self.classifier

        for param in self.parameters():
            param.requires_grad = False

        for module in self.enc:
            for param in module.parameters():
                param.requires_grad = True
        for param in self.head.parameters():
            param.requires_grad = True

    else:
        raise NotImplementedError()