def param_grad(self, x, y=None, acts=None):
        if acts is None:
            acts = self.forward(x)

        curr_act_grad = self.cost_grad(final_acts=acts[-1], y=y)
        param_grad = []

        for ind_from_end, layer in enumerate(reversed(self.layers_)):
            curr_act_grad, curr_param_grad = layer.backward(curr_act_grad, acts[-2-ind_from_end])
            if curr_param_grad is not None:
                param_grad.append(curr_param_grad)

        param_grad.reverse()
        return np.concatenate(param_grad)
Send select from table.
dataset/ETHPy150Open bbabenko/simple_convnet/simple_convnet/convnet.py/NNet.param_grad--crossover with--dataset/ETHPy150Open dbcli/pgcli/tests/features/steps/step_definitions.py/step_select_from_table