zhreshold commented on issue #13594: Autograd error when using custom parameters URL: https://github.com/apache/incubator-mxnet/issues/13594#issuecomment-445727359 @seujung read/write parameters using `.data()` and `set_data()` in computation graph, i.e. in `forward` or `hybrid_forward` is not allowed becaue it will cause autograd not successfully recording the gradients. You can use parameters directly in forward, gluon will automatically prepare them for you. Correct forward function is: ``` def forward(self, x, scale, loc, logdet): _, _, height, width = x.shape # initialization is not allowed in forward #if not self.initialized: # self.init(x) # self.initialized = True log_abs = logabs(scale) logdet = height * width * nd.sum(log_abs) if self.use_logdet: return scale * (x + loc), logdet else: return scale * (x + loc), ```
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