svj1991 opened a new issue #15047: Conv 1D block with weights initialized by me and controllable gradients URL: https://github.com/apache/incubator-mxnet/issues/15047 Hi, I’m a bit new to Gluon and mxnet, I’m sorry if my question is too trivial. I was trying to implement a Conv 1D operation on a speech waveform. I have the following, N = 512 hp = 16 re = nn.Conv1D( in_channels=1, channels=N, kernel_size=N, padding=N//2, strides=hp, groups=1, use_bias=False) Now I have a ndarray 'br' of size (N,1,N) and I wish to initialize the Conv1D layer re with this 'br' matrix. Also, I’d like to have the control to make this layer trainable or fixed, essentially setting the gradient required to True or False. I have been struggling to find how to do this in the documentation. Could anyone help? Thanks.
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