Hello, I’ve been working with a bayesian neural net and while I thought I had it, it seems not the case. This is the error I’m gettiing. ValueError: shapes (161533,53) and (128,53) not aligned: 53 (dim 1) != 128 (dim 0) The shape of my input is (161533, 53) My model is as follows: ann_input…

Got it! ann_input = tt.shared(np.asarray(X_train)) y_train_t = Y_train.transpose() ann_output = tt.shared(np.asarray(y_train_t)) #Initialize random weights between each layer init_1 = np.random.randn(X_train.shape[1], 128) init_2 = np.random.randn(128, 128) init_3 = np.random.randn(128, 64) …

Still having troubles with neural net shapes

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jordan.howell2 February 27, 2019, 7:11pm 3

Are you saying it’s as simple as switching the weights in the shapes? So on weights_2_3 instead of shape being (64, 128) it should be (128,64)?

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Still having troubles with neural net shapes

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