python - Recommendation system wirh a restricted Boltzmann machine

Question

I have seen the process of their work but after train, I want to save this model for further use. Anyone who can help?

Now we train the RBM with 5 epochs with each epoch using a batch size of 500.

epochs = 5
batchsize = 500
errors = []
weights = []
K=1
alpha = 0.1
train_ds = 
    tf.data.Dataset.from_tensor_slices((np.float32(trX))).batch(batchsize)
v0_state=v0
for epoch in range(epochs):
    batch_number = 0
    for batch_x in train_ds:

        for i_sample in range(len(batch_x)):           
            for k in range(K):
                v0_state = batch_x[i_sample]
                h0_state = hidden_layer(v0_state, W, hb)
                v1_state = reconstructed_output(h0_state, W, vb)
                h1_state = hidden_layer(v1_state, W, hb)

                delta_W = tf.matmul(tf.transpose([v0_state]), h0_state) - tf.matmul(tf.transpose([v1_state]), h1_state)
                W = W + alpha * delta_W

                vb = vb + alpha * tf.reduce_mean(v0_state - v1_state, 0)
                hb = hb + alpha * tf.reduce_mean(h0_state - h1_state, 0) 

                v0_state = v1_state

            if i_sample == len(batch_x)-1:
                err = error(batch_x[i_sample], v1_state)
                errors.append(err)
                weights.append(W)
                print ( 'Epoch: %d' % (epoch + 1), 
                       "batch #: %i " % batch_number, "of %i" % (len(trX)/batchsize), 
                       "sample #: %i" % i_sample,
                       'reconstruction error: %f' % err)
        batch_number += 1




plt.plot(errors)
plt.ylabel('Error')
plt.xlabel('Epoch')
plt.show()

question from:https://stackoverflow.com/questions/65836586/recommendation-system-wirh-a-restricted-boltzmann-machine

Answer 1

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