Saving layer weights at each epoch during training into a numpy type/array? Converting TensorFlow Variable to numpy array?
I have found that I need to use the method keras.model.layer.get_weights() to get the weights as numpy arrays.
For instance my callback would change to something like
def on_epoch_end(self, epoch, logs={}): logs = logs or {} self.epoch.append(epoch) for k, v in logs.items(): self.history.setdefault(k, []).append(v) modelWeights = [] for layer in model.layers: layerWeights = [] for weight in layer.get_weights(): layerWeights.append(weight) modelWeights.append(layerWeights) self.weights.append(modelWeights)