class LayerCustom_LayerCustom_1Keras(tf.keras.layers.Layer, PerceptiLabsVisualizer):
def call(self, inputs, training=True):
raise TypeError("Missing input connection 'input'")
output = preview = input_
"""Any variables belonging to this layer that should be rendered in the frontend.
A dictionary with tensor names for keys and picklable for values.
def visualized_trainables(self):
""" Returns two tf.Variables (weights, biases) to be visualized in the frontend """
return tf.constant(0), tf.constant(0)
class LayerCustom_LayerCustom_1(Tf2xLayer):
keras_class=LayerCustom_LayerCustom_1Keras