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Tensorflow.Keras: How to get gradient for an output class w.r.t a given input?

model with SGD w/o momentum -Set all the weights = that of the previous model -Train with the input and output i.e. the Array for epoch=1 and batch_size=1 -Get the weights again -Calculate the respective gradient … using two weights of 1st layer -If Gradient is very small, it might become zero due to matching digits of both the weights w0 = model.get_weights().copy() w0_0 = w0[0] optimizer = tf.keras.optimizers.SGD …
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