code: def call(self, inputs):
      outputs = []
      state = ops.zeros(shape=(inputs.shape[0], self.units))
      for t in range(inputs.shape[1]):
          x = inputs[:, t, :]
          h = self.projection_1(x)
          y = h + self.projection_2(state)
          state = y
          outputs.append(y)
      features = ops.stack(outputs, axis=1)
      return self.classifier(features)
  
imports: import numpy
  import keras
  from keras import layers
  from keras import ops
label_desc: Use image node_id 2 for calling the CustomRNN obj's underlying member method code with example usage: obj.call(inputs) and returns: self