code: def neural_net_predict(params, inputs):
      
      for W, b in params:
          outputs = np.dot(inputs, W) + b
          inputs = np.tanh(outputs)
      return outputs - logsumexp(outputs, axis=1, keepdims=True)
docs: Implements a deep neural network for classification.
         params is a list of (weights, bias) tuples.
         inputs is an (N x D) matrix.
         returns normalized class log-probabilities.