Affinity Interface Replacement

Check whether the Dropout and GELU interfaces on the original network have been replaced with the corresponding NPU interfaces. If they are not replaced, replace them according to the following example.

• Replace dropout in the original network with the corresponding CANN API for better performance. You must also pay attention to the impact on the accuracy.
  • If tf.nn.dropout exists, modify it as follows:

    1	layers = npu_ops.dropout()

  • If tf.layers.dropout, tf.layers.Dropout, tf.keras.layers.Dropout, tf.keras.layers.SpatialDropout1D, tf.keras.layers.SpatialDropout2D, or tf.keras.layers.SpatialDropout3D exists, add the following header file reference:

    1	from npu_bridge.estimator.npu import npu_convert_dropout

• Replace gelu in the original network with the corresponding CANN API to achieve optimal performance.
  Original TensorFlow code:

  1 2 3 4 5

  def gelu(x): cdf = 0.5 * (1.0 + tf.tanh( (np.sqrt(2 / np.pi) * (x + 0.044715 * tf.pow(x, 3))))) return x*cdf layers = gelu()

  Code after porting:

  1	layers = npu_unary_ops.gelu(x)