class_docstr: Layer that subtracts two inputs.
  
  It takes as input a list of tensors of size 2,
  both of the same shape, and returns a single tensor, (inputs[0] - inputs[1]),
  also of the same shape.
  
  Examples:
  
  ```python
      import keras
  
      input1 = keras.layers.Input(shape=(16,))
      x1 = keras.layers.Dense(8, activation='relu')(input1)
      input2 = keras.layers.Input(shape=(32,))
      x2 = keras.layers.Dense(8, activation='relu')(input2)
      # Equivalent to subtracted = keras.layers.subtract([x1, x2])
      subtracted = keras.layers.Subtract()([x1, x2])
  
      out = keras.layers.Dense(4)(subtracted)
      model = keras.models.Model(inputs=[input1, input2], outputs=out)
  ```
code: def build(self, input_shape):
      super(Subtract, self).build(input_shape)
      if len(input_shape) != 2:
          raise ValueError(
              "A `Subtract` layer should be called "
              "on exactly 2 inputs"
          )
  
imports: from tensorflow.python.keras import backend
  from tensorflow.python.keras.engine import base_layer_utils
  from tensorflow.python.keras.engine.base_layer import Layer
  from tensorflow.python.keras.utils import tf_utils
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import array_ops_stack
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import nn
label_desc: Use image node_id 1 for calling the Subtract obj's underlying member method code with example usage: obj.build(input_shape) without return types