TensorFlow 1 version View source on GitHub

Returns an element-wise x * y.

    x, y, name=None

For example:

x = tf.constant(([1, 2, 3, 4])) 
tf.math.multiply(x, x) 
<tf.Tensor: shape=(4,), dtype=..., numpy=array([ 1,  4,  9, 16], dtype=int32)> 

Since tf.math.multiply will convert its arguments to Tensors, you can also pass in non-Tensor arguments:

<tf.Tensor: shape=(), dtype=int32, numpy=42> 

If x.shape is not thes same as y.shape, they will be broadcast to a compatible shape. (More about broadcasting here.)

For example:

x = tf.ones([1, 2]); 
y = tf.ones([2, 1]); 
x * y  # Taking advantage of operator overriding 
<tf.Tensor: shape=(2, 2), dtype=float32, numpy= 
array([[1., 1.], 
     [1., 1.]], dtype=float32)> 


  • x: A Tensor. Must be one of the following types: bfloat16, half, float32, float64, uint8, int8, uint16, int16, int32, int64, complex64, complex128.
  • y: A Tensor. Must have the same type as x.
  • name: A name for the operation (optional).


A Tensor. Has the same type as x.


  • InvalidArgumentError: When x and y have incomptatible shapes or types.