| View source on GitHub | 
Returns an element-wise x * y.
tf.math.multiply(
    x, y, name=None
)
  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.math.multiply(7,6) <tf.Tensor: shape=(), dtype=int32, numpy=42>
If x.shape is not the same as y.shape, they will be broadcast to a compatible shape. (More about broadcasting here.)
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)>
 The reduction version of this elementwise operation is tf.math.reduce_prod
| Args | |
|---|---|
| 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 asx. | 
| name | A name for the operation (optional). | 
| Returns | 
|---|
A Tensor. Has the same type as x.
| Raises | |
|---|---|
| 
 | 
    © 2022 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 4.0.
Code samples licensed under the Apache 2.0 License.
    https://www.tensorflow.org/versions/r2.9/api_docs/python/tf/math/multiply