/TensorFlow 2.4

tf.math.multiply

Returns an element-wise x * y.

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 `Tensor`s, 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 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)>
```
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 as `x`.
`name` A name for the operation (optional).
Returns

A `Tensor`. Has the same type as `x`.

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