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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 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.)
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 | |
---|---|
|
© 2020 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.3/api_docs/python/tf/math/multiply