TensorFlow 1 version |
Returns the min of x and y (i.e. x < y ? x : y) element-wise.
tf.math.minimum(
x, y, name=None
)
Both inputs are number-type tensors (except complex). minimum
expects that
both tensors have the same dtype
.
Examples:
x = tf.constant([0., 0., 0., 0.])
y = tf.constant([-5., -2., 0., 3.])
tf.math.minimum(x, y)
<tf.Tensor: shape=(4,), dtype=float32, numpy=array([-5., -2., 0., 0.], dtype=float32)>
Note that minimum
supports broadcast semantics for x
and y
.
x = tf.constant([-5., 0., 0., 0.])
y = tf.constant([-3.])
tf.math.minimum(x, y)
<tf.Tensor: shape=(4,), dtype=float32, numpy=array([-5., -3., -3., -3.], dtype=float32)>
The reduction version of this elementwise operation is tf.math.reduce_min
Args | |
---|---|
x
|
A Tensor . Must be one of the following types: bfloat16 , half , float32 , float64 , uint8 , int16 , int32 , int64 .
|
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 .
|