tf.math.reduce_euclidean_norm | TensorFlow v2.0.0 (original) (raw)
tf.math.reduce_euclidean_norm
Stay organized with collections Save and categorize content based on your preferences.
Computes the Euclidean norm of elements across dimensions of a tensor.
View aliases
Compat aliases for migration
SeeMigration guide for more details.
tf.compat.v1.math.reduce_euclidean_norm
tf.math.reduce_euclidean_norm(
input_tensor, axis=None, keepdims=False, name=None
)
Reduces input_tensor along the dimensions given in axis. Unless keepdims is true, the rank of the tensor is reduced by 1 for each entry in axis. If keepdims is true, the reduced dimensions are retained with length 1.
If axis is None, all dimensions are reduced, and a tensor with a single element is returned.
For example:
x = tf.constant([[1, 2, 3], [1, 1, 1]])
tf.reduce_euclidean_norm(x) # sqrt(17)
tf.reduce_euclidean_norm(x, 0) # [sqrt(2), sqrt(5), sqrt(10)]
tf.reduce_euclidean_norm(x, 1) # [sqrt(14), sqrt(3)]
tf.reduce_euclidean_norm(x, 1, keepdims=True) # [[sqrt(14)], [sqrt(3)]]
tf.reduce_euclidean_norm(x, [0, 1]) # sqrt(17)
| Args | |
|---|---|
| input_tensor | The tensor to reduce. Should have numeric type. |
| axis | The dimensions to reduce. If None (the default), reduces all dimensions. Must be in the range [-rank(input_tensor), rank(input_tensor)). |
| keepdims | If true, retains reduced dimensions with length 1. |
| name | A name for the operation (optional). |
| Returns |
|---|
| The reduced tensor, of the same dtype as the input_tensor. |