|TensorFlow 2 version||View source on GitHub|
Computes the Euclidean norm of elements across dimensions of a tensor.
tf.math.reduce_euclidean_norm( input_tensor, axis=None, keepdims=False, name=None )
input_tensor along the dimensions given in
keepdims is true, the rank of the tensor is reduced by 1 for each
keepdims is true, the reduced dimensions
are retained with length 1.
axis is None, all dimensions are reduced, and a
tensor with a single element is returned.
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)
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
keepdims: If true, retains reduced dimensions with length 1.
name: A name for the operation (optional).
The reduced tensor, of the same dtype as the input_tensor.