|---| | [ View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.21.0/tensorflow/python/ops/math_ops.py#L2305-L2347) | Computes the Euclidean norm of elements across dimensions of a tensor. 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 of the entries in `axis`, which must be unique. 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]]) # x.dtype is tf.int32 tf.math.reduce_euclidean_norm(x) # returns 4 as dtype is tf.int32 y = tf.constant([[1, 2, 3], [1, 1, 1]], dtype = tf.float32) tf.math.reduce_euclidean_norm(y) # returns 4.1231055 which is sqrt(17) tf.math.reduce_euclidean_norm(y, 0) # [sqrt(2), sqrt(5), sqrt(10)] tf.math.reduce_euclidean_norm(y, 1) # [sqrt(14), sqrt(3)] tf.math.reduce_euclidean_norm(y, 1, keepdims=True) # [[sqrt(14)], [sqrt(3)]] tf.math.reduce_euclidean_norm(y, [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. ||