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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.

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. |

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Licensed under the Creative Commons Attribution License 3.0.

Code samples licensed under the Apache 2.0 License.

https://www.tensorflow.org/versions/r2.4/api_docs/python/tf/math/reduce_euclidean_norm