tf.math.reduce_euclidean_norm
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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.
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.
|
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Last updated 2024-04-26 UTC.
[null,null,["Last updated 2024-04-26 UTC."],[],[],null,["# tf.math.reduce_euclidean_norm\n\n\u003cbr /\u003e\n\n|------------------------------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.16.1/tensorflow/python/ops/math_ops.py#L2224-L2266) |\n\nComputes the Euclidean norm of elements across dimensions of a tensor. \n\n tf.math.reduce_euclidean_norm(\n input_tensor, axis=None, keepdims=False, name=None\n )\n\nReduces `input_tensor` along the dimensions given in `axis`.\nUnless `keepdims` is true, the rank of the tensor is reduced by 1 for each\nof the entries in `axis`, which must be unique. If `keepdims` is true, the\nreduced dimensions are retained with length 1.\n\nIf `axis` is None, all dimensions are reduced, and a\ntensor with a single element is returned.\n\n#### For example:\n\n x = tf.constant([[1, 2, 3], [1, 1, 1]]) # x.dtype is tf.int32\n tf.math.reduce_euclidean_norm(x) # returns 4 as dtype is tf.int32\n y = tf.constant([[1, 2, 3], [1, 1, 1]], dtype = tf.float32)\n tf.math.reduce_euclidean_norm(y) # returns 4.1231055 which is sqrt(17)\n tf.math.reduce_euclidean_norm(y, 0) # [sqrt(2), sqrt(5), sqrt(10)]\n tf.math.reduce_euclidean_norm(y, 1) # [sqrt(14), sqrt(3)]\n tf.math.reduce_euclidean_norm(y, 1, keepdims=True) # [[sqrt(14)], [sqrt(3)]]\n tf.math.reduce_euclidean_norm(y, [0, 1]) # sqrt(17)\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|----------------|----------------------------------------------------------------------------------------------------------------------------------------------|\n| `input_tensor` | The tensor to reduce. Should have numeric type. |\n| `axis` | The dimensions to reduce. If `None` (the default), reduces all dimensions. Must be in the range `[-rank(input_tensor), rank(input_tensor))`. |\n| `keepdims` | If true, retains reduced dimensions with length 1. |\n| `name` | A name for the operation (optional). |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|---|---|\n| The reduced tensor, of the same dtype as the input_tensor. ||\n\n\u003cbr /\u003e"]]
View source on GitHub