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View source on GitHub |
Computes the norm of vectors, matrices, and tensors. (deprecated arguments)
tf.compat.v1.norm(
tensor,
ord='euclidean',
axis=None,
keepdims=None,
name=None,
keep_dims=None
)
This function can compute several different vector norms (the 1-norm, the Euclidean or 2-norm, the inf-norm, and in general the p-norm for p > 0) and matrix norms (Frobenius, 1-norm, 2-norm and inf-norm).
Raises | |
---|---|
ValueError
|
If ord or axis is invalid.
|
numpy compatibility
Mostly equivalent to numpy.linalg.norm.
Not supported: ord <= 0, 2-norm for matrices, nuclear norm.
Other differences:
a) If axis is None
, treats the flattened tensor
as a vector
regardless of rank.
b) Explicitly supports 'euclidean' norm as the default, including for
higher order tensors.