tf.keras.ops.matrix_rank
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Return the matrix rank of one or more matrices using SVD.
tf.keras.ops.matrix_rank(
x, tol=None
)
The rank is the number of singular values that exceed tol. If tol
is None, each backend uses its own default threshold derived from
the largest singular value and the matrix dimensions.
Args |
|---|
x
|
Input tensor of shape (..., M, N).
|
tol
|
Absolute threshold below which singular values are treated
as zero. If None (default), the backend's default is used.
|
Returns |
|---|
An integer tensor of shape (...,) with the rank of each matrix
in the batch.
|
Example:
a = keras.ops.convert_to_tensor([[1., 2.], [2., 4.]])
keras.ops.matrix_rank(a)
1
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Last updated 2026-10-31 UTC.
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