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Svd

public final class Svd

Computes the singular value decompositions of one or more matrices.

Computes the SVD of each inner matrix in `input` such that `input[..., :, :] = u[..., :, :] * diag(s[..., :, :]) * transpose(v[..., :, :])`

# a is a tensor containing a batch of matrices.
 # s is a tensor of singular values for each matrix.
 # u is the tensor containing the left singular vectors for each matrix.
 # v is the tensor containing the right singular vectors for each matrix.
 s, u, v = svd(a)
 s, _, _ = svd(a, compute_uv=False)
 

Nested Classes

class Svd.Options Optional attributes for Svd

Constants

String OP_NAME The name of this op, as known by TensorFlow core engine

Public Methods

static Svd.Options
computeUv (Boolean computeUv)
static <T extends TType > Svd <T>
create ( Scope scope, Operand <T> input, Options... options)
Factory method to create a class wrapping a new Svd operation.
static Svd.Options
fullMatrices (Boolean fullMatrices)
Output <T>
s ()
Singular values.
Output <T>
u ()
Left singular vectors.
Output <T>
v ()
Left singular vectors.

Inherited Methods

Constants

public static final String OP_NAME

The name of this op, as known by TensorFlow core engine

Constant Value: "Svd"

Public Methods

public static Svd.Options computeUv (Boolean computeUv)

Parameters
computeUv If true, left and right singular vectors will be computed and returned in `u` and `v`, respectively. If false, `u` and `v` are not set and should never referenced.

public static Svd <T> create ( Scope scope, Operand <T> input, Options... options)

Factory method to create a class wrapping a new Svd operation.

Parameters
scope current scope
input A tensor of shape `[..., M, N]` whose inner-most 2 dimensions form matrices of size `[M, N]`. Let `P` be the minimum of `M` and `N`.
options carries optional attributes values
Returns
  • a new instance of Svd

public static Svd.Options fullMatrices (Boolean fullMatrices)

Parameters
fullMatrices If true, compute full-sized `u` and `v`. If false (the default), compute only the leading `P` singular vectors. Ignored if `compute_uv` is `False`.

public Output <T> s ()

Singular values. Shape is `[..., P]`.

public Output <T> u ()

Left singular vectors. If `full_matrices` is `False` then shape is `[..., M, P]`; if `full_matrices` is `True` then shape is `[..., M, M]`. Undefined if `compute_uv` is `False`.

public Output <T> v ()

Left singular vectors. If `full_matrices` is `False` then shape is `[..., N, P]`. If `full_matrices` is `True` then shape is `[..., N, N]`. Undefined if `compute_uv` is false.