Computes the singular value decompositions of one or more matrices.
tf.raw_ops.Svd(
input, compute_uv=True, full_matrices=False, name=None
)
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)
Returns | |
---|---|
A tuple of Tensor objects (s, u, v).
|
|
s
|
A Tensor . Has the same type as input .
|
u
|
A Tensor . Has the same type as input .
|
v
|
A Tensor . Has the same type as input .
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