tf.raw_ops.Svd | TensorFlow v2.16.1 (original) (raw)
tf.raw_ops.Svd
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Computes the singular value decompositions of one or more matrices.
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tf.raw_ops.Svd(
input, compute_uv=True, full_matrices=False, name=None
)
Computes the SVD of each inner matrix in input such thatinput[..., :, :] = 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)
| Args | |
|---|---|
| input | A Tensor. Must be one of the following types: float64, float32, half, complex64, complex128. 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. |
| compute_uv | An optional bool. Defaults to True. 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. |
| full_matrices | An optional bool. Defaults to False. 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. |
| name | A name for the operation (optional). |
| 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. |