# tf.raw_ops.Svd

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Computes the singular value decompositions of one or more matrices.

#### View aliases


**Compat aliases for migration**

See
[Migration guide](https://www.tensorflow.org/guide/migrate) for
more details.

[`tf.compat.v1.raw_ops.Svd`](https://www.tensorflow.org/api_docs/python/tf/raw_ops/Svd)

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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 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)

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| ## 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). |

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| ## 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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