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soumith merged 1 commit into from
Dec 15, 2017
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Improve svd doc #4155

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15 changes: 7 additions & 8 deletions torch/_torch_docs.py
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Expand Up @@ -4295,16 +4295,15 @@
`U, S, V = torch.svd(A)` returns the singular value decomposition of a
real matrix `A` of size `(n x m)` such that :math:`A = USV^T`.
`U` is of shape :math:`(n \times \min(n, m))`.
`U` is of shape :math:`(n \times n)`.
`S` is a diagonal matrix of shape :math:`(\min(n, m) \times \min(n, m))`,
represented as a vector of size :math:`\min(n, m)` containing the diagonal
entries.
`S` is a diagonal matrix of shape :math:`(n \times m)`, represented as a vector
of size :math:`\min(n, m)` containing the diagonal entries.
`V` is of shape :math:`(m \times \min(n, m))`.
`V` is of shape :math:`(m \times m)`.
:attr:`some` represents the number of singular values to be computed.
If `some=True`, it computes some and `some=False` computes all.
If :attr:`some` is ``True`` (default), the returned `U` and `V` matrices will
contain only :math:`min(n, m)` orthonormal columns.
.. note:: Irrespective of the original strides, the returned matrix `U`
will be transposed, i.e. with strides `(1, n)` instead of `(n, 1)`.
Expand All @@ -4321,7 +4320,7 @@
Args:
input (Tensor): the input 2-D tensor
some (bool, optional): controls the number of singular values to be computed
some (bool, optional): controls the shape of returned `U` and `V`
out (tuple, optional): the output tuple of tensors
Example::
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