@@ -12,7 +12,7 @@ MegEngine is a fast, scalable and easy-to-use deep learning framework, with auto
## Installation
**NOTE:** MegEngine now supports Python installation on Linux-64bit/Windows-64bit/MacOS(CPU-Only)-10.14+/Android 7+(CPU-Only) platforms with Python from 3.5 to 3.8. On Windows 10 you can either install the Linux distribution through [Windows Subsystem for Linux (WSL)](https://docs.microsoft.com/en-us/windows/wsl) or install the Windows distribution directly. Many other platforms are supported for inference.
**NOTE:** MegEngine now supports Python installation on Linux-64bit/Windows-64bit/MacOS(CPU-Only)-10.14+ platforms with Python from 3.5 to 3.8. On Windows 10 you can either install the Linux distribution through [Windows Subsystem for Linux (WSL)](https://docs.microsoft.com/en-us/windows/wsl) or install the Windows distribution directly. Many other platforms are supported for inference.
r"""Computes the singular value decompositions of input matrix.
r"""Returns a singular value decomposition ``A = USVh`` of a matrix (or a stack of matrices) ``x`` , where ``U`` is a matrix (or a stack of matrices) with orthonormal columns, ``S`` is a vector of non-negative numbers (or stack of vectors), and ``Vh`` is a matrix (or a stack of matrices) with orthonormal rows.
Args:
inp: input matrix, must has shape `[..., M, N]`.
x (Tensor): A input real tensor having the shape ``(..., M, N)`` with ``x.ndim >= 2`` .
full_matrices (bool, optional): If ``False`` , ``U`` and ``Vh`` have the shapes ``(..., M, K)`` and ``(..., K, N)`` , respectively, where ``K = min(M, N)`` . If ``True`` , the shapes are ``(..., M, M)`` and ``(..., N, N)`` , respectively. Default: ``False`` .
compute_uv (bool, optional): Whether or not to compute ``U`` and ``Vh`` in addition to ``S`` . Default: ``True`` .
Note:
* naive does not support ``full_matrices`` and ``compute_uv`` as ``True`` .
Returns:
output matrices, `(U, sigma, V)`.
Returns a tuple ( ``U`` , ``S`` , ``Vh`` ), which are SVD factors ``U`` , ``S``, ``Vh`` of input matrix ``x``. ( ``U`` , ``Vh`` only returned when ``compute_uv`` is True).
``U`` contains matrices orthonormal columns (i.e., the columns are left singular vectors). If ``full_matrices`` is ``True`` , the array must have shape ``(..., M, M)`` . If ``full_matrices`` is ``False`` , the array must have shape ``(..., M, K)`` , where ``K = min(M, N)`` .
Examples:
.. testcode::
import numpy as np
from megengine import tensor
import megengine.functional as F
x = tensor(np.arange(0, 6, dtype=np.float32).reshape(2,3))
