!45471 [MS][OP]add some primitive chinese docs
Merge pull request !45471 from mengyuanli/code_docs_export_primitive_2
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@ -230,6 +230,9 @@ MindSpore中 `mindspore.ops` 接口与上一版本相比，新增、删除和支
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mindspore.ops.Bincount
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mindspore.ops.Bucketize
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mindspore.ops.Cauchy
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mindspore.ops.Cholesky
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mindspore.ops.CholeskyInverse
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mindspore.ops.CholeskySolve
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mindspore.ops.Cross
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逐元素运算
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@ -0,0 +1,8 @@
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mindspore.ops.Cholesky
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=======================
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.. py:class:: mindspore.ops.Cholesky(upper=False)
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计算单个或成批对称正定矩阵的Cholesky分解。
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更多参考详见 :func:`mindspore.ops.cholesky`。
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@ -0,0 +1,8 @@
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mindspore.ops.CholeskyInverse
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==============================
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.. py:class:: mindspore.ops.CholeskyInverse(upper=False)
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使用Cholesky矩阵分解返回正定矩阵的逆矩阵。
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更多参考详见 :func:`mindspore.ops.cholesky_inverse`。
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@ -0,0 +1,37 @@
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mindspore.ops.CholeskySolve
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===========================
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.. py:class:: mindspore.ops.CholeskySolve(upper=False)
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给定Cholesky因子 `u` ，求解具有正定矩阵的线性方程组，结果表示为 `c` 。
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如果 `upper` 是True， `u` 是上三角形矩阵，可以通过下面公式得到 `c` ：
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.. math::
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c = (u^{T}u)^{{-1}}b
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如果 `upper` 是False， `u` 是下三角形矩阵，可以通过下面公式得到 `c` ：
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.. math::
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c = (uu^{T})^{{-1}}b
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参数：
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- **upper** (bool，可选) - 将Cholesky因子视为下三角矩阵或上三角矩阵的标志。若为True，视为上三角矩阵，反之则为下三角。默认值：False。
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输入：
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- **x1** (Tensor) - 表示二维或三维矩阵的Tensor。Shape为： :math:`(*, N, M)` ，数据类型为float32或float64。
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- **x2** (Tensor) - 表示由2D或3D正方形矩阵组成上三角形或下三角形乔列斯基因子的Tensor。Shape为： :math:`(*, N, N)` ，数据类型为float32或float64。
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`x1` 和 `x2` 必须具有相同的类型。
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输出：
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Tensor，具有与 `x1` 相同的shape和数据类型。
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异常：
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- **TypeError** - `upper` 的数据类型不是bool。
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- **TypeError** - 如果 `x1` 和 `x2` 的dtype不是以下之一：float64，float32。
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- **TypeError** - 如果 `x1` 不是Tensor。
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- **TypeError** - 如果 `x2` 不是Tensor。
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- **ValueError** - 如果 `x1` 和 `x2` 具有不同的批大小。
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- **ValueError** - 如果 `x1` 和 `x2` 具有不同的行数。
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- **ValueError** - 如果 `x1` 不是2维或3维矩阵。
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- **ValueError** - 如果 `x2` 不是2维或3维方阵。
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@ -230,6 +230,9 @@ Mathematical Operators
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mindspore.ops.Bincount
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mindspore.ops.Bucketize
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mindspore.ops.Cauchy
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mindspore.ops.Cholesky
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mindspore.ops.CholeskyInverse
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mindspore.ops.CholeskySolve
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mindspore.ops.Cross
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Element-wise Operator
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@ -6766,7 +6766,7 @@ def cholesky_inverse(input_x, upper=False):
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ValueError: If the dimension of `input_x` is not equal to 2.
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Supported Platforms:
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``CPU``
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``GPU`` ``CPU``
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Examples:
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>>> input_x = Tensor(np.array([[2,0,0], [4,1,0], [-1,1,2]]), mindspore.float32)
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@ -6422,32 +6422,7 @@ class CholeskyInverse(Primitive):
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"""
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Returns the inverse of the positive definite matrix using cholesky matrix factorization.
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If upper is False, u is a lower triangular such that the output tensor is
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.. math::
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inv = (uu^{T})^{{-1}}
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If upper is True, u is an upper triangular such that the output tensor is
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.. math::
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inv = (u^{T}u)^{{-1}}
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Note:
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The input must be either an upper triangular matrix or a lower triangular matrix.
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Args:
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upper(bool): Whether to return a lower or upper triangular matrix. Default: False.
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Inputs:
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- **x** (Tensor) - The input tensor. types: float32, float64.
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Outputs:
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Tensor, has the same shape and dtype as x.
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Raises:
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TypeError: If `x` is not a Tensor.
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TypeError: If dtype of `x` is not one of: float32, float64.
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ValueError: If the dimension of `x` is not equal to 2.
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Refer to :func::`mindspore.ops.cholesky_inverse` for more detail.
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Supported Platforms:
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``GPU`` ``CPU``
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@ -6793,33 +6768,7 @@ class Cholesky(Primitive):
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Computes the Cholesky decomposition of a symmetric positive-definite matrix `A`
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or for batches of symmetric positive-definite matrices.
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If `upper` is `True`, the returned matrix `U` is upper-triangular, and the decomposition has the form:
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.. math::
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A = U^TU
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If `upper` is `False`, the returned matrix `L` is lower-triangular, and the decomposition has the form:
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.. math::
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A = LL^T
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Args:
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upper (bool): Flag that indicates whether to return a upper or lower triangular matrix.
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Default: False.
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Inputs:
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- **input_x** (Tensor) - Tensor of shape :math:`(*, N, N)`, where :math:`*` is zero or more batch dimensions
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consisting of symmetric positive-definite matrices, with float32 or float64 data type.
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Outputs:
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Tensor, has the same shape and data type as `input_x`.
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Raises:
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TypeError: If `upper` is not a bool.
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TypeError: If dtype of `input_x` is not one of: float64, float32.
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TypeError: If `input_x` is not a Tensor.
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ValueError: If `input_x` is not batch square.
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ValueError: If `input_x` is not symmetric positive definite.
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Refer to :func::`mindspore.ops.cholesky` for more detail.
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Supported Platforms:
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``Ascend`` ``CPU``
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@ -6904,7 +6853,7 @@ class CholeskySolve(Primitive):
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c = (uu^{T})^{{-1}}b
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Args:
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upper (bool): Flag which indicates whether to consider the Cholesky factor
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upper (bool, optional): Flag which indicates whether to consider the Cholesky factor
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as a lower or upper triangular matrix. Default: False.
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Inputs:
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