| 123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081 |
- # Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved
- #
- # Licensed under the Apache License, Version 2.0 (the "License");
- # you may not use this file except in compliance with the License.
- # You may obtain a copy of the License at
- #
- # http://www.apache.org/licenses/LICENSE-2.0
- #
- # Unless required by applicable law or agreed to in writing, software
- # distributed under the License is distributed on an "AS IS" BASIS,
- # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- # See the License for the specific language governing permissions and
- # limitations under the License.
- from .tensor import inverse as inv
- from .tensor.linalg import (
- cholesky,
- cholesky_solve,
- cond,
- corrcoef,
- cov,
- det,
- eig,
- eigh,
- eigvals,
- eigvalsh,
- householder_product,
- lstsq,
- lu,
- lu_unpack,
- matrix_exp,
- matrix_norm,
- matrix_power,
- matrix_rank,
- multi_dot,
- norm,
- ormqr,
- pca_lowrank,
- pinv,
- qr,
- slogdet,
- solve,
- svd,
- svd_lowrank,
- triangular_solve,
- vector_norm,
- )
- __all__ = [
- 'cholesky',
- 'norm',
- 'matrix_norm',
- 'vector_norm',
- 'cond',
- 'cov',
- 'corrcoef',
- 'inv',
- 'eig',
- 'eigvals',
- 'multi_dot',
- 'matrix_rank',
- 'svd',
- 'qr',
- 'householder_product',
- 'pca_lowrank',
- 'svd_lowrank',
- 'lu',
- 'lu_unpack',
- 'matrix_exp',
- 'matrix_power',
- 'det',
- 'slogdet',
- 'eigh',
- 'eigvalsh',
- 'pinv',
- 'solve',
- 'cholesky_solve',
- 'triangular_solve',
- 'lstsq',
- 'ormqr',
- ]
|