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Phi2-Fine-Tuning
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"""

``numpy.linalg``

================



The NumPy linear algebra functions rely on BLAS and LAPACK to provide efficient

low level implementations of standard linear algebra algorithms. Those

libraries may be provided by NumPy itself using C versions of a subset of their

reference implementations but, when possible, highly optimized libraries that

take advantage of specialized processor functionality are preferred. Examples

of such libraries are OpenBLAS, MKL (TM), and ATLAS. Because those libraries

are multithreaded and processor dependent, environmental variables and external

packages such as threadpoolctl may be needed to control the number of threads

or specify the processor architecture.



- OpenBLAS: https://www.openblas.net/

- threadpoolctl: https://github.com/joblib/threadpoolctl



Please note that the most-used linear algebra functions in NumPy are present in

the main ``numpy`` namespace rather than in ``numpy.linalg``.  There are:

``dot``, ``vdot``, ``inner``, ``outer``, ``matmul``, ``tensordot``, ``einsum``,

``einsum_path`` and ``kron``.



Functions present in numpy.linalg are listed below.





Matrix and vector products

--------------------------



   cross

   multi_dot

   matrix_power

   tensordot

   matmul



Decompositions

--------------



   cholesky

   outer

   qr

   svd

   svdvals



Matrix eigenvalues

------------------



   eig

   eigh

   eigvals

   eigvalsh



Norms and other numbers

-----------------------



   norm

   matrix_norm

   vector_norm

   cond

   det

   matrix_rank

   slogdet

   trace (Array API compatible)



Solving equations and inverting matrices

----------------------------------------



   solve

   tensorsolve

   lstsq

   inv

   pinv

   tensorinv



Other matrix operations

-----------------------



   diagonal (Array API compatible)

   matrix_transpose (Array API compatible)



Exceptions

----------



   LinAlgError



"""
# To get sub-modules
from . import linalg  # deprecated in NumPy 2.0
from . import _linalg
from ._linalg import *

__all__ = _linalg.__all__.copy()

from numpy._pytesttester import PytestTester
test = PytestTester(__name__)
del PytestTester