Let's try to construct the KKT matrix from Mattingley and Boyd's CVXGEN paper in numpy and PyTorch:
block, there is no way to infer the appropriate sizes of
the zero and identity matrix blocks.
It is an inconvenience to think about what size these
matrices should be.
Block acts a lot like
np.bmat and replaces:
'I'with an appropriately shaped identity matrix.
'-I'with an appropriately shaped negated identity matrix.
block is meant to be a quick prototyping tool and
there's probably a more efficient way to solve your system
if it has a lot of zeros or identity elements.
blockhandle numpy and PyTorch with the same interface?
I wrote the logic to handle matrix sizing to be agnostic of the matrix library being used. numpy and PyTorch are just backends. More backends can easily be added for your favorite Python matrix library.
class Backend(metaclass=ABCMeta): def extract_shape(self, x): pass def build_eye(self, n): pass def build_full(self, shape, fill_val): pass def build(self, rows): pass def is_complete(self, rows): pass
pip install block
from block import block
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