bi dZddlmZddlmZddlmZmZddlZ dee dfdee dffd Z d eee dfdee dffd Z d ee dfd ee dfdeee dfee dfee dfffdZ d ee dfd ee dfdee dffdZde fdZy)a, Copyright 2013 Steven Diamond 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. )reduce)mul)ListTupleNshape.returnc&td|DS)Nc3,K|] }|dk7s |yw)N).0dims P/home/cdr/jupyterlab/.venv/lib/python3.12/site-packages/cvxpy/utilities/shape.py zsqueezed..s22s )tuplers rsqueezedrs 22 22shapesc&tj|S)a Give the shape resulting from summing a list of shapes. Summation semantics are exactly the same as NumPy's, including broadcasting. Parameters ---------- shapes : list of tuples The shapes of the summands Returns ------- tuple The shape of the sum. Raises ------ ValueError If the shapes are not compatible. )npbroadcast_shapes)rs r sum_shapesrs,    ''rlh_shaperh_shapec|r|s tdt|dk(rd|zn|}t|dk(r|dzn|}|d|dk7rtd|d|t|dkDst|dkDr+ tj|d d|d d}||d|dfz}n |d|df}|||fS#t$rtd|d|wxYw) a Promotes shapes as necessary and returns promoted shape of product. If lh_shape is of length one, prepend a one to it. If rh_shape is of length one, append a one to it. If either shape is greater than 2, apply broadcasting rules on the outer dimensions. Parameters ---------- lh_shape : tuple The left-hand shape of a multiplication operation. rh_shape : tuple The right-hand shape of a multiplication operation. Returns ------- tuple The promoted left-hand shape. tuple The promoted right-hand shape. tuple The promoted shape of the product. Raises ------ ValueError If either of the shapes are scalars, or if the shapes are incompatible. z+Multiplication by scalars is not permitted.r )r zIncompatible dimensions  N) ValueErrorlenrr)rr outer_dimsrs rmul_shapes_promoter$4s> 8FGG#&h-1"4th(H"%h-1"4x$(H|x|#HhOPP 8}qCMA- U,,Xcr]HSbMJJhrlHRL99"x|, h &&  U(ST T Us 3B,,Ccd||}}t||\}}}||k7r |dd|dfz}||k7r|dd}|S)a? Give the shape resulting from multiplying two shapes. Adheres the semantics of np.matmul and additionally permits multiplication by scalars. The broadcasting rules are the same as NumPy's. Parameters ---------- lh_shape : tuple The left-hand shape of a multiplication operation. rh_shape : tuple The right-hand shape of a multiplication operation. Returns ------- tuple The shape of the product as per matmul semantics. Raises ------ ValueError If either of the shapes are scalar. Nrr)r$)rrlh_oldrh_oldrs r mul_shapesr(isV0xFF 28X FHh6cr eBi\)6cr  Lrc$tt|dS)a Compute the size of a given shape by multiplying the sizes of each axis. This is a replacement for np.prod(shape, dtype=int) which is much slower for small arrays than the implementation below. Parameters ---------- shape : tuple a tuple of integers describing the shape of an object Returns ------- int The size of an object corresponding to shape. r )rrrs rsize_from_shaper*s" #ua  r)__doc__ functoolsroperatorrtypingrrnumpyrintrrr$r(r*r rrr1s3E#s(O3c3h3(tE#s(O,(sCx(22'CHo2').sCx2' 5c?E#s(OU38_ <=2'jsCxE#s(OcSVhB!c!r