*`i4.ddlZgdZdZdZdZdZdS)N))sparse_semi_structured_from_dense_cutlass'sparse_semi_structured_to_dense_cutlass mask_creatorctjd||dddfd|}tjd|||d}d}|jdkrdnd}||z|z|dzdzz|dzd zz||zd zdzdzz||zdzd zz}|dzdk|dzdkztj}|dzdk|dzdkztj} ||| z z }||| z z}d} || z} || z} | |z| z|| zz| zd S) Nrdevice@ )torcharangerepeatitemsizetoint8view) m meta_ncols meta_dtyperdst_rowsdst_colsgroup_xgroup_ytopright bottomleft interleavecols_majcols_mins /home/jaya/work/projects/VOICE-AGENT/VIET/agent-env/lib/python3.11/site-packages/compressed_tensors/utils/semi_structured_conversions.py*_calculate_meta_reordering_scatter_offsetsr%-s|Aq000D9@@JOOH|Az&999@@AFFHG'1,,bb"G Gg% a<1   a :z6LA|TYYr]];;; N'':66 77r&c |dkr%td|d|j\}}|j}|dkr%td|d|j|krtd|d|jd|j}|t jt jfvrtd|d |jd zd z}|jt j krd nd}|j\}} ||krtd |d || |z|zd|zkrtd|d| |z|zdzdt|| ||} t j | dd|  || } t j || d|zf||} |d kr| dz| dddddf<| dz dz| dddddf<| d z dz| dddddf<| dz dz| dddddf<| d z dz| ddddd f<| dz dz| dddddf<| dz dz| dddddf<| dz dz| dddddf<n$|d kr| dz| dddddf<| dz dz| dddddf<| d z dz| dddddf<| dz dz| dddddf<| d z dz| ddddd f<| dz dz| dddddf<| dz dz| dddddf<| dz dz| dddddf<| dz dz| ddddd f<| dz dz| dddddf<| dz dz| dddddf<| d z dz| ddddd!f<| d"z dz| dddddf<| d#z dz| ddddd$f<| d%z dz| dddddf<| d&z dz| ddddd'f<| dt jdd|z|z|z|(d z dddd dz} t j|dz|zf|j|}|jt j kr+|d| |dnd| t jd| | t j d| |d|zS))Nr z*Expected 2-dimensional sparse tensor, got r(z(Expected 2-dimensional meta tensor, got zExpected meta matrix to be on z device, got matrix on z devicer)z of meta matrixrrzNumber of rows of meta matrix z4 must be equal to number of columns of spase matrix z#Number of columns of sparse matrix z different from the z<, expected according to the number of columns of meta matrixrr)r6rr,r r0 r.r-r2r  r/ r1 r3r)r+r4r5rr6rr;r7rr:r%r>remptyrrzerosrBreshaper8)rXr\rrDrrrErF meta_nrowsrr]r[meta_2 dense_offsetsrCs r$rrs~ zz||q Z Z Z Z     :z6L <++B//L A A F Fq* U UD[ J223F ""+qqq!!!Qw19,qqq!!!Qw19,qqq!!!Qw19,qqq!!!Qw19,qqq!!!Qw2:-qqq!!!Qw2:-qqq!!!Qw2:-qqq!!!Qw 1 $ $+qqq!!!Qw19,qqq!!!Qw19,qqq!!!Qw19,qqq!!!Qw19,qqq!!!Qw2:-qqq!!!Qw2:-qqq!!!Qw2:-qqq!!!Qw2:-qqq!!!Qw2:-qqq!!!Qw BJ$.qqq!!!Rx BJ$.qqq!!!Rx BJ$.qqq!!!Rx BJ$.qqq!!!Rx BJ$.qqq!!!Rx BJ$.qqq!!!RxKKOO QA W,V<<>    ::aQ  r&c$d}d}d}||zdkrtd|jd|d||z}|||}t j|d dddt||z f}t j |j|j }| d|d |j}|S) aJ Class for creating N:M sparsity masks. Masks will be created using the N:M ratio, where for every block of M weights, N will be pruned based on ranked weight value. Each mask will correspond to the given tensor. :param N: The number of weights in a group to keep :param M: The size of a weight group r rNrzTensor of size z can't be evenly divided into z groupsr r*r)r+indexvalue) numel ValueErrorr5detachabsrkrargsortintonesrrB)tensorNMmask num_groups tensor_temprpw_bs r$rr9s  A A D ||~~Q Xfl X Xa X X X   1$J--//%%''// A>>K M+1 - - -aaa3q1u::o >E *[&{/A B B BC <rss,    (SSSBC8C8C8T^ ^ ^ Br&