OpenBLAS/benchmark/pybench/openblas_wrap/blas_lapack.pyf.src

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!
! Taken from scipy/linalg
!
! Shorthand notations
!
! <tchar=s,d,cs,zd>
! <tchar2c=cs,zd>
!
! <prefix2=s,d>
! <prefix2c=c,z>
! <prefix3=s,sc>
! <prefix4=d,dz>
! <prefix6=s,d,c,z,c,z>
!
! <ftype2=real,double precision>
! <ftype2c=complex,double complex>
! <ftype3=real,complex>
! <ftype4=double precision,double complex>
! <ftypereal3=real,real>
! <ftypereal4=double precision,double precision>
! <ftype6=real,double precision,complex,double complex,\2,\3>
! <ftype6creal=real,double precision,complex,double complex,\0,\1>
!
! <ctype2=float,double>
! <ctype2c=complex_float,complex_double>
! <ctype3=float,complex_float>
! <ctype4=double,complex_double>
! <ctypereal3=float,float>
! <ctypereal4=double,double>
! <ctype6=float,double,complex_float,complex_double,\2,\3>
! <ctype6creal=float,double,complex_float,complex_double,\0,\1>
!
!
! Level 1 BLAS
!
python module _flapack
usercode '''
#define F_INT int
'''
interface
subroutine <prefix>axpy(n,a,x,offx,incx,y,offy,incy)
! Calculate z = a*x+y, where a is scalar.
callstatement (*f2py_func)(&n,&a,x+offx,&incx,y+offy,&incy)
callprotoargument F_INT*,<ctype>*,<ctype>*,F_INT*,<ctype>*,F_INT*
<ftype> dimension(*), intent(in) :: x
<ftype> dimension(*), intent(in,out,out=z) :: y
<ftype> optional, intent(in):: a=<1.0,\0,(1.0\,0.0),\2>
integer optional, intent(in),check(incx>0||incx<0) :: incx = 1
integer optional, intent(in),check(incy>0||incy<0) :: incy = 1
integer optional, intent(in),depend(x) :: offx=0
integer optional, intent(in),depend(y) :: offy=0
check(offx>=0 && offx<len(x)) :: offx
check(offy>=0 && offy<len(y)) :: offy
integer optional, intent(in),depend(x,incx,offx,y,incy,offy) :: &
n = (len(x)-offx)/abs(incx)
check(len(x)-offx>(n-1)*abs(incx)) :: n
check(len(y)-offy>(n-1)*abs(incy)) :: n
end subroutine <prefix>axpy
function ddot(n,x,offx,incx,y,offy,incy) result (xy)
! Computes a vector-vector dot product.
callstatement ddot_return_value = (*f2py_func)(&n,x+offx,&incx,y+offy,&incy)
callprotoargument F_INT*,double*,F_INT*,double*,F_INT*
intent(c) ddot
fortranname F_FUNC(ddot,DDOT)
double precision dimension(*), intent(in) :: x
double precision dimension(*), intent(in) :: y
double precision ddot,xy
integer optional, intent(in),check(incx>0||incx<0) :: incx = 1
integer optional, intent(in),check(incy>0||incy<0) :: incy = 1
integer optional, intent(in),depend(x) :: offx=0
integer optional, intent(in),depend(y) :: offy=0
check(offx>=0 && offx<len(x)) :: offx
check(offy>=0 && offy<len(y)) :: offy
integer optional, intent(in),depend(x,incx,offx,y,incy,offy) :: &
n = (len(x)-offx)/abs(incx)
check(len(x)-offx>(n-1)*abs(incx)) :: n
check(len(y)-offy>(n-1)*abs(incy)) :: n
end function ddot
function <prefix4>nrm2(n,x,offx,incx) result(n2)
<ftypereal4> <prefix4>nrm2, n2
callstatement <prefix4>nrm2_return_value = (*f2py_func)(&n,x+offx,&incx)
callprotoargument F_INT*,<ctype4>*,F_INT*
intent(c) <prefix4>nrm2
fortranname F_FUNC(<prefix4>nrm2,<D,DZ>NRM2)
<ftype4> dimension(*),intent(in) :: x
integer optional, intent(in),check(incx>0) :: incx = 1
integer optional,intent(in),depend(x) :: offx=0
check(offx>=0 && offx<len(x)) :: offx
integer optional,intent(in),depend(x,incx,offx) :: n = (len(x)-offx)/abs(incx)
check(len(x)-offx>(n-1)*abs(incx)) :: n
end function <prefix4>nrm2
!
! Level 3 BLAS
!
subroutine <prefix>gemm(m,n,k,alpha,a,b,beta,c,trans_a,trans_b,lda,ka,ldb,kb)
! Computes a scalar-matrix-matrix product and adds the result to a
! scalar-matrix product.
!
! c = gemm(alpha,a,b,beta=0,c=0,trans_a=0,trans_b=0,overwrite_c=0)
! Calculate C <- alpha * op(A) * op(B) + beta * C
callstatement (*f2py_func)((trans_a?(trans_a==2?"C":"T"):"N"), &
(trans_b?(trans_b==2?"C":"T"):"N"),&m,&n,&k,&alpha,a,&lda,b,&ldb,&beta,c,&m)
callprotoargument char*,char*,F_INT*,F_INT*,F_INT*,<ctype>*,<ctype>*,F_INT*,<ctype>*, &
F_INT*,<ctype>*,<ctype>*,F_INT*
integer optional,intent(in),check(trans_a>=0 && trans_a <=2) :: trans_a = 0
integer optional,intent(in),check(trans_b>=0 && trans_b <=2) :: trans_b = 0
<ftype> intent(in) :: alpha
<ftype> intent(in),optional :: beta = <0.0,\0,(0.0\,0.0),\2>
<ftype> dimension(lda,ka),intent(in) :: a
<ftype> dimension(ldb,kb),intent(in) :: b
<ftype> dimension(m,n),intent(in,out,copy),depend(m,n),optional :: c
check(shape(c,0)==m && shape(c,1)==n) :: c
integer depend(a),intent(hide) :: lda = shape(a,0)
integer depend(a),intent(hide) :: ka = shape(a,1)
integer depend(b),intent(hide) :: ldb = shape(b,0)
integer depend(b),intent(hide) :: kb = shape(b,1)
integer depend(a,trans_a,ka,lda),intent(hide):: m = (trans_a?ka:lda)
integer depend(a,trans_a,ka,lda),intent(hide):: k = (trans_a?lda:ka)
integer depend(b,trans_b,kb,ldb,k),intent(hide),check(trans_b?kb==k:ldb==k) :: &
n = (trans_b?ldb:kb)
end subroutine <prefix>gemm
subroutine <prefix6><sy,\0,\0,\0,he,he>rk(n,k,alpha,a,beta,c,trans,lower,lda,ka)
! performs one of the symmetric rank k operations
! C := alpha*A*A**T + beta*C, or C := alpha*A**T*A + beta*C,
!
! c = syrk(alpha,a,beta=0,c=0,trans=0,lower=0,overwrite_c=0)
!
callstatement (*f2py_func)((lower?"L":"U"), &
(trans?(trans==2?"C":"T"):"N"), &n,&k,&alpha,a,&lda,&beta,c,&n)
callprotoargument char*,char*,F_INT*,F_INT*,<ctype6>*,<ctype6>*,F_INT*,<ctype6>*, &
<ctype6>*,F_INT*
integer optional, intent(in),check(lower==0||lower==1) :: lower = 0
integer optional,intent(in),check(trans>=0 && trans <=2) :: trans = 0
<ftype6> intent(in) :: alpha
<ftype6> intent(in),optional :: beta = <0.0,\0,(0.0\,0.0),\2,\2,\2>
<ftype6> dimension(lda,ka),intent(in) :: a
<ftype6> dimension(n,n),intent(in,out,copy),depend(n),optional :: c
check(shape(c,0)==n && shape(c,1)==n) :: c
integer depend(a),intent(hide) :: lda = shape(a,0)
integer depend(a),intent(hide) :: ka = shape(a,1)
integer depend(a, trans, ka, lda), intent(hide) :: n = (trans ? ka : lda)
integer depend(a, trans, ka, lda), intent(hide) :: k = (trans ? lda : ka)
end subroutine <prefix6><sy,\0,\0,\0,he,he>rk
!
! LAPACK
!
subroutine <prefix>gesv(n,nrhs,a,piv,b,info)
! lu,piv,x,info = gesv(a,b,overwrite_a=0,overwrite_b=0)
! Solve A * X = B.
! A = P * L * U
! U is upper diagonal triangular, L is unit lower triangular,
! piv pivots columns.
callstatement {F_INT i;(*f2py_func)(&n,&nrhs,a,&n,piv,b,&n,&info);for(i=0;i\<n;--piv[i++]);}
callprotoargument F_INT*,F_INT*,<ctype>*,F_INT*,F_INT*,<ctype>*,F_INT*,F_INT*
integer depend(a),intent(hide):: n = shape(a,0)
integer depend(b),intent(hide):: nrhs = shape(b,1)
<ftype> dimension(n,n),check(shape(a,0)==shape(a,1)) :: a
integer dimension(n),depend(n),intent(out) :: piv
<ftype> dimension(n,nrhs),check(shape(a,0)==shape(b,0)),depend(n) :: b
integer intent(out)::info
intent(in,out,copy,out=x) b
intent(in,out,copy,out=lu) a
end subroutine <prefix>gesv
subroutine <prefix2>gesdd(m,n,minmn,u0,u1,vt0,vt1,a,compute_uv,full_matrices,u,s,vt,work,lwork,iwork,info)
! u,s,vt,info = gesdd(a,compute_uv=1,lwork=..,overwrite_a=0)
! Compute the singular value decomposition (SVD) using divide and conquer:
! A = U * SIGMA * transpose(V)
! A - M x N matrix
! U - M x M matrix or min(M,N) x N if full_matrices=False
! SIGMA - M x N zero matrix with a main diagonal filled with min(M,N)
! singular values
! transpose(V) - N x N matrix or N x min(M,N) if full_matrices=False
callstatement (*f2py_func)((compute_uv?(full_matrices?"A":"S"):"N"),&m,&n,a,&m,s,u,&u0,vt,&vt0,work,&lwork,iwork,&info)
callprotoargument char*,F_INT*,F_INT*,<ctype2>*,F_INT*,<ctype2>*,<ctype2>*,F_INT*,<ctype2>*,F_INT*,<ctype2>*,F_INT*,F_INT*,F_INT*
integer intent(in),optional,check(compute_uv==0||compute_uv==1):: compute_uv = 1
integer intent(in),optional,check(full_matrices==0||full_matrices==1):: full_matrices = 1
integer intent(hide),depend(a):: m = shape(a,0)
integer intent(hide),depend(a):: n = shape(a,1)
integer intent(hide),depend(m,n):: minmn = MIN(m,n)
integer intent(hide),depend(compute_uv,minmn) :: u0 = (compute_uv?m:1)
integer intent(hide),depend(compute_uv,minmn, full_matrices) :: u1 = (compute_uv?(full_matrices?m:minmn):1)
integer intent(hide),depend(compute_uv,minmn, full_matrices) :: vt0 = (compute_uv?(full_matrices?n:minmn):1)
integer intent(hide),depend(compute_uv,minmn) :: vt1 = (compute_uv?n:1)
<ftype2> dimension(m,n),intent(in,copy,aligned8) :: a
<ftype2> dimension(minmn),intent(out),depend(minmn) :: s
<ftype2> dimension(u0,u1),intent(out),depend(u0, u1) :: u
<ftype2> dimension(vt0,vt1),intent(out),depend(vt0, vt1) :: vt
<ftype2> dimension(lwork),intent(hide,cache),depend(lwork) :: work
integer optional,intent(in),depend(minmn,compute_uv) &
:: lwork = max((compute_uv?4*minmn*minmn+MAX(m,n)+9*minmn:MAX(14*minmn+4,10*minmn+2+25*(25+8))+MAX(m,n)),1)
integer intent(hide,cache),dimension(8*minmn),depend(minmn) :: iwork
integer intent(out)::info
end subroutine <prefix2>gesdd
subroutine <prefix2>gesdd_lwork(m,n,minmn,u0,vt0,a,compute_uv,full_matrices,u,s,vt,work,lwork,iwork,info)
! LWORK computation for (S/D)GESDD
fortranname <prefix2>gesdd
callstatement (*f2py_func)((compute_uv?(full_matrices?"A":"S"):"N"),&m,&n,&a,&m,&s,&u,&u0,&vt,&vt0,&work,&lwork,&iwork,&info)
callprotoargument char*,F_INT*,F_INT*,<ctype2>*,F_INT*,<ctype2>*,<ctype2>*,F_INT*,<ctype2>*,F_INT*,<ctype2>*,F_INT*,F_INT*,F_INT*
integer intent(in),optional,check(compute_uv==0||compute_uv==1):: compute_uv = 1
integer intent(in),optional,check(full_matrices==0||full_matrices==1):: full_matrices = 1
integer intent(in) :: m
integer intent(in) :: n
integer intent(hide),depend(m,n):: minmn = MIN(m,n)
integer intent(hide),depend(compute_uv,minmn) :: u0 = (compute_uv?m:1)
integer intent(hide),depend(compute_uv,minmn, full_matrices) :: vt0 = (compute_uv?(full_matrices?n:minmn):1)
<ftype2> intent(hide) :: a
<ftype2> intent(hide) :: s
<ftype2> intent(hide) :: u
<ftype2> intent(hide) :: vt
<ftype2> intent(out) :: work
integer intent(hide) :: lwork = -1
integer intent(hide) :: iwork
integer intent(out) :: info
end subroutine <prefix2>gesdd_lwork
subroutine <prefix2>syev(compute_v,lower,n,w,a,lda,work,lwork,info)
! w,v,info = syev(a,compute_v=1,lower=0,lwork=3*n-1,overwrite_a=0)
! Compute all eigenvalues and, optionally, eigenvectors of a
! real symmetric matrix A.
!
! Performance tip:
! If compute_v=0 then set also overwrite_a=1.
callstatement (*f2py_func)((compute_v?"V":"N"),(lower?"L":"U"),&n,a,&lda,w,work,&lwork,&info)
callprotoargument char*,char*,F_INT*,<ctype2>*,F_INT*,<ctype2>*,<ctype2>*,F_INT*,F_INT*
integer optional,intent(in):: compute_v = 1
check(compute_v==1||compute_v==0) compute_v
integer optional,intent(in),check(lower==0||lower==1) :: lower = 0
integer intent(hide),depend(a):: n = shape(a,0)
integer intent(hide),depend(a):: lda = MAX(1,shape(a,0))
<ftype2> dimension(n,n),check(shape(a,0)==shape(a,1)) :: a
intent(in,copy,out,out=v) :: a
<ftype2> dimension(n),intent(out),depend(n) :: w
integer optional,intent(in),depend(n) :: lwork=max(3*n-1,1)
check(lwork>=3*n-1) :: lwork
<ftype2> dimension(lwork),intent(hide),depend(lwork) :: work
integer intent(out) :: info
end subroutine <prefix2>syev
subroutine <prefix2>syev_lwork(lower,n,w,a,lda,work,lwork,info)
! LWORK routines for syev
fortranname <prefix2>syev
callstatement (*f2py_func)("N",(lower?"L":"U"),&n,&a,&lda,&w,&work,&lwork,&info)
callprotoargument char*,char*,F_INT*,<ctype2>*,F_INT*,<ctype2>*,<ctype2>*,F_INT*,F_INT*
integer intent(in):: n
integer optional,intent(in),check(lower==0||lower==1) :: lower = 0
integer intent(hide),depend(n):: lda = MAX(1, n)
<ftype2> intent(hide):: a
<ftype2> intent(hide):: w
integer intent(hide):: lwork = -1
<ftype2> intent(out):: work
integer intent(out):: info
end subroutine <prefix2>syev_lwork
end interface
end python module _flapack