~L ix VdZddlmZddlZddlmZdZdZdeeded efd Zd edeed ed efd ZdeedefdZ dZ ddedee d e eeffdZ dddd efdZdddeded e eeffdZdddeded e eeffdZ dddd e eeffdZ dddddede d e eeffdZy) z8Various linear algebra utility methods for internal use.)OptionalN)Tensorct|tjr|jtjk(Sd}tj j s|dt|z }t|)zpCheck if tensor A is a sparse COO tensor. All other sparse storage formats (CSR, CSC, etc...) will return False.zexpected Tensorz but got ) isinstancetorchrlayout sparse_coojit is_scriptingtype TypeError)A error_strs Y/mnt/ssd/data/python-lab/Trading/venv/lib/python3.12/site-packages/torch/_linalg_utils.py is_sparser sZ!U\\"xx5++++!I 99 ! ! #ya ** I c|j}|tjtjtjfvr|StjS)zTReturn the floating point dtype of tensor A. Integer types map to float32. )dtyperfloat16float32float64)rrs rget_floating_dtypers7 GGE  u}}== ==rrBreturnc||St|r tjj||Stj||S)ziMultiply two matrices. If A is None, return B. A can be sparse or dense. B is always dense. )rrsparsemmmatmul)rrs rrr s;  y|||q!$$ <<1 rXYcBt|jt||S)z2Return bilinear form of matrices: :math:`X^T A Y`.)rmT)rrr s rbformr#-s !$$q! %%rSct|||S)z&Return quadratic form :math:`S^T A S`.)r#)rr$s rqformr&2s Aq>rcTtjj|jS)z%Return orthogonal basis of A columns.)rlinalgqrQ)rs rbasisr+7s <Js  ` rr;ctd)NaThis function was deprecated since version 1.9 and is now removed. `torch.solve` is deprecated in favor of `torch.linalg.solve`. `torch.linalg.solve` has its arguments reversed and does not return the LU factorization. To get the LU factorization see `torch.lu`, which can be used with `torch.lu_solve` or `torch.lu_unpack`. X = torch.solve(B, A).solution should be replaced with: X = torch.linalg.solve(A, B)r9r;rr7s rsolverARs  ' rctd)NaThis function was deprecated since version 1.9 and is now removed. `torch.lstsq` is deprecated in favor of `torch.linalg.lstsq`. `torch.linalg.lstsq` has reversed arguments and does not return the QR decomposition in the returned tuple (although it returns other information about the problem). To get the QR decomposition consider using `torch.linalg.qr`. The returned solution in `torch.lstsq` stored the residuals of the solution in the last m - n columns of the returned value whenever m > n. In torch.linalg.lstsq, the residuals are in the field 'residuals' of the returned named tuple. The unpacking of the solution, as in X, _ = torch.lstsq(B, A).solution[:A.size(1)] should be replaced with: X = torch.linalg.lstsq(A, B).solutionr9r@s rlstsqrC^s  0  rctd)NaThis function was deprecated since version 1.9 and is now removed. The default behavior has changed from using the upper triangular portion of the matrix by default to using the lower triangular portion. L, _ = torch.symeig(A, upper=upper) should be replaced with: L = torch.linalg.eigvalsh(A, UPLO='U' if upper else 'L') and L, V = torch.symeig(A, eigenvectors=True) should be replaced with: L, V = torch.linalg.eigh(A, UPLO='U' if upper else 'L')r9)r; eigenvectorsupperr7s r_symeigrGos  B  r)evselfrEctd)NaThis function was deprecated since version 1.9 and is now removed. `torch.linalg.eig` returns complex tensors of dtype `cfloat` or `cdouble` rather than real tensors mimicking complex tensors. L, _ = torch.eig(A) should be replaced with: L_complex = torch.linalg.eigvals(A) and L, V = torch.eig(A, eigenvectors=True) should be replaced with: L_complex, V_complex = torch.linalg.eig(A)r9)rJrErHrIs reigrLs  5  r)F)NF)FT)__doc__typingrrrrrrr#r&r+booltupler6r>rArCrGrLrrrRsk>  hv 6 f &V&(&V&& Xf &  f x~ %:O &,0  F E&&.4I ,0FE&&.4I&    66> .     66> r