/dports/science/py-scipy/scipy-1.7.1/scipy/linalg/ |
H A D | decomp_svd.py | 13 def svd(a, full_matrices=True, compute_uv=True, overwrite_a=False, argument 124 compute_uv=compute_uv, full_matrices=full_matrices) 127 u, s, v, info = gesXd(a1, compute_uv=compute_uv, lwork=lwork, 135 if compute_uv: 225 return svd(a, compute_uv=0, overwrite_a=overwrite_a,
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H A D | flapack_gen.pyf.src | 306 integer intent(in),optional,check(compute_uv==0||compute_uv==1):: compute_uv = 1 311 integer intent(hide),depend(compute_uv,minmn) :: u0 = (compute_uv?m:1) 334 integer intent(in),optional,check(compute_uv==0||compute_uv==1):: compute_uv = 1 339 integer intent(hide),depend(compute_uv,minmn) :: u0 = (compute_uv?m:1) 365 integer intent(in),optional,check(compute_uv==0||compute_uv==1):: compute_uv = 1 370 integer intent(hide),depend(compute_uv,minmn) :: u0 = (compute_uv?m:1) 394 integer intent(in),optional,check(compute_uv==0||compute_uv==1):: compute_uv = 1 426 integer intent(in),optional,check(compute_uv==0||compute_uv==1):: compute_uv = 1 452 integer intent(in),optional,check(compute_uv==0||compute_uv==1):: compute_uv = 1 482 integer intent(in),optional,check(compute_uv==0||compute_uv==1):: compute_uv = 1 [all …]
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/dports/math/py-jax/jax-0.2.9/jax/_src/lax/ |
H A D | linalg.py | 185 if compute_uv: 1126 compute_uv=compute_uv) 1133 c, operand, full_matrices=full_matrices, compute_uv=compute_uv) 1143 if not compute_uv: 1159 if compute_uv: 1183 if not compute_uv: 1211 if not compute_uv: 1230 c, operand, full_matrices=full_matrices, compute_uv=compute_uv) 1234 compute_uv=compute_uv) 1241 if compute_uv: [all …]
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/dports/math/py-theano/Theano-1.0.5/theano/tensor/ |
H A D | nlinalg.py | 567 def __init__(self, full_matrices=True, compute_uv=True): argument 569 self.compute_uv = compute_uv 575 if self.compute_uv: 585 if self.compute_uv: 589 self.compute_uv) 592 s[0] = self._numop(x, self.full_matrices, self.compute_uv) 599 if self.compute_uv: 607 def svd(a, full_matrices=1, compute_uv=1): argument 627 return SVD(full_matrices, compute_uv)(a)
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/dports/science/afni/afni-AFNI_21.3.16/src/pkundu/meica.libs/mdp/utils/ |
H A D | __init__.py | 67 def svd(x, compute_uv = True): argument 72 if compute_uv: 76 s = _mdp.numx_linalg.svd(x, compute_uv=False)
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/dports/science/py-mdp/MDP-3.5/mdp/utils/ |
H A D | __init__.py | 69 def svd(x, compute_uv = True): argument 74 if compute_uv: 78 s = _mdp.numx_linalg.svd(x, compute_uv=False)
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/dports/math/py-theano/Theano-1.0.5/theano/gpuarray/c_code/ |
H A D | magma_svd.c | 12 bool compute_uv = (U != NULL); in APPLY_SPECIFIC() local 62 if (compute_uv) { in APPLY_SPECIFIC() 131 if (compute_uv) { in APPLY_SPECIFIC()
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/dports/math/py-theano/Theano-1.0.5/theano/tensor/tests/ |
H A D | test_nlinalg.py | 163 fn = function([A], svd(A, compute_uv=False)) 168 self.validate_shape((4, 4), full_matrices=True, compute_uv=True) 169 self.validate_shape((4, 4), full_matrices=False, compute_uv=True) 170 self.validate_shape((2, 4), full_matrices=False, compute_uv=True) 171 self.validate_shape((4, 2), full_matrices=False, compute_uv=True) 172 self.validate_shape((4, 4), compute_uv=False) 174 def validate_shape(self, shape, compute_uv=True, full_matrices=True): argument 177 outputs = self.op(A, full_matrices=full_matrices, compute_uv=compute_uv) 178 if not compute_uv:
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/dports/math/py-theano/Theano-1.0.5/theano/gpuarray/ |
H A D | linalg.py | 661 def __init__(self, full_matrices=True, compute_uv=True): argument 663 self.compute_uv = compute_uv 674 if self.compute_uv: 690 if self.compute_uv: 705 if self.compute_uv: 713 def gpu_svd(a, full_matrices=1, compute_uv=1): argument 733 out = GpuMagmaSVD(full_matrices, compute_uv)(a) 734 if compute_uv:
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/dports/finance/py-quantecon/quantecon-0.5.2/quantecon/ |
H A D | rank_nullspace.py | 45 s = svd(A, compute_uv=False)
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/dports/science/py-chainer/chainer-7.8.0/chainerx_cc/chainerx/routines/ |
H A D | linalg.cc | 194 std::tuple<Array, Array, Array> Svd(const Array& a, bool full_matrices, bool compute_uv) { in Svd() argument 207 if (compute_uv) { in Svd() 226 a.device().backend().CallKernel<SvdKernel>(a, u, s, vt, full_matrices, compute_uv); in Svd() 239 compute_uv](BackwardContext& bctx) { in Svd() 243 if (!compute_uv) { in Svd()
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H A D | linalg.h | 18 std::tuple<Array, Array, Array> Svd(const Array& a, bool full_matrices, bool compute_uv);
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/dports/science/py-chainer/chainer-7.8.0/chainerx/linalg/ |
H A D | __init__.pyi | 21 compute_uv: bool=...) -> tp.Union[tp.Tuple[ndarray, ndarray, ndarray], ndarray]: ...
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/dports/math/py-numpy/numpy-1.20.3/numpy/linalg/ |
H A D | linalg.py | 1478 def _svd_dispatcher(a, full_matrices=None, compute_uv=None, hermitian=None): argument 1483 def svd(a, full_matrices=True, compute_uv=True, hermitian=False): argument 1624 if compute_uv: 1647 if compute_uv: 1765 s = svd(x, compute_uv=False) 1901 S = svd(M, compute_uv=False, hermitian=hermitian) 2354 result = op(svd(y, compute_uv=False), axis=-1)
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/dports/science/py-chainer/chainer-7.8.0/chainerx_cc/chainerx/kernels/ |
H A D | linalg.h | 32 …rray& a, const Array& u, const Array& s, const Array& vt, bool full_matrices, bool compute_uv) = 0;
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/dports/science/py-pyscf/pyscf-2.0.1/examples/local_orb/ |
H A D | ulocal.py | 138 sig = scipy.linalg.svd(tij,compute_uv=False) 142 sig = scipy.linalg.svd(tij,compute_uv=False)
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/dports/math/py-mpmath/mpmath-1.2.1/mpmath/matrices/ |
H A D | eigen_symmetric.py | 1523 def svd_r(ctx, A, full_matrices = False, compute_uv = True, overwrite_a = False): argument 1593 if not compute_uv: 1628 def svd_c(ctx, A, full_matrices = False, compute_uv = True, overwrite_a = False): argument 1697 if not compute_uv: 1730 def svd(ctx, A, full_matrices = False, compute_uv = True, overwrite_a = False): argument 1805 …return ctx.svd_c(A, full_matrices = full_matrices, compute_uv = compute_uv, overwrite_a = overwrit… 1807 …return ctx.svd_r(A, full_matrices = full_matrices, compute_uv = compute_uv, overwrite_a = overwrit…
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/dports/science/afni/afni-AFNI_21.3.16/src/pkundu/meica.libs/mdp/nodes/ |
H A D | lle_nodes.py | 158 sig2 = svd(M_Mi, compute_uv=0)**2 240 sig2 = (svd(M_Mi, compute_uv=0))**2 290 sig2 = (svd(M_xi, compute_uv=0))**2
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/dports/science/py-mdp/MDP-3.5/mdp/nodes/ |
H A D | lle_nodes.py | 162 sig2 = svd(M_Mi, compute_uv=0)**2 244 sig2 = (svd(M_Mi, compute_uv=0))**2 294 sig2 = (svd(M_xi, compute_uv=0))**2
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/dports/math/py-numpy/numpy-1.20.3/doc/source/release/ |
H A D | 1.8.2-notes.rst | 14 * gh-4733: fix np.linalg.svd(b, compute_uv=False)
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/dports/math/py-jax/jax-0.2.9/jax/_src/third_party/numpy/ |
H A D | linalg.py | 46 s = la.svd(x, compute_uv=False) 49 s = la.svd(x, compute_uv=False)
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/dports/math/py-jax/jax-0.2.9/jax/_src/numpy/ |
H A D | linalg.py | 56 def svd(a, full_matrices=True, compute_uv=True): argument 58 return lax_linalg.svd(a, full_matrices, compute_uv) 105 S = svd(M, full_matrices=False, compute_uv=False) 413 y = reducer(svd(x, compute_uv=False), axis=-1)
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/dports/science/py-GPy/GPy-1.10.0/GPy/models/ |
H A D | state_space_main.py | 258 compute_uv=True, overwrite_a=False, 267 compute_uv=True, 401 compute_uv=True, 412 compute_uv=True, 1182 (U,S,Vh) = sp.linalg.svd( P_init,full_matrices=False, compute_uv=True, 1412 (U,S,Vh) = sp.linalg.svd( svd_1_matr,full_matrices=False, compute_uv=True, 1721 (U,S,Vh) = sp.linalg.svd( svd_2_matr,full_matrices=False, compute_uv=True, 2405 …(U, S, Vh) = sp.linalg.svd( self.v_Qk, full_matrices=False, compute_uv=True, overwrite_a=False, ch… 2586 full_matrices=False, compute_uv=True, 2629 full_matrices=False, compute_uv=True, [all …]
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/dports/math/py-theano/Theano-1.0.5/theano/gpuarray/tests/ |
H A D | test_linalg.py | 406 def run_gpu_svd(self, A_val, full_matrices=True, compute_uv=True): argument 409 [A], gpu_svd(A, full_matrices=full_matrices, compute_uv=compute_uv), 455 [A], theano.tensor.nlinalg.svd(A, compute_uv=False), 458 [A], gpu_svd(A, compute_uv=False), mode=mode_with_gpu)
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/dports/math/py-autograd/autograd-1.3/autograd/numpy/ |
H A D | linalg.py | 134 def grad_svd(usv_, a, full_matrices=True, compute_uv=True): argument 138 if not compute_uv:
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