def batch_get_sol_params(x_nd, K_nn, bend_coefs, rot_coef=np.r_[1e-4, 1e-4, 1e-1]): n, d = x_nd.shape x_gpu = gpuarray.to_gpu(x_nd) H_arr_gpu = [] for b in bend_coefs: cur_offset = np.zeros((1 + d + n, 1 + d + n), np.float32) cur_offset[d+1:, d+1:] = b * K_nn cur_offset[1:d+1, 1:d+1] = np.diag(rot_coef) H_arr_gpu.append(gpuarray.to_gpu(cur_offset)) H_ptr_gpu = get_gpu_ptrs(H_arr_gpu) A = np.r_[np.zeros((d+1,d+1)), np.c_[np.ones((n,1)), x_nd]].T n_cnts = A.shape[0] _u,_s,_vh = np.linalg.svd(A.T) N = _u[:,n_cnts:] F = np.zeros((n + d + 1, d), np.float32) F[1:d+1, :d] -= np.diag(rot_coef) Q = np.c_[np.ones((n,1)), x_nd, K_nn].astype(np.float32) F = F.astype(np.float32) N = N.astype(np.float32) Q_gpu = gpuarray.to_gpu(Q) Q_arr_gpu = [Q_gpu for _ in range(len(bend_coefs))] Q_ptr_gpu = get_gpu_ptrs(Q_arr_gpu) F_gpu = gpuarray.to_gpu(F) F_arr_gpu = [F_gpu for _ in range(len(bend_coefs))] F_ptr_gpu = get_gpu_ptrs(F_arr_gpu) N_gpu = gpuarray.to_gpu(N) N_arr_gpu = [N_gpu for _ in range(len(bend_coefs))] N_ptr_gpu = get_gpu_ptrs(N_arr_gpu) dot_batch_nocheck(Q_arr_gpu, Q_arr_gpu, H_arr_gpu, Q_ptr_gpu, Q_ptr_gpu, H_ptr_gpu, transa = 'T') # N'HN NHN_arr_gpu, NHN_ptr_gpu = m_dot_batch((N_arr_gpu, N_ptr_gpu, 'T'), (H_arr_gpu, H_ptr_gpu, 'N'), (N_arr_gpu, N_ptr_gpu, 'N')) iH_arr = [] for NHN in NHN_arr_gpu: iH_arr.append(scipy.linalg.inv(NHN.get()).copy()) iH_arr_gpu = [gpuarray.to_gpu_async(iH) for iH in iH_arr] iH_ptr_gpu = get_gpu_ptrs(iH_arr_gpu) proj_mats = m_dot_batch((N_arr_gpu, N_ptr_gpu, 'N'), (iH_arr_gpu, iH_ptr_gpu, 'N'), (N_arr_gpu, N_ptr_gpu, 'T'), (Q_arr_gpu, Q_ptr_gpu, 'T')) offset_mats = m_dot_batch((N_arr_gpu, N_ptr_gpu, 'N'), (iH_arr_gpu, iH_ptr_gpu, 'N'), (N_arr_gpu, N_ptr_gpu, 'T'), (F_arr_gpu, F_ptr_gpu, 'N')) return proj_mats, offset_mats
def batch_get_sol_params(x_nd, K_nn, bend_coefs, rot_coef): n, d = x_nd.shape x_gpu = gpuarray.to_gpu(x_nd) H_arr_gpu = [] for b in bend_coefs: cur_offset = np.zeros((1 + d + n, 1 + d + n), np.float64) cur_offset[d + 1:, d + 1:] = b * K_nn cur_offset[1:d + 1, 1:d + 1] = np.diag(rot_coef) H_arr_gpu.append(gpuarray.to_gpu(cur_offset)) H_ptr_gpu = get_gpu_ptrs(H_arr_gpu) A = np.r_[np.zeros((d + 1, d + 1)), np.c_[np.ones((n, 1)), x_nd]].T n_cnts = A.shape[0] _u, _s, _vh = np.linalg.svd(A.T) N = _u[:, n_cnts:] F = np.zeros((n + d + 1, d), np.float64) F[1:d + 1, :d] += np.diag(rot_coef) Q = np.c_[np.ones((n, 1)), x_nd, K_nn].astype(np.float64) F = F.astype(np.float64) N = N.astype(np.float64) Q_gpu = gpuarray.to_gpu(Q) Q_arr_gpu = [Q_gpu for _ in range(len(bend_coefs))] Q_ptr_gpu = get_gpu_ptrs(Q_arr_gpu) F_gpu = gpuarray.to_gpu(F) F_arr_gpu = [F_gpu for _ in range(len(bend_coefs))] F_ptr_gpu = get_gpu_ptrs(F_arr_gpu) N_gpu = gpuarray.to_gpu(N) N_arr_gpu = [N_gpu for _ in range(len(bend_coefs))] N_ptr_gpu = get_gpu_ptrs(N_arr_gpu) dot_batch_nocheck(Q_arr_gpu, Q_arr_gpu, H_arr_gpu, Q_ptr_gpu, Q_ptr_gpu, H_ptr_gpu, transa='T') # N'HN NHN_arr_gpu, NHN_ptr_gpu = m_dot_batch((N_arr_gpu, N_ptr_gpu, 'T'), (H_arr_gpu, H_ptr_gpu, 'N'), (N_arr_gpu, N_ptr_gpu, 'N')) iH_arr = [] for NHN in NHN_arr_gpu: iH_arr.append(scipy.linalg.inv(NHN.get()).copy()) iH_arr_gpu = [gpuarray.to_gpu_async(iH) for iH in iH_arr] iH_ptr_gpu = get_gpu_ptrs(iH_arr_gpu) proj_mats = m_dot_batch( (N_arr_gpu, N_ptr_gpu, 'N'), (iH_arr_gpu, iH_ptr_gpu, 'N'), (N_arr_gpu, N_ptr_gpu, 'T'), (Q_arr_gpu, Q_ptr_gpu, 'T')) offset_mats = m_dot_batch( (N_arr_gpu, N_ptr_gpu, 'N'), (iH_arr_gpu, iH_ptr_gpu, 'N'), (N_arr_gpu, N_ptr_gpu, 'T'), (F_arr_gpu, F_ptr_gpu, 'N')) return proj_mats, offset_mats
def test_batch_get_sol_params(f, bend_coefs, rot_coef, atol=1e-7, index=0): seg_info = f.items()[index][1] inv_group = seg_info['inv'] ds_key = 'DS_SIZE_{}'.format(DS_SIZE) x_nd = inv_group[ds_key]['scaled_cloud_xyz'][:] K_nn = inv_group[ds_key]['scaled_K_nn'][:] n, d = x_nd.shape x_gpu = gpuarray.to_gpu(x_nd) H_arr_gpu = [] for b in bend_coefs: cur_offset = np.zeros((1 + d + n, 1 + d + n), np.float64) cur_offset[d + 1:, d + 1:] = b * K_nn cur_offset[1:d + 1, 1:d + 1] = np.diag(rot_coef) H_arr_gpu.append(gpuarray.to_gpu(cur_offset)) H_ptr_gpu = get_gpu_ptrs(H_arr_gpu) A = np.r_[np.zeros((d + 1, d + 1)), np.c_[np.ones((n, 1)), x_nd]].T n_cnts = A.shape[0] _u, _s, _vh = np.linalg.svd(A.T) N = _u[:, n_cnts:] F = np.zeros((n + d + 1, d), np.float64) F[1:d + 1, :d] += np.diag(rot_coef) Q = np.c_[np.ones((n, 1)), x_nd, K_nn].astype(np.float64) F = F.astype(np.float64) N = N.astype(np.float64) Q_gpu = gpuarray.to_gpu(Q) Q_arr_gpu = [Q_gpu for _ in range(len(bend_coefs))] Q_ptr_gpu = get_gpu_ptrs(Q_arr_gpu) F_gpu = gpuarray.to_gpu(F) F_arr_gpu = [F_gpu for _ in range(len(bend_coefs))] F_ptr_gpu = get_gpu_ptrs(F_arr_gpu) N_gpu = gpuarray.to_gpu(N) N_arr_gpu = [N_gpu for _ in range(len(bend_coefs))] N_ptr_gpu = get_gpu_ptrs(N_arr_gpu) dot_batch_nocheck(Q_arr_gpu, Q_arr_gpu, H_arr_gpu, Q_ptr_gpu, Q_ptr_gpu, H_ptr_gpu, transa='T') QTQ = Q.T.dot(Q) H_list = [] for i, bend_coef in enumerate(bend_coefs): H = QTQ H[d + 1:, d + 1:] += bend_coef * K_nn rot_coefs = np.ones(d) * rot_coef if np.isscalar( rot_coef) else rot_coef H[1:d + 1, 1:d + 1] += np.diag(rot_coefs) # ipdb.set_trace() H_list.append(H) # N'HN NHN_arr_gpu, NHN_ptr_gpu = m_dot_batch((N_arr_gpu, N_ptr_gpu, 'T'), (H_arr_gpu, H_ptr_gpu, 'N'), (N_arr_gpu, N_ptr_gpu, 'N')) NHN_list = [N.T.dot(H.dot(N)) for H in H_list] for i, NHN in enumerate(NHN_list): assert (np.allclose(NHN, NHN_arr_gpu[i].get(), atol=atol)) iH_arr = [] for NHN in NHN_arr_gpu: iH_arr.append(scipy.linalg.inv(NHN.get()).copy()) h_inv_list = [scipy.linalg.inv(NHN) for NHN in NHN_list] assert (np.allclose(iH_arr, h_inv_list, atol=atol)) iH_arr_gpu = [gpuarray.to_gpu_async(iH) for iH in iH_arr] iH_ptr_gpu = get_gpu_ptrs(iH_arr_gpu) proj_mats = m_dot_batch( (N_arr_gpu, N_ptr_gpu, 'N'), (iH_arr_gpu, iH_ptr_gpu, 'N'), (N_arr_gpu, N_ptr_gpu, 'T'), (Q_arr_gpu, Q_ptr_gpu, 'T')) proj_mats_list = [N.dot(h_inv.dot(N.T.dot(Q.T))) for h_inv in h_inv_list] assert (np.allclose(proj_mats_list, proj_mats[0][index].get(), atol=atol)) offset_mats = m_dot_batch( (N_arr_gpu, N_ptr_gpu, 'N'), (iH_arr_gpu, iH_ptr_gpu, 'N'), (N_arr_gpu, N_ptr_gpu, 'T'), (F_arr_gpu, F_ptr_gpu, 'N')) offset_mats_list = [N.dot(h_inv.dot(N.T.dot(F))) for h_inv in h_inv_list] assert (np.allclose(offset_mats_list, offset_mats[0][index].get(), atol=atol))
def test_batch_get_sol_params(f, bend_coefs, rot_coef, atol=1e-7, index=0): seg_info = f.items()[index][1] inv_group = seg_info['inv'] ds_key = 'DS_SIZE_{}'.format(DS_SIZE) x_nd = inv_group[ds_key]['scaled_cloud_xyz'][:] K_nn = inv_group[ds_key]['scaled_K_nn'][:] n, d = x_nd.shape x_gpu = gpuarray.to_gpu(x_nd) H_arr_gpu = [] for b in bend_coefs: cur_offset = np.zeros((1 + d + n, 1 + d + n), np.float64) cur_offset[d+1:, d+1:] = b * K_nn cur_offset[1:d+1, 1:d+1] = np.diag(rot_coef) H_arr_gpu.append(gpuarray.to_gpu(cur_offset)) H_ptr_gpu = get_gpu_ptrs(H_arr_gpu) A = np.r_[np.zeros((d+1,d+1)), np.c_[np.ones((n,1)), x_nd]].T n_cnts = A.shape[0] _u,_s,_vh = np.linalg.svd(A.T) N = _u[:,n_cnts:] F = np.zeros((n + d + 1, d), np.float64) F[1:d+1, :d] += np.diag(rot_coef) Q = np.c_[np.ones((n,1)), x_nd, K_nn].astype(np.float64) F = F.astype(np.float64) N = N.astype(np.float64) Q_gpu = gpuarray.to_gpu(Q) Q_arr_gpu = [Q_gpu for _ in range(len(bend_coefs))] Q_ptr_gpu = get_gpu_ptrs(Q_arr_gpu) F_gpu = gpuarray.to_gpu(F) F_arr_gpu = [F_gpu for _ in range(len(bend_coefs))] F_ptr_gpu = get_gpu_ptrs(F_arr_gpu) N_gpu = gpuarray.to_gpu(N) N_arr_gpu = [N_gpu for _ in range(len(bend_coefs))] N_ptr_gpu = get_gpu_ptrs(N_arr_gpu) dot_batch_nocheck(Q_arr_gpu, Q_arr_gpu, H_arr_gpu, Q_ptr_gpu, Q_ptr_gpu, H_ptr_gpu, transa = 'T') QTQ = Q.T.dot(Q) H_list = [] for i, bend_coef in enumerate(bend_coefs): H = QTQ H[d+1:,d+1:] += bend_coef * K_nn rot_coefs = np.ones(d) * rot_coef if np.isscalar(rot_coef) else rot_coef H[1:d+1, 1:d+1] += np.diag(rot_coefs) # ipdb.set_trace() H_list.append(H) # N'HN NHN_arr_gpu, NHN_ptr_gpu = m_dot_batch((N_arr_gpu, N_ptr_gpu, 'T'), (H_arr_gpu, H_ptr_gpu, 'N'), (N_arr_gpu, N_ptr_gpu, 'N')) NHN_list = [N.T.dot(H.dot(N)) for H in H_list] for i, NHN in enumerate(NHN_list): assert(np.allclose(NHN, NHN_arr_gpu[i].get(), atol=atol)) iH_arr = [] for NHN in NHN_arr_gpu: iH_arr.append(scipy.linalg.inv(NHN.get()).copy()) h_inv_list = [scipy.linalg.inv(NHN) for NHN in NHN_list] assert(np.allclose(iH_arr, h_inv_list, atol=atol)) iH_arr_gpu = [gpuarray.to_gpu_async(iH) for iH in iH_arr] iH_ptr_gpu = get_gpu_ptrs(iH_arr_gpu) proj_mats = m_dot_batch((N_arr_gpu, N_ptr_gpu, 'N'), (iH_arr_gpu, iH_ptr_gpu, 'N'), (N_arr_gpu, N_ptr_gpu, 'T'), (Q_arr_gpu, Q_ptr_gpu, 'T')) proj_mats_list = [N.dot(h_inv.dot(N.T.dot(Q.T))) for h_inv in h_inv_list] assert(np.allclose(proj_mats_list, proj_mats[0][index].get(), atol=atol)) offset_mats = m_dot_batch((N_arr_gpu, N_ptr_gpu, 'N'), (iH_arr_gpu, iH_ptr_gpu, 'N'), (N_arr_gpu, N_ptr_gpu, 'T'), (F_arr_gpu, F_ptr_gpu, 'N')) offset_mats_list = [N.dot(h_inv.dot(N.T.dot(F))) for h_inv in h_inv_list] assert(np.allclose(offset_mats_list, offset_mats[0][index].get(), atol=atol))