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))
