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How to use maybe_decorate method in Slash

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linqr.py

Source:linqr.py

...179        else:180            return np.vstack([np.atleast_2d(a) for a in arrs])181182    @staticmethod183    @maybe_decorate(nb.njit(nogil=True, parallel=False, cache=True), NUMBA_LEVEL >= 4)184    def _bld_lm_blks(blocks, valid_pts3d, pt3d_idxs, pose_idxs, rr, Jrb, Jrp, Jrl, idx_dtype, pose_size):185        # TODO: debug, some problem with logic present, results are poorer than previous method186        #       - However, not sure if worthwhile to fix, seems execution times are very similar187        #       - NUMBA_LEVEL == 3, seems best execution time -wise, also ok memory use188189        blk_i = 0190        for pt_i in np.arange(len(valid_pts3d), dtype=idx_dtype):191            if not valid_pts3d[pt_i]:192                continue193194            r_idxs = np.where(pt3d_idxs == pt_i)[0].astype(idx_dtype)195            blk_pose_idxs = pose_idxs[r_idxs]196            blk_np = len(r_idxs)197            m, n_b, n_p, n_l = blk_np * 2, Jrb.shape[1], blk_np * pose_size, 3198199            if blk_np < 2:200                # too few observations of this 3d-point201                valid_pts3d[pt_i] = False202                continue203204            if len(blocks) <= blk_i:205                blocks.append(ResidualBlock(r_idxs, blk_pose_idxs, m, n_b, n_p, n_l, pose_size))206207            blk = blocks[blk_i]208            blk.reset()209            blk_i += 1210211            for i, ri in enumerate(r_idxs):212                i = idx_dtype(i)213                for j in range(n_b):214                    j = idx_dtype(j)215                    blk.S[i*2,     j] = Jrb[ri*2,     j]216                    blk.S[i*2 + 1, j] = Jrb[ri*2 + 1, j]217218                for j in range(pose_size):219                    j = idx_dtype(j)220                    blk.S[i*2,     n_b + i * pose_size + j] = Jrp[ri*2,     blk_pose_idxs[i] + j]221                    blk.S[i*2 + 1, n_b + i * pose_size + j] = Jrp[ri*2 + 1, blk_pose_idxs[i] + j]222223                for j in range(n_l):224                    j = idx_dtype(j)225                    blk.S[i*2,     n_b + n_p + j] = Jrl[ri*2,     pt_i * 3 + j]226                    blk.S[i*2 + 1, n_b + n_p + j] = Jrl[ri*2 + 1, pt_i * 3 + j]227228                blk.S[i * 2,     -1] = rr[ri * 2,     idx_dtype(0)]229                blk.S[i * 2 + 1, -1] = rr[ri * 2 + 1, idx_dtype(0)]230231    def build_landmark_blocks(self, rr, Jrb, Jrp, Jrl):232        blk_i = 0233        for i in range(len(self.problem.pts3d)):234            if not self.problem.valid_pts3d[i]:235                continue236237            r_idxs = np.where(self.problem.pt3d_idxs == i)[0].astype(self.idx_dtype)238            blk_np = len(r_idxs)239240            if blk_np < 2:241                # too few observations of this 3d-point242                self.problem.valid_pts3d[i] = False243                continue244245            # indexing sparse array faster this way instead of Jl[v_i, i:i+3]246            pose_idxs = self.problem.pose_idxs[r_idxs]247            _, _, Jrl_i, Jrl_j = self._block_indexing(r_idxs, np.ones((len(r_idxs),), dtype=self.idx_dtype) * i, 2, 3)248            rr_i, _, Jrp_i, Jrp_j = self._block_indexing(r_idxs, pose_idxs, 2, self._pose_size)249            _, _, blk_Jp_i, blk_Jp_j = self._block_indexing(np.arange(blk_np, dtype=self.idx_dtype),250                                                            np.arange(blk_np, dtype=self.idx_dtype), 2, self._pose_size)251252            # create residual vector, assign reprojection residuals253            blk_r = np.zeros((blk_np*2, 1), dtype=self.dtype)254            blk_r[:blk_np*2] = rr[rr_i]255256            # batch jacobian related to reprojection residuals257            blk_Jb = None if Jrb is None else np.array(Jrb[rr_i, :], dtype=self.dtype)    # dense matrix here258259            # create landmark jacobian matrix, assign the three columns related to this landmark260            blk_Jl = np.zeros((blk_np*2, 3), dtype=self.dtype)261            blk_Jl[:blk_np*2, :] = np.array(self._sp_index(Jrl, Jrl_i, Jrl_j).reshape((-1, 3)), dtype=self.dtype)262263            # create pose/frame jacobian matrix, assign all frames that observe this landmark264            blk_Jp = np.zeros((blk_np*2, blk_np*self._pose_size), dtype=self.dtype)265            blk_Jp[blk_Jp_i, blk_Jp_j] = self._sp_index(Jrp, Jrp_i, Jrp_j)266267            if len(self._blocks) <= blk_i:268                m, n_b, n_p, n_l = blk_r.size, blk_Jb.shape[1], blk_Jp.shape[1], blk_Jl.shape[1]269                self._blocks.append(ResidualBlock(r_idxs, pose_idxs, m, n_b, n_p, n_l, self._pose_size))270            self._blocks[blk_i].new_linearization_point(blk_r, blk_Jb, blk_Jp, blk_Jl)271            blk_i += 1272273    def _sp_index(self, A, i, j, safe=False):274        if is_own_sp_mx(A):275            B = np.empty(len(i), dtype=self.dtype)276            A.copyto((i, j), B)277            return B278        # safe is very slow, unsafe is dangerous as bugs won't be found279        return A[i, j] if safe or not sp.issparse(A) else A._get_arrayXarray(i, j)280281    @staticmethod282    def _block_indexing(row_idxs, col_idxs, block_rows, block_cols):283        row_idxs_r = InnerLinearizerQR._augment_idxs(row_idxs, block_rows)284        row_idxs_rc = np.repeat(row_idxs_r, block_cols)285        col_idxs_c = InnerLinearizerQR._augment_idxs(col_idxs, block_cols)286        col_idxs_cr = np.repeat(col_idxs_c.reshape((-1, block_cols)), block_rows, axis=0).flatten()287        return row_idxs_r, col_idxs_c, row_idxs_rc, col_idxs_cr288289    @staticmethod290    def _augment_idxs(idxs, size):291        return (np.repeat(idxs[:, None] * size, size, axis=1) + np.arange(size, dtype=idxs.dtype)[None, :]).flatten()292293    def _apply_huber(self, r, arr_J, total_nr, huber_coef, extra_weight=1.0):294        huber_coef = np.inf if huber_coef is None else huber_coef295296        residual_weight = extra_weight * (total_nr / len(r) if self.use_weighted_residuals else 1.0)297298        abs_r = np.abs(r)299        I = abs_r > huber_coef300        huber_weight = np.ones_like(r)301        huber_weight[I] *= np.sqrt(huber_coef / abs_r[I])302        dwr_dr = np.sqrt(residual_weight * huber_weight)303304        wr = dwr_dr * r305306        if arr_J is None:307            wJ = None308        else:309            wJ = []310            for i, J in enumerate(arr_J):311                if J is None:312                    wJ.append(J)313                elif sp.issparse(J):314                    wJ.append(sp.diags(dwr_dr.flatten()).dot(J))315                elif is_own_sp_mx(J):316                    J.imul_arr(dwr_dr.reshape((dwr_dr.size, -1)))317                    wJ.append(J)318                else:319                    J *= dwr_dr320                    wJ.append(J)321322        err = np.sum(0.5 * residual_weight * huber_weight * (2 - huber_weight) * r ** 2)323        return wr, wJ, err324325    def initial_cost(self):326        return self._total_error / self.residual_count()327328    def residual_count(self):329        return self.problem.pts2d.size + self.problem.meas_r.size + self.problem.meas_aa.size330331    def current_cost(self):332        nr, nx, na = self.problem.pts2d.size, self.problem.meas_r.size, self.problem.meas_aa.size333        rr, *rxra = self.problem.residual(parts=True)334335        if self.problem.inter_batch_repr_count == 0:336            _, _, err = self._apply_huber(rr, None, nr+nx+na, self.huber_coef_repr)337        else:338            c = self.problem.inter_batch_repr_count339            _, _, err1 = self._apply_huber(rr[:-c], None, nr+nx+na, self.huber_coef_repr)340            _, _, err2 = self._apply_huber(rr[-c:], None, nr+nx+na, self.huber_coef_repr,341                                           extra_weight=self.inter_batch_repr_weight)342            err = err1 + err2343        total_error = err344345        if nx > 0:346            rx = rxra[0]347            _, _, err = self._apply_huber(rx, None, nr+nx+na, self.huber_coef_loc)348            total_error += err349350        if na > 0:351            ra = rxra[0 if nx == 0 else 1]352            _, _, err = self._apply_huber(ra, None, nr+nx+na, self.huber_coef_ori)353            total_error += err354355        return total_error / (nr + nx + na)356357    def filter(self, max_repr_err):358        n_obs = len(self.problem.pts2d)359        obs_idx = self.problem.filter(max_repr_err)360        cost = self.current_cost()361        return len(obs_idx)/n_obs, cost362363    def set_pose_damping(self, _lambda):364        self._pose_damping = _lambda365366    def marginalize(self):367        assert self._state == self.STATE_LINEARIZED, 'not linearized yet'368        if NUMBA_LEVEL >= 3:369            with warnings.catch_warnings():370                # for some reason warns about non-contiguous arrays in n_p.dot, can't find any though371                warnings.filterwarnings("ignore")372                self._marginalize(nb.typed.List(self._blocks))373        else:374            self._marginalize(self._blocks)375        self._state = self.STATE_MARGINALIZED376377    @staticmethod378    @maybe_decorate(nb.njit(nogil=True, parallel=False, cache=True), NUMBA_LEVEL >= 3)379    def _marginalize(blocks):380        for blk in blocks:381            blk.marginalize()382383    def backsub_xl(self, delta_xbp):384        assert self._state == self.STATE_MARGINALIZED, 'not linearized yet'385386        l_diff = 0387        delta_xb = delta_xbp[:self.nb]388        delta_xp = delta_xbp[self.nb:].reshape((-1, self._pose_size))389        delta_xl = np.zeros((len(self._blocks), self._blocks[0].n_l), dtype=self.dtype)390        for i, blk in enumerate(self.all_blocks):391            blk_delta_xp = delta_xp[blk.pose_idxs, :].reshape((-1, 1))392            if blk.n_l > 0:393                blk_delta_xbp = np.concatenate((delta_xb, blk_delta_xp), axis=0)394                blk_delta_xl = -np.linalg.solve(blk.R1, blk.Q1T_r + blk.Q1T_Jbp.dot(blk_delta_xbp))395                delta_xl[i, :] = blk_delta_xl.T * blk.Jl_col_scale396            else:397                blk_delta_xbp = blk_delta_xp398399            # calculate linear cost diff400            blk.damp(0)401            QT_J_deltax = blk.QT_Jbp @ blk_delta_xbp402            if blk.n_l > 0:403                QT_J_deltax[:blk.n_l] += blk.R1.dot(blk_delta_xl)404            l_diff -= QT_J_deltax.T.dot(0.5 * QT_J_deltax + blk.QT_r).flatten()[0]405406        return delta_xl, l_diff / self.residual_count()407408    # def get_Q2Tr(self):409    #     return self._Q2.T.dot(self._r)410    #411    # def get_Q2TJp(self):412    #     return self._Q2.T.dot(self._Jp)413    #414    # def get_Q2TJp_premult_x(self, x_r):415    #     return x_r.T.dot(self._Q2.T).dot(self._Jp)416    #417    # def get_Q2TJp_postmult_x(self, xp):418    #     return self._Q2.T.dot(self._Jp.dot(xp))419420    def get_Q2TJbp_T_Q2TJbp_mult_x(self, xp):421        assert self._state == self.STATE_MARGINALIZED422        assert len(self.problem.cam_param_idxs) == 0, 'not implemented for cam param estimation'423        assert len(self.problem.meas_aa) == 0, 'not implemented for absolute measures'424        assert len(self.problem.meas_r) == 0, 'not implemented for absolute measures'425426        y = np.zeros((self._pose_n, self._pose_size))427        for blk in self._blocks:428            blk_xp = xp.reshape((-1, self._pose_size))[blk.pose_idxs, :].reshape((-1, 1))429            blk_y = blk.Q2T_Jbp.T.dot(blk.Q2T_Jbp.dot(blk_xp))430            y[blk.pose_idxs, :] += blk_y.reshape((-1, self._pose_size))431432        return y.reshape((-1, 1))433434    def get_Q2TJbp_T_Q2Tr(self):435        assert self._state == self.STATE_MARGINALIZED436437        brb = np.zeros((self.nb, 1), dtype=self.dtype)438        bp = np.zeros((self._pose_n, self._pose_size), dtype=self.dtype)439        for blk in self.all_blocks:440            Q2T_Jbp = blk.Q2T_Jbp441            if sp.issparse(Q2T_Jbp):442                blk_b = (blk.Q2T_r.T @ Q2T_Jbp).T443            else:444                blk_b = (blk.Q2T_r.T.dot(Q2T_Jbp)).T445            if blk.n_b > 0:446                brb[:self.nb] += blk_b[:blk.n_b]447            bp[blk.pose_idxs, :] += blk_b[blk.n_b:].reshape((-1, self._pose_size))448449        return np.concatenate((brb, bp.reshape((-1, 1))), axis=0)450451    # def get_Q2TJp_diag2(self):452    #     pass453454    def _epow2(self, arr):455        if type(arr) == np.ndarray:456            return arr ** 2457        else:458            assert sp.issparse(arr)459            arr = arr.copy()460            arr.data *= arr.data461            return arr462463    def get_Jbp_diag2(self):464        assert self._state == self.STATE_LINEARIZED465466        db2 = np.zeros((self.nb,), dtype=self.dtype)467        dp2 = np.zeros((self._pose_n, self._pose_size), dtype=self.dtype)468        for blk in self.all_blocks:469            if blk.n_b > 0:470                db2 += np.sum(self._epow2(blk.Jb), axis=0)471            dp2[blk.pose_idxs, :] += np.sum(self._epow2(blk.Jp), axis=0).reshape((-1, self._pose_size))472473        return np.concatenate((db2, dp2.flatten()))474475    def get_Q2TJbp_T_Q2TJbp_blockdiag(self):476        assert self._state == self.STATE_MARGINALIZED477478        # TODO: don't use dense Hpp479480        if 0:481            # too slow482            Hpp = self._get_Q2TJbp_T_Q2TJbp_blockdiag_sp(self.nb, self.np, self._pose_size,483                                                         self._pose_damping, self._blocks, self.dtype)484        elif NUMBA_LEVEL >= 3:485            # no extra memory used486            Hpp = DictArray2D((self.nb + self.np, self.nb + self.np), dtype=self.dtype)487            self._get_Q2TJbp_T_Q2TJbp_blockdiag_lv3(self.nb, self.np, self._pose_size,488                                                    self._pose_damping, self._blocks, Hpp)489        else:490            # uses way too much memory for large problems due to dense Hpp491            Hpp = self._get_Q2TJbp_T_Q2TJbp_blockdiag(self.nb, self.np, self._pose_size, self._pose_damping,492                                                      nb.typed.List([blk.Q2T_Jbp for blk in self._blocks]),493                                                      nb.typed.List([blk.pose_idxs for blk in self._blocks]))494495        for blk in self.non_lm_blocks:496            blk_Hpp = blk.Q2T_Jbp.T.dot(blk.Q2T_Jbp)497            tmp = np.arange(len(blk.pose_idxs))498            _, _, bi, bj = self._block_indexing(tmp, tmp, self._pose_size, self._pose_size)499            _, _, i, j = self._block_indexing(blk.pose_idxs, blk.pose_idxs, self._pose_size, self._pose_size)500            if is_own_sp_mx(Hpp):501                Hpp.idx_isum_arr(i + self.nb, j + self.nb, np.array(blk_Hpp[bi, bj]).flatten())502            else:503                Hpp[i + self.nb, j + self.nb] += np.array(blk_Hpp[bi, bj]).flatten()504505        if sp.issparse(Hpp) and sp.isspmatrix_csc(Hpp):506            return Hpp507        if sp.issparse(Hpp):508            return Hpp.tocsc()509        if is_own_sp_mx(Hpp):510            return own_sp_mx_to_coo(Hpp).tocsc()511        return sp.csc_matrix(Hpp)512513    @staticmethod514    def _get_Q2TJbp_T_Q2TJbp_blockdiag_sp(n_b, n_p, psize, pose_damping, blocks, dtype):515        H = sp.dok_matrix((n_b + n_p, n_b + n_p), dtype=dtype)516517        bj, bi = np.meshgrid(np.arange(n_b), np.arange(n_b))518        pj, pi = np.meshgrid(np.arange(psize), np.arange(psize))519        bj, bi, pj, pi = map(lambda x: x.flatten(), (bj, bi, pj, pi))520521        for blk in blocks:522            if n_b > 0:523                A = blk.Q2T_Jbp[:, 0:n_b]  # should copy or call np.ascontiguousarray?524                blk_Hbb = A.T.dot(A).copy()525                H[bi, bj] += blk_Hbb.flatten()526527            for j, idx in enumerate(blk.pose_idxs):528                g0, b0 = n_b + idx * psize, n_b + j * psize529                A = blk.Q2T_Jbp[:, b0:b0+psize].copy()530                blk_Hpp = A.T.dot(A)531                H[g0 + pi, g0 + pj] += blk_Hpp.flatten()532533        if pose_damping is not None:534            i = np.arange(n_b + n_p, dtype=np.int32)535            H[i, i] += dtype.type(pose_damping)536537        return H538539    @staticmethod540    @maybe_decorate(nb.njit(nogil=True, parallel=False, cache=True), NUMBA_LEVEL >= 3)541    def _get_Q2TJbp_T_Q2TJbp_blockdiag_lv3(_nb, _np, psize, pose_damping, blocks, H):542        for k in range(len(blocks)):543            blk = blocks[k]544            if _nb > 0:545                A = blk.Q2T_Jbp[:, 0:_nb].copy()546                blk_Hbb = A.T.dot(A)547                for i in range(_nb):548                    for j in range(_nb):549                        H[i, j] += blk_Hbb[i, j]550551            for j, idx in enumerate(blk.pose_idxs):552                g0, b0 = _nb + idx * psize, _nb + j * psize553                g1, b1 = g0 + psize, b0 + psize554                A = blk.Q2T_Jbp[:, b0:b1].copy()555                blk_Hpp = A.T.dot(A)556                for i, gi in enumerate(range(g0, g1)):557                    for j, gj in enumerate(range(g0, g1)):558                        H[gi, gj] += blk_Hpp[i, j]559560        if pose_damping is not None:561            val = np.float32(pose_damping)562            for i in range(_nb + _np):563                H[i, i] += val564565    @staticmethod566    @maybe_decorate(nb.njit(nogil=True, parallel=False, cache=True), NUMBA_LEVEL >= 1)567    def _get_Q2TJbp_T_Q2TJbp_blockdiag(_nb, _np, psize, pose_damping, arr_Q2T_Jbp, arr_pose_idxs):568        H = np.zeros((_nb + _np, _nb + _np), dtype=arr_Q2T_Jbp[0].dtype)569        for i, Q2T_Jbp in enumerate(arr_Q2T_Jbp):570            if _nb > 0:571                A = Q2T_Jbp[:, 0:_nb].copy()572                blk_Hbb = A.T.dot(A)573                H[:_nb, :_nb] += blk_Hbb574575            for j, idx in enumerate(arr_pose_idxs[i]):576                g0, b0 = _nb + idx * psize, _nb + j * psize577                g1, b1 = g0 + psize, b0 + psize578                A = Q2T_Jbp[:, b0:b1].copy()579                blk_Hpp = A.T.dot(A)580                H[g0:g1, g0:g1] += blk_Hpp581582        if pose_damping is not None:583            H += pose_damping * np.eye(H.shape[0], dtype=H.dtype)584585        return H586587    def get_Jbp_T_Jbp_blockdiag(self):588        assert self._state == self.STATE_LINEARIZED, 'can only use if state == LINEARIZED'589        assert len(self.problem.cam_param_idxs) == 0, 'not implemented for cam param estimation'590591        Hpp = np.zeros((self.np, self.np), dtype=self.dtype)592        for blk in self.all_blocks:593            for i, idx in enumerate(blk.pose_idxs):594                g0, b0, br0 = blk.pose_idxs[i] * self._pose_size, i * self._pose_size, i * 2595                g1, b1, br1 = g0 + self._pose_size, b0 + self._pose_size, br0 + 2596                blk_Hpp = blk.Jp[br0:br1, b0:b1].T.dot(blk.Jp[br0:br1, b0:b1])597                Hpp[g0:g1, g0:g1] += blk_Hpp598599        if self._pose_damping is not None:600            Hpp += self._pose_damping * np.eye(Hpp.shape[0], dtype=self.dtype)601602        return sp.csc_matrix(Hpp)603604    def scale_Jl_cols(self):605        assert self._state == self.STATE_LINEARIZED, 'can only use if state == LINEARIZED'606        for blk in self._blocks:607            blk.Jl_col_scale = 1 / (self.jacobi_scaling_eps + np.linalg.norm(blk.Jl, axis=0, keepdims=True))608            blk.Jl *= blk.Jl_col_scale609610    def scale_Jbp_cols(self, jac_scaling):611        assert self._state == self.STATE_MARGINALIZED, 'can only use if state == MARGINALIZED'612        jac_rb_scaling = jac_scaling[None, :self.nb]613        jac_rp_scaling = jac_scaling[self.nb:].reshape((-1, self._pose_size))614        for blk in self.all_blocks:615            assert not blk.is_damped() or blk.n_l == 0, 'apply scaling before damping'616            blk_rp = jac_rp_scaling[blk.pose_idxs, :].reshape((1, -1))617            blk_jsc = np.concatenate((jac_rb_scaling, blk_rp), axis=1) if blk.n_l > 0 else blk_rp618            if sp.issparse(blk.QT_Jbp):619                blk.QT_Jbp = blk.QT_Jbp * sp.diags(blk_jsc.flatten())620            else:621                blk_QT_Jbp = blk.QT_Jbp  # direct blk.QT_Jbp inplace multiplication will fail because of @property decorator622                blk_QT_Jbp *= blk_jsc    # same as blk.QT_Jbp = blk.QT_Jbp.dot(n_p.diag(blk_jsc))623624    def set_landmark_damping(self, _lambda):625        assert self._state == self.STATE_MARGINALIZED, 'can only use if state == MARGINALIZED'626        for blk in self._blocks:627            blk.damp(_lambda)628629    def get_stage1(self, precond_mx):630        assert False, 'not implemented'631        # TODO: would need to restructure so that all block level operations implemented at ResidualBlock632633    def get_stage2(self, _lambda, jac_scaling_D, precond_mx):634        assert False, 'not implemented'635636    def right_multiply(self, xp):637        return self.get_Q2TJbp_T_Q2TJbp_mult_x(xp)638639    def nb(self) -> int:640        return len(self.problem.xb)641642643nb_type, idx_type, np_type = nb.float32, nb.int32, np.float32644array_type = nb_type[:, :]645646@maybe_decorate(647    nb.experimental.jitclass([648        ('r_idxs', idx_type[:]),649        ('pose_idxs', idx_type[:]),650        ('m', nb.intp),651        ('n_b', nb.intp),652        ('n_p', nb.intp),653        ('n_l', nb.intp),654        ('psize', nb.intp),655        ('pnum', nb.intp),656        ('S', array_type),657        ('Jl_col_scale', nb.optional(array_type)),658        ('_marginalized', nb.boolean),659        ('_damping_rots', nb.optional(nb.types.ListType(array_type))),660    ]), NUMBA_LEVEL >= 3)661class ResidualBlock:662    def __init__(self, r_idxs, pose_idxs, m, n_b, n_p, n_l, psize=6):663        self.r_idxs = r_idxs664        self.pose_idxs = pose_idxs665        self.psize = psize666        self.m, self.n_b, self.n_p, self.n_l = m, n_b, n_p, n_l667        self.pnum = self.n_p // self.psize668669        self.S = np.empty((self.m + self.n_l, self.n_b + self.n_p + self.n_l + 1), dtype=np_type)670        self.Jl_col_scale = None671        self._marginalized = False672        self._damping_rots = None673674    def reset(self):675        self._marginalized = False676        self._damping_rots = None677        self.S[:] = self.S.dtype.type(0.0)678679    def new_linearization_point(self, r, Jb, Jp, Jl):680        self.reset()681        self.r, self.Jb, self.Jp, self.Jl = r, Jb, Jp, Jl682683    def marginalize(self):684        assert not self.is_marginalized(), 'already marginalized'685        self._marginalize(self.S, self.m, self.n_b, self.n_p, self.n_l)686        self._marginalized = True687688    @staticmethod689    @maybe_decorate(nb.njit(nogil=True, parallel=False, cache=True), NUMBA_LEVEL == 2)690    def _marginalize(_S, m, n_b, n_p, n_l):691        Q, R = np.linalg.qr(_S[:m, n_b + n_p:-1], mode='complete')  # NOTE: numba 0.51.1 doesn't support mode argument,692                                                                    #       this uses own qr function at algo/linalg.py693        if 0:694            # S[:m, ...] is not contiguous, need to ignore warnings in non jitted code695            _S[:m, :n_b + n_p] = Q.T.dot(_S[:m, :n_b + n_p])   # Q.T.dot(Jbp)696            _S[:m, n_b + n_p:-1] = R                           # Q.T.dot(Jl)697            _S[:m, -1:] = Q.T.dot(_S[:m, -1:])                 # Q.T.dot(r)698        else:699            # similar speed as the alternative above, no warnings, maybe needs a bit more memory?700            A = np.ascontiguousarray(_S[:m, :])701            _S[:m, :] = Q.T.dot(A)702703    def damp(self, _lambda):704        assert self.is_marginalized(), 'not yet marginalized'705        assert _lambda >= 0, 'lambda must be >= 0'706707        if self.n_l == 0:708            return709710        if self.is_damped():711            self.undamp()712713        if _lambda == 0:714            pass  # by default lambda already zero if no damping715        else:716            # make and apply givens rotations717            self.S[-self.n_l:, self.n_b + self.n_p:self.n] = np.eye(self.n_l, dtype=self.S.dtype) * np.sqrt(_lambda)718            self._damping_rots = self._damp(self.S, self.n_b + self.n_p, self.n_l)719720    @staticmethod721    @maybe_decorate(nb.njit(nogil=True, parallel=False, cache=True), 3 > NUMBA_LEVEL >= 1)722    def _damp(S, l_idx, k):723        damping_rots = nb.typed.List.empty_list(array_type)724        for n in range(k):725            for m in range(n + 1):726                G = tools.make_givens(S[n, l_idx + n], S[-k + n - m, l_idx + n], dtype=S.dtype)727                tools.apply_givens(S, G, S.shape[0] - k + n - m, n)728                damping_rots.append(G)729        return damping_rots730731    def undamp(self):732        assert self.is_damped(), 'not damped yet'733        self._undamp(self._damping_rots, self.S, self.n_l)734        self._damping_rots = None735736    @staticmethod737    @maybe_decorate(nb.njit(nogil=True, parallel=False, cache=True), 3 > NUMBA_LEVEL >= 1)738    def _undamp(damping_rots, S, k):739        for n in range(k-1, -1, -1):740            for m in range(n, -1, -1):741                G = damping_rots.pop()742                tools.apply_givens(S, G.T, S.shape[0] - k + n - m, n)    # TODO: contiguous743744    def is_marginalized(self):745        return self._marginalized746747    def is_damped(self):748        return self._damping_rots is not None or self.n_l == 0749750    @property751    def r(self):
...

test_plugin_dependency.py

Source:test_plugin_dependency.py

...7@pytest.mark.parametrize('needs_decorate_method', [True, False])8@pytest.mark.parametrize('provides_decorate_method', [True, False])9def test_needs_provides_plugin_name(needs_decorate_method, provides_decorate_method, checkpoint1, checkpoint2):10    @slash.plugins.active  # pylint: disable=abstract-method, unused-variable11    @maybe_decorate(slash.plugins.needs('p'), not needs_decorate_method)12    @autoname13    class NeedsPlugin(PluginInterface):14        @maybe_decorate(slash.plugins.needs('p'), needs_decorate_method)15        def session_start(self):16            checkpoint2()17    @slash.plugins.active  # pylint: disable=abstract-method, unused-variable18    @maybe_decorate(slash.plugins.provides('p'), not provides_decorate_method)19    @autoname20    class ProvidesPlugin(PluginInterface):21        @maybe_decorate(slash.plugins.provides('p'), provides_decorate_method)22        def session_start(self):23            checkpoint1()24    slash.hooks.session_start()  # pylint: disable=no-member25    assert checkpoint1.timestamp < checkpoint2.timestamp26def test_provides_globally_needs_globally(checkpoint1, checkpoint2):27    '''28    Plugin A: Provides x at class level29    Plugin B: Needs x at class level30    '''31    @slash.plugins.provides('x')32    class PluginA(slash.plugins.interface.PluginInterface):33        def get_name(self):34            return 'plugin a'35        def session_start(self):36            checkpoint1()37        def test_start(self):38            pass39    @slash.plugins.needs('x')40    class PluginB(slash.plugins.interface.PluginInterface):41        def get_name(self):42            return 'plugin b'43        def session_start(self):44            checkpoint2()45        def error_added(self, result, error): # pylint: disable=unused-argument46            pass47    for plugin_cls in [PluginA, PluginB]:48        slash.plugins.manager.install(plugin_cls(), activate_later=True)49    slash.plugins.manager.activate_pending_plugins()50    slash.hooks.session_start()  # pylint: disable=no-member51    assert checkpoint1.timestamp < checkpoint2.timestamp52    slash.plugins.manager.deactivate('plugin a')53    with pytest.raises(CannotResolveDependencies) as caught:54        slash.hooks.session_start()  # pylint: disable=no-member55    assert caught.value.unmet_dependencies == set(['x'])56def test_provides_globally_needs_specific_hook(checkpoint1, checkpoint2):57    '''58    Plugin A: Provides x at class level59    Plugin B: Needs x for specific hook60    '''61    @slash.plugins.provides('x')62    class PluginA(slash.plugins.interface.PluginInterface):63        def get_name(self):64            return 'plugin a'65        def session_start(self):66            checkpoint1()67        def test_start(self):68            pass69    class PluginB(slash.plugins.interface.PluginInterface):70        def get_name(self):71            return 'plugin b'72        @slash.plugins.needs('x')73        def session_start(self):74            checkpoint2()75        def error_added(self, result, error): # pylint: disable=unused-argument76            pass77    for plugin_cls in [PluginA, PluginB]:78        slash.plugins.manager.install(plugin_cls(), activate_later=True)79    slash.plugins.manager.activate_pending_plugins()80    slash.hooks.session_start()  # pylint: disable=no-member81    assert checkpoint1.timestamp < checkpoint2.timestamp82    slash.plugins.manager.deactivate('plugin a')83    with pytest.raises(CannotResolveDependencies) as caught:84        slash.hooks.session_start()  # pylint: disable=no-member85    assert caught.value.unmet_dependencies == set(['x'])86def test_provides_globally_needs_specific_hook_which_does_not_exist_at_a(checkpoint2):87    '''88    Plugin A: Provides x at class level89    Plugin B: Needs x for specific hook, this hook does not definied in A90    Expectations:91    Should work in the empty sense92    all non-needing hooks should work, even when missing from A, the specific hook needs to happen in A before B.93    '''94    @slash.plugins.provides('x')95    class PluginA(slash.plugins.interface.PluginInterface):96        def get_name(self):97            return 'plugin a'98        def test_start(self):99            pass100    class PluginB(slash.plugins.interface.PluginInterface):101        def get_name(self):102            return 'plugin b'103        @slash.plugins.needs('x')104        def session_start(self):105            checkpoint2()106        def error_added(self, result, error): # pylint: disable=unused-argument107            pass108    for plugin_cls in [PluginA, PluginB]:109        slash.plugins.manager.install(plugin_cls(), activate_later=True)110    slash.plugins.manager.activate_pending_plugins()111    slash.hooks.session_start()  # pylint: disable=no-member112    assert checkpoint2.called113    slash.plugins.manager.deactivate('plugin a')114    with pytest.raises(CannotResolveDependencies) as caught:115        slash.hooks.session_start()  # pylint: disable=no-member116    assert caught.value.unmet_dependencies == set(['x'])117def test_provides_specific_hook_needs_globally(checkpoint1, checkpoint2):118    '''119    Plugin A: Provides x on a specific hook120    Plugin B: Needs x at class level121    Expectations:122    This case should fail, because logically the other hooks don't have anyone to provide X for them123    '''124    class PluginA(slash.plugins.interface.PluginInterface):125        def get_name(self):126            return 'plugin a'127        @slash.plugins.provides('x')128        def session_start(self):129            checkpoint1()130        def test_start(self):131            pass132    @slash.plugins.needs('x')133    class PluginB(slash.plugins.interface.PluginInterface):134        def get_name(self):135            return 'plugin b'136        def session_start(self):137            checkpoint2()138        def error_added(self, result, error): # pylint: disable=unused-argument139            pass140    for plugin_cls in [PluginA, PluginB]:141        slash.plugins.manager.install(plugin_cls(), activate_later=True)142    slash.plugins.manager.activate_pending_plugins()143    slash.hooks.session_start()  # pylint: disable=no-member144    with pytest.raises(CannotResolveDependencies) as caught:145        slash.hooks.error_added(result=None, error=None)  # pylint: disable=no-member146    assert caught.value.unmet_dependencies == set(['x'])147def test_provides_specific_hook_needs_globally_with_this_hook_only(checkpoint1, checkpoint2):148    '''149    Plugin A: Provides x on a specific hook150    Plugin B: Needs x at class level, but only has one hook (the one provided by A)151    '''152    class PluginA(slash.plugins.interface.PluginInterface):153        def get_name(self):154            return 'plugin a'155        @slash.plugins.provides('x')156        def session_start(self):157            checkpoint1()158        def test_start(self):159            pass160    @slash.plugins.needs('x')161    class PluginB(slash.plugins.interface.PluginInterface):162        def get_name(self):163            return 'plugin b'164        def session_start(self):165            checkpoint2()166    for plugin_cls in [PluginA, PluginB]:167        slash.plugins.manager.install(plugin_cls(), activate_later=True)168    slash.plugins.manager.activate_pending_plugins()169    slash.hooks.session_start()  # pylint: disable=no-member170    assert checkpoint1.timestamp < checkpoint2.timestamp171    slash.plugins.manager.deactivate('plugin a')172    with pytest.raises(CannotResolveDependencies) as caught:173        slash.hooks.session_start()  # pylint: disable=no-member174    assert caught.value.unmet_dependencies == set(['x'])175@pytest.mark.parametrize('needs_parent_level', [True, False])176@pytest.mark.parametrize('provides_parent_level', [True, False])177def test_provides_needs_with_inheritence_on_class_level(checkpoint, checkpoint1, checkpoint2, needs_parent_level, provides_parent_level):178    '''179    Plugin A: Provides x in class level (by it self or by inheritence)180    Plugin b: Needs x in class level (by it self or by inheritence)181    '''182    # pylint: disable=abstract-method183    @maybe_decorate(slash.plugins.provides('x'), provides_parent_level)184    class PluginAParent(slash.plugins.interface.PluginInterface):185        def test_start(self):186            pass187    @maybe_decorate(slash.plugins.provides('x'), not provides_parent_level)188    class PluginA(PluginAParent):189        def get_name(self):190            return 'plugin a'191        def session_start(self):192            checkpoint1()193    @maybe_decorate(slash.plugins.needs('x'), needs_parent_level)194    class PluginBParent(slash.plugins.interface.PluginInterface):195        def error_added(self, result, error): # pylint: disable=unused-argument196            checkpoint()197    @maybe_decorate(slash.plugins.needs('x'), not needs_parent_level)198    class PluginB(PluginBParent):199        def get_name(self):200            return 'plugin b'201        def session_start(self):202            checkpoint2()203    for plugin_cls in [PluginA, PluginB]:204        slash.plugins.manager.install(plugin_cls(), activate_later=True)205    slash.plugins.manager.activate_pending_plugins()206    # session_start hook should be provided the PluginA.session_start method207    slash.hooks.session_start()  # pylint: disable=no-member208    assert checkpoint1.timestamp < checkpoint2.timestamp209    # error_added hook should be provided by empty registration of pluginA210    slash.hooks.error_added(result=None, error=None)  # pylint: disable=no-member211    assert checkpoint.called...

test_plugins.py

Source:test_plugins.py

...21def test_registers_on_kwargs(class_level_needs, class_level_provides):22    needs_decorator = plugins.needs('other_requirement')23    provides_decorator = plugins.provides('another_provided_requirement')24    @slash.plugins.active  # pylint: disable=unused-variable25    @maybe_decorate(needs_decorator, class_level_needs)26    @maybe_decorate(provides_decorator, class_level_provides)27    class SamplePlugin(PluginInterface):28        def get_name(self):29            return 'sample'30        @plugins.registers_on('some.hook', provides=['provided_requirement'], needs=['some_requirement'], tags=['tag'])31        @maybe_decorate(needs_decorator, not class_level_needs)32        @maybe_decorate(provides_decorator, not class_level_provides)33        def plugin_method(self):34            pass35    @gossip.register('some.hook', provides=['some_requirement', 'other_requirement'])36    def _unused():37        pass38    gossip.trigger('some.hook')39    hook = gossip.get_hook('some.hook')40    [registration] = [reg for reg in hook.get_registrations() if reg.func.__name__ == 'plugin_method']41    assert registration.tags == {'tag'}42    assert registration.needs == frozenset(['some_requirement', 'other_requirement'])43    assert registration.provides == frozenset(['provided_requirement', 'another_provided_requirement'])44def test_registers_on_with_private_methods(restore_plugins_on_cleanup, checkpoint):45    @slash.plugins.active  # pylint: disable=unused-variable46    class SamplePlugin(PluginInterface):...

util.py

Source:util.py

...77    if hasattr(request.body, "read"):78        return request.body.read()79    return request.body80def auto_decorate(decorator, predicate=lambda name, value: isinstance(value, types.FunctionType)):81    def maybe_decorate(attribute, value):82        if predicate(attribute, value):83            value = decorator(value)84        return value85    class DecorateAll(type):86        def __setattr__(cls, attribute, value):87            return super(DecorateAll, cls).__setattr__(attribute, maybe_decorate(attribute, value))88        def __new__(cls, name, bases, attributes_dict):89            new_attributes_dict = {90                attribute: maybe_decorate(attribute, value) for attribute, value in attributes_dict.items()91            }92            return super(DecorateAll, cls).__new__(cls, name, bases, new_attributes_dict)...

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