How to use the starry.Map.utils.to_tensor function in starry

if inc is None:
                inc = self.inc
            if obl is None:
                obl = self.obl
            inc, obl = to_tensor(inc, obl)

            # Figure out the coords from the orbit
            if orbit is not None and t is not None:
                
                # Tensorize the time array
                t = to_tensor(t)

                # Only compute during transit?
                if use_in_transit:
                    zero = to_tensor([0.])
                    theta0 = tt.reshape(to_tensor(theta), [1])
                    X0 = self._X_op(u, f, inc, obl, theta0, zero, zero, zero, zero)
                    transit_model = tt.tile(X0, tt.shape_padright(t).shape, ndim=2)
                    transit_inds = orbit.in_transit(t, r=ro, texp=texp)
                    t = t[transit_inds]

                # Exposure time grid
                if texp is None:
                    
                    # Easy
                    tgrid = t
                
                else:
                    
                    # From DFM's exoplanet
                    texp = to_tensor(texp)
                    oversample = int(oversample)

for kwarg in kwargs.keys():
            warnings.warn("Unrecognized kwarg: %s. Ignoring..." % kwarg)

        # Figure out if this is a Theano Op call
        if (orbit is not None and t is not None) or is_theano(u, b, zo, ro):

            # Limb darkening coeffs
            if u is None:
                if self.udeg == 0:
                    u = []
                else:
                    if self._spectral:
                        u = self[1:, :]
                    else:
                        u = self[1:]
            u = to_tensor(u)

            # Figure out the coords from the orbit
            if orbit is not None and t is not None:
                
                # Tensorize the time array
                t = to_tensor(t)
                
                # Only compute during transit?
                if use_in_transit:
                    transit_model = tt.ones_like(t)
                    transit_inds = orbit.in_transit(t, r=ro, texp=texp)
                    t = t[transit_inds]

                # Exposure time grid
                if texp is None:

# Limb darkening coeffs
            if u is None:
                if self.udeg == 0:
                    u = []
                else:
                    if self._spectral:
                        u = self[1:, :]
                    else:
                        u = self[1:]
            u = to_tensor(u)

            # Figure out the coords from the orbit
            if orbit is not None and t is not None:
                
                # Tensorize the time array
                t = to_tensor(t)
                
                # Only compute during transit?
                if use_in_transit:
                    transit_model = tt.ones_like(t)
                    transit_inds = orbit.in_transit(t, r=ro, texp=texp)
                    t = t[transit_inds]

                # Exposure time grid
                if texp is None:
                    
                    # Easy
                    tgrid = t
                
                else:
                    
                    # From DFM's exoplanet

u = to_tensor(u)

            # Filter coeffs
            if f is None:
                if self.fdeg == 0:
                    f = []
                else:
                    f = self.f
            f = to_tensor(f)

            # Angles
            if inc is None:
                inc = self.inc
            if obl is None:
                obl = self.obl
            inc, obl = to_tensor(inc, obl)

            # Figure out the coords from the orbit
            if orbit is not None and t is not None:
                
                # Tensorize the time array
                t = to_tensor(t)

                # Only compute during transit?
                if use_in_transit:
                    zero = to_tensor([0.])
                    theta0 = tt.reshape(to_tensor(theta), [1])
                    X0 = self._X_op(u, f, inc, obl, theta0, zero, zero, zero, zero)
                    transit_model = tt.tile(X0, tt.shape_padright(t).shape, ndim=2)
                    transit_inds = orbit.in_transit(t, r=ro, texp=texp)
                    t = t[transit_inds]

theta0 = tt.reshape(to_tensor(theta), [1])
                    X0 = self._X_op(u, f, inc, obl, theta0, zero, zero, zero, zero)
                    transit_model = tt.tile(X0, tt.shape_padright(t).shape, ndim=2)
                    transit_inds = orbit.in_transit(t, r=ro, texp=texp)
                    t = t[transit_inds]

                # Exposure time grid
                if texp is None:
                    
                    # Easy
                    tgrid = t
                
                else:
                    
                    # From DFM's exoplanet
                    texp = to_tensor(texp)
                    oversample = int(oversample)
                    oversample += 1 - oversample % 2
                    stencil = np.ones(oversample)

                    # Construct the exposure time integration stencil
                    if order == 0:
                        dt = np.linspace(-0.5, 0.5, 2*oversample+1)[1:-1:2]
                    elif order == 1:
                        dt = np.linspace(-0.5, 0.5, oversample)
                        stencil[1:-1] = 2
                    elif order == 2:
                        dt = np.linspace(-0.5, 0.5, oversample)
                        stencil[1:-1:2] = 4
                        stencil[2:-1:2] = 2
                    else:
                        raise ValueError("Keyword `order` must be <= 2.")

else:
                    f = self.f
            f = to_tensor(f)

            # Angles
            if inc is None:
                inc = self.inc
            if obl is None:
                obl = self.obl
            inc, obl = to_tensor(inc, obl)

            # Figure out the coords from the orbit
            if orbit is not None and t is not None:
                
                # Tensorize the time array
                t = to_tensor(t)

                # Only compute during transit?
                if use_in_transit:
                    zero = to_tensor([0.])
                    theta0 = tt.reshape(to_tensor(theta), [1])
                    X0 = self._X_op(u, f, inc, obl, theta0, zero, zero, zero, zero)
                    transit_model = tt.tile(X0, tt.shape_padright(t).shape, ndim=2)
                    transit_inds = orbit.in_transit(t, r=ro, texp=texp)
                    t = t[transit_inds]

                # Exposure time grid
                if texp is None:
                    
                    # Easy
                    tgrid = t

ro = kwargs.pop("ro", kwargs.pop("r", 0.0)) # Lenient! Can provide `r`
        orbit = kwargs.pop("orbit", None)
        t = kwargs.pop("t", None)
        use_in_transit = kwargs.pop("use_in_transit", True)
        texp = kwargs.pop("texp", None)
        oversample = kwargs.pop("oversample", 7)
        order = kwargs.pop("order", 0)

        # Raise warnings for some combinations
        if (orbit is not None) and (t is None):
            raise ValueError("Please provide a set of times `t`.")
        if (orbit is None or t is None):
            use_in_transit = False
            if texp is not None:
                warnings.warn("Exposure time integration enabled only when an `orbit` instance is provided.") 
        if (to_tensor(theta).ndim != 0):
            use_in_transit = False
        for kwarg in kwargs.keys():
            warnings.warn("Unrecognized kwarg: %s. Ignoring..." % kwarg)

        # Figure out if this is a Theano Op call
        if (orbit is not None and t is not None) or \
            is_theano(u, f, inc, obl, theta, xo, yo, zo, ro):

            # Limb darkening coeffs
            if u is None:
                if self.udeg == 0:
                    u = []
                else:
                    if self._spectral:
                        u = self[1:, :]
                    else:

if self.udeg == 0:
                    u = []
                else:
                    if self._spectral:
                        u = self[1:, :]
                    else:
                        u = self[1:]
            u = to_tensor(u)

            # Filter coeffs
            if f is None:
                if self.fdeg == 0:
                    f = []
                else:
                    f = self.f
            f = to_tensor(f)

            # Angles
            if inc is None:
                inc = self.inc
            if obl is None:
                obl = self.obl
            inc, obl = to_tensor(inc, obl)

            # Figure out the coords from the orbit
            if orbit is not None and t is not None:
                
                # Tensorize the time array
                t = to_tensor(t)

                # Only compute during transit?
                if use_in_transit:

warnings.warn("Unrecognized kwarg: %s. Ignoring..." % kwarg)

        # Figure out if this is a Theano Op call
        if (orbit is not None and t is not None) or \
            is_theano(u, f, inc, obl, theta, xo, yo, zo, ro):

            # Limb darkening coeffs
            if u is None:
                if self.udeg == 0:
                    u = []
                else:
                    if self._spectral:
                        u = self[1:, :]
                    else:
                        u = self[1:]
            u = to_tensor(u)

            # Filter coeffs
            if f is None:
                if self.fdeg == 0:
                    f = []
                else:
                    f = self.f
            f = to_tensor(f)

            # Angles
            if inc is None:
                inc = self.inc
            if obl is None:
                obl = self.obl
            inc, obl = to_tensor(inc, obl)