symbolic-computation

If I run the copy&paste examples, such as https://mtk.sciml.ai/stable/tutorials/acausal_components/ :

using ModelingToolkit, Plots, DifferentialEquations

@variables t
@connector function Pin(;name)
    sts = @variables v(t)=1.0 i(t)=1.0 [connect = Flow]
    ODESystem(Equation[], t, sts, []; name=name)
end

function Ground(;name)
    @named g = Pin()
    eqs = [g.v ~ 0]
    

Squeeze does not seem to do anything when axis is negative:

import aesara.tensor as at
at.squeeze(at.as_tensor_variable([1]), axis=-1).eval()
# array([1])
at.squeeze(at.as_tensor_variable([[1]]), axis=-1).eval()
# array([[1]])

This doesn't happen with positive axis:

at.squeeze(at.as_tensor_variable([1]), axis=0).eval()
# array(1)
at.squeeze(at.as_tensor_variable

As a convenience, we should provide meta tensor implementations of the following:
__add__, __radd__, __sub__, __rsub__, __mul__, __rmul__, __div__, __rdiv__, __truediv__, __rtruediv__, __floordiv__, __rfloordiv__, __mod__, __rmod__, __lt__, __le__, __gt__, __ge__, __and__, __rand__, __or__, __ror__, __xor__, __rxor__, __getitem__, __pow__, `__rp