Resolving modified models with lazy constraints fails

When I build a model with a few lazy constraints, the first solve works fine. But after changing some elements and resolving, CBC reports infeasible, although after rebuilding the model from scratch it reports feasible.
This does not happen if regular constraints instead of lazy constraints are used.
Expection would be that it also works correctly with lazy constraints.

```py
import mip, numpy as np

a = np.array([
[1,0,0,1,1],
[0,-1,0,0,0],
[0,0,0,0,0],
[0,-1,0,0,-1],
[1,1,0,0,1],
[1,1,1,0,1],
[1,1,1,1,1],
[2,2,2,1,1],
])
b = np.array([[-1,1], [0,1], [1,0], [1,1], [1,-1], [0,-1], [-1,0], [-1,-1]])
c = np.array([
[0.5488135039273248, 0.6027633760716439, 0.4236547993389047, 0.4375872112626925, 0.9636627605010293],
[0.7151893663724195, 0.5448831829968969, 0.6458941130666561, 0.8917730007820798, 0.3834415188257777],
])
d = np.array([
[0.79172504, 0.52889492],
[0.46147936, 0.78052918],
])

model = mip.Model()
λ = model.add_var_tensor((len(c[0]),), 'λ', lb=0, ub=1)
z = model.add_var_tensor((len(b[0]),), 'z', lb=0, var_type=mip.BINARY)
model.add_constr(mip.xsum(λ) == 1)
for expr in a @ λ + b @ z:
model.add_lazy_constr(expr >= 0) # comment this line and uncomment next to get correct behaviour
#model.add_constr(expr >= 0)
constr = [0] * len(d[0])
for i, expr in enumerate(c @ λ):
constr[i] = model.add_constr(expr == d[0][i])
model.optimize()
print(f"Run model for d[0]: {model.status}") # reports optimal

# change model and resolve
for i, expr in enumerate(c @ λ):
constr[i].rhs = d[1][i]
model.optimize()
print(f"Modified model for d[1]: {model.status}") # reports infeasible for lazy_constr

# rebuilt model for d[1] from scratch
model = mip.Model()
λ = model.add_var_tensor((len(c[0]),), 'λ', lb=0, ub=1)
z = model.add_var_tensor((len(b[0]),), 'z', lb=0, var_type=mip.BINARY)
model.add_constr(mip.xsum(λ) == 1)
for expr in a @ λ + b @ z:
model.add_lazy_constr(expr >= 0)
for i, expr in enumerate(c @ λ):
model.add_constr(expr == d[1][i])
model.optimize()
print(f"Rebuilt model for d[1]: {model.status}") # reports optimal
´´´

Python 3.8.12
Python-mip 1.13
CBC Mar 30 2021