vectors over GF(2, impl='ntl') are crashing Sage

[dimpase]

Steps To Reproduce

sage: F = GF(2, impl='ntl')
sage: m_ntl = identity_matrix(1, F)
sage: v_ntl = vector(F, (1,))
# Now consider
sage: m_ntl * v_ntl # gives an allocation error
sage: v_ntl * m_ntl # segfaults

Expected Behavior

it should not crash, it should work.

Actual Behavior

it crashes

Additional Information

reported in
https://groups.google.com/g/sage-devel/c/uSdcoZh6mH8/m/UYP-4DpnHAAJ

Environment

- **OS**: macOS, Linux 
- **Sage Version**: recent betas (10.2.beta2+)

Checklist

• I have searched the existing issues for a bug report that matches the one I want to file, without success.
• I have read the documentation and troubleshoot guide

[dimpase]

┌────────────────────────────────────────────────────────────────────┐
│ SageMath version 10.2.beta4, Release Date: 2023-09-24              │
│ Using Python 3.11.5. Type "help()" for help.                       │
└────────────────────────────────────────────────────────────────────┘
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
┃ Warning: this is a prerelease version, and it may be unstable.     ┃
┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛
sage: sage: F = GF(2, impl='ntl')
....: sage: m_ntl = identity_matrix(1, F)
....: sage: v_ntl = vector(F, (1,))
sage: m_ntl * v_ntl
---------------------------------------------------------------------------
SignalError                               Traceback (most recent call last)
Cell In [2], line 1
----> 1 m_ntl * v_ntl

File /mnt/opt/Sage/sage-dev/src/sage/structure/element.pyx:4099, in sage.structure.element.Matrix.__mul__()
   4097 
   4098         if BOTH_ARE_ELEMENT(cl):
-> 4099             return coercion_model.bin_op(left, right, mul)
   4100 
   4101         cdef long value

File /mnt/opt/Sage/sage-dev/src/sage/structure/coerce.pyx:1222, in sage.structure.coerce.CoercionModel.bin_op()
   1220 if action is not None:
   1221     if (<Action>action)._is_left:
-> 1222         return (<Action>action)._act_(x, y)
   1223     else:
   1224         return (<Action>action)._act_(y, x)

File /mnt/opt/Sage/sage-dev/src/sage/matrix/action.pyx:328, in sage.matrix.action.MatrixVectorAction._act_()
    326     else:
    327         v = v.dense_vector()
--> 328 return A._matrix_times_vector_(v)
    329 
    330 

File /mnt/opt/Sage/sage-dev/src/sage/matrix/matrix_mod2_dense.pyx:613, in sage.matrix.matrix_mod2_dense.Matrix_mod2_dense._matrix_times_vector_()
    611     return VS.zero()
    612 cdef Vector_mod2_dense c = Vector_mod2_dense.__new__(Vector_mod2_dense)
--> 613 sig_str("matrix allocation failed")
    614 c._init(self._nrows, VS)
    615 if c._entries.nrows and c._entries.ncols:

SignalError: matrix allocation failed
sage: 

and

sage: v_ntl*m_ntl
------------------------------------------------------------------------
/mnt/opt/Sage/sage-dev/local/var/lib/sage/venv-python3.11/lib/python3.11/site-packages/cysignals/signals.cpython-311-x86_64-linux-gnu.so(+0x81db)[0x7f39cb0f71db]
/mnt/opt/Sage/sage-dev/local/var/lib/sage/venv-python3.11/lib/python3.11/site-packages/cysignals/signals.cpython-311-x86_64-linux-gnu.so(+0x8288)[0x7f39cb0f7288]
/mnt/opt/Sage/sage-dev/local/var/lib/sage/venv-python3.11/lib/python3.11/site-packages/cysignals/signals.cpython-311-x86_64-linux-gnu.so(+0x9c10)[0x7f39cb0f8c10]
/lib64/libc.so.6(+0x39660)[0x7f39d8cf0660]
/mnt/opt/Sage/sage-dev/src/sage/modules/free_module_element.cpython-311-x86_64-linux-gnu.so(__pyx_f_4sage_7modules_19free_module_element_31FreeModuleElement_generic_dense__add_+0xaa)[0x7f387f644eea]
/mnt/opt/Sage/sage-dev/src/sage/structure/element.cpython-311-x86_64-linux-gnu.so(+0x17993)[0x7f39ca260993]
/usr/lib64/libpython3.11.so.1.0(PyNumber_Add+0x99)[0x7f39d90109a9]
/usr/lib64/libpython3.11.so.1.0(+0x25356c)[0x7f39d912856c]
/usr/lib64/libpython3.11.so.1.0(+0x1ac262)[0x7f39d9081262]
/mnt/opt/Sage/sage-dev/src/sage/matrix/matrix0.cpython-311-x86_64-linux-gnu.so(+0xf76f)[0x7f387ce0d76f]
...

@videlec

[jhpalmieri]

This may work with sparse matrices: the problem may only exist for dense matrices (in case this helps to track down the problem).

[dimpase]

Indeed, if m_ntl is sparse, this all works just fine.