Check failed in jt.setitem when slicing exceeds tensor dimension boundary

[x0w3n]

Describe the bug

Check failed is triggered when the slicing operation exceeds the dimension boundary of the tensor. The error log suggests reporting this issue.

Full Log

[i 1203 09:44:05.265442 28 compiler.py:956] Jittor(1.3.9.10) src: /home/miniconda3/envs/jittor/lib/python3.9/site-packages/jittor
[i 1203 09:44:05.276319 28 compiler.py:957] g++ at /usr/bin/g++(11.2.0)
[i 1203 09:44:05.276768 28 compiler.py:958] cache_path: /home/.cache/jittor/jt1.3.9/g++11.2.0/py3.9.12/Linux-5.15.0-1x30/INTELRXEONRGOLx51/ef26/default
[i 1203 09:44:05.345767 28 install_cuda.py:93] cuda_driver_version: [12, 2]
[i 1203 09:44:05.356495 28 __init__.py:412] Found /home/.cache/jittor/jtcuda/cuda12.2_cudnn8_linux/bin/nvcc(12.2.140) at /home/.cache/jittor/jtcuda/cuda12.2_cudnn8_linux/bin/nvcc.
[i 1203 09:44:05.804737 28 __init__.py:412] Found gdb(12.0.90) at /usr/bin/gdb.
[i 1203 09:44:05.807506 28 __init__.py:412] Found addr2line(2.38) at /usr/bin/addr2line.
[i 1203 09:44:06.177937 28 compiler.py:1013] cuda key:cu12.2.140_sm_89
[i 1203 09:44:07.469918 28 __init__.py:227] Total mem: 251.50GB, using 16 procs for compiling.
[i 1203 09:44:07.673996 28 jit_compiler.cc:28] Load cc_path: /usr/bin/g++
[i 1203 09:44:07.922802 28 init.cc:63] Found cuda archs: [89,]
Traceback (most recent call last):
  File "/home/work/data/2024-10-23-single-tf-pytorch/Results/test/crash_pool/jittor/jittor_core.Var.setitem_oneflow_oneflow.var_13dd5d.py", line 8, in <module>
    result = jt.setitem(x, slice(3, 4), y)
RuntimeError: Wrong inputs arguments, Please refer to examples(help(jt.ops.setitem)).

Types of your inputs are:
 self   = module,
 args   = (Var, slice, Var, ),

The function declarations are:
 VarHolder* setitem(VarHolder* x,  VarSlices&& slices, VarHolder* y,  NanoString op=ns_void)

Failed reason:[f 1203 09:44:08.673939 28 nano_vector.h:32] Check failed: start==stop || (start>=0 && stop>=-1 && start<size && stop<=size)  Something wrong... Could you please report this issue?
 slice overflow: 3 2 1

Minimal Reproduce

import jittor as jt

x = jt.array([[1, 2, 3], [1, 2, 3]])
y = jt.array([0.1, 0.2])
result = jt.setitem(x, slice(1, 2), y)

Expected behavior