Check failed in jt.nn.Upsample/jt.nn.UpsamplingBilinear2d

[x0w3n]

Describe the bug

A Check failed is triggered when the scale_factor parameter is negative. The error log suggests reporting this issue.

Full Log

[i 1203 16:10:38.227348 24 compiler.py:956] Jittor(1.3.9.10) src: /home/miniconda3/envs/jittor/lib/python3.9/site-packages/jittor
[i 1203 16:10:38.237853 24 compiler.py:957] g++ at /usr/bin/g++(11.2.0)
[i 1203 16:10:38.238358 24 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 16:10:38.324648 24 install_cuda.py:93] cuda_driver_version: [12, 2]
[i 1203 16:10:38.338726 24 __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 16:10:38.775386 24 __init__.py:412] Found gdb(12.0.90) at /usr/bin/gdb.
[i 1203 16:10:38.779183 24 __init__.py:412] Found addr2line(2.38) at /usr/bin/addr2line.
[i 1203 16:10:39.119073 24 compiler.py:1013] cuda key:cu12.2.140_sm_89
[i 1203 16:10:40.288988 24 __init__.py:227] Total mem: 251.50GB, using 16 procs for compiling.
[i 1203 16:10:40.444035 24 jit_compiler.cc:28] Load cc_path: /usr/bin/g++
[i 1203 16:10:40.657266 24 init.cc:63] Found cuda archs: [89,]
Traceback (most recent call last):
  File "test.py", line 8, in <module>
    output = upsampling_layer(sample_input)
  File "/home/miniconda3/envs/jittor/lib/python3.9/site-packages/jittor/__init__.py", line 1211, in __call__
    return self.execute(*args, **kw)
  File "/home/miniconda3/envs/jittor/lib/python3.9/site-packages/jittor/nn.py", line 2276, in execute
    int(x.shape[3]*self.scale_factor)),
RuntimeError: Wrong inputs arguments, Please refer to examples(help(jt.NanoVector.__map_getitem__)).

Types of your inputs are:
 self   = NanoVector,
 arg0   = int,

The function declarations are:
 inline int64 at(int i)
 inline NanoVector slice(Slice slice)

Failed reason:[f 1203 16:10:41.545195 24 nano_vector.h:116] Check failed: i>=0 && i<size()  Something wrong... Could you please report this issue?

Minimal Reproduce

import jittor as jt

x = jt.rand(32, 32)
scale_factor = (1.0, -1.0)
p = jt.nn.Upsample(scale_factor=scale_factor)
result = p(x)

import jittor as jt
from jittor import nn

sample_input = jt.rand(3, 128, 127)
upsampling_layer = nn.UpsamplingBilinear2d(scale_factor=-1)
output = upsampling_layer(sample_input)
print(output.shape)

Expected behavior