[CUDA] ConvTranspose2D Error with PreconditionNotMet

[jwnhy]

bug描述 Describe the Bug

当执行下列代码时，报错 PreconditionNotMet.

import paddle as pdl

model = pdl.nn.Conv2DTranspose(1, 1, kernel_size=[1, 1], stride=[46889, 4], padding=[0, 1])
tensor = pdl.rand([1, 1, 46889, 2])

model(tensor)

错误信息如下

W0115 10:23:44.565328 2009009 gpu_resources.cc:119] Please NOTE: device: 0, GPU Compute Capability: 9.0, Driver API Version: 12.6, Runtime API Version: 12.3
W0115 10:23:44.565850 2009009 gpu_resources.cc:164] device: 0, cuDNN Version: 9.0.
Traceback (most recent call last):
  File "/home/jwnhy/gpu_fuzz/gen/poc3.py", line 6, in <module>
    model(tensor)
  File "/home/jwnhy/miniconda3/lib/python3.12/site-packages/paddle/nn/layer/layers.py", line 1426, in __call__
    return self.forward(*inputs, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/jwnhy/miniconda3/lib/python3.12/site-packages/paddle/nn/layer/conv.py", line 883, in forward
    out = F.conv2d_transpose(
          ^^^^^^^^^^^^^^^^^^^
  File "/home/jwnhy/miniconda3/lib/python3.12/site-packages/paddle/nn/functional/conv.py", line 1262, in conv2d_transpose
    pre_bias = op(
               ^^^
RuntimeError: (PreconditionNotMet) Tensor's dimension is out of bound.Tensor's dimension must be equal or less than the size of its memory.But received Tensor's dimension is 18446744048552321260, memory's size is 26382377216.
  [Hint: Expected numel() * SizeOf(dtype()) <= memory_size(), but received numel() * SizeOf(dtype()):18446744048552321260 > memory_size():26382377216.] (at ../paddle/phi/core/dense_tensor_impl.cc:46)

显然我的 Tensor 的长度并没有达到 18446744048552321260，疑似是库中存在整数溢出 Bug

我的环境如下：

[pip3] numpy==1.26.4
[pip3] nvidia-cublas-cu12==12.3.4.1
[pip3] nvidia-cuda-cupti-cu12==12.3.101
[pip3] nvidia-cuda-nvrtc-cu12==12.3.107
[pip3] nvidia-cuda-runtime-cu12==12.3.101
[pip3] nvidia-cudnn-cu12==9.0.0.312
[pip3] nvidia-cufft-cu12==11.2.1.3
[pip3] nvidia-curand-cu12==10.3.5.147
[pip3] nvidia-cusolver-cu12==11.6.1.9
[pip3] nvidia-cusparse-cu12==12.3.1.170
[pip3] nvidia-nccl-cu12==2.19.3
[pip3] nvidia-nvjitlink-cu12==12.6.85
[pip3] nvidia-nvtx-cu12==12.4.127
[conda] numpy                     1.26.4                   pypi_0    pypi
[conda] nvidia-cublas-cu12        12.3.4.1                 pypi_0    pypi
[conda] nvidia-cuda-cupti-cu12    12.3.101                 pypi_0    pypi
[conda] nvidia-cuda-nvrtc-cu12    12.3.107                 pypi_0    pypi
[conda] nvidia-cuda-runtime-cu12  12.3.101                 pypi_0    pypi
[conda] nvidia-cudnn-cu12         9.0.0.312                pypi_0    pypi
[conda] nvidia-cufft-cu12         11.2.1.3                 pypi_0    pypi
[conda] nvidia-curand-cu12        10.3.5.147               pypi_0    pypi
[conda] nvidia-cusolver-cu12      11.6.1.9                 pypi_0    pypi
[conda] nvidia-cusparse-cu12      12.3.1.170               pypi_0    pypi
[conda] nvidia-nccl-cu12          2.19.3                   pypi_0    pypi
[conda] nvidia-nvjitlink-cu12     12.6.85                  pypi_0    pypi
[conda] nvidia-nvtx-cu12          12.4.127                 pypi_0    pypi

其他补充信息 Additional Supplementary Information

No response

[liym27]

感谢反馈，已复现该问题，我们将修复该问题。@jwnhy