Build MSAttn in Deformable DETR
最近一个任务需要用到Deformable-DETR，其中比较关键的一步是Multi-scale Deformable Attention Module （MSDeformAttn），这个模块能够实现在multi-scale的feature map上的deformable convolution操作。
所用的代码是Deformable DETR的官方实现1，其中需要先对CUDA的算子进行编译
cd ./models/ops
sh ./make.sh
# unit test (should see all checking is True)
python test.py
我这里编译完之后，在集群上的M40 GPU上是可以正常训练的，但是切换到P40之后，运行就一直刷错误
error in ms_deformable_im2col_cuda: no kernel image is available for execution on the device
集群上的环境是:
CUDA 10.2
torch 1.7.0+cu101
torchvision 0.8.1+cu101
OS 4.14.105-1-tlinux3-0013
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 440.64.00 Driver Version: 440.64.00 CUDA Version: 10.2 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
|===============================+======================+======================|
| 0 Tesla P40 On | 00000000:04:00.0 Off | Off |
| N/A 43C P0 57W / 250W | 20653MiB / 24451MiB | 100% Default |
+-------------------------------+----------------------+----------------------+
+-------------------------------+----------------------+----------------------+
| 7 Tesla P40 On | 00000000:0F:00.0 Off | Off |
| N/A 47C P0 142W / 250W | 20653MiB / 24451MiB | 40% Default |
+-------------------------------+----------------------+----------------------+
找到这段错误代码来自models/ops/src/cuda/ms_deform_im2col_cuda.cuh
void ms_deformable_im2col_cuda(cudaStream_t stream,
const scalar_t* data_value,
const int64_t* data_spatial_shapes,
const int64_t* data_level_start_index,
const scalar_t* data_sampling_loc,
const scalar_t* data_attn_weight,
const int batch_size,
const int spatial_size,
const int num_heads,
const int channels,
const int num_levels,
const int num_query,
const int num_point,
scalar_t* data_col)
{
const int num_kernels = batch_size * num_query * num_heads * channels;
const int num_actual_kernels = batch_size * num_query * num_heads * channels;
const int num_threads = CUDA_NUM_THREADS;
ms_deformable_im2col_gpu_kernel<scalar_t>
<<<GET_BLOCKS(num_actual_kernels, num_threads), num_threads,
0, stream>>>(
num_kernels, data_value, data_spatial_shapes, data_level_start_index, data_sampling_loc, data_attn_weight,
batch_size, spatial_size, num_heads, channels, num_levels, num_query, num_point, data_col);
cudaError_t err = cudaGetLastError();
if (err != cudaSuccess)
{
printf("error in ms_deformable_im2col_cuda: %s\n", cudaGetErrorString(err));
}
}
在调用ms_deformable_im2col_gpu_kernel之后出现了问题，网上搜了一下也没发现解决方案。
只能自己看了一下setup.py, 发现里面与编译相关配置为
if torch.cuda.is_available() and CUDA_HOME is not None:
extension = CUDAExtension
sources += source_cuda
define_macros += [("WITH_CUDA", None)]
extra_compile_args["nvcc"] = [
"-DCUDA_HAS_FP16=1",
"-D__CUDA_NO_HALF_OPERATORS__",
"-D__CUDA_NO_HALF_CONVERSIONS__",
"-D__CUDA_NO_HALF2_OPERATORS__",
]
else:
raise NotImplementedError('Cuda is not availabel')
P40上也没有FP16的支持，遂将-DCUDA_HAS_FP16=1改成了-DCUDA_HAS_FP16=0。
然后删除build文件重新编译一遍，运行就都正常了。