Comments (1)
>>> out=deform_conv2d(data,offset,weight,bias,stride,padding,dilation,groups,deformable_groups,in_step)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "D:\conda\envs\pytorch1.10.0\lib\site-packages\modulated_deform_conv-1.0.2-py3.8-win-amd64.egg\modulated_deform_conv.py", line 28, in forward
MDCONV_CUDA.deform_conv2d_forward_cuda(
AttributeError: module 'MDCONV_CUDA' has no attribute 'deform_conv2d_forward_cuda'
>>> out=modulated_deform_conv2d(data,offset,mask,weight,bias,stride,padding,dilation,groups,deformable_groups,in_step)
>>> print(out)
tensor([[[[4., 6., 6., 6., 4.],
[6., 9., 9., 9., 6.],
[6., 9., 9., 9., 6.],
[6., 9., 9., 9., 6.],
[4., 6., 6., 6., 4.]]]], device='cuda:0',
grad_fn=<ModulatedDeformConv2dFunctionBackward>)
from modulated-deform-conv.
Related Issues (9)
- Unsupported gpu architecture 'compute_86'
- Unsupported gpu architecture 'compute_86' HOT 1
- module 'MDCONV_CUDA' has no attribute 'deform_conv2d_forward_cuda' HOT 1
- TypeError: a bytes-like object is required, not 'str' HOT 1
- 3D deformable ROI / 3D modulated RoI pooling
- speed compared to 3dconv
- 'ModulatedDeformConv3d' object has no attribute 'deformable_group' HOT 1
- IndexError: tuple index out of range
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from modulated-deform-conv.