DAIN: "no kernel image is available for execution on the device" #33
Description
When I proceed to try DAIN on a video file I receive the following:
(Btw, will or does your version of DAIN support Adaptive Record timestamps like the DAIN APP? Reference: https://imgur.com/a/7ihS2ir )
Current PyTorch version is 1.0.0
ffmpeg -hide_banner -loglevel warning -threads 4 -i /content/MVIMP/Data/Input/danny.mp4 /content/MVIMP/Data/Input/%8d.png
The video-image extracting job is done.
--------------------SUMMARY--------------------
Current input video file is danny.mp4,
danny.mp4's fps is 29.97,
danny.mp4 has 6211 frames.
Now we will process this video to 59.94 fps.
Frame split method will not be used.
--------------------NOW END--------------------
python3 -W ignore vfi_helper.py --src /content/MVIMP/Data/Input --dst /content/MVIMP/Data/Output --time_step 0.5
revise the unique id to a random numer 33628
Namespace(SAVED_MODEL='./model_weights/best.pth', alpha=[0.0, 1.0], arg='./model_weights/33628-Sun-Sep-06-02:23/args.txt', batch_size=1, channels=3, ctx_lr_coe=1.0, datasetName='Vimeo_90K_interp', datasetPath='', dataset_split=97, debug=False, depth_lr_coe=0.001, dst='/content/MVIMP/Data/Output', dtype=<class 'torch.cuda.FloatTensor'>, epsilon=1e-06, factor=0.2, filter_lr_coe=1.0, filter_size=4, flow_lr_coe=0.01, force=False, high_resolution=False, log='./model_weights/33628-Sun-Sep-06-02:23/log.txt', lr=0.002, netName='DAIN_slowmotion', no_date=False, numEpoch=100, occ_lr_coe=1.0, patience=5, rectify_lr=0.001, save_path='./model_weights/33628-Sun-Sep-06-02:23', save_which=1, seed=1, src='/content/MVIMP/Data/Input', time_step=0.5, uid=None, use_cuda=True, use_cudnn=1, weight_decay=0, workers=8)
cudnn is used
Interpolate 1 frames
The model weight is: ./model_weights/best.pth
************** current handling frame from /content/MVIMP/Data/Input. **************
************** current time_step is 0.5 **************
************** current output_dir is /content/MVIMP/Data/Output **************
************** high resolution method not used. **************
0% 0/6210 [00:00<?, ?it/s]error in correlation_forward_cuda_kernel: no kernel image is available for execution on the device
0% 0/6210 [00:04<?, ?it/s]
Traceback (most recent call last):
File "vfi_helper.py", line 204, in
input_dir=args.src, output_dir=args.dst, time_step=args.time_step,
File "vfi_helper.py", line 45, in continue_frames_insertion_helper
time_step=time_step,
File "vfi_helper.py", line 77, in frames_insertion_helper
y_0 = model_inference_helper(im_0, im_1)
File "vfi_helper.py", line 150, in model_inference_helper
y_s, _, _ = model(torch.stack((x_0, x_1), dim=0))
File "/usr/local/lib/python3.6/dist-packages/torch/nn/modules/module.py", line 489, in call
result = self.forward(*input, **kwargs)
File "/content/MVIMP/third_party/DAIN/networks/DAIN_slowmotion.py", line 170, in forward
self.flownets, cur_offset_input, time_offsets=time_offsets
File "/content/MVIMP/third_party/DAIN/networks/DAIN_slowmotion.py", line 268, in forward_flownets
input
File "/usr/local/lib/python3.6/dist-packages/torch/nn/modules/module.py", line 489, in call
result = self.forward(*input, **kwargs)
File "/content/MVIMP/third_party/DAIN/PWCNet/PWCNet.py", line 241, in forward
corr6 = self.corr(c16, c26)
File "/usr/local/lib/python3.6/dist-packages/torch/nn/modules/module.py", line 489, in call
result = self.forward(*input, kwargs)
File "/content/MVIMP/third_party/DAIN/PWCNet/correlation_package_pytorch1_0/correlation.py", line 106, in forward
)(input1, input2)
File "/content/MVIMP/third_party/DAIN/PWCNet/correlation_package_pytorch1_0/correlation.py", line 45, in forward
self.corr_multiply,
RuntimeError: CUDA call failed (correlation_forward_cuda at correlation_cuda.cc:80)
frame #0: std::function<std::string ()>::operator()() const + 0x11 (0x7f429e43bfe1 in /usr/local/lib/python3.6/dist-packages/torch/lib/libc10.so)
frame #1: c10::Error::Error(c10::SourceLocation, std::string const&) + 0x2a (0x7f429e43bdfa in /usr/local/lib/python3.6/dist-packages/torch/lib/libc10.so)
frame #2: correlation_forward_cuda(at::Tensor&, at::Tensor&, at::Tensor&, at::Tensor&, at::Tensor&, int, int, int, int, int, int) + 0x624 (0x7f429b008ba4 in /usr/local/lib/python3.6/dist-packages/correlation_cuda-0.0.0-py3.6-linux-x86_64.egg/correlation_cuda.cpython-36m-x86_64-linux-gnu.so)
frame #3: + 0x1556a (0x7f429b01456a in /usr/local/lib/python3.6/dist-packages/correlation_cuda-0.0.0-py3.6-linux-x86_64.egg/correlation_cuda.cpython-36m-x86_64-linux-gnu.so)
frame #4: + 0x12767 (0x7f429b011767 in /usr/local/lib/python3.6/dist-packages/correlation_cuda-0.0.0-py3.6-linux-x86_64.egg/correlation_cuda.cpython-36m-x86_64-linux-gnu.so)
frame #5: python3() [0x50a7f5]
frame #8: python3() [0x594b01]
frame #10: THPFunction_do_forward(THPFunction, _object) + 0x15c (0x7f42d876dbdc in /usr/local/lib/python3.6/dist-packages/torch/lib/libtorch_python.so)
frame #12: python3() [0x54ac61]
frame #14: python3() [0x50a783]
frame #17: python3() [0x594b01]
frame #20: python3() [0x507f24]
frame #22: python3() [0x594b01]
frame #23: python3() [0x54ac61]
frame #25: python3() [0x50a783]
frame #27: python3() [0x507f24]
frame #29: python3() [0x594b01]
frame #32: python3() [0x507f24]
frame #34: python3() [0x594b01]
frame #35: python3() [0x54ac61]
frame #37: python3() [0x50a783]
frame #39: python3() [0x507f24]
frame #40: python3() [0x509c50]
frame #41: python3() [0x50a64d]
frame #43: python3() [0x507f24]
frame #45: python3() [0x594b01]
frame #48: python3() [0x507f24]
frame #50: python3() [0x594b01]
frame #51: python3() [0x54ac61]
frame #53: python3() [0x50a783]
frame #55: python3() [0x507f24]
frame #56: python3() [0x509c50]
frame #57: python3() [0x50a64d]
frame #59: python3() [0x507f24]
frame #60: python3() [0x509c50]
frame #61: python3() [0x50a64d]
frame #63: python3() [0x507f24]
ffmpeg -hide_banner -loglevel warning -threads 4 -r 59.94 -f image2 -i /content/MVIMP/Data/Input/%10d.png -y -c:v libx264 -preset slow -crf 8 /content/MVIMP/Data/Output/danny-59.94.mp4
[png @ 0x559727e3c800] Invalid PNG signature 0x1A45DFA301000000.
Error while decoding stream #0:0: Invalid data found when processing input
The image-video fusion job is done.