Pranav-Goyal
commented
4 years ago I'm posting the system configurations and versions of relevant libraries
OS: Ubuntu 16.04.6 LTS GCC version: (Ubuntu 5.4.0-6ubuntu1~16.04.12) 5.4.0 20160609 CMake version: version 3.5.1
Python version: 3.7 Is CUDA available: Yes CUDA runtime version: 9.0.176 GPU models and configuration: GPU 0: GeForce GTX 1080 Ti GPU 1: GeForce GTX 1080 Ti
Nvidia driver version: 440.33.01 cuDNN version: /usr/lib/x86_64-linux-gnu/libcudnn.so.7.6.5
Versions of relevant libraries:
[pip] numpy==1.17.4
[pip] torch==1.1.0
[pip] torchvision==0.2.2
[conda] blas 1.0 mkl
[conda] mkl 2019.4 243
[conda] mkl-service 2.3.0 py37he904b0f_0
[conda] mkl_fft 1.0.15 py37ha843d7b_0
[conda] mkl_random 1.1.0 py37hd6b4f25_0
[conda] pytorch 1.1.0 py3.7_cuda9.0.176_cudnn7.5.1_0 pytorch
[conda] pytorch-nightly 1.0.0.dev20190328 py3.7_cuda9.0.176_cudnn7.4.2_0 pytorch
[conda] torchvision 0.2.2 py_3 pytorch
Pillow (6.2.1)
kalupiu
On executing tools/test_net.py, I am getting a runtime error. I am using the default configurations with the pretrained model. When I increase the value of IMS_PER_BATCH, the error vanishes, however, the predictions that I obtain after this are highly incomplete, with most of the words not being detected.
File "tools/test_net.py", line 131, in
main()
File "tools/test_net.py", line 116, in main
output_folder=output_folder,
File "/home/pranav/PMTD/maskrcnn_benchmark/engine/inference.py", line 82, in inference
predictions = compute_on_dataset(model, data_loader, device, inference_timer)
File "/home/pranav/PMTD/maskrcnn_benchmark/engine/inference.py", line 28, in compute_on_dataset
output = model(images)
File "/tmp/yes/envs/maskrcnn_benchmark/lib/python3.7/site-packages/torch/nn/modules/module.py", line 491, in call
result = self.forward(*input, kwargs)
File "/home/pranav/PMTD/maskrcnn_benchmark/modeling/detector/generalized_rcnn.py", line 52, in forward
x, result, detector_losses = self.roi_heads(features, proposals, targets)
File "/tmp/yes/envs/maskrcnn_benchmark/lib/python3.7/site-packages/torch/nn/modules/module.py", line 491, in call
result = self.forward(*input, *kwargs)
File "/home/pranav/PMTD/maskrcnn_benchmark/modeling/roi_heads/roi_heads.py", line 39, in forward
x, detections, loss_mask = self.mask(mask_features, detections, targets)
File "/tmp/yes/envs/maskrcnn_benchmark/lib/python3.7/site-packages/torch/nn/modules/module.py", line 491, in call
result = self.forward(input, kwargs)
File "/home/pranav/PMTD/maskrcnn_benchmark/modeling/roi_heads/mask_head/mask_head.py", line 71, in forward
mask_logits = self.predictor(x)
File "/tmp/yes/envs/maskrcnn_benchmark/lib/python3.7/site-packages/torch/nn/modules/module.py", line 491, in call
result = self.forward(*input, kwargs)
File "/home/pranav/PMTD/maskrcnn_benchmark/modeling/roi_heads/mask_head/roi_mask_predictors.py", line 33, in forward
x = F.relu(self.conv5_mask(x))
File "/tmp/yes/envs/maskrcnn_benchmark/lib/python3.7/site-packages/torch/nn/modules/module.py", line 491, in call
result = self.forward(*input, *kwargs)
File "/tmp/yes/envs/maskrcnn_benchmark/lib/python3.7/site-packages/torch/nn/modules/container.py", line 97, in forward
input = module(input)
File "/tmp/yes/envs/maskrcnn_benchmark/lib/python3.7/site-packages/torch/nn/modules/module.py", line 491, in call
result = self.forward(input, kwargs)
File "/tmp/yes/envs/maskrcnn_benchmark/lib/python3.7/site-packages/torch/nn/modules/upsampling.py", line 134, in forward
return F.interpolate(input, self.size, self.scale_factor, self.mode, self.align_corners)
File "/tmp/yes/envs/maskrcnn_benchmark/lib/python3.7/site-packages/torch/nn/functional.py", line 2523, in interpolate
return torch._C._nn.upsample_bilinear2d(input, _output_size(2), align_corners)
RuntimeError: invalid argument 2: non-empty 4D input tensor expected but got: [0 x 256 x 14 x 14] at /opt/conda/conda-bld/pytorch-nightly_1553749764730/work/aten/src/THCUNN/generic/SpatialUpSamplingBilinear.cu:21