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