daniilidis-group / daniilidis-group/EV-FlowNet

error in test.py

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Python
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Description

Hi, I run the test.py but I got some errors, when I run

python test.py --training_instance ev-flownet --test_sequence outdoor_day1

`2020-03-04 11:05:04.723091: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1097] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 10556 MB memory) -> physical GPU (device: 0, name: TITAN V, pci bus id: 0000:0f:00.0, compute capability: 7.0)
Loading data!
Read 787 images
Testing done.
2020-03-04 11:05:07.412942: W tensorflow/core/kernels/queue_base.cc:285] _0_parallel_read/filenames: Skipping cancelled dequeue attempt with queue not closed
2020-03-04 11:05:07.414032: W tensorflow/core/kernels/queue_base.cc:285] _1_parallel_read/common_queue: Skipping cancelled dequeue attempt with queue not closed
2020-03-04 11:05:07.414954: W tensorflow/core/kernels/queue_base.cc:285] _0_parallel_read/filenames: Skipping cancelled dequeue attempt with queue not closed
2020-03-04 11:05:07.414973: W tensorflow/core/kernels/queue_base.cc:285] _0_parallel_read/filenames: Skipping cancelled dequeue attempt with queue not closed
2020-03-04 11:05:07.416645: W tensorflow/core/kernels/queue_base.cc:285] _1_parallel_read/common_queue: Skipping cancelled dequeue attempt with queue not closed
2020-03-04 11:05:07.416663: W tensorflow/core/kernels/queue_base.cc:285] _1_parallel_read/common_queue: Skipping cancelled dequeue attempt with queue not closed
2020-03-04 11:05:07.416672: W tensorflow/core/kernels/queue_base.cc:285] _1_parallel_read/common_queue: Skipping cancelled dequeue attempt with queue not closed
`

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Research direction

Start with test.py and reproduce the reported command: python test.py --training_instance ev-flownet --test_sequence outdoor_day1. Compare the observed TensorFlow GPU and queue warnings with the expected test result and determine whether testing actually failed after “Testing done.” Done means documenting a confirmed cause and reproducible fix or clarification.

Written by the indexing model from the issue text.

Assessment

Tech stack
python, tensorflow
Domain
machine-learning
Issue type
Bug
Difficulty
4/5
Estimated time
3-5 days
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
30/100

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