learn_prox_ops
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Error when training the DNCNN
I tried to train the model by running the command
python3 src/tf_solver.py --sigma_noise 0.02 --batch_size 128 --network DNCNN --channels 1 --pipeline bsds500 --device_name /gpu:0 --train_epochs 100
But I received an error
Traceback (most recent call last):
File "src/tf_solver.py", line 326, in <module>
main()
File "src/tf_solver.py", line 322, in main
solver = Solver()
File "src/tf_solver.py", line 120, in __init__
pipelines = PIPELINES[opt.pipelines](opt, test_epochs=None)
File "/home/uzair/Denoising_Raeid/learn_prox_ops/src/data.py", line 143, in __init__
opt.train_epochs)
File "/home/uzair/Denoising_Raeid/learn_prox_ops/src/data.py", line 239, in tf_data_pipeline
min_after_dequeue=min_after_dequeue)
File "/home/uzair/Denoising_Raeid/learn_prox_ops/src/utilities.py", line 291, in
tf_shuffle_batch_join
tensor_list_list, enqueue_many)
TypeError: _store_sparse_tensors_join() missing 1 required positional argument: 'keep_input'
How can I fix this? Thanks
I reproduced the error and there seems to be a problem with the TensorFlow version. I will try to fix it but until then I can highly recommend this repository. Which includes a more recent DnCNN reimplementation with scores closer to the original paper.