Output of Network is NaN about complex-networks-release HOT 2 OPEN

Hi @Mrvolcan,

I have the same error and could not overcome it. If you could overcome, please share it. Because I could not have reconstructed Bart recon,too with NaN metric value.

Best,

from complex-networks-release.

I ran into the same problem as above:
I carefully check the Data, network architecture and training parameters as follows:

Train data:
The knee dataset: http://old.mrida​ta.org/fully​sampl​ed/knees
20 subjects, spliting into train, validation, and test subset. The training data consists of 4800 images.

Network architecture
I used the default codes to construct network architecture:

im_out_place = mri_model.unroll_fista(
            ks_place,
            sense_place,
            is_training=True,
            verbose=True,
            do_hardproj=FLAGS.do_hard_proj,
            num_summary_image=FLAGS.num_summary_image,
            resblock_num_features=FLAGS.feat_map,
            num_grad_steps=FLAGS.num_grad_steps,
            conv=FLAGS.conv,
            do_conjugate=FLAGS.do_conjugate,
            activation=FLAGS.activation
        )

Training parameters:
I used the same training parameters as in the article:

batch_size = 2
adam_beta1 = 0.9,
adam_beta1 = 0.999. 
learning rate = 0.001

Error results:
As the number of training steps increases, the reconstructed image suddenly becomes abnormal and the error is very large as follows:

Results of step = 33:

Results of step = 175:

The loss function:

from complex-networks-release.