Facing the error about relgan

[weilinie]

The error seems come from gen_o has not been properly converted to a Tensor from a TenorArray. Could you add gen_o.stack() in your code? I also updated the rmc_att and rmc_vdcnn in case that you were using them.

[mmkjj]

But after adding gen_o.stack(),Another Error happended:

\oracle\oracle_gan\oracle_train.py", line 314, in get_train_ops
temp_train_op = temp_optimizer.apply_gradients(zip(temp_grads, [temperature]))
lib\site-packages\tensorflow\python\training\optimizer.py", line 472, in apply_gradients
([str(v) for _, _, v in converted_grads_and_vars],))
ValueError: No gradients provided for any variable: ['<tensorflow.python.training.optimizer._RefVariableProcessor object at 0x000001CF5ED1C390>'].

[weilinie]

Not sure where you added gen_o.stack(). Can you confirm if you are using rmc_att or rmc_vdcnn? If so, maybe you can pull it again and see if you can run properly.

[mmkjj]

I changed the get_losses() function in oracle_train.py:
from log_pg = tf.reduce_mean(tf.log(gen_o + EPS))
to 'log_pg = tf.reduce_mean(tf.log(gen_o.stack() + EPS))'
I used the default parameters, So I think that the generator and discriminator are both rmc_att, and type of the GAN is standard

[weilinie]

OK, there is something wrong with rmc_att and I fixed it. Also, I changed the default GAN architecture in run.py to rmc_vanilla, because all the experiments in the paper are based on rmc_vanilla actually. Can you pull it again?

[mmkjj]

I downloaded all of your new code again,. This time I think the default GAN architecture is rmc_vanilla.
However it seems that I'm facing a new Error :

oracle\oracle_gan\oracle_train.py", line 355, in get_metric_summary_op
metric_summary_op = tf.summary.merge(metrics_sum)
lib\site-packages\tensorflow\python\summary\summary.py", line 271, in merge
val = _gen_logging_ops._merge_summary(inputs=inputs, name=name)
lib\site-packages\tensorflow\python\ops\gen_logging_ops.py", line 314, in _merge_summary
"MergeSummary", inputs=inputs, name=name)
lib\site-packages\tensorflow\python\framework\op_def_library.py", line 570, in _apply_op_helper
(input_name, op_type_name, len(values), num_attr.minimum))
ValueError: List argument 'inputs' to 'MergeSummary' Op with length 0 shorter than minimum length 1.

[weilinie]

This is because all the metrics are set to False with the default setting in run.py (line 41-45). You can set at least one of the metrics to True to avoid this issue.

[mmkjj]

Oh,solved..
Thank you very much :)