train_channels_GAN.py--rep${TRAIN_REP}--get_mat--gpu"0"--gen_nhiddens400,400,400--disc_nhiddens100,100,100\--gen_noise0.01--disc_noise0.2--gen_keep_prob0.5--disc_keep_prob0.5--gen_learning_rate0.001\--disc_learning_rate0.001--max_auc_batch1000--disc_global_p0.5--gen_global_p0.5--cross_entropy_weight0.5\--batch_size1000--csvs_freq5000--batch_num100000--n_dsteps5--n_gsteps3--round1--nout50000\--work_output_dir${output_directory}--samples${SAMPLES_PATH}--model${WORK_PATH}/base_model.bin--sub_sample0#disc_nhiddens - discriminator hidden layers#gen_nhiddens - generator hidden layers#model - to generate matrix with missing values to learn the GAN. this is trained model path, Or when no "get_mat", you can specify matrix directly in "data", "validation_data" argument.
Example output files:
W:\Users\Alon\But_Why\outputs\GAN\crc_gan_model.txt
there are 2 more files with additional suffix, when used, please specify the shortest file path without suffix