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sumuzhao / CycleGAN-Music-Style-Transfer

Symbolic Music Genre Transfer with CycleGAN
MIT License
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Unable to train CycleGAN or genre classifier model #1

Closed wanshun123 closed 6 years ago

wanshun123 commented 6 years ago

I'm trying to train a CycleGAN model as follows:

python main.py --dataset_A_dir='Pop' --dataset_B_dir='Classic' --type='cyclegan' --model='full' --sigma_d=1 --phase='train'

This doesn't seem to generate anything on my machine, though there is no error - I just get the following output:

generatorA2B/g_e1_c/Conv/weights:0
generatorA2B/g_e1_bn/scale:0
generatorA2B/g_e1_bn/offset:0
generatorA2B/g_e2_c/Conv/weights:0
generatorA2B/g_e2_bn/scale:0
generatorA2B/g_e2_bn/offset:0
generatorA2B/g_e3_c/Conv/weights:0
generatorA2B/g_e3_bn/scale:0
generatorA2B/g_e3_bn/offset:0
generatorA2B/g_r1_c1/Conv/weights:0
generatorA2B/g_r1_bn1/scale:0
generatorA2B/g_r1_bn1/offset:0
generatorA2B/g_r1_c2/Conv/weights:0
generatorA2B/g_r1_bn2/scale:0
generatorA2B/g_r1_bn2/offset:0
generatorA2B/g_r2_c1/Conv/weights:0
generatorA2B/g_r2_bn1/scale:0
generatorA2B/g_r2_bn1/offset:0
generatorA2B/g_r2_c2/Conv/weights:0
generatorA2B/g_r2_bn2/scale:0
generatorA2B/g_r2_bn2/offset:0
generatorA2B/g_r3_c1/Conv/weights:0
generatorA2B/g_r3_bn1/scale:0
generatorA2B/g_r3_bn1/offset:0
generatorA2B/g_r3_c2/Conv/weights:0
generatorA2B/g_r3_bn2/scale:0
generatorA2B/g_r3_bn2/offset:0
generatorA2B/g_r4_c1/Conv/weights:0
generatorA2B/g_r4_bn1/scale:0
generatorA2B/g_r4_bn1/offset:0
generatorA2B/g_r4_c2/Conv/weights:0
generatorA2B/g_r4_bn2/scale:0
generatorA2B/g_r4_bn2/offset:0
generatorA2B/g_r5_c1/Conv/weights:0
generatorA2B/g_r5_bn1/scale:0
generatorA2B/g_r5_bn1/offset:0
generatorA2B/g_r5_c2/Conv/weights:0
generatorA2B/g_r5_bn2/scale:0
generatorA2B/g_r5_bn2/offset:0
generatorA2B/g_r6_c1/Conv/weights:0
generatorA2B/g_r6_bn1/scale:0
generatorA2B/g_r6_bn1/offset:0
generatorA2B/g_r6_c2/Conv/weights:0
generatorA2B/g_r6_bn2/scale:0
generatorA2B/g_r6_bn2/offset:0
generatorA2B/g_r7_c1/Conv/weights:0
generatorA2B/g_r7_bn1/scale:0
generatorA2B/g_r7_bn1/offset:0
generatorA2B/g_r7_c2/Conv/weights:0
generatorA2B/g_r7_bn2/scale:0
generatorA2B/g_r7_bn2/offset:0
generatorA2B/g_r8_c1/Conv/weights:0
generatorA2B/g_r8_bn1/scale:0
generatorA2B/g_r8_bn1/offset:0
generatorA2B/g_r8_c2/Conv/weights:0
generatorA2B/g_r8_bn2/scale:0
generatorA2B/g_r8_bn2/offset:0
generatorA2B/g_r9_c1/Conv/weights:0
generatorA2B/g_r9_bn1/scale:0
generatorA2B/g_r9_bn1/offset:0
generatorA2B/g_r9_c2/Conv/weights:0
generatorA2B/g_r9_bn2/scale:0
generatorA2B/g_r9_bn2/offset:0
generatorA2B/g_r10_c1/Conv/weights:0
generatorA2B/g_r10_bn1/scale:0
generatorA2B/g_r10_bn1/offset:0
generatorA2B/g_r10_c2/Conv/weights:0
generatorA2B/g_r10_bn2/scale:0
generatorA2B/g_r10_bn2/offset:0
generatorA2B/g_d1_dc/Conv2d_transpose/weights:0
generatorA2B/g_d1_bn/scale:0
generatorA2B/g_d1_bn/offset:0
generatorA2B/g_d2_dc/Conv2d_transpose/weights:0
generatorA2B/g_d2_bn/scale:0
generatorA2B/g_d2_bn/offset:0
generatorA2B/g_pred_c/Conv/weights:0
generatorB2A/g_e1_c/Conv/weights:0
generatorB2A/g_e1_bn/scale:0
generatorB2A/g_e1_bn/offset:0
generatorB2A/g_e2_c/Conv/weights:0
generatorB2A/g_e2_bn/scale:0
generatorB2A/g_e2_bn/offset:0
generatorB2A/g_e3_c/Conv/weights:0
generatorB2A/g_e3_bn/scale:0
generatorB2A/g_e3_bn/offset:0
generatorB2A/g_r1_c1/Conv/weights:0
generatorB2A/g_r1_bn1/scale:0
generatorB2A/g_r1_bn1/offset:0
generatorB2A/g_r1_c2/Conv/weights:0
generatorB2A/g_r1_bn2/scale:0
generatorB2A/g_r1_bn2/offset:0
generatorB2A/g_r2_c1/Conv/weights:0
generatorB2A/g_r2_bn1/scale:0
generatorB2A/g_r2_bn1/offset:0
generatorB2A/g_r2_c2/Conv/weights:0
generatorB2A/g_r2_bn2/scale:0
generatorB2A/g_r2_bn2/offset:0
generatorB2A/g_r3_c1/Conv/weights:0
generatorB2A/g_r3_bn1/scale:0
generatorB2A/g_r3_bn1/offset:0
generatorB2A/g_r3_c2/Conv/weights:0
generatorB2A/g_r3_bn2/scale:0
generatorB2A/g_r3_bn2/offset:0
generatorB2A/g_r4_c1/Conv/weights:0
generatorB2A/g_r4_bn1/scale:0
generatorB2A/g_r4_bn1/offset:0
generatorB2A/g_r4_c2/Conv/weights:0
generatorB2A/g_r4_bn2/scale:0
generatorB2A/g_r4_bn2/offset:0
generatorB2A/g_r5_c1/Conv/weights:0
generatorB2A/g_r5_bn1/scale:0
generatorB2A/g_r5_bn1/offset:0
generatorB2A/g_r5_c2/Conv/weights:0
generatorB2A/g_r5_bn2/scale:0
generatorB2A/g_r5_bn2/offset:0
generatorB2A/g_r6_c1/Conv/weights:0
generatorB2A/g_r6_bn1/scale:0
generatorB2A/g_r6_bn1/offset:0
generatorB2A/g_r6_c2/Conv/weights:0
generatorB2A/g_r6_bn2/scale:0
generatorB2A/g_r6_bn2/offset:0
generatorB2A/g_r7_c1/Conv/weights:0
generatorB2A/g_r7_bn1/scale:0
generatorB2A/g_r7_bn1/offset:0
generatorB2A/g_r7_c2/Conv/weights:0
generatorB2A/g_r7_bn2/scale:0
generatorB2A/g_r7_bn2/offset:0
generatorB2A/g_r8_c1/Conv/weights:0
generatorB2A/g_r8_bn1/scale:0
generatorB2A/g_r8_bn1/offset:0
generatorB2A/g_r8_c2/Conv/weights:0
generatorB2A/g_r8_bn2/scale:0
generatorB2A/g_r8_bn2/offset:0
generatorB2A/g_r9_c1/Conv/weights:0
generatorB2A/g_r9_bn1/scale:0
generatorB2A/g_r9_bn1/offset:0
generatorB2A/g_r9_c2/Conv/weights:0
generatorB2A/g_r9_bn2/scale:0
generatorB2A/g_r9_bn2/offset:0
generatorB2A/g_r10_c1/Conv/weights:0
generatorB2A/g_r10_bn1/scale:0
generatorB2A/g_r10_bn1/offset:0
generatorB2A/g_r10_c2/Conv/weights:0
generatorB2A/g_r10_bn2/scale:0
generatorB2A/g_r10_bn2/offset:0
generatorB2A/g_d1_dc/Conv2d_transpose/weights:0
generatorB2A/g_d1_bn/scale:0
generatorB2A/g_d1_bn/offset:0
generatorB2A/g_d2_dc/Conv2d_transpose/weights:0
generatorB2A/g_d2_bn/scale:0
generatorB2A/g_d2_bn/offset:0
generatorB2A/g_pred_c/Conv/weights:0
discriminatorB/d_h0_conv/Conv/weights:0
discriminatorB/d_h1_conv/Conv/weights:0
discriminatorB/d_bn1/scale:0
discriminatorB/d_bn1/offset:0
discriminatorB/d_h3_pred/Conv/weights:0
discriminatorA/d_h0_conv/Conv/weights:0
discriminatorA/d_h1_conv/Conv/weights:0
discriminatorA/d_bn1/scale:0
discriminatorA/d_bn1/offset:0
discriminatorA/d_h3_pred/Conv/weights:0
discriminatorA_all/d_h0_conv/Conv/weights:0
discriminatorA_all/d_h1_conv/Conv/weights:0
discriminatorA_all/d_bn1/scale:0
discriminatorA_all/d_bn1/offset:0
discriminatorA_all/d_h3_pred/Conv/weights:0
discriminatorB_all/d_h0_conv/Conv/weights:0
discriminatorB_all/d_h1_conv/Conv/weights:0
discriminatorB_all/d_bn1/scale:0
discriminatorB_all/d_bn1/offset:0
discriminatorB_all/d_h3_pred/Conv/weights:0

While with the genre classifier, If I try for example:

python main.py --dataset_A_dir='Pop' --dataset_B_dir='Classic' --type='classifier' --sigma_c=1 --phase='train' I get the following:

Traceback (most recent call last):
  File "main.py", line 72, in <module>
    tf.app.run()
  File "/home/paperspace/anaconda3/lib/python3.6/site-packages/tensorflow/python/platform/app.py", line 126, in run
    _sys.exit(main(argv))
  File "main.py", line 68, in main
    classifier.train(args) if args.phase == 'train' else classifier.test(args)
  File "/home/paperspace/music/CycleGAN-Music-Style-Transfer/style_classifier.py", line 124, in train
    gaussian_noise = np.random.normal(0, self.sigma_c, [data_test.shape[0], data_test.shape[1],
IndexError: tuple index out of range
sumuzhao commented 6 years ago

Hey, I run the cyclegan model and classifier model and it seems there is no problems. First, I update the ReadMe, and go to have a look at version part to make sure all your packages with the right versions. Also, make sure your GPU settings correctly. Second, you cannot feed the datasets in the google drive directly. I explain a bit in the datasets part. You should do some further processing before you feed them to the inputs.