Closed edmondja closed 1 year ago
@edmondja oh my bad, do you want to try 0.1.5?
No worries thanks, the fix worked (but I had to use 64x64 pictures instead of 32x32 "RuntimeError: Calculated padded input size per channel: (2 x 2). Kernel size: (4 x 4). Kernel size can't be greater than actual input size")
cool, happy training :smile:
Hello, after running the below code, it says "TypeError: isinstance() arg 2 must be a type or tuple of types", what did I do wrong ? ` for i in range(len(train)): im = np.array(train[i]) im = cv2.resize(im, dsize=(32, 32), interpolation=cv2.INTERCUBIC)[:, :, None] im = np.concatenate((im,im,im), axis=2) name = './mnist/im'+str(i)+'.png' cv2.imwrite(name, im)
import torch from muse_maskgit_pytorch import VQGanVAE, VQGanVAETrainer
vae = VQGanVAE( dim = 16, vq_codebook_size = 32 )
train on folder of images, as many images as possible
trainer = VQGanVAETrainer( vae = vae, image_size = 32, # you may want to start with small images, and then curriculum learn to larger ones, but because the vae is all convolution, it should generalize to 512 (as in paper) without training on it folder = './mnist', batch_size = 2, grad_accum_every = 8, num_train_steps = 100000 )#.cuda() Traceback (most recent call last):
File "C:\Users\Ext.Edmond_Jacoupeau\AppData\Local\Temp\ipykernel_3136\1437749784.py", line 11, in
trainer = VQGanVAETrainer(
File "<@beartype(muse_maskgit_pytorch.trainers.VQGanVAETrainer.init) at 0x278d4d5e040>", line 48, in init
File "C:\Users\Ext.Edmond_Jacoupeau\Anaconda3\envs\py39\lib\site-packages\muse_maskgit_pytorch\trainers.py", line 149, in init ddp_kwargs = find_and_pop(
File "C:\Users\Ext.Edmond_Jacoupeau\Anaconda3\envs\py39\lib\site-packages\muse_maskgit_pytorch\trainers.py", line 47, in find_and_pop ind = find_index(arr, cond)
File "C:\Users\Ext.Edmond_Jacoupeau\Anaconda3\envs\py39\lib\site-packages\muse_maskgit_pytorch\trainers.py", line 42, in find_index if cond(el):
TypeError: isinstance() arg 2 must be a type or tuple of types `