FFHQ Training

[KomputerMaster64]

Thank you for sharing the implementation of the DDGAN model. I am trying to train the model on FFHQ 256x256 dataset. I used the NVLabs/NVAE repository for the dataset preparation. I have the file structure as follows:



To use another dataset similar to the CelebA-HQ 256x256, I modified the train function given in the line 190 of the train_ddgan.py file.

    elif args.dataset == 'ffhq_256':
        train_transform = transforms.Compose([
                transforms.Resize(args.image_size),
                transforms.RandomHorizontalFlip(),
                transforms.ToTensor(),
                transforms.Normalize((0.5,0.5,0.5), (0.5,0.5,0.5))
            ])
        dataset = LMDBDataset(root='/datasets/ffhq-lmdb/', name='ffhq', train=True, transform=train_transform)

My implementation for the DDGAN uses 4 NVIDIA GTX 1080ti GPUs with a total batch size of 32 for training the CelebA-HQ 256x256 dataset

(--batch_size 8 and --num_process_per_node 4)

I use the following command for training!python3 train_ddgan.py --dataset ffhq_256 --image_size 256 --exp ddgan_celebahq_exp1 --num_channels 3 --num_channels_dae 64 --ch_mult 1 1 2 2 4 4 --num_timesteps 2 --num_res_blocks 2 --batch_size 8 --num_epoch 800 --ngf 64 --embedding_type positional --use_ema --r1_gamma 2. --z_emb_dim 256 --lr_d 1e-4 --lr_g 2e-4 --lazy_reg 10 --num_process_per_node 4 --save_content

I am getting the following output message:

Node rank 0, local proc 0, global proc 0
Node rank 0, local proc 1, global proc 1
Node rank 0, local proc 2, global proc 2
Node rank 0, local proc 3, global proc 3
Process Process-4:
Traceback (most recent call last):
  File "/usr/local/apps/python-3.8.3/lib/python3.8/multiprocessing/process.py", line 315, in _bootstrap
    self.run()
  File "/usr/local/apps/python-3.8.3/lib/python3.8/multiprocessing/process.py", line 108, in run
    self._target(*self._args, **self._kwargs)
  File "train_ddgan.py", line 482, in init_processes
    fn(rank, gpu, args)
  File "train_ddgan.py", line 248, in train
    dataset = LMDBDataset(root='/datasets/ffhq-lmdb/', name='ffhq', train=True, transform=train_transform)
  File "/home/manisha.padala/gan/denoising-diffusion-gan/datasets_prep/lmdb_datasets.py", line 33, in __init__
    self.data_lmdb = lmdb.open(lmdb_path, readonly=True, max_readers=1,
lmdb.Error: /datasets/ffhq-lmdb/train.lmdb: No such file or directory
Process Process-2:
Traceback (most recent call last):
  File "/usr/local/apps/python-3.8.3/lib/python3.8/multiprocessing/process.py", line 315, in _bootstrap
    self.run()
  File "/usr/local/apps/python-3.8.3/lib/python3.8/multiprocessing/process.py", line 108, in run
    self._target(*self._args, **self._kwargs)
  File "train_ddgan.py", line 482, in init_processes
    fn(rank, gpu, args)
  File "train_ddgan.py", line 248, in train
    dataset = LMDBDataset(root='/datasets/ffhq-lmdb/', name='ffhq', train=True, transform=train_transform)
  File "/home/manisha.padala/gan/denoising-diffusion-gan/datasets_prep/lmdb_datasets.py", line 33, in __init__
    self.data_lmdb = lmdb.open(lmdb_path, readonly=True, max_readers=1,
lmdb.Error: /datasets/ffhq-lmdb/train.lmdb: No such file or directory
Process Process-1:
Traceback (most recent call last):
  File "/usr/local/apps/python-3.8.3/lib/python3.8/multiprocessing/process.py", line 315, in _bootstrap
    self.run()
  File "/usr/local/apps/python-3.8.3/lib/python3.8/multiprocessing/process.py", line 108, in run
    self._target(*self._args, **self._kwargs)
  File "train_ddgan.py", line 482, in init_processes
    fn(rank, gpu, args)
  File "train_ddgan.py", line 248, in train
    dataset = LMDBDataset(root='/datasets/ffhq-lmdb/', name='ffhq', train=True, transform=train_transform)
  File "/home/manisha.padala/gan/denoising-diffusion-gan/datasets_prep/lmdb_datasets.py", line 33, in __init__
    self.data_lmdb = lmdb.open(lmdb_path, readonly=True, max_readers=1,
lmdb.Error: /datasets/ffhq-lmdb/train.lmdb: No such file or directory
Process Process-3:
Traceback (most recent call last):
  File "/usr/local/apps/python-3.8.3/lib/python3.8/multiprocessing/process.py", line 315, in _bootstrap
    self.run()
  File "/usr/local/apps/python-3.8.3/lib/python3.8/multiprocessing/process.py", line 108, in run
    self._target(*self._args, **self._kwargs)
  File "train_ddgan.py", line 482, in init_processes
    fn(rank, gpu, args)
  File "train_ddgan.py", line 248, in train
    dataset = LMDBDataset(root='/datasets/ffhq-lmdb/', name='ffhq', train=True, transform=train_transform)
  File "/home/manisha.padala/gan/denoising-diffusion-gan/datasets_prep/lmdb_datasets.py", line 33, in __init__
    self.data_lmdb = lmdb.open(lmdb_path, readonly=True, max_readers=1,
lmdb.Error: /datasets/ffhq-lmdb/train.lmdb: No such file or directory