Fail to load network .pkl file

[Baoren1996]

I tried to download the saved network from the link below:
https://zenodo.org/record/10947091/files/stylesan-xl_cifar10.pkl
however, when I tried to use the following code for evaluation:

python calc_metrics.py --metrics=fid50k_full --network=./stylesan-xl_cifar10.pkl

but got error:

Python==3.8.10
Pytorch==2.4.0+cu121

Can somebody help?

[TakashiShibuyaSony]

Hello, thank you for reaching out to us!

Our recommendation is preparing a Docker container, following the README.md.
https://github.com/sony/san/tree/main/stylesan-xl#requirements

If you don't want to rely on Docker for some reason, it should be good to use the same versions of packages described in the following files.

san/stylesan-xl/requirements.txt

Lines 1 to 20 in 0e52b14

	numpy>=1.20
	click>=8.0
	pillow>=8.3.1
	scipy>=1.7.1
	requests>=2.26.0
	tqdm>=4.62.2
	ninja>=1.10.2
	matplotlib>=3.4.2
	imageio>=2.9.0
	dill>=0.3.4
	psutil>=5.8.0
	regex>=2022.3.15
	pillow>=8.3.1
	imgui>=1.3.0
	glfw>=2.2.0
	pyopengl>=3.1.5
	imageio-ffmpeg>=0.4.3
	pyspng
	ftfy>=6.1.1
	timm==0.4.12

san/stylesan-xl/Dockerfile

Line 5 in 0e52b14

RUN pip install torch==2.1.1 torchvision==0.16.1 torchaudio==2.1.1 --index-url https://download.pytorch.org/whl/cu121

This may work.

Thank you.

[Baoren1996]

Hello, thank you for reaching out to us!

Our recommendation is preparing a Docker container, following the README.md. https://github.com/sony/san/tree/main/stylesan-xl#requirements

If you don't want to rely on Docker for some reason, it should be good to use the same versions of packages described in the following files.

san/stylesan-xl/requirements.txt

Lines 1 to 20 in 0e52b14

	numpy>=1.20
	click>=8.0
	pillow>=8.3.1
	scipy>=1.7.1
	requests>=2.26.0
	tqdm>=4.62.2
	ninja>=1.10.2
	matplotlib>=3.4.2
	imageio>=2.9.0
	dill>=0.3.4
	psutil>=5.8.0
	regex>=2022.3.15
	pillow>=8.3.1
	imgui>=1.3.0
	glfw>=2.2.0
	pyopengl>=3.1.5
	imageio-ffmpeg>=0.4.3
	pyspng
	ftfy>=6.1.1
	timm==0.4.12

san/stylesan-xl/Dockerfile

Line 5 in 0e52b14

RUN pip install torch==2.1.1 torchvision==0.16.1 torchaudio==2.1.1 --index-url https://download.pytorch.org/whl/cu121

This may work.
Thank you.

Hi @TakashiShibuyaSony, thanks for your instruction which works perfectly for me.

Another question, given the CIFAR model snapshot, is there any way to resume the training from the pkl file? do I also need the stem network .pkl file?

Thanks a lot in advance.

Best,
Baoren

[TakashiShibuyaSony]

Hi @Baoren1996,
You can resume the training by using the following option. You should provide the path of the .pkl file.

san/stylesan-xl/train.py

Line 144 in 0e52b14

@click.option('--resume', help='Resume from given network pickle', metavar='[PATH|URL]', type=str)

Regarding the .pkl file of the stem network, the current code requires it (Our codebase build on that of StyleGAN-XL, and their code requires a stem network even in resuming training). But, I guess you can resume the training without the stem network by reloading the ckpt for resume in the following lines again.

san/stylesan-xl/training/networks_stylegan3_resetting.py

Lines 613 to 614 in 0e52b14

	with dnnlib.util.open_url(path_stem) as f:
	G_stem = legacy.load_network_pkl(f)['G_ema']

And, the succeeding lines should also be modified. In particular, the following lines are not necessary in this case because these lines are for appending new layers in progressive training.

san/stylesan-xl/training/networks_stylegan3_resetting.py

Lines 651 to 673 in 0e52b14

	# initialize new_layers
	last_stem_layer = getattr(self.synthesis, self.synthesis.layer_names[-1])
	fparams = self.compute_superres_filterparams(up_factor, self.img_resolution, last_stem_layer, head_layers)
	self.head_layer_names = []
	for idx in range(head_layers + 1):
	prev = max(idx - 1, 0)
	is_torgb = (idx == head_layers)
	is_critically_sampled = (idx >= head_layers - self.num_critical)
	use_fp16 = (fparams.sampling_rates[idx] * (2 ** self.num_fp16_res) > self.img_resolution)
	layer = SynthesisLayer(
	w_dim=self.w_dim, is_torgb=is_torgb, is_critically_sampled=is_critically_sampled, use_fp16=use_fp16,
	in_channels=int(fparams.channels[prev]), out_channels= int(fparams.channels[idx]),
	in_size=int(fparams.sizes[prev]), out_size=int(fparams.sizes[idx]),
	in_sampling_rate=int(fparams.sampling_rates[prev]), out_sampling_rate=int(fparams.sampling_rates[idx]),
	in_cutoff=fparams.cutoffs[prev], out_cutoff=fparams.cutoffs[idx],
	in_half_width=fparams.half_widths[prev], out_half_width=fparams.half_widths[idx],
	conv_kernel=self.conv_kernel, use_radial_filters=self.use_radial_filters,
	)
	name = f'L{idx+stem_len}_{layer.out_size[0]}_{layer.out_channels}'
	setattr(self.synthesis, name, layer)
	self.synthesis.layer_names.append(name)
	self.head_layer_names.append(name)

Thanks!

[Cwyxx]

Update dill to 0.3.9. It works for me.

[TakashiShibuyaSony]

Hi @Cwyxx, Thank you very much for your helpful information. We updated requirements.txt

[rielmvp]

Hello @Baoren1996 and author @TakashiShibuyaSony ,

I also downloaded the saved network from the link below:
https://zenodo.org/record/10947091/files/stylesan-xl_cifar10.pkl

and I also got the same error when I tried to run the code for evaluation:
python calc_metrics.py --metrics=fid50k_full --network=./stylesan-xl_cifar10.pkl

I also got a similar error when I wanted to run this code:

import torch
import numpy as np
import pickle
import dill
import legacy
from tqdm import tqdm
from torch.utils.data import DataLoader, Dataset
import torchvision.transforms as transforms
import os
import re
from typing import List, Optional, Tuple, Union

import click
import dnnlib
import PIL.Image
import legacy
from torch_utils import gen_utils
import torch_utils

#Load the pre-trained StyleGANXL-SAN Model and set the device (GPU 0)
pkl_path = 'stylesan-xl_cifar10.pkl'  # Path to your .pkl file
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
# Load the pretrained StyleGAN-XL-SAN model and extract the discriminator
print(f"Loading model from {pkl_path}...")
with dnnlib.util.open_url(pkl_path) as f:
    model = legacy.load_network_pkl(f)  # Load the full model dictionary

print(model)

These are the errors:

My Python version is 3.8.20, Pytorch version 2.4.1+cu121 and I installed all packages as mentioned in requirements.txt (including dill==0.3.9). I was wondering about how to fix the issue, since I think I followed all the requirements
@Baoren1996 Did you use Docker instead, by any chance?

Any insight would be very helpful.