"eval_realpath = '/home/wn455752/repo/evaluation/data/afhq' # path to real images (assumes the dir has two subdirs - train and test)\n",
"eval_genpath = '/home/wn455752/repo/evaluation/samples/afhq_samples/samples/epoch_499_no_cfg/epoch_500/sample_1' # path to sampled images\n",
"eval_size=image_size # resolution of training images\n",
"eval_arch='clip' # DO NOT CHANGE\n",
"eval_mode='both' # choose between 'kNN' and 'pairs' (for closest pairs) or 'both'\n",
"eval_k_kNN=3 # choose k for kNN\n",
"eval_sample=10 # in case of kNN, find kNN of first 'sample' number of generated samples\n",
" # in case of pairs, find top 'sample' number of closest pairs of \n",
" # real-generated images from the entire set of generated samples\n",
"eval_fid='yes' # whether to compute FID, IS scores (for class conditional)\n",
"eval_name_appendix='afhq_eval_ep_499_no_cfg' # name appendix\n",
"\n",
"# inpainting\n",
"#eval_realpath = '/home/wn455752/repo/evaluation/samples/inpainting_samples/paint_lhq/samples/epoch_190/sample_12/raw/' # path to real images (assumes the dir has two subdirs - train and test)\n",
"#eval_genpath = '/home/wn455752/repo/evaluation/samples/inpainting_samples/paint_lhq/samples/epoch_190/sample_12/inpaint/' # path to sampled images\n",
"#eval_size=image_size # resolution of training images\n",
"#eval_arch='clip' # choose between 'clip' or 'cnn'\n",
"#eval_mode='pairs' # DO NOT CHANGE\n",
"#eval_k_kNN=3 # choose k for kNN\n",
"#eval_sample=20 # in case of kNN, find kNN of first 'sample' number of generated samples\n",
" # in case of pairs, find top 'sample' number of closest pairs of \n",
" # real-generated images from the entire set of generated samples\n",
"#eval_fid='yes' # whether to compute PSNR & SSIM\n",
"#eval_name_appendix='inpaint_eval_ep_190' # name appendix\n",
# Path to save generated experiment folder on local machine
# Path to save generated experiment folder on local machine
local_path="experiments/"+run_name+'/settings'
local_path="experiments/"+run_name+'/settings'
# Diffusion Model Settings
# Diffusion Model Settings
diffusion_steps=1000
diffusion_steps=1000
image_size=128
image_size=128
channels=3
channels=3
# Training
# Training
batchsize=32
batchsize=32
epochs=100
epochs=100
store_iter=10
store_iter=10
eval_iter=500
eval_iter=500
learning_rate=0.0001
learning_rate=0.0001
optimizername="torch.optim.AdamW"
optimizername="torch.optim.AdamW"
optimizer_params=None
optimizer_params=None
verbose=False
verbose=False
# checkpoint = None #(If no checkpoint training, ie. random weights)
# checkpoint = None #(If no checkpoint training, ie. random weights)
# Sampling
# Sampling
sample_size=20
sample_size=20
intermediate=False# True if you want to sample one image and all ist intermediate latents
intermediate=False# True if you want to sample one image and all ist intermediate latents
sample_all=False
sample_all=False
# Evaluating
# Evaluating
...
# class conditional
eval_realpath='/home/wn455752/repo/evaluation/data/afhq'# path to real images (assumes the dir has two subdirs - train and test)
eval_genpath='/home/wn455752/repo/evaluation/samples/afhq_samples/samples/epoch_499_no_cfg/epoch_500/sample_1'# path to sampled images
eval_size=image_size# resolution of training images
eval_arch='clip'# DO NOT CHANGE
eval_mode='both'# choose between 'kNN' and 'pairs' (for closest pairs) or 'both'
eval_k_kNN=3# choose k for kNN
eval_sample=10# in case of kNN, find kNN of first 'sample' number of generated samples
# in case of pairs, find top 'sample' number of closest pairs of
# real-generated images from the entire set of generated samples
eval_fid='yes'# whether to compute FID, IS scores (for class conditional)
eval_name_appendix='afhq_eval_ep_499_no_cfg'# name appendix
# inpainting
#eval_realpath = '/home/wn455752/repo/evaluation/samples/inpainting_samples/paint_lhq/samples/epoch_190/sample_12/raw/' # path to real images (assumes the dir has two subdirs - train and test)
#eval_genpath = '/home/wn455752/repo/evaluation/samples/inpainting_samples/paint_lhq/samples/epoch_190/sample_12/inpaint/' # path to sampled images
#eval_size=image_size # resolution of training images
#eval_arch='clip' # choose between 'clip' or 'cnn'
#eval_mode='pairs' # DO NOT CHANGE
#eval_k_kNN=3 # choose k for kNN
#eval_sample=20 # in case of kNN, find kNN of first 'sample' number of generated samples
# in case of pairs, find top 'sample' number of closest pairs of
# real-generated images from the entire set of generated samples
#eval_fid='yes' # whether to compute PSNR & SSIM
#eval_name_appendix='inpaint_eval_ep_190' # name appendix