eldar

def train():
    torch.backends.cuda.matmul.allow_tf32 = True
    # ...
    
    args.lr = 0.00005 # best for Mast3r
    args.weight_decay = 0.05 # from Mast3r
    
    # following timm: set wd as 0 for bias and norm layers
    param_groups = misc.get_parameter_groups(model_without_ddp, args.weight_decay)
    optimizer = torch.optim.AdamW(param_groups, lr=args.lr, betas=(0.9, 0.95))

eldar

import argparse
from pathlib import Path
import json

from pyquaternion import Quaternion
import numpy as np
import torch
import torch.nn.functional as F
from imageio.v3 import imread