import os import torch device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') # sets device for model and PyTorch tensors # Model parameters image_w = 112 image_h = 112 channel = 3 emb_size = 512 # Training parameters num_workers = 1 # for data-loading; right now, only 1 works with h5py grad_clip = 5. # clip gradients at an absolute value of print_freq = 100 # print training/validation stats every __ batches checkpoint = None # path to checkpoint, None if none # Data parameters num_classes = 93431 num_samples = 5179510 DATA_DIR = 'data' # faces_ms1m_folder = 'data/faces_ms1m_112x112' faces_ms1m_folder = 'data/ms1m-retinaface-t1' path_imgidx = os.path.join(faces_ms1m_folder, 'train.idx') path_imgrec = os.path.join(faces_ms1m_folder, 'train.rec') IMG_DIR = 'data/images' pickle_file = 'data/faces_ms1m_112x112.pickle'