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							- 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'
 
 
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