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