def __init__(self, options=None, conf_path=None):
self.settings = options or Option(conf_path)
self.checkpoint = None
self.train_loader = None
self.val_loader = None
self.original_model = None
self.pruned_model = None
self.aux_fc_state = None
self.aux_fc_opt_state = None
self.seg_opt_state = None
self.current_pivot_index = None
self.epoch = 0
os.environ['CUDA_VISIBLE_DEVICES'] = self.settings.gpu
self.settings.set_save_path()
write_settings(self.settings)
self.logger = get_logger(self.settings.save_path, "dcp")
self.tensorboard_logger = TensorboardLogger(self.settings.save_path)
self.settings.copy_code(self.logger,
src=os.path.abspath('./'),
dst=os.path.join(self.settings.save_path,
'code'))
self.logger.info("|===>Result will be saved at {}".format(
self.settings.save_path))
self.prepare()
def __init__(self, options=None, conf_path=None):
self.settings = options or Option(conf_path)
self.checkpoint = None
self.train_loader = None
self.val_loader = None
self.pruned_model = None
self.network_wise_trainer = None
self.optimizer_state = None
self.aux_fc_state = None
os.environ['CUDA_VISIBLE_DEVICES'] = self.settings.gpu
self.settings.set_save_path()
write_settings(self.settings)
self.logger = get_logger(self.settings.save_path, "finetune")
self.tensorboard_logger = TensorboardLogger(self.settings.save_path)
self.logger.info("|===>Result will be saved at {}".format(self.settings.save_path))
self.epoch = 0
self.test_input = None
self.prepare()
if __name__ == "__main__":
# model = MobileFaceNet(128, blocks=[1, 2, 2, 1]) # 2.36 M
# model = MobileFaceNet(128, blocks=[1, 2, 3, 1]) # 2.62 M
# model = MobileFaceNet(128, blocks=[1, 4, 6, 2]) # 3.83 M
# model = MobileFaceNet(256, blocks=[2, 8, 16, 4]) # 7.61 M
# model = MobileFaceNet(256, blocks=[4, 8, 16, 8]) # 8.75 M
# zqcnn mobilefacenet_v2
# model = ZQMobileFaceNet(256, blocks=[1, 4, 6, 2]) # 11.34 M
# model = ZQMobileFaceNet(256, blocks=[4,8,16,4]) # 21.25 M
# model = ZQMobileFaceNet(512, blocks=[4, 8, 16, 4]) # 21.75 M
model = ZQMobileFaceNet(512, blocks=[4, 8, 16, 8]) # 29.88 M
# model = ZQMobileFaceNet(512, blocks=[8, 16, 32, 8]) # 39.36 M
print(model)
summary(model, (3, 112, 112))
save_path = './finetune-test'
if not os.path.exists(save_path):
os.makedirs(save_path)
logger = get_logger(save_path, "finetune-test")
test_input = torch.randn(1, 3, 112, 112)
model_analyse = ModelAnalyse(model, logger)
model_analyse.flops_compute(test_input)
# count = 0
# for module in model.modules():
# print("{:d} = {}".format(count, module))
# count += 1
