forked from mindspore-Ecosystem/mindspore
modify alexnet get_lr args
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46c8ef28de
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@ -45,7 +45,7 @@ if __name__ == "__main__":
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loss = nn.SoftmaxCrossEntropyWithLogits(is_grad=False, sparse=True, reduction="mean")
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repeat_size = cfg.epoch_size
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opt = nn.Momentum(network.trainable_params(), cfg.learning_rate, cfg.momentum)
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model = Model(network, loss, opt, metrics={"Accuracy": Accuracy()}) # test
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model = Model(network, loss, opt, metrics={"Accuracy": Accuracy()})
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print("============== Starting Testing ==============")
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param_dict = load_checkpoint(args.ckpt_path)
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@ -43,19 +43,17 @@ if __name__ == "__main__":
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context.set_context(mode=context.GRAPH_MODE, device_target=args.device_target)
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ds_train = create_dataset_mnist(args.data_path, cfg.batch_size, cfg.epoch_size)
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network = AlexNet(cfg.num_classes)
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loss = nn.SoftmaxCrossEntropyWithLogits(is_grad=False, sparse=True, reduction="mean")
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lr = Tensor(get_lr(0, cfg.learning_rate, cfg.epoch_size, cfg.save_checkpoint_steps))
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lr = Tensor(get_lr(0, cfg.learning_rate, cfg.epoch_size, ds_train.get_dataset_size()))
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opt = nn.Momentum(network.trainable_params(), lr, cfg.momentum)
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model = Model(network, loss, opt, metrics={"Accuracy": Accuracy()}) # test
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print("============== Starting Training ==============")
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ds_train = create_dataset_mnist(args.data_path,
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cfg.batch_size,
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cfg.epoch_size)
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model = Model(network, loss, opt, metrics={"Accuracy": Accuracy()})
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time_cb = TimeMonitor(data_size=ds_train.get_dataset_size())
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config_ck = CheckpointConfig(save_checkpoint_steps=cfg.save_checkpoint_steps,
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keep_checkpoint_max=cfg.keep_checkpoint_max)
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ckpoint_cb = ModelCheckpoint(prefix="checkpoint_alexnet", directory=args.ckpt_path, config=config_ck)
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print("============== Starting Training ==============")
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model.train(cfg.epoch_size, ds_train, callbacks=[time_cb, ckpoint_cb, LossMonitor()],
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dataset_sink_mode=args.dataset_sink_mode)
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