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mindspore/model_zoo/alexnet
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README.md

AlexNet Example

Description

Training AlexNet with dataset in MindSpore.

This is the simple tutorial for training AlexNet in MindSpore.

Requirements

  • Install MindSpore.

  • Download the dataset, the directory structure is as follows:

├─10-batches-bin
│
└─10-verify-bin

Running the example

# train AlexNet, hyperparameter setting in config.py
python train.py --data_path 10-batches-bin

You will get the loss value of each step as following:

epoch: 1 step: 1, loss is 2.2791853
...
epoch: 1 step: 1536, loss is 1.9366643
epoch: 1 step: 1537, loss is 1.6983616
epoch: 1 step: 1538, loss is 1.0221305
...

Then, evaluate AlexNet according to network model

# evaluate AlexNet
python eval.py --data_path 10-verify-bin --ckpt_path checkpoint_alexnet-1_1562.ckpt

Note

Here are some optional parameters:

--device_target {Ascend,GPU}
                     device where the code will be implemented (default: Ascend)
--data_path DATA_PATH
                     path where the dataset is saved
--dataset_sink_mode DATASET_SINK_MODE
                     dataset_sink_mode is False or True

You can run python train.py -h or python eval.py -h to get more information.

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MindSpore is a new open source deep learning training/inference framework that could be used for mobile, edge and cloud scenarios.

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