From dc7503c48869a49ea7f2cc28bc528328d992fb05 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=E9=A9=AC=E5=A4=A9=E5=A7=BF?= <mtz982437365@163.com>
Date: Wed, 8 Jul 2020 02:42:20 +0800
Subject: [PATCH] =?UTF-8?q?=E7=AC=AC=E4=BA=8C=E5=85=B3=E4=BB=A3=E7=A0=81?=
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---
 MindSpore/src/step2/step2.py | 35 +++++++++++++++++++++++++++++++++++
 1 file changed, 35 insertions(+)
 create mode 100644 MindSpore/src/step2/step2.py

diff --git a/MindSpore/src/step2/step2.py b/MindSpore/src/step2/step2.py
new file mode 100644
index 0000000..332b721
--- /dev/null
+++ b/MindSpore/src/step2/step2.py
@@ -0,0 +1,35 @@
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(description='MindSpore LeNet Example')
+    parser.add_argument('--device_target', type=str, default="CPU", choices=['Ascend', 'GPU', 'CPU'],
+                        help='device where the code will be implemented (default: CPU)')
+    args = parser.parse_args()
+    context.set_context(mode=context.GRAPH_MODE, device_target=args.device_target)
+    # download mnist dataset
+    download_dataset()
+    # learning rate setting
+    lr = 0.01
+    momentum = 0.9
+    epoch_size = 1
+    mnist_path = "./MNIST_Data"
+    # 请在此添加代码完成本关任务
+    # **********Begin*********#
+    ##提示：补全损失函数的定义
+
+    # **********End**********#
+    repeat_size = epoch_size
+    # create the network
+    network = LeNet5()
+    # define the optimizer
+    # 请在此添加代码完成本关任务
+    # **********Begin*********#
+    ##提示：补全优化器的定义
+
+    # **********End**********#
+
+    # save the network model and parameters for subsequence fine-tuning
+    ckpoint_cb = ModelCheckpoint(prefix="checkpoint_lenet", config=config_ck)
+    # group layers into an object with training and evaluation features
+    model = Model(network, net_loss, net_opt, metrics={"Accuracy": Accuracy()})
+
+    train_net(args, model, epoch_size, mnist_path, repeat_size, ckpoint_cb)
+    test_net(args, network, model, mnist_path)