set config template to safety number

mindinsight/wizard/conf/templates/network/alexnet/src/config.py-tpl

@@ -33,7 +33,7 @@ cfg = edict({
     'lr': 0.001,
     {% endif %}
     'epoch_size': 1,
-    'batch_size': 32,
+    'batch_size': 16,
     'loss_scale': 1024,
     'buffer_size': 1000,
     'image_height': 227,

mindinsight/wizard/conf/templates/network/lenet/src/config.py-tpl

@@ -28,7 +28,7 @@ cfg = edict({
     'lr': 0.001,
     {% endif %}
     'epoch_size': 1,
-    'batch_size': 32,
+    'batch_size': 16,
     'buffer_size': 1000,
     'image_height': 32,
     'image_width': 32,

mindinsight/wizard/conf/templates/network/lenet/train.py-tpl

@@ -28,11 +28,14 @@ from mindspore.train import Model
 from mindspore.context import ParallelMode
 from mindspore.train.serialization import load_checkpoint, load_param_into_net
 from mindspore.nn.metrics import Accuracy
+from mindspore.common import set_seed
 
 from src.config import cfg
 from src.dataset import create_dataset
 from src.lenet import LeNet5
 
+set_seed(1)
+
 if __name__ == "__main__":
     parser = argparse.ArgumentParser(description='MindSpore Lenet Example')
     parser.add_argument('--run_distribute', type=bool, default=False, help='Run distribute')

mindinsight/wizard/conf/templates/network/resnet50/src/config.py-tpl

@@ -23,7 +23,7 @@ cfg = ed({
     {% elif dataset=='ImageNet' %}
     'num_classes': 1001,
     {% endif %}
-    'batch_size': 32,
+    'batch_size': 16,
     'loss_scale': 1024,
     {% if optimizer=='Momentum' %}
     'lr': 0.01,