[example] update resnet example result (#4457)

hpcaitech · Aug 16, 2023 · 2597801 · 2597801
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diff --git a/examples/images/resnet/README.md b/examples/images/resnet/README.md
@@ -49,8 +49,8 @@ python eval.py -c ./ckpt-low_level_zero -e 80
 
 Expected accuracy performance will be:
 
-| Model     | Single-GPU Baseline FP32 | Booster DDP with FP32 | Booster DDP with FP16 | Booster Low Level Zero |
-| --------- | ------------------------ | --------------------- | --------------------- | ---------------------- |
-| ResNet-18 | 85.85%                   | 84.91%                | 85.46%                | 84.50%                 |
+| Model     | Single-GPU Baseline FP32 | Booster DDP with FP32 | Booster DDP with FP16 | Booster Low Level Zero | Booster Gemini |
+| --------- | ------------------------ | --------------------- | --------------------- | ---------------------- | -------------- |
+| ResNet-18 | 85.85%                   | 84.91%                | 85.46%                | 84.50%                 | 84.60%         |
 
 **Note: the baseline is adapted from the [script](https://pytorch-tutorial.readthedocs.io/en/latest/tutorial/chapter03_intermediate/3_2_2_cnn_resnet_cifar10/) to use `torchvision.models.resnet18`**
diff --git a/examples/images/resnet/train.py b/examples/images/resnet/train.py
@@ -104,7 +104,7 @@ def main():
                         '--plugin',
                         type=str,
                         default='torch_ddp',
-                        choices=['torch_ddp', 'torch_ddp_fp16', 'low_level_zero'],
+                        choices=['torch_ddp', 'torch_ddp_fp16', 'low_level_zero', 'gemini'],
                         help="plugin to use")
     parser.add_argument('-r', '--resume', type=int, default=-1, help="resume from the epoch's checkpoint")
     parser.add_argument('-c', '--checkpoint', type=str, default='./checkpoint', help="checkpoint directory")
@@ -141,7 +141,7 @@ def main():
     if args.plugin.startswith('torch_ddp'):
         plugin = TorchDDPPlugin()
     elif args.plugin == 'gemini':
-        plugin = GeminiPlugin(placement_policy='cuda', strict_ddp_mode=True, initial_scale=2**5)
+        plugin = GeminiPlugin(initial_scale=2**5)
     elif args.plugin == 'low_level_zero':
         plugin = LowLevelZeroPlugin(initial_scale=2**5)