Refine Pytorch 3x Mixed Precision Example

examples/.config/model_params_pytorch_3x.json

@@ -152,7 +152,7 @@
         "dataset_location": "/tf_dataset/pytorch/ImageNet/raw",
         "input_model": "resnet18",
         "main_script": "main.py",
-        "batch_size": 100
+        "batch_size": 20
       }
     }
 }

examples/3.x_api/pytorch/cv/mixed_precision/README.md

@@ -36,7 +36,8 @@ bash run_autotune.sh --input_model=resnet18 --dataset_location=/path/to/imagenet
 ## Benchmark
 ```Shell
 # run optimized performance
-bash run_benchmark.sh --input_model=resnet18 --dataset_location=/path/to/imagenet --mode=performance --batch_size=100 --optimized=true --iters=500
+bash run_benchmark.sh --input_model=resnet18 --dataset_location=/path/to/imagenet --mode=performance --batch_size=20 --optimized=true --iters=500
+
 # run optimized accuracy
 bash run_benchmark.sh --input_model=resnet18 --dataset_location=/path/to/imagenet --mode=accuracy --batch_size=1 --optimized=true
 ```

examples/3.x_api/pytorch/cv/mixed_precision/run_benchmark.sh

@@ -13,7 +13,7 @@ function main {
 function init_params {
   iters=100
   tuned_checkpoint=saved_results
-  batch_size=30
+  batch_size=20
   for var in "$@"
   do
     case $var in