Merge pull request #1998 from shippingwang/fix_python3_tab_bug

fix train python3 tab bug

PaddleCV/image_classification/README.md

@@ -165,4 +165,3 @@ Available top-1/top-5 validation accuracy on ImageNet 2012 are listed in table.
 |[SE_ResNeXt101_32x4d](https://paddle-imagenet-models-name.bj.bcebos.com/SE_ResNeXt101_32x4d_pretrained.zip) | 79.26%/94.22% | 79.12%/94.20% |
 |[GoogleNet](https://paddle-imagenet-models-name.bj.bcebos.com/GoogleNet_pretrained.tar) | 70.50%/89.59% | 70.27%/89.58% |
 |[ShuffleNetV2](https://paddle-imagenet-models-name.bj.bcebos.com/ShuffleNet_pretrained.tar) |  | 69.48%/88.99% |
->>>>>>> dc1b032d2616972b974999b7eebe7b35bfeca2f1

PaddleCV/image_classification/train.py

@@ -74,7 +74,7 @@ def optimizer_setting(params):
         batch_size = ls["batch_size"]
         l2_decay = params["l2_decay"]
         momentum_rate = params["momentum_rate"]
-	step = int(math.ceil(float(total_images) / batch_size))
+        step = int(math.ceil(float(total_images) / batch_size))
         lr = params["lr"]
         num_epochs = params["num_epochs"]
 
@@ -92,7 +92,7 @@ def optimizer_setting(params):
         batch_size = ls["batch_size"]
         l2_decay = params["l2_decay"]
         momentum_rate = params["momentum_rate"]
-	step = int(math.ceil(float(total_images) / batch_size))
+        step = int(math.ceil(float(total_images) / batch_size))
         lr = params["lr"]
         num_epochs = params["num_epochs"]