refactor: deprecate MixCELoss

ppcls/configs/ImageNet/DPN/DPN107.yaml

@@ -22,7 +22,7 @@ Arch:
 # loss function config for traing/eval process
 Loss:
   Train:
-    - MixCELoss:
+    - CELoss:
         weight: 1.0
         epsilon: 0.1
   Eval:

ppcls/configs/ImageNet/DPN/DPN131.yaml

@@ -22,7 +22,7 @@ Arch:
 # loss function config for traing/eval process
 Loss:
   Train:
-    - MixCELoss:
+    - CELoss:
         weight: 1.0
         epsilon: 0.1
   Eval:

ppcls/configs/ImageNet/DPN/DPN68.yaml

@@ -22,7 +22,7 @@ Arch:
 # loss function config for traing/eval process
 Loss:
   Train:
-    - MixCELoss:
+    - CELoss:
         weight: 1.0
         epsilon: 0.1
   Eval:

ppcls/configs/ImageNet/DPN/DPN92.yaml

@@ -22,7 +22,7 @@ Arch:
 # loss function config for traing/eval process
 Loss:
   Train:
-    - MixCELoss:
+    - CELoss:
         weight: 1.0
         epsilon: 0.1
   Eval:

ppcls/configs/ImageNet/DPN/DPN98.yaml

@@ -22,7 +22,7 @@ Arch:
 # loss function config for traing/eval process
 Loss:
   Train:
-    - MixCELoss:
+    - CELoss:
         weight: 1.0
         epsilon: 0.1
   Eval:

ppcls/configs/ImageNet/DarkNet/DarkNet53.yaml

@@ -22,7 +22,7 @@ Arch:
 # loss function config for traing/eval process
 Loss:
   Train:
-    - MixCELoss:
+    - CELoss:
         weight: 1.0
         epsilon: 0.1
   Eval:

ppcls/configs/ImageNet/DataAugment/ResNet50_Cutmix.yaml

@@ -22,7 +22,7 @@ Arch:
 # loss function config for traing/eval process
 Loss:
   Train:
-    - MixCELoss:
+    - CELoss:
         weight: 1.0
   Eval:
     - CELoss:

ppcls/configs/ImageNet/DataAugment/ResNet50_Mixup.yaml

@@ -22,7 +22,7 @@ Arch:
 # loss function config for traing/eval process
 Loss:
   Train:
-    - MixCELoss:
+    - CELoss:
         weight: 1.0
   Eval:
     - CELoss:

ppcls/configs/ImageNet/DeiT/DeiT_base_distilled_patch16_224.yaml

@@ -24,7 +24,7 @@ Arch:
 # loss function config for traing/eval process
 Loss:
   Train:
-    - MixCELoss:
+    - CELoss:
         weight: 1.0
         epsilon: 0.1
   Eval:

ppcls/configs/ImageNet/DeiT/DeiT_base_distilled_patch16_384.yaml

@@ -24,7 +24,7 @@ Arch:
 # loss function config for traing/eval process
 Loss:
   Train:
-    - MixCELoss:
+    - CELoss:
         weight: 1.0
         epsilon: 0.1
   Eval:

ppcls/configs/ImageNet/DeiT/DeiT_base_patch16_224.yaml

@@ -24,7 +24,7 @@ Arch:
 # loss function config for traing/eval process
 Loss:
   Train:
-    - MixCELoss:
+    - CELoss:
         weight: 1.0
         epsilon: 0.1
   Eval:

ppcls/configs/ImageNet/DeiT/DeiT_base_patch16_384.yaml

@@ -24,7 +24,7 @@ Arch:
 # loss function config for traing/eval process
 Loss:
   Train:
-    - MixCELoss:
+    - CELoss:
         weight: 1.0
         epsilon: 0.1
   Eval:

ppcls/configs/ImageNet/DeiT/DeiT_small_distilled_patch16_224.yaml

@@ -24,7 +24,7 @@ Arch:
 # loss function config for traing/eval process
 Loss:
   Train:
-    - MixCELoss:
+    - CELoss:
         weight: 1.0
         epsilon: 0.1
   Eval:

ppcls/configs/ImageNet/DeiT/DeiT_small_patch16_224.yaml

@@ -24,7 +24,7 @@ Arch:
 # loss function config for traing/eval process
 Loss:
   Train:
-    - MixCELoss:
+    - CELoss:
         weight: 1.0
         epsilon: 0.1
   Eval:

ppcls/configs/ImageNet/DeiT/DeiT_tiny_distilled_patch16_224.yaml

@@ -24,7 +24,7 @@ Arch:
 # loss function config for traing/eval process
 Loss:
   Train:
-    - MixCELoss:
+    - CELoss:
         weight: 1.0
         epsilon: 0.1
   Eval:

ppcls/configs/ImageNet/DeiT/DeiT_tiny_patch16_224.yaml

@@ -24,7 +24,7 @@ Arch:
 # loss function config for traing/eval process
 Loss:
   Train:
-    - MixCELoss:
+    - CELoss:
         weight: 1.0
         epsilon: 0.1
   Eval:

ppcls/configs/ImageNet/Inception/InceptionV3.yaml

@@ -22,7 +22,7 @@ Arch:
 # loss function config for traing/eval process
 Loss:
   Train:
-    - MixCELoss:
+    - CELoss:
         weight: 1.0
         epsilon: 0.1
   Eval:

ppcls/configs/ImageNet/Inception/InceptionV4.yaml

@@ -22,7 +22,7 @@ Arch:
 # loss function config for traing/eval process
 Loss:
   Train:
-    - MixCELoss:
+    - CELoss:
         weight: 1.0
         epsilon: 0.1
   Eval:

ppcls/configs/ImageNet/Res2Net/Res2Net101_vd_26w_4s.yaml

@@ -22,7 +22,7 @@ Arch:
 # loss function config for traing/eval process
 Loss:
   Train:
-    - MixCELoss:
+    - CELoss:
         weight: 1.0
         epsilon: 0.1
   Eval:

ppcls/configs/ImageNet/Res2Net/Res2Net200_vd_26w_4s.yaml

@@ -22,7 +22,7 @@ Arch:
 # loss function config for traing/eval process
 Loss:
   Train:
-    - MixCELoss:
+    - CELoss:
         weight: 1.0
         epsilon: 0.1
   Eval:

ppcls/configs/ImageNet/Res2Net/Res2Net50_14w_8s.yaml

@@ -22,7 +22,7 @@ Arch:
 # loss function config for traing/eval process
 Loss:
   Train:
-    - MixCELoss:
+    - CELoss:
         weight: 1.0
         epsilon: 0.1
   Eval:

ppcls/configs/ImageNet/Res2Net/Res2Net50_26w_4s.yaml

@@ -22,7 +22,7 @@ Arch:
 # loss function config for traing/eval process
 Loss:
   Train:
-    - MixCELoss:
+    - CELoss:
         weight: 1.0
         epsilon: 0.1
   Eval:

ppcls/configs/ImageNet/Res2Net/Res2Net50_vd_26w_4s.yaml

@@ -22,7 +22,7 @@ Arch:
 # loss function config for traing/eval process
 Loss:
   Train:
-    - MixCELoss:
+    - CELoss:
         weight: 1.0
         epsilon: 0.1
   Eval:

ppcls/configs/ImageNet/ResNeSt/ResNeSt101.yaml

@@ -22,7 +22,7 @@ Arch:
 # loss function config for traing/eval process
 Loss:
   Train:
-    - MixCELoss:
+    - CELoss:
         weight: 1.0
         epsilon: 0.1
   Eval:

ppcls/configs/ImageNet/ResNeSt/ResNeSt50.yaml

@@ -22,7 +22,7 @@ Arch:
 # loss function config for traing/eval process
 Loss:
   Train:
-    - MixCELoss:
+    - CELoss:
         weight: 1.0
         epsilon: 0.1
   Eval:

ppcls/configs/ImageNet/ResNeSt/ResNeSt50_fast_1s1x64d.yaml

@@ -22,7 +22,7 @@ Arch:
 # loss function config for traing/eval process
 Loss:
   Train:
-    - MixCELoss:
+    - CELoss:
         weight: 1.0
         epsilon: 0.1
   Eval:

ppcls/configs/ImageNet/ResNeXt/ResNeXt101_vd_32x4d.yaml

@@ -22,7 +22,7 @@ Arch:
 # loss function config for traing/eval process
 Loss:
   Train:
-    - MixCELoss:
+    - CELoss:
         weight: 1.0
         epsilon: 0.1
   Eval:

ppcls/configs/ImageNet/ResNeXt/ResNeXt101_vd_64x4d.yaml

@@ -22,7 +22,7 @@ Arch:
 # loss function config for traing/eval process
 Loss:
   Train:
-    - MixCELoss:
+    - CELoss:
         weight: 1.0
         epsilon: 0.1
   Eval:

ppcls/configs/ImageNet/ResNeXt/ResNeXt152_vd_32x4d.yaml

@@ -22,7 +22,7 @@ Arch:
 # loss function config for traing/eval process
 Loss:
   Train:
-    - MixCELoss:
+    - CELoss:
         weight: 1.0
         epsilon: 0.1
   Eval:

ppcls/configs/ImageNet/ResNeXt/ResNeXt152_vd_64x4d.yaml

@@ -22,7 +22,7 @@ Arch:
 # loss function config for traing/eval process
 Loss:
   Train:
-    - MixCELoss:
+    - CELoss:
         weight: 1.0
         epsilon: 0.1
   Eval:

ppcls/configs/ImageNet/ResNeXt/ResNeXt50_vd_32x4d.yaml

@@ -22,7 +22,7 @@ Arch:
 # loss function config for traing/eval process
 Loss:
   Train:
-    - MixCELoss:
+    - CELoss:
         weight: 1.0
         epsilon: 0.1
   Eval:

ppcls/configs/ImageNet/ResNeXt/ResNeXt50_vd_64x4d.yaml

@@ -22,7 +22,7 @@ Arch:
 # loss function config for traing/eval process
 Loss:
   Train:
-    - MixCELoss:
+    - CELoss:
         weight: 1.0
         epsilon: 0.1
   Eval:

ppcls/configs/ImageNet/ResNet/ResNet101_vd.yaml

@@ -22,7 +22,7 @@ Arch:
 # loss function config for traing/eval process
 Loss:
   Train:
-    - MixCELoss:
+    - CELoss:
         weight: 1.0
         epsilon: 0.1
   Eval:

ppcls/configs/ImageNet/ResNet/ResNet152_vd.yaml

@@ -22,7 +22,7 @@ Arch:
 # loss function config for traing/eval process
 Loss:
   Train:
-    - MixCELoss:
+    - CELoss:
         weight: 1.0
         epsilon: 0.1
   Eval:

ppcls/configs/ImageNet/ResNet/ResNet18_vd.yaml

@@ -22,7 +22,7 @@ Arch:
 # loss function config for traing/eval process
 Loss:
   Train:
-    - MixCELoss:
+    - CELoss:
         weight: 1.0
         epsilon: 0.1
   Eval:

ppcls/configs/ImageNet/ResNet/ResNet200_vd.yaml

@@ -22,7 +22,7 @@ Arch:
 # loss function config for traing/eval process
 Loss:
   Train:
-    - MixCELoss:
+    - CELoss:
         weight: 1.0
         epsilon: 0.1
   Eval:

ppcls/configs/ImageNet/ResNet/ResNet34_vd.yaml

@@ -22,7 +22,7 @@ Arch:
 # loss function config for traing/eval process
 Loss:
   Train:
-    - MixCELoss:
+    - CELoss:
         weight: 1.0
         epsilon: 0.1
   Eval:

ppcls/configs/ImageNet/ResNet/ResNet50_vd.yaml

@@ -22,7 +22,7 @@ Arch:
 # loss function config for traing/eval process
 Loss:
   Train:
-    - MixCELoss:
+    - CELoss:
         weight: 1.0
         epsilon: 0.1
   Eval:

ppcls/configs/ImageNet/SENet/SENet154_vd.yaml

@@ -22,7 +22,7 @@ Arch:
 # loss function config for traing/eval process
 Loss:
   Train:
-    - MixCELoss:
+    - CELoss:
         weight: 1.0
         epsilon: 0.1
   Eval:

ppcls/configs/ImageNet/SENet/SE_ResNeXt101_32x4d.yaml

@@ -22,7 +22,7 @@ Arch:
 # loss function config for traing/eval process
 Loss:
   Train:
-    - MixCELoss:
+    - CELoss:
         weight: 1.0
         epsilon: 0.1
   Eval:

ppcls/configs/ImageNet/SENet/SE_ResNeXt50_32x4d.yaml

@@ -22,7 +22,7 @@ Arch:
 # loss function config for traing/eval process
 Loss:
   Train:
-    - MixCELoss:
+    - CELoss:
         weight: 1.0
         epsilon: 0.1
   Eval:

ppcls/configs/ImageNet/SENet/SE_ResNeXt50_vd_32x4d.yaml

@@ -22,7 +22,7 @@ Arch:
 # loss function config for traing/eval process
 Loss:
   Train:
-    - MixCELoss:
+    - CELoss:
         weight: 1.0
         epsilon: 0.1
   Eval:

ppcls/configs/ImageNet/SENet/SE_ResNet18_vd.yaml

@@ -22,7 +22,7 @@ Arch:
 # loss function config for traing/eval process
 Loss:
   Train:
-    - MixCELoss:
+    - CELoss:
         weight: 1.0
         epsilon: 0.1
   Eval:

ppcls/configs/ImageNet/SENet/SE_ResNet34_vd.yaml

@@ -22,7 +22,7 @@ Arch:
 # loss function config for traing/eval process
 Loss:
   Train:
-    - MixCELoss:
+    - CELoss:
         weight: 1.0
         epsilon: 0.1
   Eval:

ppcls/configs/ImageNet/SENet/SE_ResNet50_vd.yaml

@@ -22,7 +22,7 @@ Arch:
 # loss function config for traing/eval process
 Loss:
   Train:
-    - MixCELoss:
+    - CELoss:
         weight: 1.0
         epsilon: 0.1
   Eval:

ppcls/configs/ImageNet/SwinTransformer/SwinTransformer_base_patch4_window12_384.yaml

@@ -24,7 +24,7 @@ Arch:
 # loss function config for traing/eval process
 Loss:
   Train:
-    - MixCELoss:
+    - CELoss:
         weight: 1.0
         epsilon: 0.1
   Eval:

ppcls/configs/ImageNet/SwinTransformer/SwinTransformer_base_patch4_window7_224.yaml

@@ -24,7 +24,7 @@ Arch:
 # loss function config for traing/eval process
 Loss:
   Train:
-    - MixCELoss:
+    - CELoss:
         weight: 1.0
         epsilon: 0.1
   Eval:

ppcls/configs/ImageNet/SwinTransformer/SwinTransformer_large_patch4_window12_384.yaml

@@ -24,7 +24,7 @@ Arch:
 # loss function config for traing/eval process
 Loss:
   Train:
-    - MixCELoss:
+    - CELoss:
         weight: 1.0
         epsilon: 0.1
   Eval:

ppcls/configs/ImageNet/SwinTransformer/SwinTransformer_large_patch4_window7_224.yaml

@@ -24,7 +24,7 @@ Arch:
 # loss function config for traing/eval process
 Loss:
   Train:
-    - MixCELoss:
+    - CELoss:
         weight: 1.0
         epsilon: 0.1
   Eval:

ppcls/configs/ImageNet/SwinTransformer/SwinTransformer_small_patch4_window7_224.yaml

@@ -24,7 +24,7 @@ Arch:
 # loss function config for traing/eval process
 Loss:
   Train:
-    - MixCELoss:
+    - CELoss:
         weight: 1.0
         epsilon: 0.1
   Eval:

ppcls/configs/ImageNet/SwinTransformer/SwinTransformer_tiny_patch4_window7_224.yaml

@@ -24,7 +24,7 @@ Arch:
 # loss function config for traing/eval process
 Loss:
   Train:
-    - MixCELoss:
+    - CELoss:
         weight: 1.0
         epsilon: 0.1
   Eval:

ppcls/configs/ImageNet/Twins/alt_gvt_base.yaml

@@ -26,7 +26,7 @@ Arch:
 # loss function config for traing/eval process
 Loss:
   Train:
-    - MixCELoss:
+    - CELoss:
         weight: 1.0
         epsilon: 0.1
   Eval:

ppcls/configs/ImageNet/Twins/alt_gvt_large.yaml

@@ -26,7 +26,7 @@ Arch:
 # loss function config for traing/eval process
 Loss:
   Train:
-    - MixCELoss:
+    - CELoss:
         weight: 1.0
         epsilon: 0.1
   Eval:

ppcls/configs/ImageNet/Twins/alt_gvt_small.yaml

@@ -26,7 +26,7 @@ Arch:
 # loss function config for traing/eval process
 Loss:
   Train:
-    - MixCELoss:
+    - CELoss:
         weight: 1.0
         epsilon: 0.1
   Eval:

ppcls/configs/ImageNet/Twins/pcpvt_base.yaml

@@ -26,7 +26,7 @@ Arch:
 # loss function config for traing/eval process
 Loss:
   Train:
-    - MixCELoss:
+    - CELoss:
         weight: 1.0
         epsilon: 0.1
   Eval:

ppcls/configs/ImageNet/Twins/pcpvt_large.yaml

@@ -26,7 +26,7 @@ Arch:
 # loss function config for traing/eval process
 Loss:
   Train:
-    - MixCELoss:
+    - CELoss:
         weight: 1.0
         epsilon: 0.1
   Eval:

ppcls/configs/ImageNet/Twins/pcpvt_small.yaml

@@ -26,7 +26,7 @@ Arch:
 # loss function config for traing/eval process
 Loss:
   Train:
-    - MixCELoss:
+    - CELoss:
         weight: 1.0
         epsilon: 0.1
   Eval:

ppcls/configs/ImageNet/Xception/Xception65.yaml

@@ -22,7 +22,7 @@ Arch:
 # loss function config for traing/eval process
 Loss:
   Train:
-    - MixCELoss:
+    - CELoss:
         weight: 1.0
         epsilon: 0.1
   Eval:

ppcls/configs/ImageNet/Xception/Xception71.yaml

@@ -22,7 +22,7 @@ Arch:
 # loss function config for traing/eval process
 Loss:
   Train:
-    - MixCELoss:
+    - CELoss:
         weight: 1.0
         epsilon: 0.1
   Eval:

ppcls/configs/slim/ResNet50_vd_prune.yaml

@@ -30,7 +30,7 @@ Arch:
 # loss function config for traing/eval process
 Loss:
   Train:
-    - MixCELoss:
+    - CELoss:
         weight: 1.0
         epsilon: 0.1
   Eval:

ppcls/configs/slim/ResNet50_vd_quantization.yaml

@@ -29,7 +29,7 @@ Arch:
 # loss function config for traing/eval process
 Loss:
   Train:
-    - MixCELoss:
+    - CELoss:
         weight: 1.0
         epsilon: 0.1
   Eval:

ppcls/data/__init__.py

@@ -12,6 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import inspect
 import copy
 import paddle
 import numpy as np
@@ -36,7 +37,7 @@ from ppcls.data import preprocess
 from ppcls.data.preprocess import transform
 
 
-def create_operators(params):
+def create_operators(params, class_num=None):
     """
     create operators based on the config
 
@@ -50,7 +51,10 @@ def create_operators(params):
                           dict) and len(operator) == 1, "yaml format error"
         op_name = list(operator)[0]
         param = {} if operator[op_name] is None else operator[op_name]
-        op = getattr(preprocess, op_name)(**param)
+        op_func = getattr(preprocess, op_name)
+        if "class_num" in inspect.getfullargspec(op_func).args:
+            param.update({"class_num": class_num})
+        op = op_func(**param)
         ops.append(op)
 
     return ops
@@ -65,6 +69,7 @@ def build_dataloader(config, mode, device, use_dali=False, seed=None):
         from ppcls.data.dataloader.dali import dali_dataloader
         return dali_dataloader(config, mode, paddle.device.get_device(), seed)
 
+    class_num = config.get("class_num", None)
     config_dataset = config[mode]['dataset']
     config_dataset = copy.deepcopy(config_dataset)
     dataset_name = config_dataset.pop('name')
@@ -104,7 +109,7 @@ def build_dataloader(config, mode, device, use_dali=False, seed=None):
         return [np.stack(slot, axis=0) for slot in slots]
 
     if isinstance(batch_transform, list):
-        batch_ops = create_operators(batch_transform)
+        batch_ops = create_operators(batch_transform, class_num)
         batch_collate_fn = mix_collate_fn
     else:
         batch_collate_fn = None

ppcls/data/preprocess/batch_ops/batch_operators.py

@@ -44,6 +44,14 @@ class BatchOperator(object):
             labels.append(item[1])
         return np.array(imgs), np.array(labels), bs
 
+    def _one_hot(self, targets):
+        return np.eye(self.class_num, dtype="float32")[targets]
+
+    def _mix_target(self, targets0, targets1, lam):
+        one_hots0 = self._one_hot(targets0)
+        one_hots1 = self._one_hot(targets1)
+        return one_hots0 * lam + one_hots1 * (1 - lam)
+
     def __call__(self, batch):
         return batch
 
@@ -51,7 +59,7 @@ class BatchOperator(object):
 class MixupOperator(BatchOperator):
     """ Mixup operator """
 
-    def __init__(self, alpha: float=1.):
+    def __init__(self, class_num, alpha: float=1.):
         """Build Mixup operator
 
         Args:
@@ -64,21 +72,27 @@ class MixupOperator(BatchOperator):
             raise Exception(
                 f"Parameter \"alpha\" of Mixup should be greater than 0. \"alpha\": {alpha}."
             )
+        if not class_num:
+            msg = "Please set \"Arch.class_num\" in config if use \"MixupOperator\"."
+            logger.error(Exception(msg))
+            raise Exception(msg)
+
         self._alpha = alpha
+        self.class_num = class_num
 
     def __call__(self, batch):
         imgs, labels, bs = self._unpack(batch)
         idx = np.random.permutation(bs)
         lam = np.random.beta(self._alpha, self._alpha)
-        lams = np.array([lam] * bs, dtype=np.float32)
         imgs = lam * imgs + (1 - lam) * imgs[idx]
-        return list(zip(imgs, labels, labels[idx], lams))
+        targets = self._mix_target(labels, labels[idx], lam)
+        return list(zip(imgs, targets))
 
 
 class CutmixOperator(BatchOperator):
     """ Cutmix operator """
 
-    def __init__(self, alpha=0.2):
+    def __init__(self, class_num, alpha=0.2):
         """Build Cutmix operator
 
         Args:
@@ -91,7 +105,13 @@ class CutmixOperator(BatchOperator):
             raise Exception(
                 f"Parameter \"alpha\" of Cutmix should be greater than 0. \"alpha\": {alpha}."
             )
+        if not class_num:
+            msg = "Please set \"Arch.class_num\" in config if use \"CutmixOperator\"."
+            logger.error(Exception(msg))
+            raise Exception(msg)
+
         self._alpha = alpha
+        self.class_num = class_num
 
     def _rand_bbox(self, size, lam):
         """ _rand_bbox """
@@ -121,18 +141,29 @@ class CutmixOperator(BatchOperator):
         imgs[:, :, bbx1:bbx2, bby1:bby2] = imgs[idx, :, bbx1:bbx2, bby1:bby2]
         lam = 1 - (float(bbx2 - bbx1) * (bby2 - bby1) /
                    (imgs.shape[-2] * imgs.shape[-1]))
-        lams = np.array([lam] * bs, dtype=np.float32)
-        return list(zip(imgs, labels, labels[idx], lams))
+        targets = self._mix_target(labels, labels[idx], lam)
+        return list(zip(imgs, targets))
 
 
 class FmixOperator(BatchOperator):
     """ Fmix operator """
 
-    def __init__(self, alpha=1, decay_power=3, max_soft=0., reformulate=False):
+    def __init__(self,
+                 class_num,
+                 alpha=1,
+                 decay_power=3,
+                 max_soft=0.,
+                 reformulate=False):
+        if not class_num:
+            msg = "Please set \"Arch.class_num\" in config if use \"FmixOperator\"."
+            logger.error(Exception(msg))
+            raise Exception(msg)
+
         self._alpha = alpha
         self._decay_power = decay_power
         self._max_soft = max_soft
         self._reformulate = reformulate
+        self.class_num = class_num
 
     def __call__(self, batch):
         imgs, labels, bs = self._unpack(batch)
@@ -141,20 +172,27 @@ class FmixOperator(BatchOperator):
         lam, mask = sample_mask(self._alpha, self._decay_power, \
                 size, self._max_soft, self._reformulate)
         imgs = mask * imgs + (1 - mask) * imgs[idx]
-        return list(zip(imgs, labels, labels[idx], [lam] * bs))
+        targets = self._mix_target(labels, labels[idx], lam)
+        return list(zip(imgs, targets))
 
 
 class OpSampler(object):
     """ Sample a operator from  """
 
-    def __init__(self, **op_dict):
+    def __init__(self, class_num, **op_dict):
         """Build OpSampler
 
         Raises:
             Exception: The parameter \"prob\" of operator(s) are be set error.
         """
+        if not class_num:
+            msg = "Please set \"Arch.class_num\" in config if use \"OpSampler\"."
+            logger.error(Exception(msg))
+            raise Exception(msg)
+
         if len(op_dict) < 1:
             msg = f"ConfigWarning: No operator in \"OpSampler\". \"OpSampler\" has been skipped."
+            logger.warning(msg)
 
         self.ops = {}
         total_prob = 0
@@ -165,12 +203,13 @@ class OpSampler(object):
                 logger.warning(msg)
             prob = param.pop("prob", 0)
             total_prob += prob
+            param.update({"class_num": class_num})
             op = eval(op_name)(**param)
             self.ops.update({op: prob})
 
         if total_prob > 1:
             msg = f"ConfigError: The total prob of operators in \"OpSampler\" should be less 1."
-            logger.error(msg)
+            logger.error(Exception(msg))
             raise Exception(msg)
 
         # add "None Op" when total_prob < 1, "None Op" do nothing

ppcls/engine/engine.py

@@ -112,6 +112,8 @@ class Engine(object):
             }
             paddle.fluid.set_flags(AMP_RELATED_FLAGS_SETTING)
 
+        class_num = config["Arch"].get("class_num", None)
+        self.config["DataLoader"].update({"class_num": class_num})
         # build dataloader
         if self.mode == 'train':
             self.train_dataloader = build_dataloader(

ppcls/engine/train/train.py

@@ -36,25 +36,19 @@ def train_epoch(engine, epoch_id, print_batch_step):
             ]
         batch_size = batch[0].shape[0]
         if not engine.config["Global"].get("use_multilabel", False):
-            batch[1] = batch[1].reshape([-1, 1]).astype("int64")
+            batch[1] = batch[1].reshape([batch_size, -1])
         engine.global_step += 1
 
-        if engine.config["DataLoader"]["Train"]["dataset"].get(
-                "batch_transform_ops", None):
-            gt_input = batch[1:]
-        else:
-            gt_input = batch[1]
-
         # image input
         if engine.amp:
             with paddle.amp.auto_cast(custom_black_list={
                     "flatten_contiguous_range", "greater_than"
             }):
                 out = forward(engine, batch)
-                loss_dict = engine.train_loss_func(out, gt_input)
         else:
             out = forward(engine, batch)
-            loss_dict = engine.train_loss_func(out, gt_input)
+
+        loss_dict = engine.train_loss_func(out, batch[1])
 
         # step opt and lr
         if engine.amp:

ppcls/loss/celoss.py

@@ -12,10 +12,14 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import warnings
+
 import paddle
 import paddle.nn as nn
 import paddle.nn.functional as F
 
+from ppcls.utils import logger
+
 
 class CELoss(nn.Layer):
     """
@@ -56,19 +60,8 @@ class CELoss(nn.Layer):
         return {"CELoss": loss}
 
 
-class MixCELoss(CELoss):
-    """
-    Cross entropy loss with mix(mixup, cutmix, fixmix)
-    """
-
-    def __init__(self, epsilon=None):
-        super().__init__()
-        self.epsilon = epsilon
-
-    def __call__(self, input, batch):
-        target0, target1, lam = batch
-        loss0 = super().forward(input, target0)["CELoss"]
-        loss1 = super().forward(input, target1)["CELoss"]
-        loss = lam * loss0 + (1.0 - lam) * loss1
-        loss = paddle.mean(loss)
-        return {"MixCELoss": loss}
+class MixCELoss(object):
+    def __init__(self, *args, **kwargs):
+        msg = "\"MixCELos\" is deprecated, please use \"CELoss\" instead."
+        logger.error(DeprecationWarning(msg))
+        raise DeprecationWarning(msg)