diff --git a/PyTorch/contrib/cv/classification/Efficient-3DCNNs_ID1230_for_PyTorch/main.py b/PyTorch/contrib/cv/classification/Efficient-3DCNNs_ID1230_for_PyTorch/main.py
index c7bdf20029af5e256afcd2230ba5b28d9e587086..301ce9d5d9b901304eee1ee9f698cd9fe16864f5 100644
--- a/PyTorch/contrib/cv/classification/Efficient-3DCNNs_ID1230_for_PyTorch/main.py
+++ b/PyTorch/contrib/cv/classification/Efficient-3DCNNs_ID1230_for_PyTorch/main.py
@@ -15,6 +15,8 @@
 import os
 import json
 import torch
+if torch.__version__.startswith('1.8'):
+    import torch_npu
 from torch import nn
 from torch import optim
 from torch.optim import lr_scheduler
@@ -112,11 +114,12 @@ if __name__ == '__main__':
 
     if opt.use_apex == 1:
         from apex import amp
-        if opt.loss_scale < 0:
-            model, optimizer = amp.initialize(model, optimizer, opt_level=opt.opt_level, loss_scale=None)
-        else:
-            # model, optimizer = amp.initialize(model, optimizer, opt_level=opt.opt_level, loss_scale=opt.loss_scale, combine_grad=True)
-            model, optimizer = amp.initialize(model, optimizer, opt_level=opt.opt_level, loss_scale=opt.loss_scale)
+        #if opt.loss_scale < 0:
+        #    model, optimizer = amp.initialize(model, optimizer, opt_level=opt.opt_level, loss_scale=None)
+        #else:
+        #    # model, optimizer = amp.initialize(model, optimizer, opt_level=opt.opt_level, loss_scale=opt.loss_scale, combine_grad=True)
+        #    model, optimizer = amp.initialize(model, optimizer, opt_level=opt.opt_level, loss_scale=opt.loss_scale)
+        model,optimizer = amp.initialize(model, optimizer, opt_level=opt.opt_level,loss_scale=opt.loss_scale)
 
     # resume model
     best_pre1 = 0
diff --git a/PyTorch/contrib/cv/classification/Efficient-3DCNNs_ID1230_for_PyTorch/run/getmodel.py b/PyTorch/contrib/cv/classification/Efficient-3DCNNs_ID1230_for_PyTorch/run/getmodel.py
index 2e6b18ed23a9a1e855193f0f677cbac63791d18e..6a4db1bd282ad538a9cb75ef4e4cc48a166f377e 100644
--- a/PyTorch/contrib/cv/classification/Efficient-3DCNNs_ID1230_for_PyTorch/run/getmodel.py
+++ b/PyTorch/contrib/cv/classification/Efficient-3DCNNs_ID1230_for_PyTorch/run/getmodel.py
@@ -15,6 +15,9 @@
 import os
 import json
 import torch
+if torch.__version__.startswith('1.8'):
+    import torch_npu
+
 from torch import nn
 from torch import optim
 from torch.optim import lr_scheduler
diff --git a/PyTorch/contrib/cv/classification/Efficient-3DCNNs_ID1230_for_PyTorch/run/opts.py b/PyTorch/contrib/cv/classification/Efficient-3DCNNs_ID1230_for_PyTorch/run/opts.py
index e4583c32e613ba471d873a4d9971d3e5455f19c6..5165ec11c249b7cd2d173e70de000b2c6c7987c7 100644
--- a/PyTorch/contrib/cv/classification/Efficient-3DCNNs_ID1230_for_PyTorch/run/opts.py
+++ b/PyTorch/contrib/cv/classification/Efficient-3DCNNs_ID1230_for_PyTorch/run/opts.py
@@ -17,14 +17,14 @@ import argparse
 
 def parse_opts():
     parser = argparse.ArgumentParser()
-    parser.add_argument('--root_path', default='/root/ennengyang_space/Efficient-3DCNNs-master/', type=str, help='Root directory path of data')
+    parser.add_argument('--root_path', default='/home/jsz/Efficient-3DCNNs_ID1230_for_PyTorch/', type=str, help='Root directory path of data')
     parser.add_argument('--video_path', default='annotation_UCF101/UCF-101-image', type=str, help='Directory path of Videos')
     parser.add_argument('--annotation_path', default='annotation_UCF101/ucf101_01.json', type=str, help='Annotation file path')
     # parser.add_argument('--resume_path', default='results/ucf101_mobilenetv2_1.0x_RGB_16_checkpoint.pth', type=str, help='Save data (.pth) of previous training')
     parser.add_argument('--resume_path', default='', type=str, help='Save data (.pth) of previous training')
     # parser.add_argument('--pretrain_path', default='pretrain/kinetics_mobilenetv2_1.0x_RGB_16_best_dp.pth', type=str, help='Pretrained model (.pth)')
     parser.add_argument('--pretrain_path', default='', type=str, help='Pretrained model (.pth)')
-    parser.add_argument('--ft_portion', default='complete', type=str, help='The portion of the model to apply fine tuning, either complete or last_layer')
+    parser.add_argument('--ft_portion', default='last_layer', type=str, help='The portion of the model to apply fine tuning, either complete or last_layer')
 
     parser.add_argument('--no_drive', action='store_true', help='If true, cuda or npu is not used.')
     parser.set_defaults(no_drive=False)
@@ -41,14 +41,14 @@ def parse_opts():
     parser.add_argument('--use_prof', default=1, type=int, help='use_prof')
     parser.add_argument('--use_apex', default=0, type=int, help='use_apex')
     parser.add_argument('--opt_level', default='O2', type=str, help='Initial opt_level')
-    parser.add_argument('--loss_scale', default=128, type=float, help='Initial loss_scale')
+    parser.add_argument('--loss_scale', default='dynamic',  help='Initial loss_scale')
 
-    parser.add_argument('--batch_size', default=8, type=int, help='Batch Size')
+    parser.add_argument('--batch_size', default=80, type=int, help='Batch Size')
     parser.add_argument('--n_epochs', default=2, type=int, help='Number of total epochs to run')
-    parser.add_argument('--learning_rate', default=0.1, type=float, help='Initial learning rate')
+    parser.add_argument('--learning_rate', default=0.01, type=float, help='Initial learning rate')
     parser.add_argument('--droupout_rate', default=0.9, type=float, help='Droupout rate')
     parser.add_argument('--lr_steps', default=[15, 25, 35, 40, 45], type=float, nargs="+", metavar='LRSteps', help='epochs to decay learning rate by 10')
-    parser.add_argument('--n_threads', default=0, type=int, help='Number of threads for multi-thread loading')
+    parser.add_argument('--n_threads', default=16, type=int, help='Number of threads for multi-thread loading')
 
     parser.add_argument('--no_train', default=0, type=int, help='If true, training is not performed.')
     parser.add_argument('--no_val', default=0, type=int, help='If true, validation is not performed.')
diff --git a/PyTorch/contrib/cv/classification/Efficient-3DCNNs_ID1230_for_PyTorch/run/spatial_transforms.py b/PyTorch/contrib/cv/classification/Efficient-3DCNNs_ID1230_for_PyTorch/run/spatial_transforms.py
index bc532e2093be2256191bdd0f0c4f44e744b24f01..5bb23484f41da97b38581a60b443df2d55f18f30 100644
--- a/PyTorch/contrib/cv/classification/Efficient-3DCNNs_ID1230_for_PyTorch/run/spatial_transforms.py
+++ b/PyTorch/contrib/cv/classification/Efficient-3DCNNs_ID1230_for_PyTorch/run/spatial_transforms.py
@@ -18,6 +18,9 @@ import numbers
 import collections
 import numpy as np
 import torch
+if torch.__version__.startswith('1.8'):
+    import torch_npu
+
 import cv2
 import scipy.ndimage
 from PIL import Image, ImageOps
diff --git a/PyTorch/contrib/cv/classification/Efficient-3DCNNs_ID1230_for_PyTorch/run/test.py b/PyTorch/contrib/cv/classification/Efficient-3DCNNs_ID1230_for_PyTorch/run/test.py
index 4a1abb3f5dc4ca7ed0f7e0c24e89213a6afca50c..b780dd1557c77607d4a9c8b05ab37476b42d15e6 100644
--- a/PyTorch/contrib/cv/classification/Efficient-3DCNNs_ID1230_for_PyTorch/run/test.py
+++ b/PyTorch/contrib/cv/classification/Efficient-3DCNNs_ID1230_for_PyTorch/run/test.py
@@ -19,6 +19,8 @@ import time
 import os
 import sys
 import json
+if torch.__version__.startswith('1.8'):
+    import torch_npu
 
 from run.utils import AverageMeter
 
diff --git a/PyTorch/contrib/cv/classification/Efficient-3DCNNs_ID1230_for_PyTorch/run/train.py b/PyTorch/contrib/cv/classification/Efficient-3DCNNs_ID1230_for_PyTorch/run/train.py
index 312ff580551ef382c2e41618d2d0153b2eba4405..14225a0476736fc1b013e370bf4f422e3966e746 100644
--- a/PyTorch/contrib/cv/classification/Efficient-3DCNNs_ID1230_for_PyTorch/run/train.py
+++ b/PyTorch/contrib/cv/classification/Efficient-3DCNNs_ID1230_for_PyTorch/run/train.py
@@ -17,6 +17,8 @@ from torch.autograd import Variable
 import time
 import os
 import sys
+if torch.__version__.startswith('1.8'):
+    import torch_npu
 
 from run.utils import AverageMeter, calculate_accuracy
 
@@ -126,7 +128,7 @@ def train_epoch(epoch, data_loader, model, criterion, optimizer, opt,
         if i >= 2:
             tot_time.update(current_batch_time)
 
-        if device_ids == 0:  # distributed master or 1p
+        if (device_ids == 0) or (opt.device_num == 1): # distributed master or 1p
             batch_logger.log({
                 'date': time.strftime('%Y%m%d%H%M%S', time.localtime(time.time())),
                 'epoch': epoch,
@@ -159,7 +161,7 @@ def train_epoch(epoch, data_loader, model, criterion, optimizer, opt,
 
     epoch_fps = opt.batch_size * opt.device_num / tot_time.avg
 
-    if device_ids == 0:  # distributed master or 1p
+    if (device_ids == 0)or (opt.device_num == 1):  # distributed master or 1p
         epochlog = {
             'date': time.strftime('%Y%m%d%H%M%S', time.localtime(time.time())),
             'epoch': epoch,
diff --git a/PyTorch/contrib/cv/classification/Efficient-3DCNNs_ID1230_for_PyTorch/run/utils.py b/PyTorch/contrib/cv/classification/Efficient-3DCNNs_ID1230_for_PyTorch/run/utils.py
index 70357d2254782432d3a9d3c66068c79aa3f85442..40c1216f99eae37b70cf4cceeae3ae556eaf378f 100644
--- a/PyTorch/contrib/cv/classification/Efficient-3DCNNs_ID1230_for_PyTorch/run/utils.py
+++ b/PyTorch/contrib/cv/classification/Efficient-3DCNNs_ID1230_for_PyTorch/run/utils.py
@@ -18,6 +18,9 @@ import shutil
 import numpy as np
 import json
 import os
+if torch.__version__.startswith('1.8'):
+    import torch_npu
+
 from run.mean import get_mean, get_std
 
 class AverageMeter(object):
diff --git a/PyTorch/contrib/cv/classification/Efficient-3DCNNs_ID1230_for_PyTorch/run/validation.py b/PyTorch/contrib/cv/classification/Efficient-3DCNNs_ID1230_for_PyTorch/run/validation.py
index 61827e741592b277f61c32a2b470f61d67d3a41e..795e555bc17be55fdcdd5ae288efa1033c6eef22 100644
--- a/PyTorch/contrib/cv/classification/Efficient-3DCNNs_ID1230_for_PyTorch/run/validation.py
+++ b/PyTorch/contrib/cv/classification/Efficient-3DCNNs_ID1230_for_PyTorch/run/validation.py
@@ -13,6 +13,9 @@
 # limitations under the License.
 # ============================================================================
 import torch
+if torch.__version__.startswith('1.8'):
+    import torch_npu
+
 from torch.autograd import Variable
 import time
 import sys