keras,the accuracy and loss stay the same no matter how many epochs it trained

When i run the same code with tensorflow1.13 keras,the accuracy and loss stay the same no matter how many epochs it trained, but with tensorflow1.10, the model will be trained normally.

tensorflow 1.13

      from tensorflow.python.keras.layers import Dense, Dropout, Flatten, Conv1D ,Lambda
      #from tensorflow.python.keras.applications.resnet50 import ResNet50
      from tensorflow.python.keras.applications.mobilenet_v2 import MobileNetV2
      from tensorflow.python.keras.models import Model
      from tensorflow.python.keras.optimizers import SGD,Adam
      import os
      path = os.getcwd()
      path = os.path.abspath(__file__)
      h5_file = path[:-8]+'mobilenet_1_0_224_tf_no_top.h5'
      print (h5_file)
      #base_model = MobileNetV2(pooling='avg',dropout=0.15,include_top=False, weights=h5_file,input_shape=(self.tensor_shape[1],self.tensor_shape[2],self.tensor_shape[3]))
      print (time.time())
      base_model = MobileNetV2(pooling='avg',include_top=False, weights=None,input_shape=(self.tensor_shape[1],self.tensor_shape[2],self.tensor_shape[3]))
      x = base_model.output