import numpy as np
from keras.applications.vgg19 import decode_predictions
from prettytable import PrettyTable
import time
from keras import backend as K
from tensorflow import keras
from tensorflow.python import keras
from keras import models,layers,Model,Input
import tensorflow as tf

model_2=keras.models.load_model('model_2.h5',compile=False)
model_2.summary()

predictions1= np.load('D:/predictions_result.npy')
def profiler(model,test_input):
 data_input=test_input
 for layer in model.layers:
    start = time.time()
    im_imput=keras.layers.Input(batch_shape=model.get_layer(layer.name).get_input_shape_at(0))
    im_out = layer(im_imput)
    new_model = keras.models.Model(inputs=im_imput,outputs=im_out)
    data_input = new_model.predict(data_input)
    end = time.time() - start
    print(end)
    result=1


profiler(model_2,predictions1)

tmp=np.zeros((1,224,64))

for i in range(0,1):
   tmp[i,:,:]=predictions1[i,:]

predictions2 = model_2.predict(tmp)
label_vgg19 = decode_predictions(predictions2)
print ('label_vgg19 =',label_vgg19)

当我尝试运行以上代码时，出现以下错误。我的问题是如何在加载后删除模型的第一层。我最初将VGG模型拆分为子模型，然后加载该子模型。我尝试了不同的方法，但是没有一个起作用。非常感谢您的帮助。

  Traceback (most recent call last):
  File "C:/Users/40227422/PycharmProjects/model_partititon/model_2_sock.py",line 42,in <module>
  profiler(model_2,predictions1)
  File "C:/Users/40227422/PycharmProjects/model_partititon/model_2_sock.py",line 28,in the 
    profiler
  data_input = new_model.predict(data_input)
  File "C:\Users\40227422\AppData\Local\Continuum\miniconda3\envs\tensorflow\lib\site- 
  packages\tensorflow\python\keras\engine\training_utils.py",line 332,in standardize_input_data
  ' but got array with shape ' + str(data_shape))
  ValueError: Error when checking input: expected input_1 to have shape (224,3) but got array 
  with shape (224,64)

当我尝试使用kerassurgeon使用以下代码删除图层时，出现错误 ValueError：没有足够的值可解包（预期2，得到0）

 from kerassurgeon import Surgeon
 surgeon = Surgeon(model_2)
 layer_1 = model_2.layers[0] # selecting 2nd layer

 surgeon.add_job('delete_layer',layer_1)
 new_model = surgeon.operate()