python，keras。构建训练模型时出错：TypeError：'int'对象不可调用

Question

我遇到了构建我的火车模型的问题。它返回'int'对象不可调用。

这里是我的代码：

from __future__ import print_function 
import keras 

from keras.models import Sequential 
from keras.layers import Dense, Dropout, Flatten 
from keras.layers import Conv2D, MaxPooling2D 
from keras.utils import np_utils 
from keras import backend as K 
import pandas as pd 
import numpy as np 


# input image dimensions 
img_rows, img_cols = 7, 7 

# fix random seed for reproducibility 
seed = 7 
np.random.seed(seed) 

x_train = pd.read_csv('palm_3x3_test.csv') 
x_train.drop(['class'],axis=1,inplace=True) 
x_train = x_train.as_matrix().reshape(-1, 7, 7) 

y_train = pd.read_csv('palm_3x3_test.csv') 
y_train = y_train[['class']] 


x_test = pd.read_csv('palm_3x3_data.csv') 
x_test.drop(['class'],axis=1,inplace=True) 
x_test = x_test.as_matrix().reshape(-1, 7, 7) 

y_test = pd.read_csv('palm_3x3_data.csv') 
y_test = y_test[['class']] 

# reshape to be [samples][pixels][width][height] 
x_train_final = x_train.reshape(x_train.shape[0], 7, 7,1).astype('float32') 
x_test_final = x_test.reshape(x_test.shape[0], 7, 7,1).astype('float32') 

# normalize inputs from 0-255 to 0-1 
x_train_final = x_train_final/255 
x_test_final = x_test_final/255 

# one hot encode outputs 
y_train = np_utils.to_categorical(y_train) 
y_test = np_utils.to_categorical(y_test) 
num_classes = y_test.shape[1] 

input_shape = (img_rows,img_cols , 1) 

def baseline_model(): 
#  create model 

    model = Sequential() 
    model.add(Conv2D(30 (5,5), border_mode='valid', input_shape=(1,(7,7)), activation='relu')) 
    model.add(MaxPooling2D(pool_size=(2, 2))) 
    model.add(Conv2D(15 (3, 3), activation='relu')) 
    model.add(MaxPooling2D(pool_size=(2, 2))) 
    model.add(Dropout(0.2)) 
    model.add(Flatten()) 
    model.add(Dense(128, activation='relu')) 
    model.add(Dense(50, activation='relu')) 
    model.add(Dense(num_classes, activation='softmax')) 

    # Compile model 
    model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy']) 
    return model 

# build the model 
model = baseline_model() 
# Fit the model 
model.fit(x_train_final,y_train_final, validation_data=(x_test,y_test), nb_epoch=10, batch_size=200,verbose=2) 
# Final evaluation of the model 
scores = model.evaluate(x_test,y_test, verbose=0) 
print("CNN Error: %.2f%%" % (100-scores[1]*100)) 

以下是错误：

--------------------------------------------------------------------------- 
TypeError         Traceback (most recent call last) 
<ipython-input-42-7f55d9765a8e> in <module>() 
    76 
    77 # build the model 
---> 78 model = baseline_model() 
    79 # Fit the model 
    80 model.fit(x_train_final,y_train_final, validation_data=(x_test,y_test), nb_epoch=10, batch_size=200,verbose=2) 

<ipython-input-42-7f55d9765a8e> in baseline_model() 
    61 
    62  model = Sequential() 
---> 63  model.add(Conv2D(30 (5,5), border_mode='valid', input_shape=(1,(7,7)), activation='relu')) 
    64  model.add(MaxPooling2D(pool_size=(2, 2))) 
    65  model.add(Conv2D(15 (3, 3), activation='relu')) 

TypeError: 'int' object is not callable 

我尝试搜索相关的错误和大多数的回答是怎么说的变量命名冲突函数名。这个错误的原因是因为我命名的变量？

Answer 1

你缺少30后一个逗号

model.add(Conv2D(30 (5,5), border_mode='valid', input_shape=(1,(7,7)), activation='relu')) 

这就是为什么它试图调用30与参数5,5。