示例代码:
model = Model(inputs=self.inpt, outputs=self.net)
model.compile(loss='categorical_crossentropy', optimizer='adadelta', metrics=['accuracy'])
print("[INFO] Method 1...")
model.summary()
print("[INFO] Method 2...")
for i in range(len(model.layers)):
print(model.get_layer(index=i).output)
print("[INFO] Method 3...")
for layer in model.layers:
print(layer.output_shape)
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# @Time : 2019/5/20
# @Author : Chen
from keras.models import Model
from keras.layers import Dense, Flatten, Input
from keras.layers import Conv2D
class Example:
def __init__(self):
self.inpt = Input(shape=(224, 224, 3))
self.net = self.build_network()
def build_network(self):
inpt = self.inpt
x = Conv2D(64, kernel_size=(3, 3), padding='same', activation='relu')(inpt)
...
x = Flatten()(x)
x = Dense(1000)(x)
return x
def get_layer(self):
model = Model(inputs=self.inpt, outputs=self.net)
model.compile(loss='categorical_crossentropy', optimizer='adadelta', metrics=['accuracy'])
print("[INFO] Method 1...")
model.summary()
print("[INFO] Method 2...")
for i in range(len(model.layers)):
print(model.get_layer(index=i).output)
print("[INFO] Method 3...")
for layer in model.layers:
print(layer.output_shape)
if __name__ == '__main__':
ex = Example()
ex.get_layer()