【发布时间】:2021-03-03 09:15:44
【问题描述】:
Nvidia 模型显示步幅错误,即使我将它们初始化为 (1,1) 的默认值 我在以前版本的 keras 中使用 'strides' 作为 'subsample' 参数的替代品,有人可以解释使用它们的新语法。
def nvidia_model():
model = Sequential()
model.add(Conv2D(24,5,5, strides = (2,2), input_shape= (66,200,3), activation='relu'))
model.add(Conv2D(36,5,5, strides = (2,2), activation = 'relu'))
model.add(Conv2D(48,5,5, strides = (2,2), activation = 'relu'))
model.add(Conv2D(64,3,3, activation = 'relu'))
model.add(Conv2D(64,3,3, activation = 'relu'))
model.add(Dropout(0.5)) #50% nodes turned to zero
model.add( Flatten())
model.add(Dense(100, activation ='relu'))
model.add(Dropout(0.5))
model.add(Dense(50, activation ='relu'))
model.add(Dense(10, activation ='relu'))
model.add(Dense(1))
optimizer = Adam(lr = 1e-3)
model.compile(loss = 'mse' , optimizer = optimizer)
return model
model = nvidia_model()
print(model.summary)
Error:
TypeError Traceback (most recent call last)
<ipython-input-83-aff2a2709b79> in <module>()
----> 1 model = nvidia_model()
2 print(model.summary)
<ipython-input-82-7942ade664af> in nvidia_model()
1 def nvidia_model():
2 model = Sequential()
----> 3 model.add(Conv2D(24,5,5, strides = (2,2), input_shape= (66,200,3), activation='relu'))
4 model.add(Conv2D(36,5,5, strides = (2,2), activation = 'relu'))
5 model.add(Conv2D(48,5,5, strides = (2,2), activation = 'relu'))
TypeError: __init__() got multiple values for argument 'strides'
【问题讨论】:
标签: python keras conv-neural-network