我正在使用 Keras 模型進(jìn)行訓(xùn)練，但它拋出了錯(cuò)誤。我用 Conv2D 替換了 Convolution2D，但不起作用。---------------------------------------------------------------------------TypeError Traceback (most recent call last)<ipython-input-99-e85c5751f266> in <module>() 26 model.compile(loss='mse', optimizer=optimizer) 27 return model---> 28 model = nvidia_model() 29 print(model.summary())5 frames/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/utils/generic_utils.py in validate_kwargs(kwargs, allowed_kwargs, error_message) 776 for kwarg in kwargs: 777 if kwarg not in allowed_kwargs:--> 778 raise TypeError(error_message, kwarg) 779 780 TypeError: ('Keyword argument not understood:', 'subsample')修改后的代碼我目前正在使用 keras 2.2.4 我目前正在使用 keras 2.2.4 我目前正在使用 keras 2.2.4 我目前正在使用 keras 2.2.4定義 nvidia 模型def nvidia_model(): model = Sequential() model.add(Conv2D(24, 5, 5, strides=(2, 2), input_shape=(66, 200, 3), activation='elu')) model.add(Conv2D(36, 5, 5, strides=(2, 2), activation='elu')) model.add(Conv2D(48, 5, 5, strides=(2, 2), activation='elu')) model.add(Conv2D(64, 3, 3, activation='elu')) model.add(Conv2D(64, 3, 3, activation='elu'))# model.add(Dropout(0.5)) model.add(Flatten()) model.add(Dense(100, activation = 'elu'))# model.add(Dropout(0.5)) model.add(Dense(50, activation = 'elu'))# model.add(Dropout(0.5)) model.add(Dense(10, activation = 'elu'))# model.add(Dropout(0.5)) model.add(Dense(1)) optimizer = Adam(lr=1e-3) model.compile(loss='mse', optimizer=optimizer) return modelmodel = nvidia_model()print(model.summary())
2 回答
RISEBY
TA貢獻(xiàn)1856條經(jīng)驗(yàn) 獲得超5個(gè)贊
它明確表示子樣本未知。嘗試將“subsample”替換為“strides”，在最新版本的 keras 中，它是這樣調(diào)用的。
江戶川亂折騰
TA貢獻(xiàn)1851條經(jīng)驗(yàn) 獲得超5個(gè)贊
試試這個(gè)方法：
def nvidia_model():
model = Sequential()
model.add(Conv2D(24,(5,5), strides=(2, 2), input_shape=(66, 200, 3), activation='elu'))
model.add(Conv2D(36, (5,5), strides=(2, 2), activation='elu'))
model.add(Conv2D(48, (5,5), strides=(2, 2), activation='elu'))
model.add(Conv2D(64, (3,3), activation='elu'))
model.add(Conv2D(64, (3,3), activation='elu'))
# model.add(Dropout(0.5))
model.add(Flatten())
model.add(Dense(100, activation = 'elu'))
# model.add(Dropout(0.5))
model.add(Dense(50, activation = 'elu'))
# model.add(Dropout(0.5))
model.add(Dense(10, activation = 'elu'))
# model.add(Dropout(0.5))
model.add(Dense(1))
optimizer = Adam(lr=1e-3)
model.compile(loss='mse', optimizer=optimizer)
return model
model = nvidia_model()
print(model.summary())
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