我正在用 python 学习 tensorflow2，我想知道是什么设置了 ndim？

如何解决我正在用 python 学习 tensorflow2，我想知道是什么设置了 ndim？

# map function

def area_triangle(b,h):
    area =  b*h/2
    return area

lists = [[4,5],[2,3],[11,45]]

list(map(area_triangle,lists))

然后当我尝试在构建它后运行 model.fit 时。那是错误被抛出的时候。这是正在构建的模型和 model.fit 函数的代码片段。

def build_model(layers):
    model = Sequential()

    # By setting return_sequences to True we are able to stack another LSTM layer
    model.add(LSTM(layers[0],input_shape=(1,2),return_sequences=True))

    model.add(LSTM(layers[0],return_sequences=False))
    model.add(Dropout(0.2))

    model.add(Activation("linear"))

    start = time.time()
    model.compile(loss="mse",optimizer="rmsprop",metrics=['accuracy'])
    print("Compile Time : ",time.time() - start)
    return model

这是错误信息。 ValueError：层“顺序”的输入 0 与层不兼容：预期 ndim=3，发现 ndim=2。什么是 ndim？它的值对模型有何调整？我如何理解我设置的 ndim。

window = 20
print("X_train",X_train.shape)
print("y_train",y_train.shape)
print("X_test",X_test.shape)
print("y_test",y_test.shape)

model = build_model([1374,window,100,1])

model.fit(X_train,y_train,batch_size=3,epochs=5,validation_split=0.1,verbose=0).

这是打印出来的形状。

ValueError: Input 0 of layer sequential is incompatible with the layer: expected ndim=3,found ndim=2. Full shape received: (None,2).

解决方法

正如@yudhiesh 所建议的，LSTM 期望输入形状为 [batch,timesteps,feature] 的形状 3D 张量 我可以重现您的问题

import tensorflow as tf
inputs = tf.random.normal([32,8])
lstm = tf.keras.layers.LSTM(4)
output = lstm(inputs)
print(output.shape)

输出

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-2-160c5e8d5d9a> in <module>()
      2 inputs = tf.random.normal([32,8])
      3 lstm = tf.keras.layers.LSTM(4)
----> 4 output = lstm(inputs)
      5 print(output.shape)

2 frames
/usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/engine/input_spec.py in assert_input_compatibility(input_spec,inputs,layer_name)
    217                          'expected ndim=' + str(spec.ndim) + ',found ndim=' +
    218                          str(ndim) + '. Full shape received: ' +
--> 219                          str(tuple(shape)))
    220     if spec.max_ndim is not None:
    221       ndim = x.shape.rank

ValueError: Input 0 of layer lstm_1 is incompatible with the layer: expected ndim=3,found ndim=2. Full shape received: (32,8)

工作示例代码

inputs = tf.random.normal([32,10,8])
lstm = tf.keras.layers.LSTM(4)
output = lstm(inputs)
print(output.shape)

输出：

(32,4)