神经网络烤宽面条

Question

我正在尝试构建一个卷积神经网络，这是我的代码：

def build_cnn(input_var=None):
    network = lasagne.layers.InputLayer(shape=(None ,1 ,700, 21),
                                    input_var=input_var)
    batchsize, seqlen, _, _ = network.input_var.shape
    network = lasagne.layers.Conv2DLayer(
        network, num_filters=32, filter_size=(5, 5),
        nonlinearity=lasagne.nonlinearities.sigmoid,
        W=lasagne.init.GlorotUniform())


    network = lasagne.layers.MaxPool2DLayer(network, pool_size=(2, 2))

    network = lasagne.layers.Conv2DLayer(
        network, num_filters=32, filter_size=(5, 5),
        nonlinearity=lasagne.nonlinearities.sigmoid)
    network = lasagne.layers.MaxPool2DLayer(network, pool_size=(2, 2))

    network = lasagne.layers.DenseLayer(
        lasagne.layers.dropout(network, p=.5),
        num_units=256,
        nonlinearity=lasagne.nonlinearities.sigmoid)

  network = lasagne.layers.DenseLayer(
        lasagne.layers.dropout(network, p=.5),
        num_units=8,
        nonlinearity=lasagne.nonlinearities.softmax)
l_out = lasagne.layers.ReshapeLayer(network, (batchsize*seqlen, 1, 700, 8))

return l_out

我在训练期间从train_fn（）继续收到此错误：

   ValueError: total size of new array must be unchanged
   Apply node that caused the error: Reshape{3}(SoftmaxWithBias.0, Join.0)
   Toposort index: 52
   Inputs types: [TensorType(float64, matrix), TensorType(int64, vector)]
   Inputs shapes: [(500, 8), (3,)]
   Inputs strides: [(64, 8), (8,)]
   Inputs values: ['not shown', array([500, 700,   8], dtype=int64)]
   Outputs clients: [[InplaceDimShuffle{0,x,1,2}(Reshape{3}.0)]]

如有必要，我可以提供更多详细信息