卷积时Convolution1D和Convolution2D的不同

Convolution1D的示例代码 # apply a convolution 1d of length 3 to a sequence with 10 timesteps, # with 64 output filters model = Sequential() model.add(Convolution1D(64, 3, border_mode='same', input_shape=(10, 32))) # now model.output_shape == (None, 10, 64) # add a new conv1d on top model.add(Convolution1