LSTM 输入和 Keras 中的 output 维度

Question

I am confused about LSTM input/output dimensions, specifically in keras library. How do keras return 2D output while its input is 3D? I know it can return 3D output using “return_sequence = Trure,” but if return_sequence = False, how can it deal with 3D and produces 2D output? For example, if input data of shape (32, 16, 20), 32 batch size, 16 timestep, 20 features, and output of shape (32, 100), 32 batch size, 100 hidden states; how keras processes input of 3d and returns output 2d. Additionally, how can concatenate input and hidden state if they don't have the exact dimensions?

Answer 1

I found the answer to my question in the link below: https://mmuratarat.github.io/2019-01-19/dimensions-of-lstm it's very helpful!