Thanks for your reply. Do you mean that I should use an attention over all the time steps to get an attention vector whose shape is [batch_size, 1, num_timesteps] and then multiply this attention vector with another vector whose shape is [batch_size, num_channels, num_timesteps] and then compute the mean along the 2nd dimension (num_timesteps) to get an output vector whose shape is [batch_size, num_channels] ?