Deep learning framework by BAIR

Created by
Yangqing Jia
Lead Developer
Evan Shelhamer

LSTM Layer


// Message that stores parameters used by RecurrentLayer
message RecurrentParameter {
  // The dimension of the output (and usually hidden state) representation --
  // must be explicitly set to non-zero.
  optional uint32 num_output = 1 [default = 0];

  optional FillerParameter weight_filler = 2; // The filler for the weight
  optional FillerParameter bias_filler = 3; // The filler for the bias

  // Whether to enable displaying debug_info in the unrolled recurrent net.
  optional bool debug_info = 4 [default = false];

  // Whether to add as additional inputs (bottoms) the initial hidden state
  // blobs, and add as additional outputs (tops) the final timestep hidden state
  // blobs.  The number of additional bottom/top blobs required depends on the
  // recurrent architecture -- e.g., 1 for RNNs, 2 for LSTMs.
  optional bool expose_hidden = 5 [default = false];