Caffe

Deep learning framework by BAIR

Created by
Yangqing Jia
Lead Developer
Evan Shelhamer

Recurrent Layer

Parameters

// 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];
}

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