Add compute_generic_dense()

And missing prototypes

2 files changed, 11 insertions, 0 deletions

diff --git a/dnn/nnet.c b/dnn/nnet.c
index 2af1743e..a01f3726 100644
--- a/dnn/nnet.c
+++ b/dnn/nnet.c
@@ -102,6 +102,12 @@ void compute_linear(const LinearLayer *linear, float *out, const float *in)
    }
 }
 
+void compute_generic_dense(const LinearLayer *layer, float *output, const float *input, int activation)
+{
+   compute_linear(layer, output, input);
+   compute_activation(output, output, layer->nb_outputs, activation);
+}
+
 #define MAX_RNN_NEURONS_ALL IMAX(IMAX(MAX_RNN_NEURONS, PLC_MAX_RNN_NEURONS), DRED_MAX_RNN_NEURONS)
 
 
diff --git a/dnn/nnet.h b/dnn/nnet.h
index 649a1cc3..71c91ca3 100644
--- a/dnn/nnet.h
+++ b/dnn/nnet.h
@@ -131,6 +131,11 @@ typedef struct {
   int dim;
 } EmbeddingLayer;
 
+void compute_linear(const LinearLayer *linear, float *out, const float *in);
+void compute_generic_dense(const LinearLayer *layer, float *output, const float *input, int activation);
+void compute_generic_gru(const LinearLayer *input_weights, const LinearLayer *recurrent_weights, float *state, const float *in);
+void compute_generic_conv1d(const LinearLayer *layer, float *output, float *mem, const float *input, int input_size, int activation);
+
 void compute_activation(float *output, const float *input, int N, int activation);
 
 void _lpcnet_compute_dense(const DenseLayer *layer, float *output, const float *input);