shithub: opus

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minor optimization: removing some copying

--- a/dnn/nnet.c

+++ b/dnn/nnet.c

@@ -281,46 +281,42 @@

       state[i] = h[i];

 }

-void compute_sparse_gru(const SparseGRULayer *gru, float *state, const float *input)

+/* WARNING: for efficiency reasons, this function overwrites the input vector. */

+void compute_sparse_gru(const SparseGRULayer *gru, float *state, float *input)

 {

    int i, k;

    int N;

-   float zrh[3*MAX_RNN_NEURONS];

    float recur[3*MAX_RNN_NEURONS];

    float *z;

    float *r;

    float *h;

+   const float *bias;

    N = gru->nb_neurons;

-   z = zrh;

-   r = &zrh[N];

-   h = &zrh[2*N];

+   z = input;

+   r = &input[N];

+   h = &input[2*N];

    celt_assert(gru->nb_neurons <= MAX_RNN_NEURONS);

    celt_assert(input != state);

    celt_assert(gru->reset_after);

-   RNN_COPY(zrh, input, 3*N);

 #ifdef USE_SU_BIAS

-   for (i=0;i<3*N;i++)

-      recur[i] = gru->subias[3*N + i];

+   bias = &gru->subias[3*N];

 #else

-   for (i=0;i<3*N;i++)

-      recur[i] = gru->bias[3*N + i];   

+   bias = &gru->bias[3*N];   

 #endif

    for (k=0;k<3;k++)

    {

       for (i=0;i<N;i++)

-         recur[k*N + i] += gru->diag_weights[k*N + i]*state[i];

+         recur[k*N + i] = bias[k*N + i] + gru->diag_weights[k*N + i]*state[i];

    }

    sparse_sgemv_accum8x4(recur, gru->recurrent_weights, 3*N, N, gru->idx, state);

    for (i=0;i<2*N;i++)

-      zrh[i] += recur[i];

-   compute_activation(zrh, zrh, 2*N, ACTIVATION_SIGMOID);

+      input[i] += recur[i];

+   compute_activation(input, input, 2*N, ACTIVATION_SIGMOID);

    for (i=0;i<N;i++)

       h[i] += recur[2*N+i]*r[i];

    compute_activation(h, h, N, gru->activation);

    for (i=0;i<N;i++)

-      h[i] = z[i]*state[i] + (1-z[i])*h[i];

-   for (i=0;i<N;i++)

-      state[i] = h[i];

+      state[i] = z[i]*state[i] + (1-z[i])*h[i];

 }

 void compute_conv1d(const Conv1DLayer *layer, float *output, float *mem, const float *input)

--- a/dnn/nnet.h

+++ b/dnn/nnet.h

@@ -103,7 +103,7 @@

 void compute_gru3(const GRULayer *gru, float *state, const float *input);

-void compute_sparse_gru(const SparseGRULayer *gru, float *state, const float *input);

+void compute_sparse_gru(const SparseGRULayer *gru, float *state, float *input);

 void compute_conv1d(const Conv1DLayer *layer, float *output, float *mem, const float *input);

-- 

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