From 5571ef1b8ebce4bb698c249bf9f63e4d076efc9b Mon Sep 17 00:00:00 2001
From: Jean-Marc Valin <jmvalin@amazon.com>
Date: Sat, 26 Jun 2021 01:27:03 -0400
Subject: [PATCH] minor optimization: removing some copying
---
dnn/nnet.c | 28 ++++++++++++----------------
dnn/nnet.h | 2 +-
2 files changed, 13 insertions(+), 17 deletions(-)
diff --git a/dnn/nnet.c b/dnn/nnet.c
index 5730c3f8f..567362f94 100644
--- a/dnn/nnet.c
+++ b/dnn/nnet.c
@@ -281,46 +281,42 @@ void compute_gru3(const GRULayer *gru, float *state, const float *input)
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)
diff --git a/dnn/nnet.h b/dnn/nnet.h
index a5257700d..ac0417695 100644
--- a/dnn/nnet.h
+++ b/dnn/nnet.h
@@ -103,7 +103,7 @@ void compute_gru2(const GRULayer *gru, float *state, const float *input);
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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