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Fixing includes

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This commit is contained in:
Jean-Marc Valin 2018-11-24 16:00:30 -05:00
parent 37fbcaee0b
commit 141830ce5a
2 changed files with 14 additions and 4 deletions
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16
dnn/dump_lpcnet.py
View file

@ -134,15 +134,23 @@ model.compile(optimizer='adam', loss='sparse_categorical_crossentropy', metrics=
model.load_weights(sys.argv[1]) model.load_weights(sys.argv[1])
f = open(sys.argv[2], 'w') if len(sys.argv) > 2:
hf = open(sys.argv[3], 'w') cfile = sys.argv[2];
hfile = sys.argv[3];
else:
cfile = 'nnet_data.c'
hfile = 'nnet_data.h'
f = open(cfile, 'w')
hf = open(hfile, 'w')
f.write('/*This file is automatically generated from a Keras model*/\n\n') f.write('/*This file is automatically generated from a Keras model*/\n\n')
f.write('#ifdef HAVE_CONFIG_H\n#include "config.h"\n#endif\n\n#include "nnet.h"\n#include "foo.h"\n\n') f.write('#ifdef HAVE_CONFIG_H\n#include "config.h"\n#endif\n\n#include "nnet.h"\n#include "{}"\n\n'.format(hfile))
hf.write('/*This file is automatically generated from a Keras model*/\n\n') hf.write('/*This file is automatically generated from a Keras model*/\n\n')
hf.write('#ifndef RNN_DATA_H\n#define RNN_DATA_H\n\n#include "{}"\n\n'.format(sys.argv[3])) hf.write('#ifndef RNN_DATA_H\n#define RNN_DATA_H\n\n#include "nnet.h"\n\n')
layer_list = [] layer_list = []
for i, layer in enumerate(model.layers): for i, layer in enumerate(model.layers):

2
dnn/nnet.c
View file

@ -36,6 +36,7 @@
#include "common.h" #include "common.h"
#include "tansig_table.h" #include "tansig_table.h"
#include "nnet.h" #include "nnet.h"
#include "nnet_data.h"
static OPUS_INLINE float tansig_approx(float x) static OPUS_INLINE float tansig_approx(float x)
{ {
@ -136,6 +137,7 @@ void compute_mdense(const MDenseLayer *layer, float *output, const float *input)
M = layer->nb_inputs; M = layer->nb_inputs;
N = layer->nb_neurons; N = layer->nb_neurons;
C = layer->nb_channels; C = layer->nb_channels;
celt_assert(N*C <= MAX_MDENSE_TMP);
stride = N*C; stride = N*C;
for (i=0;i<N*C;i++) for (i=0;i<N*C;i++)
tmp[i] = layer->bias[i]; tmp[i] = layer->bias[i];