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Fixing includes
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37fbcaee0b
commit
141830ce5a
2 changed files with 14 additions and 4 deletions
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@ -134,15 +134,23 @@ model.compile(optimizer='adam', loss='sparse_categorical_crossentropy', metrics=
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model.load_weights(sys.argv[1])
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f = open(sys.argv[2], 'w')
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hf = open(sys.argv[3], 'w')
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if len(sys.argv) > 2:
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cfile = sys.argv[2];
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hfile = sys.argv[3];
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else:
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cfile = 'nnet_data.c'
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hfile = 'nnet_data.h'
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f = open(cfile, 'w')
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hf = open(hfile, 'w')
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f.write('/*This file is automatically generated from a Keras model*/\n\n')
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f.write('#ifdef HAVE_CONFIG_H\n#include "config.h"\n#endif\n\n#include "nnet.h"\n#include "foo.h"\n\n')
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f.write('#ifdef HAVE_CONFIG_H\n#include "config.h"\n#endif\n\n#include "nnet.h"\n#include "{}"\n\n'.format(hfile))
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hf.write('/*This file is automatically generated from a Keras model*/\n\n')
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hf.write('#ifndef RNN_DATA_H\n#define RNN_DATA_H\n\n#include "{}"\n\n'.format(sys.argv[3]))
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hf.write('#ifndef RNN_DATA_H\n#define RNN_DATA_H\n\n#include "nnet.h"\n\n')
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layer_list = []
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for i, layer in enumerate(model.layers):
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@ -36,6 +36,7 @@
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#include "common.h"
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#include "tansig_table.h"
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#include "nnet.h"
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#include "nnet_data.h"
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static OPUS_INLINE float tansig_approx(float x)
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{
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@ -136,6 +137,7 @@ void compute_mdense(const MDenseLayer *layer, float *output, const float *input)
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M = layer->nb_inputs;
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N = layer->nb_neurons;
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C = layer->nb_channels;
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celt_assert(N*C <= MAX_MDENSE_TMP);
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stride = N*C;
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for (i=0;i<N*C;i++)
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tmp[i] = layer->bias[i];
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