ref: 6d7ae213ce07cd3090a3d77ad0e79035bcf5d191
dir: /dnn/parse_lpcnet_weights.c/
/* Copyright (c) 2023 Amazon */
/*
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions
are met:
- Redistributions of source code must retain the above copyright
notice, this list of conditions and the following disclaimer.
- Redistributions in binary form must reproduce the above copyright
notice, this list of conditions and the following disclaimer in the
documentation and/or other materials provided with the distribution.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
``AS IS'' AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE FOUNDATION OR
CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
#ifdef HAVE_CONFIG_H
#include "config.h"
#endif
#include <string.h>
#include <stdlib.h>
#include "nnet.h"
#define SPARSE_BLOCK_SIZE 32
int parse_record(const unsigned char **data, int *len, WeightArray *array) {
WeightHead *h = (WeightHead *)*data;
if (*len < WEIGHT_BLOCK_SIZE) return -1;
if (h->block_size < h->size) return -1;
if (h->block_size > *len-WEIGHT_BLOCK_SIZE) return -1;
if (h->name[sizeof(h->name)-1] != 0) return -1;
if (h->size < 0) return -1;
array->name = h->name;
array->type = h->type;
array->size = h->size;
array->data = (*data)+WEIGHT_BLOCK_SIZE;
*data += h->block_size+WEIGHT_BLOCK_SIZE;
*len -= h->block_size+WEIGHT_BLOCK_SIZE;
return array->size;
}
int parse_weights(WeightArray **list, const unsigned char *data, int len)
{
int nb_arrays=0;
int capacity=20;
*list = malloc(capacity*sizeof(WeightArray));
while (len > 0) {
int ret;
WeightArray array = {NULL, 0, 0, 0};
ret = parse_record(&data, &len, &array);
if (ret > 0) {
if (nb_arrays+1 >= capacity) {
/* Make sure there's room for the ending NULL element too. */
capacity = capacity*3/2;
*list = realloc(*list, capacity*sizeof(WeightArray));
}
(*list)[nb_arrays++] = array;
} else {
free(*list);
*list = NULL;
return -1;
}
}
(*list)[nb_arrays].name=NULL;
return nb_arrays;
}
static const void *find_array_entry(const WeightArray *arrays, const char *name) {
while (arrays->name && strcmp(arrays->name, name) != 0) arrays++;
return arrays;
}
static const void *find_array_check(const WeightArray *arrays, const char *name, int size) {
const WeightArray *a = find_array_entry(arrays, name);
if (a->name && a->size == size) return a->data;
else return NULL;
}
static const void *opt_array_check(const WeightArray *arrays, const char *name, int size, int *error) {
const WeightArray *a = find_array_entry(arrays, name);
*error = (a->name != NULL && a->size != size);
if (a->name && a->size == size) return a->data;
else return NULL;
}
static const void *find_idx_check(const WeightArray *arrays, const char *name, int nb_in, int nb_out, int *total_blocks) {
int remain;
const int *idx;
const WeightArray *a = find_array_entry(arrays, name);
*total_blocks = 0;
if (a == NULL) return NULL;
idx = a->data;
remain = a->size/sizeof(int);
while (remain > 0) {
int nb_blocks;
int i;
nb_blocks = *idx++;
if (remain < nb_blocks+1) return NULL;
for (i=0;i<nb_blocks;i++) {
int pos = *idx++;
if (pos+3 >= nb_in || (pos&0x3)) return NULL;
}
nb_out -= 8;
remain -= nb_blocks+1;
*total_blocks += nb_blocks;
}
if (nb_out != 0) return NULL;
return a->data;
}
int linear_init(LinearLayer *layer, const WeightArray *arrays,
const char *bias,
const char *subias,
const char *weights,
const char *float_weights,
const char *weights_idx,
const char *diag,
const char *scale,
int nb_inputs,
int nb_outputs)
{
int err;
layer->bias = NULL;
layer->subias = NULL;
layer->weights = NULL;
layer->float_weights = NULL;
layer->weights_idx = NULL;
layer->diag = NULL;
layer->scale = NULL;
if (bias != NULL) {
if ((layer->bias = find_array_check(arrays, bias, nb_outputs*sizeof(layer->bias[0]))) == NULL) return 1;
}
if (subias != NULL) {
if ((layer->subias = find_array_check(arrays, subias, nb_outputs*sizeof(layer->subias[0]))) == NULL) return 1;
}
if (weights_idx != NULL) {
int total_blocks;
if ((layer->weights_idx = find_idx_check(arrays, weights_idx, nb_inputs, nb_outputs, &total_blocks)) == NULL) return 1;
if (weights != NULL) {
if ((layer->weights = find_array_check(arrays, weights, SPARSE_BLOCK_SIZE*total_blocks*sizeof(layer->weights[0]))) == NULL) return 1;
}
if (float_weights != NULL) {
layer->float_weights = opt_array_check(arrays, float_weights, SPARSE_BLOCK_SIZE*total_blocks*sizeof(layer->float_weights[0]), &err);
if (err) return 1;
}
} else {
if (weights != NULL) {
if ((layer->weights = find_array_check(arrays, weights, nb_inputs*nb_outputs*sizeof(layer->weights[0]))) == NULL) return 1;
}
if (float_weights != NULL) {
layer->float_weights = opt_array_check(arrays, float_weights, nb_inputs*nb_outputs*sizeof(layer->float_weights[0]), &err);
if (err) return 1;
}
}
if (diag != NULL) {
if ((layer->diag = find_array_check(arrays, diag, nb_outputs*sizeof(layer->diag[0]))) == NULL) return 1;
}
if (weights != NULL) {
if ((layer->scale = find_array_check(arrays, scale, nb_outputs*sizeof(layer->scale[0]))) == NULL) return 1;
}
layer->nb_inputs = nb_inputs;
layer->nb_outputs = nb_outputs;
return 0;
}
int dense_init(DenseLayer *layer, const WeightArray *arrays,
const char *bias,
const char *input_weights,
int nb_inputs,
int nb_neurons,
int activation)
{
if ((layer->bias = find_array_check(arrays, bias, nb_neurons*sizeof(layer->bias[0]))) == NULL) return 1;
if ((layer->input_weights = find_array_check(arrays, input_weights, nb_inputs*nb_neurons*sizeof(layer->input_weights[0]))) == NULL) return 1;
layer->nb_inputs = nb_inputs;
layer->nb_neurons = nb_neurons;
layer->activation = activation;
return 0;
}
int gru_init(GRULayer *layer, const WeightArray *arrays,
const char *bias,
const char *subias,
const char *input_weights,
const char *input_weights_idx,
const char *recurrent_weights,
int nb_inputs,
int nb_neurons,
int activation,
int reset_after)
{
int total_blocks;
if ((layer->bias = find_array_check(arrays, bias, 6*nb_neurons*sizeof(layer->bias[0]))) == NULL) return 1;
if ((layer->subias = find_array_check(arrays, subias, 6*nb_neurons*sizeof(layer->subias[0]))) == NULL) return 1;
if ((layer->input_weights_idx = find_idx_check(arrays, input_weights_idx, nb_inputs, 3*nb_neurons, &total_blocks)) == NULL) return 1;
if ((layer->input_weights = find_array_check(arrays, input_weights, SPARSE_BLOCK_SIZE*total_blocks*sizeof(layer->input_weights[0]))) == NULL) return 1;
if ((layer->recurrent_weights = find_array_check(arrays, recurrent_weights, 3*nb_neurons*nb_neurons*sizeof(layer->recurrent_weights[0]))) == NULL) return 1;
layer->nb_inputs = nb_inputs;
layer->nb_neurons = nb_neurons;
layer->activation = activation;
layer->reset_after = reset_after;
return 0;
}
int conv2d_init(Conv2dLayer *layer, const WeightArray *arrays,
const char *bias,
const char *float_weights,
int in_channels,
int out_channels,
int ktime,
int kheight)
{
int err;
layer->bias = NULL;
layer->float_weights = NULL;
if (bias != NULL) {
if ((layer->bias = find_array_check(arrays, bias, out_channels*sizeof(layer->bias[0]))) == NULL) return 1;
}
if (float_weights != NULL) {
layer->float_weights = opt_array_check(arrays, float_weights, in_channels*out_channels*ktime*kheight*sizeof(layer->float_weights[0]), &err);
if (err) return 1;
}
layer->in_channels = in_channels;
layer->out_channels = out_channels;
layer->ktime = ktime;
layer->kheight = kheight;
return 0;
}
#if 0
#include <fcntl.h>
#include <sys/mman.h>
#include <unistd.h>
#include <sys/stat.h>
#include <stdio.h>
int main()
{
int fd;
unsigned char *data;
int len;
int nb_arrays;
int i;
WeightArray *list;
struct stat st;
const char *filename = "weights_blob.bin";
stat(filename, &st);
len = st.st_size;
fd = open(filename, O_RDONLY);
data = mmap(NULL, len, PROT_READ, MAP_SHARED, fd, 0);
printf("size is %d\n", len);
nb_arrays = parse_weights(&list, data, len);
for (i=0;i<nb_arrays;i++) {
printf("found %s: size %d\n", list[i].name, list[i].size);
}
printf("%p\n", list[i].name);
free(list);
munmap(data, len);
close(fd);
return 0;
}
#endif