1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
|
- Fix incorrect printf format specifier (-Wformat)
* fann.c: In function ‘fann_print_connections’:
* fann.c:889:11: warning: format ‘%d’ expects argument of type ‘int’, but argument 2 has type ‘long int’ [-Wformat=]
* printf("L %3d / N %4d %s\n", layer_it - ann->first_layer,
- Fix erroneous memset call
* md5.c: In function ‘MD5Final’:
* md5.c:152:26: warning: argument to ‘sizeof’ in ‘memset’ call is the same expression as the destination; did you mean to dereference it? [-Wsizeof-pointer-memaccess]
* memset(ctx, 0, sizeof(ctx)); /* In case it's sensitive */
--- a/fann-2.1.0/fann.c
+++ b/fann-2.1.0/fann.c
@@ -886,7 +886,7 @@
neurons[ann->connections[i] - ann->first_layer->first_neuron] = (char)('A' + value);
}
}
- printf("L %3d / N %4d %s\n", layer_it - ann->first_layer,
+ printf("L %3ld / N %4ld %s\n", layer_it - ann->first_layer,
neuron_it - ann->first_layer->first_neuron, neurons);
}
}
@@ -987,12 +987,12 @@
{
if(ann->network_type == FANN_NETTYPE_SHORTCUT)
{
- printf(" Hidden layer :%4d neurons, 0 bias\n",
+ printf(" Hidden layer :%4ld neurons, 0 bias\n",
layer_it->last_neuron - layer_it->first_neuron);
}
else
{
- printf(" Hidden layer :%4d neurons, 1 bias\n",
+ printf(" Hidden layer :%4ld neurons, 1 bias\n",
layer_it->last_neuron - layer_it->first_neuron - 1);
}
}
--- a/fann-2.1.0/fann_io.c
+++ b/fann-2.1.0/fann_io.c
@@ -174,7 +174,7 @@
#endif
/* Save network parameters */
- fprintf(conf, "num_layers=%u\n", ann->last_layer - ann->first_layer);
+ fprintf(conf, "num_layers=%ld\n", ann->last_layer - ann->first_layer);
fprintf(conf, "learning_rate=%f\n", ann->learning_rate);
fprintf(conf, "connection_rate=%f\n", ann->connection_rate);
fprintf(conf, "network_type=%u\n", ann->network_type);
@@ -236,7 +236,7 @@
for(layer_it = ann->first_layer; layer_it != ann->last_layer; layer_it++)
{
/* the number of neurons in the layers (in the last layer, there is always one too many neurons, because of an unused bias) */
- fprintf(conf, "%u ", layer_it->last_neuron - layer_it->first_neuron);
+ fprintf(conf, "%ld ", layer_it->last_neuron - layer_it->first_neuron);
}
fprintf(conf, "\n");
@@ -316,14 +316,14 @@
if(save_as_fixed)
{
/* save the connection "(source weight) " */
- fprintf(conf, "(%u, %d) ",
+ fprintf(conf, "(%ld, %d) ",
connected_neurons[i] - first_neuron,
(int) floor((weights[i] * fixed_multiplier) + 0.5));
}
else
{
/* save the connection "(source weight) " */
- fprintf(conf, "(%u, " FANNPRINTF ") ", connected_neurons[i] - first_neuron, weights[i]);
+ fprintf(conf, "(%ld, " FANNPRINTF ") ", connected_neurons[i] - first_neuron, weights[i]);
}
#else
/* save the connection "(source weight) " */
--- a/CommonSource/Utilities/md5.c
+++ b/CommonSource/Utilities/md5.c
@@ -149,7 +149,7 @@
MD5Transform(ctx->buf, (uint32 *) ctx->in);
byteReverse((unsigned char *) ctx->buf, 4);
memcpy(digest, ctx->buf, 16);
- memset(ctx, 0, sizeof(ctx)); /* In case it's sensitive */
+ memset(ctx, 0, sizeof(*ctx)); /* In case it's sensitive */
}
|
