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ttt #19

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8 changes: 7 additions & 1 deletion C/Makefile
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Original file line number Diff line number Diff line change
Expand Up @@ -15,8 +15,14 @@
# IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN
# CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

UNAME := $(shell uname)

CC = clang
ifeq ($(UNAME), Linux)
CC_FLAGS = -Wfatal-errors -Wall -Wextra -Wpedantic -Wconversion -Wshadow -lm
else
CC_FLAGS = -Wfatal-errors -Wall -Wextra -Wpedantic -Wconversion -Wshadow
endif

# Final binary
BIN = cmain
Expand All @@ -25,7 +31,7 @@ BIN = cmain
BUILD_DIR = ./build

# List of all .c source files.
CCS = main.c $(wildcard *.c)
CCS = $(wildcard *.c)

# All .o files go to build dir.
OBJ = $(CCS:%.c=$(BUILD_DIR)/%.o)
Expand Down
149 changes: 59 additions & 90 deletions C/main.c
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Expand Up @@ -18,20 +18,10 @@ CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
*/

#include "neural.h"
#include <stdlib.h>
#include "ttt.h"
#include "util.h"
#include <stdio.h>

uint32_t P = 2147483647;
uint32_t A = 16807;
uint32_t current = 1;

double Rand() {
current = current * A % P;
double result = (double)current / P;
return result;
}

void print_network(const Network* network);
#include <string.h>

static uint32_t xor(uint32_t i, uint32_t j) { return i ^ j; }
static uint32_t xnor(uint32_t i, uint32_t j) { return 1 - xor(i, j); }
Expand All @@ -42,86 +32,65 @@ static uint32_t nand(uint32_t i, uint32_t j) { return 1 - and(i, j); }

const int ITERS = 4000;

int main() {
Network network = {0};
network_init(&network, 2, 2, 6, Rand);
Trainer trainer = {0};
trainer_init(&trainer, &network);
double inputs[4][2] = {
{0, 0},
{0, 1},
{1, 0},
{1, 1}
};
double outputs[4][6] = {
{ xor(0, 0), xnor(0, 0), or(0, 0), and(0, 0), nor(0, 0), nand(0, 0) },
{ xor(0, 1), xnor(0, 1), or(0, 1), and(0, 1), nor(0, 1), nand(0, 1) },
{ xor(1, 0), xnor(1, 0), or(1, 0), and(1, 0), nor(1, 0), nand(1, 0) },
{ xor(1, 1), xnor(1, 1), or(1, 1), and(1, 1), nor(1, 1), nand(1, 1) }
};

for (size_t i = 0; i < ITERS; i++) {
double* input = inputs[i % 4];
double* output = outputs[i % 4];

trainer_train(&trainer, &network, input, output, 1.0);
}

int logical_functions(void) {
Network network = {0};
network_init(&network, 2, 2, 6, Rand);
Trainer trainer = {0};
trainer_init(&trainer, &network);
double inputs[4][2] = {
{0, 0},
{0, 1},
{1, 0},
{1, 1}
};
double outputs[4][6] = {
{ xor(0, 0), xnor(0, 0), or(0, 0), and(0, 0), nor(0, 0), nand(0, 0) },
{ xor(0, 1), xnor(0, 1), or(0, 1), and(0, 1), nor(0, 1), nand(0, 1) },
{ xor(1, 0), xnor(1, 0), or(1, 0), and(1, 0), nor(1, 0), nand(1, 0) },
{ xor(1, 1), xnor(1, 1), or(1, 1), and(1, 1), nor(1, 1), nand(1, 1) }
};

for (size_t i = 0; i < ITERS; i++) {
double* input = inputs[i % 4];
double* output = outputs[i % 4];

trainer_train(&trainer, &network, input, output, 1.0);
}

printf(
"Result after %d iterations\n"
" XOR XNOR OR AND NOR NAND\n",
ITERS);
for (size_t i = 0; i < 4; i++) {
double* input = inputs[i % 4];
network_predict(&network, input);
printf(
"Result after %d iterations\n XOR XNOR OR AND NOR NAND\n",
ITERS);
for (size_t i = 0; i < 4; i++)
{
double* input = inputs[i % 4];
network_predict(&network, input);
printf(
"%.0f,%.0f = %.3f %.3f %.3f %.3f %.3f %.3f\n",
input[0],
input[1],
network.output[0],
network.output[1],
network.output[2],
network.output[3],
network.output[4],
network.output[5]);
}

print_network(&network);
trainer_free(&trainer);
network_free(&network);
return 0;
"%.0f,%.0f = %.3f %.3f %.3f %.3f %.3f %.3f\n",
input[0],
input[1],
network.output[0],
network.output[1],
network.output[2],
network.output[3],
network.output[4],
network.output[5]);
}

network_print(&network);
trainer_free(&trainer);
network_free(&network);
return 0;
}

void print_network(const Network* network) {
printf("weights hidden:\n");
for (size_t i = 0; i < network->n_inputs; i++) {
for (size_t j = 0; j < network->n_hidden; j++) {
printf(" %9.6f", network->weights_hidden[network->n_inputs * i + j]);
}

printf("\n");
}

printf("biases hidden:\n");
for (size_t i = 0; i < network->n_hidden; i++) {
printf(" %9.6f", network->biases_hidden[i]);
}

printf("\n");

printf("weights output:\n");
for (size_t i = 0; i < network->n_hidden; i++) {
for (size_t j = 0; j < network->n_outputs; j++) {
printf(" %9.6f", network->weights_output[i * network->n_outputs + j]);
}

printf("\n");
}

printf("biases output:\n");
for (size_t i = 0; i < network->n_outputs; i++) {
printf(" %9.6f", network->biases_output[i]);
}
int main(int argc, char** argv) {
if (argc == 1) {
logical_functions();
} else if (argc == 2 && strcmp("ttt", argv[1]) == 0) {
tic_tac_toe();
} else {
printf("Usage:\n%s <> | ttt\n", argv[0]);
}

printf("\n");
return 0;
}
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