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feat: binary to int conversion

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This commit is contained in:
Loïc GUEZO
2025-07-12 11:55:12 +02:00
parent b2465410bf
commit 7bc05a2563
1 changed files with 15 additions and 8 deletions
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23
main.py
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@@ -10,6 +10,9 @@ def data(size:int, max_val: int):
for i in range(max_val + 1) for i in range(max_val + 1)
] ]
def binatodeci(binary: list[int]):
return sum(val*(2**idx) for idx, val in enumerate(reversed(binary)))
def train_network(network: NeuralNetwork, epochs=10000, learning_rate=0.1, def train_network(network: NeuralNetwork, epochs=10000, learning_rate=0.1,
verbose: bool = False, size_data: int = 8, max_val: int = 255): verbose: bool = False, size_data: int = 8, max_val: int = 255):
@@ -23,31 +26,35 @@ def train_network(network: NeuralNetwork, epochs=10000, learning_rate=0.1,
output = network.forward(bits)[0] output = network.forward(bits)[0]
loss = (output - target[0]) ** 2 loss = (output - target[0]) ** 2
print(f"Epoch: {epoch}, Loss: {loss:.6f}") print(f"Epoch: {epoch}, Loss: {loss:.6f} {(loss*100):.6f}%")
def main(): def main():
size = 8 size = 4
max_val = (1 << size) - 1 max_val = (1 << size) - 1
epoch_size = 6_500
network = NeuralNetwork([8, 16, 1]) network = NeuralNetwork([size, 16, 1])
print("Start training...") print("Start training...")
train_network(network, verbose=True, size_data=size, epochs=5_000, max_val=max_val) train_network(network, verbose=True, size_data=size, epochs=epoch_size, max_val=max_val)
print("End training...") print("End training...")
while True: while True:
string = input("Enter 8 bit number (ex: 01101001) or 'quit' to close: ") \ string = input(f"Enter {size} bit number (ex: {''.join([str(random.randint(0, 1)) for i in range(size)])}) or 'quit' to close: ") \
.strip().lower() .strip().lower()
if (string == 'quit'): break if (string == 'quit'): break
if (len(string) != 8 or any (char not in '01' for char in string)): if (len(string) != size or any (char not in '01' for char in string)):
print("Error: please enter exactly 8 bits (only 0 or 1).") print(f"Error: please enter exactly {size} bits (only 0 or 1).")
continue continue
bits_input = [int(char) for char in string] bits_input = [int(char) for char in string]
output = network.forward(bits_input)[0] * max_val output = network.forward(bits_input)[0] * max_val
print(f"Estimated value: {output} (approx: {round(output)})\n") print("\n===== Estimated value =====")
print(f"{output} (approx: {round(output)})")
print("\n===== Real value =====")
print(f"{binatodeci(bits_input)}\n")
if __name__ == "__main__": if __name__ == "__main__":
main() main()