temperature(a),
temperature((a + b) % 10),
temperature((a + b) // 10)
])
x = np.array(x)
y = np.array(y)
test_x = np.array(test_x)
test_y = np.array(test_y)
model = LSTMModel(4, [20, 20], 12, 9)
model.train(x, y, x, y, 10, 5000)
results = model.predict(test_x)
activations_0 = model.getActivations(0, test_x)
activations_1 = model.getActivations(1, test_x)
count = 0
for index, result in enumerate(results):
right = temperatureToInt(result[2])
left = temperatureToInt(result[3])
rightTarget = temperatureToInt(test_y[index][2])
leftTarget = temperatureToInt(test_y[index][3])
if left == leftTarget and right == rightTarget:
count += 1
renderResults("temperature", results, test_x, activations_0, activations_1)
y.append([
one_hot(c),
one_hot(b),
one_hot(a),
one_hot((a + b + c) % 10),
one_hot((a + b + c) // 10)
])
x = np.array(x)
y = np.array(y)
model = LSTMModel(5, [10, 10], 12, 12)
model.train(x, y, x, y, 10, 5000)
results = model.predict(x)
activations_0 = model.getActivations(0, x)
activations_1 = model.getActivations(1, x)
count = 0
for index, result in enumerate(results):
left = argmax(result[3])
right = argmax(result[4])
leftTarget = argmax(y[index][3])
rightTarget = argmax(y[index][4])
if left == leftTarget and right == rightTarget:
count += 1
for i in range(10):
renderResults("symbols-activations-multi-" + str(i),