def from_weights(cls, layers, weights, biases):
"""
Создание агента по параметрам его нейронной сети. Разбираться не обязательно.
"""
agent = SimpleCarAgent()
agent._rays = weights[0].shape[1] - 4
nn = Network(layers, output_function=lambda x: x, output_derivative=lambda x: 1)
if len(weights) != len(nn.weights):
raise AssertionError("You provided %d weight matrices instead of %d" % (len(weights), len(nn.weights)))
for i, (w, right_w) in enumerate(zip(weights, nn.weights)):
if w.shape != right_w.shape:
raise AssertionError("weights[%d].shape = %s instead of %s" % (i, w.shape, right_w.shape))
nn.weights = weights
if len(biases) != len(nn.biases):
raise AssertionError("You provided %d bias vectors instead of %d" % (len(weights), len(nn.weights)))
for i, (b, right_b) in enumerate(zip(biases, nn.biases)):
if b.shape != right_b.shape:
raise AssertionError("biases[%d].shape = %s instead of %s" % (i, b.shape, right_b.shape))
nn.biases = biases
agent.neural_net = nn
return agent
def from_weights(cls, layers, weights, biases):
"""
Создание агента по параметрам его нейронной сети. Разбираться не обязательно.
"""
agent = SimpleCarAgent()
agent._rays = weights[0].shape[1] - 4
nn = Network(layers,
output_function=lambda x: x,
output_derivative=lambda x: 1)
if len(weights) != len(nn.weights):
raise AssertionError(
"You provided %d weight matrices instead of %d" %
(len(weights), len(nn.weights)))
for i, (w, right_w) in enumerate(zip(weights, nn.weights)):
if w.shape != right_w.shape:
raise AssertionError("weights[%d].shape = %s instead of %s" %
(i, w.shape, right_w.shape))
nn.weights = weights
if len(biases) != len(nn.biases):
raise AssertionError("You provided %d bias vectors instead of %d" %
(len(weights), len(nn.weights)))
for i, (b, right_b) in enumerate(zip(biases, nn.biases)):
if b.shape != right_b.shape:
raise AssertionError("biases[%d].shape = %s instead of %s" %
(i, b.shape, right_b.shape))
nn.biases = biases
agent.neural_net = nn
return agent
def from_weights(cls, layers: List[int], weights, biases):
"""
Creates agent by neural network params.
"""
agent = SimpleCarAgent()
agent._rays = weights[0].shape[1] - NUM_DEFAULT_INPUT_NEURONS
nn = Network(layers,
output_function=lambda x: x,
output_derivative=lambda x: 1)
if len(weights) != len(nn.weights):
raise AssertionError(
"You provided %d weight matrices instead of %d" %
(len(weights), len(nn.weights)))
for i, (w, right_w) in enumerate(zip(weights, nn.weights)):
if w.shape != right_w.shape:
raise AssertionError("weights[%d].shape = %s instead of %s" %
(i, w.shape, right_w.shape))
nn.weights = weights
if len(biases) != len(nn.biases):
raise AssertionError("You provided %d bias vectors instead of %d" %
(len(weights), len(nn.weights)))
for i, (b, right_b) in enumerate(zip(biases, nn.biases)):
if b.shape != right_b.shape:
raise AssertionError("biases[%d].shape = %s instead of %s" %
(i, b.shape, right_b.shape))
nn.biases = biases
agent.neural_net = nn
return agent