22 lines
626 B
Python
22 lines
626 B
Python
import jax, jax.numpy as jnp
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from tensorneat.algorithm import NEAT
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from tensorneat.genome import DefaultGenome, RecurrentGenome
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key = jax.random.key(0)
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genome = DefaultGenome(num_inputs=5, num_outputs=3, max_nodes=100, max_conns=500, init_hidden_layers=(1, 2 ,3))
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state = genome.setup()
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nodes, conns = genome.initialize(state, key)
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print(genome.repr(state, nodes, conns))
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inputs = jnp.array([1, 2, 3, 4, 5])
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transformed = genome.transform(state, nodes, conns)
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outputs = genome.forward(state, transformed, inputs)
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print(outputs)
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network = genome.network_dict(state, nodes, conns)
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print(network)
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genome.visualize(network)
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