def test_integration_with_keras():
TestTransition = collections.namedtuple('TestTransition', ['observation'])
# Just a smoke test, that nothing errors out.
n_transitions = 10
obs_shape = (4, )
network_sig = data.NetworkSignature(
input=data.TensorSignature(shape=obs_shape),
output=data.TensorSignature(shape=(1, )),
)
trainer = supervised.SupervisedTrainer(
network_signature=network_sig,
target=supervised.target_solved,
batch_size=2,
n_steps_per_epoch=3,
replay_buffer_capacity=n_transitions,
)
trainer.add_episode(
data.Episode(
transition_batch=TestTransition(
observation=np.zeros((n_transitions, ) + obs_shape), ),
return_=123,
solved=False,
))
network = keras.KerasNetwork(network_signature=network_sig)
trainer.train_epoch(network)
def test_model_valid(model_fn, input_shape, output_shape):
network = keras_networks.KerasNetwork(model_fn=model_fn,
input_shape=input_shape)
batch_size = 7
inp = np.zeros((batch_size, ) + input_shape)
out = network.predict(inp)
assert out.shape == (batch_size, ) + output_shape
def test_model_valid(model_fn, input_shape, output_shape):
network = keras_networks.KerasNetwork(
model_fn=model_fn,
network_signature=data.NetworkSignature(
input=data.TensorSignature(shape=input_shape),
output=data.TensorSignature(shape=output_shape),
),
)
batch_size = 7
inp = np.zeros((batch_size, ) + input_shape)
out = network.predict(inp)
assert out.shape == (batch_size, ) + output_shape
def test_integration_with_keras():
# Just a smoke test, that nothing errors out.
n_transitions = 10
obs_shape = (4, )
trainer = supervised.SupervisedTrainer(
input_shape=obs_shape,
target_fn=supervised.target_solved,
batch_size=2,
n_steps_per_epoch=3,
replay_buffer_capacity=n_transitions,
)
trainer.add_episode(
data.Episode(
transition_batch=_TestTransition(
observation=np.zeros((n_transitions, ) + obs_shape), ),
return_=123,
solved=False,
))
network = keras.KerasNetwork(input_shape=obs_shape)
trainer.train_epoch(network)
def keras_mlp():
return keras_networks.KerasNetwork(input_shape=(13, ))
def keras_mlp():
return keras_networks.KerasNetwork(network_signature=data.NetworkSignature(
input=data.TensorSignature(shape=(13, )),
output=data.TensorSignature(shape=(1, )),
))