def network_signature(self, observation_space, action_space):
n_actions = space_utils.max_size(action_space)
if self._use_policy:
return data.NetworkSignature(
input=space_utils.signature(observation_space),
output=(data.TensorSignature(shape=(1, )),
data.TensorSignature(shape=(n_actions, ))),
)
else:
return data.NetworkSignature(
input=space_utils.signature(observation_space),
output=data.TensorSignature(shape=(1, )),
)
def network_signature(self, observation_space, action_space):
del action_space
# Input: observation, output: scalar value.
return data.NetworkSignature(
input=space_utils.signature(observation_space),
output=data.TensorSignature(shape=(1,)),
)
def network_signature(self, observation_space, action_space):
return {
data.AgentRequest: data.NetworkSignature(
input=space.signature(observation_space),
output=data.TensorSignature(shape=(1,)),
),
data.ModelRequest: data.NetworkSignature(
input={
'observation': space.signature(observation_space),
'action': data.TensorSignature(
shape=(space.max_size(action_space),)
),
},
output={
'next_observation': space.signature(observation_space),
'reward': data.TensorSignature(shape=(1,)),
'done': data.TensorSignature(shape=(1,)),
},
)
}
def network_signature(self, observation_space, action_space):
n_actions = space_utils.max_size(action_space)
action_vector_sig = data.TensorSignature(shape=(n_actions, ))
if self._use_policy:
output_sig = (action_vector_sig, ) * 2
else:
output_sig = action_vector_sig
return data.NetworkSignature(
input=space_utils.signature(observation_space),
output=output_sig,
)
def network_signature(self, observation_space, action_space):
obs_sig = space_utils.signature(observation_space)
if self._inject_log_temperature:
input_sig = (obs_sig, data.TensorSignature(shape=(1,)))
else:
input_sig = obs_sig
n_actions = space_utils.max_size(action_space)
action_vector_sig = data.TensorSignature(shape=(n_actions,))
output_sig = action_vector_sig
return data.NetworkSignature(input=input_sig, output=output_sig)
def test_signature_for_tuples():
"""Test generation of signatures for observation that are gym Tuples"""
observation_space = Tuple((Tuple(
(Box(np.array([-2, -2]),
np.array([2, 2])), Discrete(3))), Tuple(
(Discrete(4), Discrete(5)))))
observation_space_signature = signature(observation_space)
assert observation_space_signature == ((TensorSignature(
shape=(2, ), dtype=np.dtype('float32')),
TensorSignature(
shape=(),
dtype=np.dtype('int64'))),
(TensorSignature(
shape=(),
dtype=np.dtype('int64')),
TensorSignature(
shape=(),
dtype=np.dtype('int64'))))
def network_signature(self, observation_space, action_space):
return data.NetworkSignature(
input=space_utils.signature(observation_space),
output=self.distribution.params_signature(action_space),
)
def network_signature(self, observation_space, action_space):
return data.NetworkSignature(
input=space_utils.signature(observation_space),
output=(data.TensorSignature(shape=(1, )),
self.distribution.params_signature(action_space)))
def network_signature(observation_space, action_space):
del action_space
return data.NetworkSignature(
input=space_utils.signature(observation_space),
output=data.TensorSignature(shape=(1, )),
)
def network_signature(observation_space, action_space):
# print("MCTS sign")
return data.NetworkSignature(
input=space_utils.signature(observation_space),
output=data.TensorSignature(shape=(action_space.n, )),
)
