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, )), )