def __init__(self,
name: str,
observer_system: ObserverSystem,
strip_observer_name_prefix: str = ''):
self._strip_observer_name_prefix = strip_observer_name_prefix
self.name = name
self._observer_system = observer_system
self._observables = {}
observer_system.signals.window_closed.connect(self.on_window_closed)
self._prop_builder = ObserverPropertiesBuilder(self)
def __init__(self, is_buffer: bool):
self._real_shape = []
self._shape = []
self._items_per_row = 1
self._min = 0
self._max = 1
self._logger = logging.getLogger(
f"{__name__}.Observer.{type(self).__name__}")
self._is_buffer = is_buffer
self._sum_dim = None
self._prop_builder = ObserverPropertiesBuilder(self)
def __init__(self, node: HierarchicalObservableNode, expert_no: int):
super().__init__()
self._node = node
self._expert_no = expert_no
self._properties = {}
self._grouped_projections = None
self.prop_builder = ObserverPropertiesBuilder()
# TODO HACK - persisted values are loaded prior to the node unit initialization which determines the number
# of groups
# properties not initialized - create dummy properties just to fix persistence
self._default_properties = {
i: HierarchicalGroupProperties(i, self)
for i in range(self._groups_max_count)
}
def __init__(self, tensor_provider: TensorProvider):
self._has_temporal_pooler = tensor_provider.has_temporal_pooler()
self._n_cluster_centers = tensor_provider.n_cluster_centers()
self._n_sequences = tensor_provider.n_sequences()
self._sequence_length = tensor_provider.sequence_length()
self.cluster_centers = ClusterCentersDataBuilder(tensor_provider)
self.fdsim = FDsimDataBuilder(tensor_provider)
self.n_dims = 2
self.pca = PcaDataBuilder(tensor_provider)
self.spring_lines = SpringLinesBuilder(tensor_provider)
self.spline_arrows = SplineArrowsBuilder(tensor_provider)
self._prop_builder = ObserverPropertiesBuilder()
self._sequences_builder = SequencesBuilder(tensor_provider)
self._show_cluster_centers = True
self._show_cluster_datapoints = True
self._show_spring_lines = self._has_temporal_pooler
self._show_spline_arrows = self._has_temporal_pooler
self._projection_type = ClusterObserverProjection.PCA
def __init__(self,
name: str = None,
inputs: TInputs = None,
memory_blocks: TOutputs = None,
outputs: TOutputs = None):
"""Initializes the node.
Inputs, memory_blocks (== internals) and outputs should be initialized here and accessible from now on
for connecting.
"""
# TODO (Feat): Auto-name nodes as in BrainSimulator, or remove the default value of parameter 'name'.
self._name = name
self.topological_order = -1
self._id = 0
self._skip = False
self.inputs = inputs if inputs is not None else EmptyInputs(self)
self.memory_blocks = memory_blocks if memory_blocks is not None else EmptyOutputs(
self)
self.outputs = outputs if outputs is not None else EmptyOutputs(self)
self._prop_builder = ObserverPropertiesBuilder(
self, source_type=ObserverPropertiesItemSourceType.MODEL)
self._single_step_scoped_cache = SimpleResettableCache()
def __init__(self):
self._prop_builder = ObserverPropertiesBuilder(self)
self.tensor_view_projection = TensorViewProjection(is_buffer=False)
def __init__(self, tensor_provider: 'TensorProvider'):
self._prop_builder = ObserverPropertiesBuilder(self)
self._tensor_provider = tensor_provider
def __init__(self, params: GradualLearningBasicTopologyParams = GradualLearningBasicTopologyParams()):
super().__init__('cuda')
self._prop_builder = ObserverPropertiesBuilder(self, source_type=ObserverPropertiesItemSourceType.MODEL)
self._params = params
self.create_topology()
def test_resolve_state_edit_strategy_exception(self):
builder = ObserverPropertiesBuilder(DataIsNotInitializable())
with raises(IllegalArgumentException,
match=r'Expected instance of .*Initializable.* but .*DataIsNotInitializable.* received.'):
builder._resolve_state_strategy(ObserverPropertiesItemState.ENABLED, enable_on_runtime)
def test_resolve_state_edit_strategy(self, initializable, state, strategy, exp_state, exp_description):
builder = ObserverPropertiesBuilder(DataIsInitializable(initializable))
res_state, res_description = builder._resolve_state_strategy(state, strategy)
assert exp_state == res_state
assert exp_description == res_description
def test_auto_needs_instance_to_be_set(self):
with raises(IllegalArgumentException, match=r'.*Instance not set.*'):
builder = ObserverPropertiesBuilder()
builder.auto("Test", Data.p_int)
def setup_method(self):
self.data = Data()
self.builder = ObserverPropertiesBuilder(self.data)
def __init__(self, params: ExpertParams, unit: 'ExpertFlockUnit'):
self._unit = unit
self._params = params
self._prop_builder = ObserverPropertiesBuilder(self, source_type=ObserverPropertiesItemSourceType.MODEL)
def __init__(self, params: SpatialPoolerParams, flock: SPFlock):
self._flock = flock
self._params = params
self._prop_builder = ObserverPropertiesBuilder(self, source_type=ObserverPropertiesItemSourceType.MODEL)