def __init__(self, params, input_vectors, dimensions, plot_for_itr=0, activity_classes=None, output_loc=None): self.parameters = params self.inputs = np.asarray(input_vectors) self.growth_handler = Growth_Handler.GrowthHandler() self.dimensions = dimensions self.learn_smooth_sample_size = self.parameters.get_learn_smooth_sample_size( len(self.inputs)) self.gsom_nodemap = {} self.plot_for_itr = plot_for_itr self.display = Display_Utils.Display(None, None) self.activity_classes = activity_classes self.output_save_location = output_loc # Parameters for recurrent gsom self.globalContexts = np.zeros( (self.parameters.NUMBER_OF_TEMPORAL_CONTEXTS, self.dimensions)) self.globalContexts_evaluation = np.zeros( (self.parameters.NUMBER_OF_TEMPORAL_CONTEXTS, self.dimensions)) self.alphas = Utils.Utilities.get_decremental_alphas( self.parameters.NUMBER_OF_TEMPORAL_CONTEXTS) self.previousBMU = np.zeros( (1, self.parameters.NUMBER_OF_TEMPORAL_CONTEXTS, self.dimensions)) self.previousBMU_evaluation = np.zeros( (1, self.parameters.NUMBER_OF_TEMPORAL_CONTEXTS, self.dimensions))
def __init__(self, params, dimensions, plot_for_itr=0, activity_classes=None, output_loc=None): threading.Thread.__init__(self) self.parameters = params self.growth_handler = Growth_Handler.GrowthHandler() self.dimensions = dimensions # self.learn_smooth_sample_size = self.parameters.get_learn_smooth_sample_size(len(inputs)) self.gsom_nodemap = {} self.plot_for_itr = plot_for_itr self.display = Display_Utils.Display(None, None) self.activity_classes = activity_classes self.output_save_location = output_loc self.att = 0.5 self.att_learning_rate = 0.01 self.recurrent_weights_batch = [] self.emotion_features_batch = [] self.behaviour_features_batch = [] self.BATCH_SIZE = 10 # Parameters for recurrent gsom self.globalContexts = np.zeros( (self.parameters.NUMBER_OF_TEMPORAL_CONTEXTS, self.dimensions)) self.globalContexts_evaluation = np.zeros( (self.parameters.NUMBER_OF_TEMPORAL_CONTEXTS, self.dimensions)) self.alphas = Utils.Utilities.get_decremental_alphas( self.parameters.NUMBER_OF_TEMPORAL_CONTEXTS) self.previousBMU = np.zeros( (1, self.parameters.NUMBER_OF_TEMPORAL_CONTEXTS, self.dimensions)) self.previousBMU_evaluation = np.zeros( (1, self.parameters.NUMBER_OF_TEMPORAL_CONTEXTS, self.dimensions))
def __init__(self, params): threading.Thread.__init__(self) self.parameters = params self.growth_handler = Growth_Handler.GrowthHandler() self.gsom_nodemap = {} # Parameters for recurrent gsom self.alphas = Utils.Utilities.get_decremental_alphas( self.parameters.NUMBER_OF_TEMPORAL_CONTEXTS)