def save_rbm_weights(weight_matrices,hidden_biases,visible_biases): """ Save the weight matrices from the rbm pretraining. @param weight_matrices: the weight matrices of the rbm pretraining. """ s.dump([w.tolist() for w in weight_matrices] , open( env_paths.get_rbm_weights_path(), "wb" ) ) s.dump([b.tolist() for b in hidden_biases] , open( env_paths.get_rbm_hidden_biases_path(), "wb" ) ) s.dump([b.tolist() for b in visible_biases] , open( env_paths.get_rbm_visible_biases_path(), "wb" ) )
def load_rbm_weights(): """ Load the weight matrices from the rbm pretraining. @param weight_matrices: the weight matrices of the rbm pretraining. """ weights = [array(w) for w in s.load( open( env_paths.get_rbm_weights_path(), "rb" ) )] hid_bias = [array(b) for b in s.load( open( env_paths.get_rbm_hidden_biases_path(), "rb" ) )] vis_bias = [array(b) for b in s.load( open( env_paths.get_rbm_visible_biases_path(), "rb" ) )] return weights,hid_bias,vis_bias
def save_rbm_weights(weight_matrices, hidden_biases, visible_biases): """ Save the weight matrices from the rbm pretraining. @param weight_matrices: the weight matrices of the rbm pretraining. """ s.dump([w.tolist() for w in weight_matrices], open(env_paths.get_rbm_weights_path(), "wb")) s.dump([b.tolist() for b in hidden_biases], open(env_paths.get_rbm_hidden_biases_path(), "wb")) s.dump([b.tolist() for b in visible_biases], open(env_paths.get_rbm_visible_biases_path(), "wb"))
def load_rbm_weights(): """ Load the weight matrices from the rbm pretraining. @param weight_matrices: the weight matrices of the rbm pretraining. """ weights = [ array(w) for w in s.load(open(env_paths.get_rbm_weights_path(), "rb")) ] hid_bias = [ array(b) for b in s.load(open(env_paths.get_rbm_hidden_biases_path(), "rb")) ] vis_bias = [ array(b) for b in s.load(open(env_paths.get_rbm_visible_biases_path(), "rb")) ] return weights, hid_bias, vis_bias