def generate_method(debug, test): if debug: method = { 'DAE': DAE({'save-model-path': 'DAE', 'pretrained-model-path': None, 'n_epochs': 1, 'batch_size': 256}), # 'RNN': RNN({'save-model-path': 'RNN', 'pretrained-model-path': None, 'n_epochs': 1, 'batch_size': 256}), # 'Seq2Point': Seq2Point({'save-model-path': 'Seq2Point', 'pretrained-model-path': None, 'n_epochs': 1, 'batch_size': 256}), # 'Seq2Seq': Seq2Seq({'save-model-path': 'Seq2Seq', 'pretraiTruened-model-path': None, 'n_epochs': 1, 'batch_size': 256}), # 'GRU': WindowGRU({'save-model-path': 'GRU', 'pretrained-model-path': None, 'n_epochs': 1, 'batch_size': 256}), } else: method = { 'DAE': DAE({'save-model-path': 'DAE', 'pretrained-model-path': None}), 'RNN': RNN({'save-model-path': 'RNN', 'pretrained-model-path': None}), 'Seq2Point': Seq2Point({'save-model-path': 'Seq2Point', 'pretrained-model-path': None}), 'Seq2Seq': Seq2Seq({'save-model-path': 'Seq2Seq', 'pretrained-model-path': None}), 'GRU': WindowGRU({'save-model-path': 'GRU', 'pretrained-model-path': None}), } if test: method = { 'DAE': DAE({'save-model-path': 'DAE', 'pretrained-model-path': 'DAE', 'batch_size': 256}), 'RNN': RNN({'save-model-path': 'RNN', 'pretrained-model-path': 'RNN', 'batch_size': 256}), 'Seq2Point': Seq2Point( {'save-model-path': 'Seq2Point', 'pretrained-model-path': 'Seq2Point', 'batch_size': 256}), 'Seq2Seq': Seq2Seq({'save-model-path': 'Seq2Seq', 'pretrained-model-path': 'Seq2Seq', 'batch_size': 256}), 'GRU': WindowGRU({'save-model-path': 'GRU', 'pretrained-model-path': 'GRU', 'batch_size': 256}), } return method
from disaggregate import ADAE, DAE, Seq2Point, Seq2Seq, WindowGRU, RNN import warnings warnings.filterwarnings("ignore") path = 'D:/workspace/nilm/data/redd_data.h5' # path = 'D:/workspace/nilm/code/databank/redd_data.h5' debug = False test = False if(debug): method = { 'DAE': DAE({'save-model-path': 'DAE', 'pretrained-model-path': None, 'n_epochs': 1, 'batch_size': 256}), 'RNN': RNN({'save-model-path': 'RNN', 'pretrained-model-path': None, 'n_epochs': 1, 'batch_size': 256}), 'Seq2Point': Seq2Point({'save-model-path': 'Seq2Point', 'pretrained-model-path': None, 'n_epochs': 1, 'batch_size': 256}), 'Seq2Seq': Seq2Seq({'save-model-path': 'Seq2Seq', 'pretrained-model-path': None, 'n_epochs': 1, 'batch_size': 256}), 'GRU': WindowGRU({'save-model-path': 'GRU', 'pretrained-model-path': None, 'n_epochs': 1, 'batch_size': 256}), } else: method = { 'DAE': DAE({'save-model-path': 'DAE', 'pretrained-model-path': None}), 'RNN': RNN({'save-model-path': 'RNN', 'pretrained-model-path': None}), 'Seq2Point': Seq2Point({'save-model-path': 'Seq2Point', 'pretrained-model-path': None}), 'Seq2Seq': Seq2Seq({'save-model-path': 'Seq2Seq', 'pretrained-model-path': None}), 'GRU': WindowGRU({'save-model-path': 'GRU', 'pretrained-model-path': None}), } if test: method = { 'DAE': DAE({'save-model-path': 'DAE', 'pretrained-model-path': 'DAE'}), 'RNN': RNN({'save-model-path': 'RNN', 'pretrained-model-path': 'RNN'}),
} else: method = { 'DAE': DAE({ 'save-model-path': 'DAE', 'pretrained-model-path': None }), 'RNN': RNN({ 'save-model-path': 'RNN', 'pretrained-model-path': None }), 'Seq2Point': Seq2Point({ 'save-model-path': 'Seq2Point', 'pretrained-model-path': None }), 'Seq2Seq': Seq2Seq({ 'save-model-path': 'Seq2Seq', 'pretrained-model-path': None }), 'GRU': WindowGRU({ 'save-model-path': 'GRU', 'pretrained-model-path': None }), } if test: method = { 'DAE':