File size: 2,418 Bytes
2d06dcc | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 | import logging
import os
from utils.metrics import clustering_score
from sklearn.metrics import confusion_matrix
class SAEManager:
def __init__(self, args, data, model, logger_name = 'Discovery'):
self.logger = logging.getLogger(logger_name)
self.sae = model.set_model(args, data, 'sae')
self.tfidf_train, self.tfidf_test = data.dataloader.tfidf_train, data.dataloader.tfidf_test
self.num_labels = data.num_labels
self.test_y = data.dataloader.test_true_labels
def train(self, args, data):
self.logger.info('SAE (emb) training start...')
self.sae.fit(self.tfidf_train, self.tfidf_train, epochs = args.num_train_epochs, batch_size = args.batch_size, shuffle=True,
validation_data=(self.tfidf_test, self.tfidf_test), verbose=1)
self.logger.info('SAE (emb) training finished...')
if args.save_model:
save_path = os.path.join(args.model_output_dir, args.model_name)
self.logger.info('Save models at %s', str(save_path))
self.sae.save_weights(save_path)
def test(self, args, data, show=False):
from backbones.sae import get_sae
if not args.train:
save_path = os.path.join(args.model_output_dir, args.model_name)
self.sae.load_weights(save_path)
sae_emb_train, sae_emb_test = get_sae(args, self.sae, self.tfidf_train, self.tfidf_test)
self.logger.info('K-Means start...')
from sklearn.cluster import KMeans
km = KMeans(n_clusters= self.num_labels, n_jobs=-1, random_state=args.seed)
km.fit(sae_emb_train)
self.logger.info('K-Means finished...')
y_pred = km.predict(sae_emb_test)
y_true = self.test_y
test_results = clustering_score(y_true, y_pred)
cm = confusion_matrix(y_true, y_pred)
if show:
self.logger.info
self.logger.info("***** Test: Confusion Matrix *****")
self.logger.info("%s", str(cm))
self.logger.info("***** Test results *****")
for key in sorted(test_results.keys()):
self.logger.info(" %s = %s", key, str(test_results[key]))
test_results['y_true'] = y_true
test_results['y_pred'] = y_pred
return test_results
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