def __getitem__(self, index):
name = self.df.iloc[index][0]
data = {'name': name, 'x': lineToTensor(name)}
if self.task == 'train':
target = self.df.iloc[index][1]
data.update(
{'y': torch.tensor(self.class_dict[target], dtype=torch.long)})
return data
def prepareTensors(labeled_pair):
sequence,label = labeled_pair
category_tensor = torch.tensor([label], dtype=torch.long)
line_tensor = lineToTensor(sequence)
category = categories[label]
return category, sequence, category_tensor, line_tensor
net = NameClassifier()
try:
net.load_from_checkpoint(
os.path.join(model_dir, 'names_classifier.ckpt'))
except:
net.load_from_checkpoint(
os.path.join(model_dir, 'names_classifier-v0.ckpt'))
net.eval()
while (1):
name_line = input(
'[🤗 Classifier - running] Enter the name : \n>>> ')
try:
if name_line in ['q', 'quit']:
print('🤗 Bye !')
break
else:
name_tensor = lineToTensor(name_line)
pred = evaluate(name_tensor, net)
c = classes[pred]
print(
f"[Classifier] >>> {name_line} seems to be a {c} name i think...\n"
)
except Exception as e:
print(f"[Error] {e}")