def __init__(self):
self.dst = RuleDST()
self.nlu = OneNetLU(
archive_file='models/onenet.tar.gz',
cuda_device=-1,
model_file=
'https://convlab.blob.core.windows.net/models/onenet.tar.gz')
class NLU_DST:
def __init__(self):
self.dst = RuleDST()
self.nlu = OneNetLU(
archive_file='models/onenet.tar.gz',
cuda_device=-1,
model_file=
'https://convlab.blob.core.windows.net/models/onenet.tar.gz')
def update(self, action, observation):
# update history
self.dst.state['history'].append([str(action)])
# NLU parsing
input_act = self.nlu.parse(observation,
sum(self.dst.state['history'],
[])) if self.nlu else observation
# state tracking
self.dst.update(input_act)
# update history
self.dst.state['history'][-1].append(str(observation))
return self.dst.state
def reset(self):
self.dst.init_session()
self.dst.state['history'].append(['null'])
from convlab.modules.nlu.multiwoz.onenet.nlu import OneNetLU
input1 = input("Enter your name: ")
#There is a movie at 10:15 on wednesday .
print(input1)
oneNetLU = OneNetLU(
model_file='https://convlab.blob.core.windows.net/models/onenet.tar.gz')
print(oneNetLU.parse(input1))
from convlab.modules.nlu.multiwoz.onenet.nlu import OneNetLU
from convlab.modules.nlu.multiwoz.milu.nlu import MILU
oneNetLU = OneNetLU(model_file='https://convlab.blob.core.windows.net/models/onenet.tar.gz')
miLU = MILU(model_file='https://convlab.blob.core.windows.net/models/milu.tar.gz')
print(oneNetLU.parse('I want Indian food at 10:15 on wednesday .'))
print(miLU.parse('There is a train leaving at 10:15 on wednesday .'))