def on_train_begin(self):
if (len(self.datasets) > 0 or len(self.testers) > 0) and self.trainer.dev_data is None:
raise RuntimeError("Trainer has no dev data, you cannot pass extra data to do evaluation.")
if len(self.datasets) > 0:
for key, data in self.datasets.items():
tester = Tester(data=data, model=self.model, batch_size=self.batch_size, metrics=self.trainer.metrics,
verbose=0)
self.testers[key] = tester
fitlog.add_progress(total_steps=self.n_steps)
def on_train_begin(self):
if len(self.datasets) > 0:
for key, data in self.datasets.items():
tester = Tester(data=data, model=self.model,
batch_size=self.trainer.kwargs.get('dev_batch_size', self.batch_size),
metrics=self.trainer.metrics,
verbose=0,
use_tqdm=self.trainer.test_use_tqdm)
self.testers[key] = tester
fitlog.add_progress(total_steps=self.n_steps)
def on_train_begin(self):
if (len(self.datasets) > 0 or len(self.testers) > 0) and self.trainer.dev_data is None:
raise RuntimeError("Trainer has no dev data, you cannot pass extra data to do evaluation.")
if len(self.datasets) > 0:
for key, data in self.datasets.items():
tester = Tester(data=data, model=self.model,
batch_size=self.trainer.kwargs.get('dev_batch_size', self.trainer.batch_size),
metrics=self.trainer.metrics,
verbose=0,
use_tqdm=self.trainer.kwargs.get('test_use_tqdm', self.trainer.use_tqdm),
sampler=self.trainer.kwargs.get('test_sampler', None))
self.testers[key] = tester
fitlog.add_progress(total_steps=self.n_steps)