Merge pull request #2584 from kshen3778/valcallback (43a79ec9) · Commits · 钟慕尧 / deepchem

deepchem/models/callbacks.py

+8 −2

Original line number	Diff line number	Diff line
		@@ -26,7 +26,8 @@ class ValidationCallback(object):
		output_file=sys.stdout,
		save_dir=None,
		save_metric=0,
		save_on_minimum=True):
		save_on_minimum=True,
		transformers=[]):
		"""Create a ValidationCallback.

		Parameters
		@@ -49,6 +50,10 @@ class ValidationCallback(object):
		if True, the best model is considered to be the one that minimizes the
		validation metric. If False, the best model is considered to be the one
		that maximizes it.
		transformers: List[Transformer]
		List of `dc.trans.Transformer` objects. These transformations
		must have been applied to `dataset` previously. The dataset will
		be untransformed for metric evaluation.
		"""
		self.dataset = dataset
		self.interval = interval
		@@ -58,6 +63,7 @@ class ValidationCallback(object):
		self.save_metric = save_metric
		self.save_on_minimum = save_on_minimum
		self._best_score = None
		self.transformers = transformers

		def __call__(self, model, step):
		"""This is invoked by the KerasModel after every step of fitting.
		@@ -71,7 +77,7 @@ class ValidationCallback(object):
		"""
		if step % self.interval != 0:
		return
		scores = model.evaluate(self.dataset, self.metrics)
		scores = model.evaluate(self.dataset, self.metrics, self.transformers)
		message = 'Step %d validation:' % step
		for key in scores:
		message += ' %s=%g' % (key, scores[key])

+2 −1

Original line number	Diff line number	Diff line
		@@ -35,7 +35,8 @@ class TestCallbacks(unittest.TestCase):
		30, [metric],
		log,
		save_dir=save_dir,
		save_on_minimum=False)
		save_on_minimum=False,
		transformers=transformers)
		model.fit(train_dataset, callbacks=callback)

		# Parse the log to pull out the AUC scores.