Loading deepchem/models/keras_model.py +4 −4 Original line number Diff line number Diff line Loading @@ -947,7 +947,7 @@ class KerasModel(Model): model_dir = self.model_dir return tf.train.get_checkpoint_state(model_dir).all_model_checkpoint_paths def restore(self, checkpoint=None, restore_from=None): def restore(self, checkpoint=None, model_dir=None): """Reload the values of all variables from a checkpoint file. Parameters Loading @@ -960,10 +960,10 @@ class KerasModel(Model): Directory to restore checkpoint from. If None, use self.model_dir. """ self._ensure_built() if restore_from is None: restore_from = self.model_dir if model_dir is None: model_dir = self.model_dir if checkpoint is None: checkpoint = tf.train.latest_checkpoint(restore_from) checkpoint = tf.train.latest_checkpoint(model_dir) if checkpoint is None: raise ValueError('No checkpoint found') if tf.executing_eagerly(): Loading Loading
deepchem/models/keras_model.py +4 −4 Original line number Diff line number Diff line Loading @@ -947,7 +947,7 @@ class KerasModel(Model): model_dir = self.model_dir return tf.train.get_checkpoint_state(model_dir).all_model_checkpoint_paths def restore(self, checkpoint=None, restore_from=None): def restore(self, checkpoint=None, model_dir=None): """Reload the values of all variables from a checkpoint file. Parameters Loading @@ -960,10 +960,10 @@ class KerasModel(Model): Directory to restore checkpoint from. If None, use self.model_dir. """ self._ensure_built() if restore_from is None: restore_from = self.model_dir if model_dir is None: model_dir = self.model_dir if checkpoint is None: checkpoint = tf.train.latest_checkpoint(restore_from) checkpoint = tf.train.latest_checkpoint(model_dir) if checkpoint is None: raise ValueError('No checkpoint found') if tf.executing_eagerly(): Loading
