Loading deepchem/models/tensorgraph/tensor_graph.py +3 −3 Original line number Diff line number Diff line Loading @@ -30,6 +30,7 @@ class TensorGraph(Model): use_queue=True, graph=None, learning_rate=0.001, configproto=None, **kwargs): """ Parameters Loading @@ -51,8 +52,7 @@ class TensorGraph(Model): is created. learning_rate: float or LearningRateSchedule the learning rate to use for optimization kwargs "configproto": a tf.ConfigProto() object used to create tf.Session() configproto: a tf.ConfigProto() object used to create tf.Session() """ # Layer Management Loading @@ -67,7 +67,7 @@ class TensorGraph(Model): self.queue_installed = False self.optimizer = Adam( learning_rate=learning_rate, beta1=0.9, beta2=0.999, epsilon=1e-7) self.configproto = kwargs.pop("configproto", tf.ConfigProto()) self.configproto = configproto # Singular place to hold Tensor objects which don't serialize # These have to be reconstructed on restoring from pickle Loading Loading
deepchem/models/tensorgraph/tensor_graph.py +3 −3 Original line number Diff line number Diff line Loading @@ -30,6 +30,7 @@ class TensorGraph(Model): use_queue=True, graph=None, learning_rate=0.001, configproto=None, **kwargs): """ Parameters Loading @@ -51,8 +52,7 @@ class TensorGraph(Model): is created. learning_rate: float or LearningRateSchedule the learning rate to use for optimization kwargs "configproto": a tf.ConfigProto() object used to create tf.Session() configproto: a tf.ConfigProto() object used to create tf.Session() """ # Layer Management Loading @@ -67,7 +67,7 @@ class TensorGraph(Model): self.queue_installed = False self.optimizer = Adam( learning_rate=learning_rate, beta1=0.9, beta2=0.999, epsilon=1e-7) self.configproto = kwargs.pop("configproto", tf.ConfigProto()) self.configproto = configproto # Singular place to hold Tensor objects which don't serialize # These have to be reconstructed on restoring from pickle Loading
