SINGA-350 Error from python3 test Add encode() back in optimizer.py
Project: http://git-wip-us.apache.org/repos/asf/incubator-singa/repo Commit: http://git-wip-us.apache.org/repos/asf/incubator-singa/commit/2d255613 Tree: http://git-wip-us.apache.org/repos/asf/incubator-singa/tree/2d255613 Diff: http://git-wip-us.apache.org/repos/asf/incubator-singa/diff/2d255613 Branch: refs/heads/master Commit: 2d2556135bc04282f382ad3fc5071fc51a6aad28 Parents: 72b1a69 Author: Wang Wei <[email protected]> Authored: Wed May 2 21:39:28 2018 +0800 Committer: Wang Wei <[email protected]> Committed: Wed May 2 21:39:28 2018 +0800 ---------------------------------------------------------------------- python/singa/optimizer.py | 16 ++++++++-------- 1 file changed, 8 insertions(+), 8 deletions(-) ---------------------------------------------------------------------- http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/2d255613/python/singa/optimizer.py ---------------------------------------------------------------------- diff --git a/python/singa/optimizer.py b/python/singa/optimizer.py index 5cb02e5..975641a 100644 --- a/python/singa/optimizer.py +++ b/python/singa/optimizer.py @@ -206,7 +206,7 @@ class SGD(Optimizer): if self.momentum is not None: conf.momentum = self.momentum conf.type = 'sgd' - self.opt = singa.CreateOptimizer('SGD') + self.opt = singa.CreateOptimizer('SGD'.encode()) self.opt.Setup(conf.SerializeToString()) def apply_with_lr(self, epoch, lr, grad, value, name, step=-1): @@ -216,7 +216,7 @@ class SGD(Optimizer): epoch, value, grad, name, step) if name is not None and name in self.learning_rate_multiplier: lr = lr * self.learning_rate_multiplier[name] - self.opt.Apply(epoch, lr, name, grad.data, + self.opt.Apply(epoch, lr, name.encode(), grad.data, value.data) return value @@ -235,7 +235,7 @@ class Nesterov(Optimizer): if self.momentum is not None: conf.momentum = momentum conf.type = 'nesterov' - self.opt = singa.CreateOptimizer('Nesterov') + self.opt = singa.CreateOptimizer('Nesterov'.encode()) self.opt.Setup(conf.SerializeToString()) def apply_with_lr(self, epoch, lr, grad, value, name, step=-1): @@ -246,7 +246,7 @@ class Nesterov(Optimizer): epoch, value, grad, name, step) if name is not None and name in self.learning_rate_multiplier: lr = lr * self.learning_rate_multiplier[name] - self.opt.Apply(epoch, lr, name, grad.data, + self.opt.Apply(epoch, lr, name.encode(), grad.data, value.data) return value @@ -268,7 +268,7 @@ class RMSProp(Optimizer): conf = model_pb2.OptimizerConf() conf.rho = rho conf.delta = epsilon - self.opt = singa.CreateOptimizer('RMSProp') + self.opt = singa.CreateOptimizer('RMSProp'.encode()) self.opt.Setup(conf.SerializeToString()) def apply_with_lr(self, epoch, lr, grad, value, name, step=-1): @@ -279,7 +279,7 @@ class RMSProp(Optimizer): epoch, value, grad, name, step) if name is not None and name in self.learning_rate_multiplier: lr = lr * self.learning_rate_multiplier[name] - self.opt.Apply(step, lr, name, grad.data, + self.opt.Apply(step, lr, name.encode(), grad.data, value.data) return value @@ -300,7 +300,7 @@ class AdaGrad(Optimizer): conf = model_pb2.OptimizerConf() conf.delta = epsilon conf.type = 'adagrad' - self.opt = singa.CreateOptimizer('AdaGrad') + self.opt = singa.CreateOptimizer('AdaGrad'.encode()) self.opt.Setup(conf.SerializeToString()) def apply_with_lr(self, epoch, lr, grad, value, name, step=-1): @@ -311,7 +311,7 @@ class AdaGrad(Optimizer): epoch, value, grad, name, step) if name is not None and name in self.learning_rate_multiplier: lr = lr * self.learning_rate_multiplier[name] - self.opt.Apply(epoch, lr, name, grad.data, + self.opt.Apply(epoch, lr, name.encode(), grad.data, value.data) return value
