| /dports/misc/tvm/incubator-tvm-0.6.1/nnvm/tests/python/compiler/ |
| H A D | test_optimizer.py | 59 lr_factor = 0.5
64 scheduler = lr_scheduler.FactorScheduler(base_lr=base_lr, step=1, factor=lr_factor)
76 weight_0 = weight - base_lr * lr_factor * (gradient_0 + wd * weight)
79 weight_1 = weight_0 - base_lr * (lr_factor ** 2) * (gradient_1 + wd * weight_0)
99 lr_factor = 0.5
104 scheduler = lr_scheduler.FactorScheduler(base_lr=base_lr, step=1, factor=lr_factor)
115 lr_0 = base_lr * lr_factor * rate_0
122 lr_1 = base_lr * (lr_factor ** 2) * rate_1
|
| /dports/misc/py-tvm/incubator-tvm-0.6.1/nnvm/tests/python/compiler/ |
| H A D | test_optimizer.py | 59 lr_factor = 0.5
64 scheduler = lr_scheduler.FactorScheduler(base_lr=base_lr, step=1, factor=lr_factor)
76 weight_0 = weight - base_lr * lr_factor * (gradient_0 + wd * weight)
79 weight_1 = weight_0 - base_lr * (lr_factor ** 2) * (gradient_1 + wd * weight_0)
99 lr_factor = 0.5
104 scheduler = lr_scheduler.FactorScheduler(base_lr=base_lr, step=1, factor=lr_factor)
115 lr_0 = base_lr * lr_factor * rate_0
122 lr_1 = base_lr * (lr_factor ** 2) * rate_1
|
| /dports/misc/mxnet/incubator-mxnet-1.9.0/example/image-classification/ |
| H A D | train_model.R | 67 if (args$lr_factor < 1){
74 … lr_scheduler <- mx.lr_scheduler.MultiFactorScheduler(step=step_batch, factor_val=args$lr_factor)
78 factor_val = args$lr_factor)
|
| /dports/misc/py-mxnet/incubator-mxnet-1.9.0/example/image-classification/ |
| H A D | train_model.R | 67 if (args$lr_factor < 1){
74 … lr_scheduler <- mx.lr_scheduler.MultiFactorScheduler(step=step_batch, factor_val=args$lr_factor)
78 factor_val = args$lr_factor)
|
| /dports/misc/mxnet/incubator-mxnet-1.9.0/example/caffe/ |
| H A D | train_model.py | 77 if 'lr_factor' in args and args.lr_factor < 1:
80 factor=args.lr_factor)
|
| /dports/misc/py-mxnet/incubator-mxnet-1.9.0/example/caffe/ |
| H A D | train_model.py | 77 if 'lr_factor' in args and args.lr_factor < 1:
80 factor=args.lr_factor)
|
| /dports/misc/py-gluoncv/gluon-cv-0.9.0/scripts/classification/finetune/ |
| H A D | finetune_minc.py | 54 lr_factor = opts.lr_factor variable
134 trainer.set_learning_rate(trainer.learning_rate*lr_factor)
|
| /dports/misc/py-gluoncv/gluon-cv-0.9.0/docs/tutorials/classification/ |
| H A D | transfer_learning_minc.py | 116 lr_factor = 0.75 variable
255 trainer.set_learning_rate(trainer.learning_rate*lr_factor)
|
| /dports/misc/mxnet/incubator-mxnet-1.9.0/example/stochastic-depth/ |
| H A D | sd_cifar10.py | 185 lr_factor = 0.5 variable
194 …= mx.lr_scheduler.FactorScheduler(step=max(int(epoch_size * lr_factor_epoch), 1), factor=lr_factor)
|
| /dports/misc/py-mxnet/incubator-mxnet-1.9.0/example/stochastic-depth/ |
| H A D | sd_cifar10.py | 185 lr_factor = 0.5 variable
194 …= mx.lr_scheduler.FactorScheduler(step=max(int(epoch_size * lr_factor_epoch), 1), factor=lr_factor)
|
| /dports/misc/mxnet/incubator-mxnet-1.9.0/example/image-classification/common/ |
| H A D | fit.py | 30 if 'lr_factor' not in args or args.lr_factor >= 1:
44 lr *= args.lr_factor
52 return (lr, mx.lr_scheduler.MultiFactorScheduler(step=steps, factor=args.lr_factor,
|
| /dports/misc/py-mxnet/incubator-mxnet-1.9.0/example/image-classification/common/ |
| H A D | fit.py | 30 if 'lr_factor' not in args or args.lr_factor >= 1:
44 lr *= args.lr_factor
52 return (lr, mx.lr_scheduler.MultiFactorScheduler(step=steps, factor=args.lr_factor,
|
| /dports/misc/mxnet/incubator-mxnet-1.9.0/example/rcnn/ |
| H A D | train.py | 98 lr_factor = 0.1
101 lr = base_lr * (lr_factor ** (len(lr_epoch) - len(lr_epoch_diff)))
104 lr_scheduler = mx.lr_scheduler.MultiFactorScheduler(lr_iters, lr_factor)
|
| /dports/misc/py-mxnet/incubator-mxnet-1.9.0/example/rcnn/ |
| H A D | train.py | 98 lr_factor = 0.1
101 lr = base_lr * (lr_factor ** (len(lr_epoch) - len(lr_epoch_diff)))
104 lr_scheduler = mx.lr_scheduler.MultiFactorScheduler(lr_iters, lr_factor)
|
| /dports/misc/mxnet/incubator-mxnet-1.9.0/example/gluon/ |
| H A D | image_classification.py | 209 trainer = update_learning_rate(opt.lr, trainer, epoch, opt.lr_factor, lr_steps)
|
| /dports/misc/py-mxnet/incubator-mxnet-1.9.0/example/gluon/ |
| H A D | image_classification.py | 209 trainer = update_learning_rate(opt.lr, trainer, epoch, opt.lr_factor, lr_steps)
|