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There is a set of Pixel Level transforms that is used in the work Benchmarking Neural Network Robustness to Common Corruptions and Perturbations

The authors also share the code => we can absorb some transforms that they have into the library.

https://github.com/hendrycks/robustness/blob/master/ImageNet-C/create_c/make_imagenet_c.py

• ShotNoise
• Defocus
• GlassBlur

Hi, thanks for the great code!

I wonder do you have plans to support resuming from checkpoints for classification? As we all know, in terms of training ImageNet, the training process is really long and it can be interrupted somehow, but I haven't notice any code related to "resume" in scripts/classification/train_imagenet.py.

Maybe @hetong007 ? Thanks in advance.

how to use gui in the AidLearning?how to custom the gui?

hello大家好，我是该仓库的作者。鉴于我复现tensorflow-yolov3踩了太多坑，特此发个贴，帮助大家少走弯路。大家有问题可以在下面留言。

How do i resume training for text classification?

Feature Request

I want to obtain the evaluation of different datasets of a single job
lumi eval -h && lumi eval -c config_ssd.yml --split valid --split train --split test --watch --from-global-step 0

I understand that it is not so trivial because it was being kept as a summary of work scalars like this
![image](https://user-images.githubusercontent.com/7362688/48442210-8be6d080-e75b

Describe the bug
I found that some names agruments in framework aren't consistent.
So for example:

class SupervisedRunner(Runner):
    """Runner for experiments with supervised model."""

    _experiment_fn: Callable = SupervisedExperiment

    def __init__(
        self,
        model: Model = None,
        device: Device = None,
        input_key: Any = "features",