Lesson 1 In-Class Discussion

Part 1 (2018)
210

If no mistaken, he said that backpropagation is not a real thing that happens in the brain and we should start all again

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This works, thanks.

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Code complexity in course part1-v2 is significantly different from code level of part1-v1. Nested classes (ModelData>ImageData>ImageClassifierData + FilesIndexArrayDataset + FilesIndexArrayRegressionDataset ), decorators, tons of parameter passing

def __init__(self, path, datasets, bs, num_workers, classes):
    trn_ds,val_ds,fix_ds,aug_ds,test_ds,test_aug_ds = datasets
    self.path,self.bs,self.num_workers,self.classes = path,bs,num_workers,classes
    self.trn_dl,self.val_dl,self.fix_dl,self.aug_dl,self.test_dl,self.test_aug_dl = [
        self.get_dl(ds,shuf) for ds,shuf in [
            (trn_ds,True),(val_ds,False),(fix_ds,False),(aug_ds,False),
            (test_ds,False),(test_aug_ds,False)
        ]
    ]

It looks like spaceship much more complicated than it was a year ago and I wonder why?

5 Likes
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We’ve built a whole new framework, not just a few little wrapper classes. It’s so we can go far deeper than last year, get much better results, but do it with less/simpler code in the notebooks.

More advanced students can help contribute to the new library.

8 Likes
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I’ve added the recordings to the top post of this thread, BTW.

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@jeremy is the framework contribution is restricted to the advanced level candidates? Because, If you have a thread with the SOP’s, Test cases and design documents people can pull over and start forking the framework’s repo, you can evaluate the merge request with the test cases, This will give you more quality and productivity in-terms of frame-work.

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You can ask some of us to create the SOP and design documents and you can validate it for the pre-design phase.

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Anyone is welcome to contribute!

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Thank you, Jeremy. Any Forum thread for the contributors?

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Is there a way to set the code to run in CPU only mode? ( like v1 class).

When i ran the model, got the below Assertion error:

~/anaconda3/lib/python3.6/site-packages/torch/cuda/init.py in _check_driver()
56 Found no NVIDIA driver on your system. Please check that you
57 have an NVIDIA GPU and installed a driver from
—> 58 http://www.nvidia.com/Download/index.aspx""")
59 else:
60 # TODO: directly link to the alternative bin that needs install

AssertionError:
Found no NVIDIA driver on your system. Please check that you
have an NVIDIA GPU and installed a driver from
http://www.nvidia.com/Download/index.aspx

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Not currently. It wouldn’t take much to modify fastai to make this possible, but I haven’t had the time yet. If anyone wants to contribute this, feel free! :slight_smile:

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Not as yet, but if you have some code to discuss, feel free to create one.

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Sure, I will.

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Ok. Thanks for your response.

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No. There are two plots. In one plot you have x=mini-batch y = learning rate. This is showing how learning rate is increasing as a function of mini-batch. This is for the algorithm that find best learning rate.
The other plot is learning rate as a function of loss.

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when will be remaining part of lesson available ??

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What do you mean @HariSumanth9 ? I think it’s all already there.

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Check the top of this thread, Jeremy has posted the recorded video links for both section 1 and 2.

1 Like