Nale Raphael

Hi @doob09, it seems that your data `batch_data` is a `list`, not a `dict`. You might need to checkout the implementation of your dataset (e.g. `torch.Dataset`) to see whether the...

By the way, you can also checkout the implementation of base class `DataLoaderIter` https://github.com/davidtvs/pytorch-lr-finder/blob/acc5e7ee7711a460bf3e1cc5c5f05575ba1e1b4b/torch_lr_finder/lr_finder.py#L31-L41 In line 39, `batch_data` is unpacked into 3 values `inputs, labels, *_`, that's because we assume...

Sorry for the late reply. Actually, you don't need to convert `batch_data` from `list` to `dict`. You can just unpack `batch_data` in the `inputs_labels_from_batch()`, like this: ```python # assume that...

My pleasure :) It's simply a class inheritance here. And the reason why we have to wrap a `torch.Dataset` or `torch.DataLoader` with `DataLoaderIter` is that we need to make it:...

Hi @snoozeyouloose. `lr_finder.plot()` will return a `matplotlib.axes.Axes` object and a suggested learning rate (which is currently determined by a point with negative & minimal gradient) when given argument `suggest_lr` is...

With regard to the problem of finding the best learning rate, you can just set the argument `suggest_lr` of `lr_finder.plot()` to True, then you can get the suggested value without...

Hi @paulhager! Is the situation mentioned in this issue similar to the one you ran into? https://github.com/davidtvs/pytorch-lr-finder/issues/61#issuecomment-692715109 If not, can you describe more about it?

Hi @RowanG1, Currently provided trackback message is not complete and it shows only code related to the callback from `fastai` library, could you provide further more information about it? And...

Hi @manza-ari , sorry that I missed the notification of this issue. Regarding the error "ModuleDict.update should be called with an iterable of key/value pairs, but got ResNet", it seems...

Hi @manza-ari In the original implementation, `models` is actually a dictionary like this: ```python # src: https://github.com/razvancaramalau/Sequential-GCN-for-Active-Learning/blob/master/main.py#L111-L113 models = {'backbone': resnet18} if method =='lloss': models = {'backbone': resnet18, 'module': loss_module}...