Guocheng
Guocheng
I'm building a model training API server, I want the request body (training config) to be as simple as possible because our users have no ML experience,and the request body...
Using dependency injection sounds great, I just need to write more data validation code when developing my API :thinking: .
> This is because your shell is modifying the values before they get to the python code. You need to quote them to prevent this. > > ``` > $...
> I can look into what happened with the first one. But you need to provide the exact type hint of `augmentations` and say which shell you are using. The...
Hi, @mauvilsa The LightningCLI `subclass_mode_model` and `subclass_mode_data` is `False` And I upgraded `jsonargparse` to `4.27.0`, still have errors: ```bash error: Validation failed: No action for key "augmentations+.c" to check its...
Hi, @mauvilsa Appears the `subclass_mode_model` is `True`, although I did not explicitly set it to `True`, since I did not provide the `model_class`, it is set to `True` in the...
wow ! this tutorials helps a lot ! many thanks !
Hi, @ariel415el Thanks for your attention! Clipping the `x_0` yields better results, it's because we know that `x_0` has the `[-1,1]` distribution(`x_0` is the normed input image, we norm the...
@ariel415el Yes, the code is here. https://github.com/bot66/MNISTDiffusion/blob/c7ba8e09174cbb88b9cc314db3bf2e514668681c/model.py#L102
Yes, simply typing `python train_mnist.py` in your terminal will reproduce the result!