Machine learning

Current implementation of Go binding can not specify options.

GPUOptions struct is in internal package. And go generate doesn't work for protobuf directory. So we can't specify GPUOptions for NewSession.

This issue is part of our Doc Test Sprint. If you're interested in helping out come join us on Discord and talk with other contributors!

Docstring examples are often the first point of contact when trying out a new library! So far we haven't done a very good job at ensuring that all docstring examples work correctly in 🤗 Transformers - but we're now very

https://github.com/pytorch/pytorch/blob/9270bccaf67022042f42b57b97c7b630b1e05750/torch/utils/data/sampler.py#L86

The optional argument 'num_samples' to the RandomSampler class is listed as type Optional[int], but it is not optional, as an exception is raised if an int is not passed in:

https://github.com/pytorch/pytorch/blob/9270bccaf67022042f42b57b97c7b630b1e05750/torch/utils/data/sampler.p

Describe the issue linked to the documentation

Documentation should be changed to reflect that one-vs-rest is possible.

x = np.array([0,1,2,3,4,5,3,3,5,5,5,7,7,2])
x = x.reshape(-1,1)#this has 1 feature, therefore reshaping properly

y = [0,0,0,1,0,2,1,1,2,2,2,3,3,0] #note: y has multiple classes.


model = SVC(gamma = "auto", decision_function_shape="ovr")
model.fit(x,y)
p

As discussed on Discourse, it would be nice to have !foo return a ComposedFunction, which would

1. allow dispatch and specialized methods for !foo
2. allow nicer pretty printing of !foo as "!foo" rather than as "#xx (generic function with 1 method)" (by overloading show for ComposedFunction{typeof(!)}

Currently many more Python projects like dask and optuna are using Python type hints. With the Python package of xgboost gaining more and more features, we should also adopt mypy as a safe guard against some type errors and for better code documentation.