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.

Feature request

We currently have 2 monocular depth estimation models in the library, namely DPT and GLPN.

It would be great to have a pipeline for this task, with the following API:

from transformers import pipeline

pipe = pipeline("depth-estimation")
pipe("ca

Tracking issue on the onnx opset 17 support.

• Add version 17 as a known version
• stft
• istft
• bartlett_window
• blackman_window
• hamming_window
• hann_window
• kaiser_window

Closes #80834

Describe the bug

The acceptable values for max_samples are (0, 1]. One possible option for class_weight is balanced_subsample. However, for values of max_samples near zero and class_weight='balanced_subsample', the model fails with an unhelpful error related to having an empty array as an indexer.

This is only likely to come up in a grid search, as it seems unlikely that some

This subject was initially discussed in https://discourse.julialang.org/t/efficient-way-to-split-string-at-specific-index/83115/17 regarding a way to split a string into equal-length substrings.

The solutions discussed involved (for a string composed of 10 blocks of 8 strings)

• using a comprehension split8(str::String) = [str[i+1:8] for i in 0:8:length(str)]
• using a comprehension and `S

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.

This is a nice first issue:

Add types/docments to the Learner.get_preds function. This function is essential to any fastai user and has almost no documentation. Add types and text to the variables as we have in many places now.