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.

New Operator

Describe the operator

Why is this operator necessary? What does it accomplish?

This is a frequently used operator in tensorflow/keras

Can this operator be constructed using existing onnx operators?

If so, why not add it as a function?

I don't know.

Is this operator used by any model currently? Which one?

Are you willing to contribute it?

MLflow Roadmap Item

This is an MLflow Roadmap item that has been prioritized by the MLflow maintainers. We're seeking help with the implementation of roadmap items tagged with the help wanted label.

For requirements clarifications and implementation questions, or to request a PR review, please tag @BenWilson2 in your communications related to this issue.

Proposal Summary

Includ

Every kubeflow image should be scanned for security vulnerabilities.
It would be great to have a periodic security report.
Each of these images with vulnerability should be patched and updated.

Let's make the error message more actionable.

Error user sees:

I would recommend adding similar named column(s):

- $"Provided {columnPurpose} column '{columnName}' not found in training data."
+ $"Provided {columnPurpose} column '{columnName}' not found in training 

Metaflow currently supports Py>=3.4 (with limited support for Py2.7) and R>=3.8. The GH tests only test for Py3.7 and R4.1. We should ensure we test on the whole set of permutations.

Is your feature request related to a problem? Please describe.
Add exogenous variable plots in plot_models() for time series

Describe the solution you'd like

plot_model()

The current solution only plots the target. It would be nice to see all the exogenous variables along with this as well (plotted below it and synchronized in x-axis).

We need to increase the number of datasources that MindsDB supports. This task should add a new datasource for connecting to Redash. You can get more info on Redash docs.
If possible, please include a test for the datasource. You can check the example here.

Note: if you are familiar with another datasource tha

🚨🚨 Feature Request

If your feature will improve HUB

To explore the structure of a dataset it is convenient to have nicer and more informative prints of dataset objects and samples

Description of the possible solution

1) show ds

now

> ds
Dataset(path='hub://activeloop/abalone_full_dataset', tensors=['length', 'diameter', 'height', 'weight'])

In Ue format string it represent float with comma separator, it crash css style

To fix it you can Round/replace/incluse culture info

samples/csharp/end-to-end-apps/ScalableSentimentAnalysisBlazorWebApp/BlazorSentiment.Client/Shared/HappinessScale.razor

I have a simple regression task (using a LightGBMRegressor) where I want to penalize negative predictions more than positive ones. Is there a way to achieve this with the default regression LightGBM objectives (see https://lightgbm.readthedocs.io/en/latest/Parameters.html)? If not, is it somehow possible to define (many example for default LightGBM model) and pass a custom regression objective?

Use case

Polyaxon tracking can be used to automatically log all information generated by Ludwig.

We should probably think about adding support for Polyaxon's tracking module in Ludwig contrib.

在oneflow里，交叉熵损失有以下几种：

• binary_cross_entropy_loss
• binary_cross_entropy_with_logits_loss
• sparse_cross_entropy
• distributed_sparse_cross_entropy
• cross_entropy
• sparse_softmax_cross_entropy
• softmax_cross_entropy

在pytorch里，交叉熵损失有以下几种：

• binary_cross_entropy
• binary_cross_entropy_with_logits
• cross_entropy

由此可见，oneflow中交叉熵损失存在API冗余，重复，容易让用户疑惑，因此，这里应该精简一下。除此之外，label smooth