Please make sure that this is a bug. As per our
GitHub Policy,
we only address code/doc bugs, performance issues, feature requests and
build/installation issues on GitHub. tag:bug_template

System information

• Have I written custom code (as opposed to using a stock
  example script provided in TensorFlow): Yes

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.

Spawned off https://github.com/onnx/onnx/pull/2772/files/7ab93cc1b635eada330dae7424d4ff7e8c22c295#r440422245, opening issue to track resolution

MLflow seems to have a length limit of 5000 when setting tags (see below).

[...]
  File "/home/smay/miniconda3/envs/py38/lib/python3.8/site-packages/mlflow/utils/validation.py", line 136, in _validate_length_limit
    raise MlflowException(
mlflow.exceptions.MlflowException: Tag value '[0.8562690322984875, 0.8544098885636596, 0.8544098885636596, 0.8544098885636596, 0.85440988856365

There are 2 places we are using BufferBlock<T> today:

https://github.com/dotnet/machinelearning/blob/b7db4fa475ba4bd52824eb98bbf5f5bf4a0a6f7a/src/Microsoft.ML.Data/Transforms/RowShufflingTransformer.cs#L486-L487

https://github.com/dotnet/machinelearning/blob/b7db4fa475ba4bd52824eb98bbf5f5bf4a0a6f7a/src/Microsoft.ML.Sweeper/AsyncSweeper.cs#L171

We should consider replacing this depende

All available samples code target .Net Core, Do we have samples for .Net Framework ?

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.

When setting fix_imbalance=True,fix_imbalance_method=imblearn.over_sampling.RandomOverSampler in setup (or any other imblearn method, including SMOTE), I always get this error when calling create_model('rf'):

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-164-5b7c9

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?

I am aggregating some events for 7 days from a partitioned table, and want to use mockTable for integration tests of my SQL.
SELECT flight_id AS flightId, campaign_id AS campaignId, ad_format FROM ad-selfserve.ad_platform_services.clean_flights_* WHERE _TABLE_SUFFIX >= $START_DATE AND _TABLE_SUFFIX < $END_DATE)

tests:
`
val CLEAN_FLIGHTS_TABLE_REF = "ad-selfserve:ad

Problem
Since Java 8 was introduced there is no need to use Joda as it has been replaced the native Date-Time API.

Solution
Ideally greping and replacing the text should work (mostly)

Additional context
Need to check if de/serializing will still work.

Describe the bug

I believe this is a bug, but I might just be missing how to properly use the containerize functionality.

The Dockerfile generated by https://github.com/bentoml/BentoML/blob/master/bentoml/clipper/__init__.py#L97 includes two args for PIP repos. However, the containerize functionality doesn't seem to expose these arguments. The problem is that this will override other p

There are a number of empty notebooks. Task here is to find them all, and convert each one to its own backlog ticket. Delete those notebooks and remove references to them from other notebooks. You'll also need to check if any of the text surrounding links needs adjusting.