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System information

• TensorFlow version: 1.13.1
• Doc Link: https://www.tensorflow.org/api_docs/python/tf/cus

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.

Bug Report

These tests were run on s390x. s390x is big-endian architecture.

Failure log for helper_test.py

________________________________________________ TestHelperTensorFunctions.test_make_tensor ________________________________________________

self = <helper_test.TestHelperTensorFunctions testMethod=test_make_tensor>

    def test_make_tensor(self):  # type: () -> None
    

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

As mentioned by Diego, these additions would help by simplifying the API usage for users even further and it should be pretty easy to implement for us: 👍

@divega commented: dotnet/machinelearning-samples#617 (review)

@CESARDELATORRE, I did a deferred review. The experience seems pretty good.

1:
And I agree with you that it could be even better

Recently, we did a lot of new changes around our documentation and had a lot of new contributions. We need new users to visit our docs and help us to fix/find broken links, typos, or any general improvements/ideas to the MindsDB documentation..

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.

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?

With the addition of avro read/write support in Bigquery there's no need to have these extra conversions and extension methods laying around as they might add confusion to the user.

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.

Is your feature request related to a problem? Please describe.

Currently, the BentoML API model server does not print the errors and stack trace when the exception was raised within the user's inference API function code. This makes it hard for users to debug issues in their code.

**D

Description

Implement a YOLO model and add it to the DJL model zoo

References

• https://arxiv.org/abs/1506.02640

I'm trying to have a multi-dimensional lengthscale for my kernel, and cannot find in the documentation how to do this. The closest I've come is specifying input_dim, as described here, but in version 2.0.5 I get an error that input_dim is an unknown keyword argument. How would I get these multidimensional lengthscales in gpfl