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System information

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

/kind feature

This is a sub-issue from #5494.
We need to remove any f"strings" from the backend of the Jupyter web app in order to be able to use lower versions from Python 3.6 to run it.

/good-first-issue

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
    

URLS with the issue:

• https://mlflow.org/docs/latest/python_api/mlflow.html#mlflow.log_param
• https://mlflow.org/docs/latest/python_api/mlflow.html#mlflow.log_metric
• https://mlflow.org/docs/latest/python_api/mlflow.html#mlflow.set_tag

Description of proposal:

Document the maximum value and legal characters for log_param, log_metric and set_tag. Note that log_metric's value i

Remove logging line, or modify from ch.Info to ch.Trace:
https://github.com/dotnet/machinelearning/blob/5dbfd8acac0bf798957eea122f1413209cdf07dc/src/Microsoft.ML.Mkl.Components/SymSgdClassificationTrainer.cs#L813

For my text dataset, this logging line dumps ~100 pages of floats to my console. That level of verbosity is unneeded at the Info level.

I'd recommend just removing the loggin

How do I get TOP-K evaluation indicators for multi-classification? For example, TOP-3 accuracy.

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

🚨🚨 Feature Request

• Related to an existing Issue
• A new implementation (Improvement, Extension)

Move the docker setup to a separate repository. Moving this outside core makes cleaner code.

Keeping docker-setup inside the core code, then adding a number of other similar systems like Vagrant, will over time create a mess. Better move them out. It also mak

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?

Today batch BigQuery writes require saving the data as GCS Avro files first then LOAD into BQ, which is wasteful if user also save as Avro in the same pipeline. Should we add a syntactic sugar for this?

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.