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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

Add a new API for converting a model to external data. Today the conversion happens in 2 steps
external_data_helper.convert_model_to_external_data(<model>, <all_tensors_to_one_file>, <size_threshold>) save_model(model, output_path)
We want to add another api which combines the 2 steps
`
save_model_to_external_data(, <output_

Willingness to contribute

• Yes. I can contribute this feature independently.

Proposal Summary

By default, artifacts are stored to ./mlruns (hard coded constant: DEFAULT_LOCAL_FILE_AND_ARTIFACT_PATH). The idea is to give the possibility to change this behaviour by setting an env var.

The same mechanism exists but not generalized:

_TRACKING_DIR_ENV_VAR = "MLFLOW_TRAC

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

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.

🚨🚨 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

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?

Currently com.spotify.scio.bigtable.syntax.ScioContextOps#updateNumberOfBigtableNodes updates all clusters for the instance.
That is not desired behaviour if each cluster is dedicated for specific task - one for batch jobs, another for service, etc.
Desired API is to allow change node count for only specific cluster (dedicated for batch jobs).

Proposed API change:

- def updateNumberOf

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.

Description

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

References

• https://arxiv.org/abs/1506.02640