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Artificial Intelligence

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The branch of computer science dealing with the reproduction, or mimicking of human-level intelligence, self-awareness, knowledge, conscience, and thought in computer programs.

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pytorch-lightning
awaelchli
awaelchli commented Dec 8, 2021

Proposed refactor

Deprecate tpu_global_core_rank in favor of global_rank.

Pitch

It "looks" like tpu_global_core_rank in the TPUPlugin is just another name for what is known as the global rank. After #10896 we should investigate whether the two are equivalent and revert back to using the unified global_rank property exclusively.


dbczumar
dbczumar commented Sep 18, 2021

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

milvus
binbinlv
binbinlv commented Nov 23, 2021

Is there an existing issue for this?

  • I have searched the existing issues

Environment

- Milvus version: latest
- Deployment mode(standalone or cluster):both
- SDK version(e.g. pymilvus v2.0.0rc2): latest
- OS(Ubuntu or CentOS): 
- CPU/Memory: 
- GPU: 
- Others:

Current Behavior

1 Good
res = collection.search(vectors[:nq], "float_vector", default_sear

olistic
olistic commented May 25, 2018

Currently, when entering epic mode the README is frozen in the last level of the tower. When you're trying to fine-tune the score for a level other than the last one, it would be helpful if we had the README for that level available. The proposal is that when entering epic mode, the README is updated with all levels, one following the other.

Example:

# Starbolt - beginner
leon
Lp-Francois
Lp-Francois commented Oct 5, 2019

Specs

  • Leon version: latest
  • OS (or browser) version: Fedora 30
  • Node.js version: 10.16.3
  • Complete "npm run check" output:
➡ Here is the diagnosis about your current setup
✔ Run
✔ Run modules
✔ Reply you by texting
❗ Amazon Polly text-to-speech
❗ Google Cloud text-to-speech
❗ Watson text-to-speech
❗ Offline text-to-speech
❗ Google Cloud speech-to-text
❗ Watson spee
metaflow
tuulos
tuulos commented Sep 7, 2021

With a config like this

{
    "METAFLOW_DATASTORE_SYSROOT_S3": "s3://mf-test/metaflow/",
}

(note a slash after METAFLOW_DATASTORE_SYSROOT_S3)

metaflow.S3(run=self).put* produces double-slashes like here:

s3://mf-test/metaflow//data/DataLoader/1630978962283843/month=01/data.parquet

The trailing slash in the config shouldn't make a difference