🐛 Bug

Tensorboard logging metrics from different GPUs when using DataParallel training.

To Reproduce

Use any arbitrary toy model with DP as an accelerator and in training_step(), include the below line of code:

self.log(mode + '_loss', sum(losses), on_epoch=False, on_step=True, prog_bar=True, logger=True, sync_dist=True)

In the trainer, specify tensorboard logger with

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

🙌🙌🙌🙌🙌

Bug Report

Got error message on an empty directory, shouldn't it show nothing? like ls command.

Description

![image](htt

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

Steps/Code to reproduce:

We've seen a searchResultBufFlags array in proxy task scheduler.
It is never cleaned from the map so I guess there is a memory leak especially when search number is going up.

We need to check on how to fix it

Expected result:

Delete or clean it when ne

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

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

2019/12/02 和Yi Wang沟通交流考虑SQLFLOW可以支持如下的特性

一、基础功能：好用的工具需要一个更加简易友好的界面，让业务开发/分析更加简单
1)设计分析类工具，提供自动联想输入、快速语法、常见语义错误，提升用户体验
应用场景：提供IDE的自动联想功能，提高开发效率；语法和基本语义提前检查，避免提交到后台，执行较长时间后报错
2)大数据量时时间较长，建议提供任务(job)管理、允许用户了解数据执行的状态、监控进度、提供动态调试、watch能力，方便用户感知和调优
应用场景：耗时任务可以快速了解整体进度，提供一些中间的过程信息、耗时等，方便用户进行调优,优化开发
3) 安全权限、用户管理、
应用场景：增加新的数据分析人员、用户权