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---
title: Version 0.11
---
:::important
**Trains** is now **ClearML** .
:::
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### Trains 0.11.3
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**Features and Bug Fixes**
* Resource-Monitor will only monitor active GPU devices based on environment variables: `NVIDIA_VISIBLE_DEVICES` or `CUDA_VISIBLE_DEVICES` .
* Fix issue ([GitHub Issue #48 ](https://github.com/allegroai/trains/issues/48)).
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### Trains 0.11.2
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**Features and Bug Fixes**
* Fix Python 2.7 support.
* Improve sample code Windows support.
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### Trains 0.11.1
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**Features and Bug Fixes**
* Embed GPU Monitoring into **Trains** (removed gpustat dependency).
* Add initial support for TensorFlow v2.0 (tested with v2.0.0rc1).
* Add artifact upload retry on network errors (default: 3).
* Suppress urllib3 retry warnings.
* Fix Matplotlib support with Agg backend (multiple plot windows caused repeated graphs to be sent).
* Fix support for tuples in hyperparameters.
* Fix multi processing issues with different task types.
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### Trains 0.11.0
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**Features and Bug Fixes**
* Full artifacts support (supported by trains-server >= 0.11.0).
* Artifacts include, Pandas.DataFrame, Numpy, PIL Image, local files, and local folder / wildcard ([example](https://github.com/allegroai/trains/blob/master/examples/reporting/artifacts.py)).
* Artifacts support for folder / wildcard, selected files will be zipped and uploaded.
* Resource monitoring, remove sensor reading failure warnings.
**Breaking Changes**
* Logger `info` /`error`/`warning`/`console` functions were removed, use `Logger.report_text` (or Python logging or print instead).
* TensorBoard scalars are not grouped into one graph, but are stored on individual graphs (to match TensorBoard behavior).
To restore previous behavior call: `Logger.tensorboard_auto_group_scalars(group_scalars=True)` .
