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101 lines
4.3 KiB
Markdown
101 lines
4.3 KiB
Markdown
---
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title: Logger
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---
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The ClearML **Logger** object is used to report experiments' results such as metrics, graphs, and debug samples. It is a
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member of the [Task](task.md) object.
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ClearML integrates with the leading visualization libraries, and automatically captures reports to them.
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## Types of Logged Results
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In ClearML, there are four types of reports:
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- Text - Mostly captured automatically from stdout and stderr but can be logged manually.
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- Scalars - Time series data. X-axis is always a sequential number, usually iterations but can be epochs or others.
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- Plots - General graphs and diagrams, such as histograms, confusion matrices line plots, and custom plotly charts.
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- Debug Samples - Images, audio, and videos. Can be reported per iteration.
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## Automatic Reporting
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ClearML automatically captures metrics reported to tools, such as TensorBoard and Matplotlib, with no additional code
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necessary.
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In addition, ClearML will capture and log everything written to standard output, from debug messages to errors to
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library warning messages.
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GPU, CPU, Memory and Network information is also automatically captured.
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### Supported Packages
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- [TensorBoard](https://www.tensorflow.org/tensorboard)
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- [TensorBoardX](https://github.com/lanpa/tensorboardX)
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- [Matplotlib](https://matplotlib.org/)
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### Automatic Reporting Examples
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Check out some of ClearML's automatic reporting examples for supported packages:
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* TensorBoard
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* [TensorBoard PR Curve](../guides/frameworks/tensorflow/tensorboard_pr_curve.md) - logging TensorBoard outputs and
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TensorFlow flags
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* [TensorBoard Toy](../guides/frameworks/tensorflow/tensorboard_toy.md) - logging TensorBoard histograms, scalars, images, text, and
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TensorFlow flags
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* [Tensorboard with PyTorch](../guides/frameworks/pytorch/pytorch_tensorboard.md) - logging TensorBoard scalars, debug samples, and text integrated into
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code that uses PyTorch
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* [TensorBoardX](../guides/frameworks/tensorboardx/tensorboardx.md) - logging TensorBoardX scalars, debug
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samples, and text in code using PyTorch
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* Matplotlib
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* [Matplotlib Script Example](../guides/frameworks/matplotlib/matplotlib_example.md) and [Jupyter Notebook](../guides/frameworks/matplotlib/allegro_clearml_matplotlib_example.md) -
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logging scatter diagrams plotted with Matplotlib
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* [Matplotlib with PyTorch](../guides/frameworks/pytorch/pytorch_matplotlib.md) - logging debug images shown
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by Matplotlib
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## Manual Reporting
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ClearML also supports manually reporting multiple types of metrics and plots, such as line plots, histograms, and even plotly
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charts.
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The object used for reporting metrics is called **logger** and is obtained by calling
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```python
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logger = task.get_logger()
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```
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### Media Reporting
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ClearML also supports reporting media (such as audio, video and images) for every iteration.
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This section is mostly used for debugging. It's recommended to use [artifacts](artifacts.md#artifacts) for storing script
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outputs that would be used later on.
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Only the last X results of each title \ series are saved to prevent overloading the server.
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See details in [Logger.report_media](../references/sdk/logger.md#report_media).
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### Explicit Reporting Examples
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Check out ClearML's explicit reporting examples for various types of results:
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- [Text](../guides/reporting/text_reporting.md)
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- [Scalars](../guides/reporting/scalar_reporting.md)
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- Plots
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- [2d plots](../guides/reporting/scatter_hist_confusion_mat_reporting.md)
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- Histograms
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- Confusion matrices
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- Scatter plots
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- [3d plots](../guides/reporting/3d_plots_reporting.md)
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- Surface plots
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- Scatter plots
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- [Tables](../guides/reporting/pandas_reporting.md)
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- Pandas DataFrames
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- CSV file
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- [Matplotlib figures](../guides/reporting/manual_matplotlib_reporting.md)
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- [Plotly figures](../guides/reporting/plotly_reporting.md)
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- Debug Samples
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- [Images](../guides/reporting/image_reporting.md)
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- [HTML](../guides/reporting/html_reporting.md)
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- [Media - images, audio, video](../guides/reporting/media_reporting.md)
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- Explicit reporting in Jupyter Notebook [example](../guides/reporting/clearml_logging_example.md)
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