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2
docs/clearml_sdk/clearml_sdk.md
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@ -82,7 +82,7 @@ See [ClearML Data](../clearml_data/clearml_data.md) or the [Dataset SDK referenc
The `StorageManager` class provides support for downloading and uploading from storage,
including local folders, S3, Google Cloud Storage, Azure Storage, and http(s).
See the [StorageManager SDK reference page](../references/sdk/storage.md).
See [examples](../guides/storage/examples_storagehelper.md) of `StorageManager` usage or the [StorageManager SDK reference page](../references/sdk/storage.md).
### APIClient
The `APIClient` class provides a Pythonic interface to access ClearML's backend REST API.

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docs/guides/frameworks/tensorflow/tensorboard_pr_curve.md
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@ -11,7 +11,7 @@ The example script does the following:
label of each random color is associated with the normal distribution that generated it.
* Computes the probability that each color belongs to the class, using three other normal distributions.
* Generate PR curves using those probabilities.
* Creates a summary per class using [tensorboard.plugins.pr_curve.summary](https://github.com/tensorflow/tensorboard/blob/master/tensorboard/plugins/pr_curve/summary.py).
* Creates a summary per class using [`tensorboard.plugins.pr_curve.summary`](https://github.com/tensorflow/tensorboard/blob/master/tensorboard/plugins/pr_curve/summary.py).
* ClearML automatically captures TensorBoard output, TensorFlow Definitions, and output to the console.
## Plots
@ -19,11 +19,16 @@ The example script does the following:
In the **ClearML Web UI**, the PR Curve summaries appear in the experiment's page under **PLOTS**.
* Blue PR curves
![image](../../../img/examples_tensorboard_pr_curve_01.png)
![image](../../../img/examples_tensorboard_pr_curve_01.png)
* Green PR curves
![image](../../../img/examples_tensorboard_pr_curve_02.png)
![image](../../../img/examples_tensorboard_pr_curve_02.png)
* Red PR curves
![image](../../../img/examples_tensorboard_pr_curve_03.png)
![image](../../../img/examples_tensorboard_pr_curve_03.png)
## Hyperparameters

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docs/webapp/webapp_exp_table.md
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@ -13,8 +13,9 @@ using the buttons on the top left of the page. Use the table view for a comparat
to columns of interest. Use the details view to access a selected experiment's details, while keeping the experiment list
in view. Details view can also be accessed by double-clicking a specific experiment in the table view to open its details view.
Use the [comparison view](#comparing-experiments) to compare your experiments' scalar and plot results (for a more in
depth comparison, see [Comparing Experiments](webapp_exp_comparing.md)). When selected, this view presents a comparison
of all selected experiments. If no experiments are selected, all currently visible experiments in the table are compared.
depth comparison, see [Comparing Experiments](webapp_exp_comparing.md)). This view compares
the scalars/plots of currently selected experiments. If no experiments are selected, the first 100
visible experiments in the table are compared.
You can archive experiments so the experiments table doesn't get too cluttered. Click **OPEN ARCHIVE** on the top of the
table to open the archive and view all archived experiments. From the archive, you can restore
@ -266,7 +267,7 @@ selecting items beyond the items currently on-screen:
The comparison view compares experiment scalar and plot results (for a more in depth comparison, see [Comparing Experiments](webapp_exp_comparing.md)).
When selected, the view presents a comparison of all [selected experiments](#selecting-multiple-experiments). If no
experiments are selected, all currently visible experiments in the table are displayed in the comparison.
experiments are selected, the first 100 visible experiments in the table are displayed in the comparison.
In the dropdown menu, select to view **Scalars** or **Plots**. **Scalars** shows experiment scalar results as time
series line graphs. **Plots** shows the last reported iteration sample of each metric/variant combination per compared