Add HuggingFace Accelerate integration page (#778)

docs/integrations/accelerate.md

@@ -0,0 +1,127 @@
+---
+title: Accelerate
+---
+
+HuggingFace's [Accelerate](https://huggingface.co/docs/accelerate/main/en/index) library simplifies DL model training 
+and inference. ClearML is a supported tracker in Accelerate: It automatically logs experiment environment information, 
+such as required packages and uncommitted changes, and supports reporting scalars, parameters, debug samples, and plots.
+
+
+## Setup
+
+To use Accelerate's ClearML tracker, make sure that `clearml` is [installed and set up](../getting_started/ds/ds_first_steps.md#install-clearml) 
+in your environment, and use the `log_with` parameter when instantiating an `Accelerator`:
+
+```python
+from accelerate import Accelerator
+
+accelerator = Accelerator(log_with="all")  # For all available trackers in the environment
+accelerator = Accelerator(log_with="clearml") # For the ClearML tracker only
+```
+
+Add `Accelerator.init_trackers()` in the beginning of your experiment. Specify the project where the ClearML task should
+be saved in the `project_name` parameter, and add any experiment hyperparameters to be logged in the `config` parameter. 
+
+The following code initializes the ClearML Task, which will capture all environment details, such as required packages 
+and uncommitted code. The logged hyperparameters are displayed in the experiment's **Hyperparameters** tab:
+
+
+```python
+hps = {"lr": 0.03, "num_epochs": 3, "seed": 42, "batch_size": 64, "image_size": 224}
+accelerator.init_trackers(project_name="my_project", config=hps)
+```
+
+:::tip
+You can also pass parameters to [`Task.init()`](../references/sdk/task.md#taskinit) by adding a nested dictionary
+to the `init_kwargs` argument of `Accelerator.init_trackers()`: use `"clearml"` as the key, and a dictionary of 
+parameter-name/parameter-value pairs as the value. For example, the following code adds tags to your task:
+
+```python
+accelerator.init_trackers(
+    project_name="my_project", 
+    configs=hp, 
+    init_kwargs={"clearml": {"tags": ["tag_a", "tag_b"]}}
+)
+```
+:::
+
+![Accelerate params](../img/integrations_accelerate_params.png)
+
+## Logging 
+
+### Scalars 
+To log scalars use `Accelerator.log()`. Specify a dictionary of name-value pairs under `values` and the step number 
+under `step`.
+
+Within the `values` dictionary, the name in each name-value pair is a string representing the title (metric) and series 
+(variant) of the scalar. The `eval_`, `test_`, or `train_` name prefixes, will cause the scalar to be logged under the 
+corresponding `eval`, `test`, or `train` title, and the remaining part of the name will be logged as the series. If none 
+of these prefixes is used, the entire string is used as the series, and the title will default to `train`. 
+
+If `step` is not specified, the scalar is reported as a single-value scalar. 
+
+```python
+accelerator.log(values={"accuracy": accuracy}, step=epoch)
+```
+
+The scalars are displayed in the experiment's **Scalars** tab. 
+
+### Images and Table Plots
+To add images or table plots to your experiment, you can use the `ClearMLTracker.log_images()` and `ClearMLTracker.log_table()`
+respectively. 
+
+First instantiate the `ClearMLTracker`. If you have run `Accelerator.init_trackers()` in your script, that means a ClearML 
+task has already been initialized, so anything logged through the tracker will be logged to the existing task.  
+Otherwise, just specify the experiment name under `run_name` and any kwargs to pass to 
+[`Task.init()`](../references/sdk/task.md#taskinit):
+
+```python
+from accelerate.tracking import ClearMLTracker
+
+clearml_tracker= ClearMLTracker(run_name="Example experiment")
+```
+
+#### Logging Images 
+To log images, use `ClearMLTracker.log_images()`. Specify a dictionary of name-image pairs under `values` and the step
+number under `step`. 
+
+Within the `values` dictionary, the name in each name-image pair should be a string representing the title (metric) and 
+series (variant) of the image. The `eval_`, `test_`, or `train_` name prefixes, will cause the image to be logged under 
+the corresponding `eval`, `test`, or `train` title, and the remaining part of the name will be logged as the series. 
+If none of these prefixes is used, the entire string is used as the series, and the title will default to `train`. The 
+image in the name-image pair should be either a numpy array or a `PIL.Image` object.
+
+```python
+clearml_tracker.log_images(values={"test_cat_siamese":[image_obect]})
+```
+
+The images will be displayed in the experiment's **Debug Samples**
+
+#### Logging Plots 
+
+To log plots, use `ClearMLTracker.log_table()`. Specify the data under the `dataframe` or `data` parameters. List the 
+name of the columns under `columns`, otherwise the first entry in `data` will be used as the column names. 
+
+The plot will appear in the experiment's **Plots** tab. 
+
+### Additional Logging Options
+
+To augment its automatic logging, ClearML also provides an explicit logging interface.
+
+See more information about explicitly logging information to a ClearML Task:
+* [Models](../clearml_sdk/model_sdk.md#manually-logging-models)
+* [Configuration](../clearml_sdk/task_sdk.md#configuration) (e.g. parameters, configuration files)
+* [Artifacts](../clearml_sdk/task_sdk.md#artifacts) (e.g. output files or python objects created by a task)
+* [Scalars](../clearml_sdk/task_sdk.md#scalars) 
+* [Text/Plots/Debug Samples](../fundamentals/logger.md#manual-reporting)
+
+See [Explicit Reporting Tutorial](../guides/reporting/explicit_reporting.md).
+
+## Close Task 
+
+Once you've finished training, make sure to run `Accelerator.end_training()` so that ClearML can mark the task as 
+completed.
+
+```python
+accelerator.end_training()
+```

docs/integrations/transformers.md

@@ -1,5 +1,5 @@
 ---
-title: HuggingFace Transformers
+title: Transformers
 ---
 
 HuggingFace's [Transformers](https://huggingface.co/docs/transformers/index) is a popular deep learning framework. You can 

sidebars.js

@@ -71,7 +71,10 @@ module.exports = {
         {'CLI Tools': ['apps/clearml_task', 'apps/clearml_param_search']},
         {'Integrations': [
                 'integrations/autokeras',
-                'integrations/catboost', 'integrations/click', 'integrations/fastai', 'integrations/transformers',
+                'integrations/catboost',
+                'integrations/click',
+                'integrations/fastai',
+                {"HuggingFace": ['integrations/transformers', 'integrations/accelerate']},
                 'integrations/hydra', 'integrations/jsonargparse',
                 'integrations/keras', 'integrations/keras_tuner',
                 'integrations/lightgbm', 'integrations/matplotlib',