Add abseil example (#157)

docs/guides/frameworks/pytorch/pytorch_abseil.md

@@ -0,0 +1,71 @@
+---
+title: PyTorch Abseil
+---
+
+The [pytorch_abseil.py](https://github.com/allegroai/clearml/blob/master/examples/frameworks/pytorch/pytorch_abseil.py) 
+example demonstrates the integration of ClearML into code that uses PyTorch and [`absl.flags`](https://abseil.io/docs/python/guides/flags). 
+
+The example script does the following:
+* Trains a simple deep neural network on the PyTorch built-in [MNIST](https://pytorch.org/vision/stable/datasets.html#mnist)
+  dataset
+* Creates an experiment named `pytorch mnist train with abseil`, which is associated with the `examples` project
+* ClearML automatically logs the absl.flags, and the models (and their snapshots) created by PyTorch 
+* Additional metrics are logged by calling the [Logger.report_scalar](../../../references/sdk/logger.md#report_scalar) 
+  method
+  
+## Scalars
+
+In the example script's `train` function, the following code explicitly reports scalars to **ClearML**:
+
+```python
+Logger.current_logger().report_scalar(
+    "train", 
+    "loss", 
+    iteration=(epoch * len(train_loader) + batch_idx), 
+    value=loss.item()
+)
+```
+
+In the `test` method, the code explicitly reports `loss` and `accuracy` scalars.
+
+```python
+Logger.current_logger().report_scalar(
+    "test", "loss", iteration=epoch, value=test_loss
+)
+Logger.current_logger().report_scalar(
+    "test", 
+    "accuracy", 
+    iteration=epoch, 
+    value=(correct / len(test_loader.dataset))
+)
+```    
+
+These scalars can be visualized in plots, which appear in the [ClearML web UI](../../../webapp/webapp_overview.md), in 
+the experiment's page **>** **RESULTS** **>** **SCALARS**. 
+
+![image](../../../img/examples_pytorch_mnist_07.png)
+
+## Hyperparameters
+
+ClearML automatically logs command line options defined with abseil flags. They appear in **CONFIGURATIONS** **>** 
+**HYPER PARAMETERS** **>** **TF_DEFINE**.
+
+![image](../../../img/examples_pytorch_abseil_params.png)
+
+## Console
+
+Text printed to the console for training progress, as well as all other console output, appear in **RESULTS** **>** **CONSOLE**.
+
+![image](../../../img/examples_pytorch_mnist_06.png)
+
+## Artifacts
+
+Models created by the experiment appear in the experiment's **ARTIFACTS** tab. ClearML automatically logs and tracks 
+models and any snapshots created using PyTorch.  
+
+![image](../../../img/examples_pytorch_abseil_models.png)
+
+Clicking on the model name takes you to the [model's page](../../../webapp/webapp_model_viewing.md), where you can view 
+the model's details and access the model.
+
+![image](../../../img/examples_pytorch_abseil_models_2.png)

sidebars.js

@@ -77,9 +77,10 @@ module.exports = {
                 'guides/frameworks/matplotlib/matplotlib_example',
                 'guides/frameworks/megengine/megengine_mnist',
                 {'PyTorch':
-                        ['guides/frameworks/pytorch/pytorch_distributed_example', 'guides/frameworks/pytorch/pytorch_matplotlib',
+                        [
-                        'guides/frameworks/pytorch/pytorch_mnist', 'guides/frameworks/pytorch/pytorch_tensorboard', 'guides/frameworks/pytorch/pytorch_tensorboardx',
+                            'guides/frameworks/pytorch/pytorch_distributed_example', 'guides/frameworks/pytorch/pytorch_matplotlib',
-                        'guides/frameworks/pytorch/tensorboard_toy_pytorch',
+                            'guides/frameworks/pytorch/pytorch_mnist', 'guides/frameworks/pytorch/pytorch_tensorboard','guides/frameworks/pytorch/tensorboard_toy_pytorch',
+                            'guides/frameworks/pytorch/pytorch_tensorboardx', 'guides/frameworks/pytorch/pytorch_abseil',
                             {'PyTorch Notebooks': [
                                 {'Audio': ['guides/frameworks/pytorch/notebooks/audio/audio_classification_UrbanSound8K', 'guides/frameworks/pytorch/notebooks/audio/audio_preprocessing_example']},
                                 {'Image': ['guides/frameworks/pytorch/notebooks/image/hyperparameter_search', 'guides/frameworks/pytorch/notebooks/image/image_classification_CIFAR10']},