[wip] FAQ

catalyst/callbacks/early_stop.py

@@ -7,7 +7,44 @@
 
 
 class CheckRunCallback(Callback):
-    """Executes only a pipeline part from the ``Experiment``."""
+    """Executes only a pipeline part from the ``Experiment``.
+
+    Minimal working example (Notebook API):
+
+    .. code-block:: python
+
+        import torch
+        from torch.utils.data import DataLoader, TensorDataset
+        from catalyst import dl
+
+        # data
+        num_samples, num_features = int(1e4), int(1e1)
+        X, y = torch.rand(num_samples, num_features), torch.rand(num_samples)
+        dataset = TensorDataset(X, y)
+        loader = DataLoader(dataset, batch_size=32, num_workers=1)
+        loaders = {"train": loader, "valid": loader}
+
+        # model, criterion, optimizer, scheduler
+        model = torch.nn.Linear(num_features, 1)
+        criterion = torch.nn.MSELoss()
+        optimizer = torch.optim.Adam(model.parameters())
+        scheduler = torch.optim.lr_scheduler.MultiStepLR(optimizer, [3, 6])
+
+        # model training
+        runner = dl.SupervisedRunner()
+        runner.train(
+            model=model,
+            criterion=criterion,
+            optimizer=optimizer,
+            scheduler=scheduler,
+            loaders=loaders,
+            logdir="./logdir",
+            num_epochs=8,
+            verbose=True,
+            callbacks=[dl.CheckRunCallback(num_batch_steps=3, num_epoch_steps=3)]
+        )
+
+    """
 
     def __init__(self, num_batch_steps: int = 3, num_epoch_steps: int = 2):
         """
@@ -41,24 +78,40 @@ def on_batch_end(self, runner: "IRunner"):
 class EarlyStoppingCallback(Callback):
     """Early exit based on metric.
 
-    Example of usage in notebook API:
+    Minimal working example (Notebook API):
 
     .. code-block:: python
 
-        runner = SupervisedRunner()
+        import torch
+        from torch.utils.data import DataLoader, TensorDataset
+        from catalyst import dl
+
+        # data
+        num_samples, num_features = int(1e4), int(1e1)
+        X, y = torch.rand(num_samples, num_features), torch.rand(num_samples)
+        dataset = TensorDataset(X, y)
+        loader = DataLoader(dataset, batch_size=32, num_workers=1)
+        loaders = {"train": loader, "valid": loader}
+
+        # model, criterion, optimizer, scheduler
+        model = torch.nn.Linear(num_features, 1)
+        criterion = torch.nn.MSELoss()
+        optimizer = torch.optim.Adam(model.parameters())
+        scheduler = torch.optim.lr_scheduler.MultiStepLR(optimizer, [3, 6])
+
+        # model training
+        runner = dl.SupervisedRunner()
         runner.train(
-            ...
-            callbacks=[
-                ...
-                EarlyStoppingCallback(
-                    patience=5,
-                    metric="my_metric",
-                    minimize=True,
-                )
-                ...
-            ]
+            model=model,
+            criterion=criterion,
+            optimizer=optimizer,
+            scheduler=scheduler,
+            loaders=loaders,
+            logdir="./logdir",
+            num_epochs=8,
+            verbose=True,
+            callbacks=[dl.EarlyStoppingCallback(patience=2, metric="loss", minimize=True)]
         )
-        ...
 
     Example of usage in config API:
 

docs/core/callback.rst

@@ -0,0 +1,3 @@
+Callback
+==============================================================================
+

docs/core/experiment.rst

@@ -0,0 +1,29 @@
+Experiment
+==============================================================================
+
+Experiment - an abstraction that contains information about the experiment
+- a model, a criterion, an optimizer, a scheduler, and their hyperparameters.
+It also has information about the data and transformations used.
+The Experiment knows **what** you would like to run.
+
+Each deep learning project has several main components.
+These primitives define what we want to use during the experiment:
+
+- the data
+- the model(s)
+- the optimizer(s)
+- the loss(es)
+- and the scheduler(s) if we need them.
+
+That are the abstractions that Experiment covers in Catalyst,
+with a few modifications for easier experiment monitoring
+and hyperparameters logging. For each stage of our experiment,
+the Experiment provides interfaces to all primitives above + the callbacks.
+
+.. image:: https://raw.githubusercontent.com/catalyst-team/catalyst-pics/master/third_party_pics/catalyst102-experiment.png
+    :alt: Experiment
+
+
+---
+
+- what is the difference between different Experiments?

docs/core/runner.rst

@@ -0,0 +1,6 @@
+Runner
+==============================================================================
+
+---
+
+- what is the difference between different Runners?

docs/faq/amp.rst

@@ -0,0 +1,9 @@
+Mixed precision training
+==============================================================================
+
+- How to use Nvidia Apex?
+- How to use torch.amp?
+
+If you haven't found the answer for your question, feel free to `join our slack`_ for the discussion.
+
+.. _`join our slack`: https://join.slack.com/t/catalyst-team-core/shared_invite/zt-d9miirnn-z86oKDzFMKlMG4fgFdZafw

docs/faq/checkpointing.rst

@@ -0,0 +1,12 @@
+Model checkpointing
+==============================================================================
+
+- how to load bset model?
+    - notebook and config api
+- how to save model?
+- how to load model?
+- whats the difference between checkpoint and checkpoint_full?
+
+If you haven't found the answer for your question, feel free to `join our slack`_ for the discussion.
+
+.. _`join our slack`: https://join.slack.com/t/catalyst-team-core/shared_invite/zt-d9miirnn-z86oKDzFMKlMG4fgFdZafw

docs/contributing/codestyle.rst → docs/faq/config_api.rst

@@ -1,4 +1,4 @@
-Codestyle
+[WIP] Config API
 ==============================================================================
 
 Hi,
@@ -11,4 +11,8 @@ But don't feel upset, check out the kitty... `Kittylyst`_ tutorial.
 
 .. image:: https://raw.githubusercontent.com/Scitator/kittylyst/master/assets/kitty.jpg
     :target: https://github.com/Scitator/kittylyst
-    :alt: kitty
+    :alt: kitty
+
+If you haven't found the answer for your question, feel free to `join our slack`_ for the discussion.
+
+.. _`join our slack`: https://join.slack.com/t/catalyst-team-core/shared_invite/zt-d9miirnn-z86oKDzFMKlMG4fgFdZafw