Docs improvements (#1403)

* quickstart + core

* +

* +

* +

* docs

Author: Scitator

CHANGELOG.md

@@ -23,6 +23,44 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 -
 
 
+## [22.02] - 2022-02-13
+
+### Tl;dr
+- Catalyst architecture simplification.
+- [#1395](https://github.com/catalyst-team/catalyst/issues/1395), [#1396](https://github.com/catalyst-team/catalyst/issues/1396), [#1397](https://github.com/catalyst-team/catalyst/issues/1397), [#1398](https://github.com/catalyst-team/catalyst/issues/1398), [#1399](https://github.com/catalyst-team/catalyst/issues/1399), [#1400](https://github.com/catalyst-team/catalyst/issues/1400), [#1401](https://github.com/catalyst-team/catalyst/issues/1401), [#1402](https://github.com/catalyst-team/catalyst/issues/1402), [#1403](https://github.com/catalyst-team/catalyst/issues/1403).
+
+### Added
+
+- Additional tests for different hardware accelerators setups. Please check out the `tests/pipelines` folder for more information.
+- `BackwardCallback` and `BackwardCallbackOrder` as an abstraction on top of `loss.backward`. Now you could easily log model gradients or transform them before `OptimizerCallback`.
+- `CheckpointCallbackOrder` for `ICheckpointCallback`.
+
+### Changed
+
+- Minimal python version moved to `3.7`, minimal pytorch version moved to `1.4.0`.
+- Engines rewritten on top of Accelerate. First, we found these two abstractions very close to each other. Second, Accelerate provides additional user-friendly API and more stable API for "Nvidia APEX" and "Facebook Fairscale" - it does not support them.
+- SelfSupervisedRunner moved to the `examples` folder from the Catalyst API. The only Runners API, that will be supported in the future: `IRunner`, `Runner`, `ISupervisedRunner`, `SupervisedRunner` due to their consistency. If you are interested in any other Runner API - feel free to write your own `CustomRunner` and use `SelfSupervisedRunner` as an example.
+- `Runner.{global/stage}_{batch/loader/epoch}_metrics` renamed to `Runner.{batch/loader/epoch}_metrics`
+- `CheckpointCallback` rewritten from scratch.
+- Catalyst registry moved to full-imports-paths only.
+- Logger API changed to receive `IRunner` for all `log_*` methods.
+- Metric API: `topk_args` renamed to `topk`
+- Contrib API: init imports from `catalyst.contrib` - removed, use `from catalyst.contrib.{smth} import {smth}`. Could be change to full-imports-only in future versions for stability.
+- All quickstarts, minimal examples, notebooks and pipelines moved to new version.
+- Codestyle moved to `89` right margin. Honestly speaking, it's much easier to maintain Catalyst with `89` right margin on MBP'16.
+
+### Removed
+
+- `ITrial` removed.
+- Stages support removed. While we embrace stages in deep learning experiments, current hardware accelerators are not prepared well for such setups. Additionally, ~95% of dl pipelines are single-stage. Multi-stage runner support is under review. For multi-stage support, please define a `CustomRunner` with rewritten API.
+- Config/Hydra API support removed. Config API is under review. For now, you could write your own Config API with [hydra-slayer](https://github.com/catalyst-team/hydra-slayer) if needed.
+- `catalyst-dl` scripts removed. Without Config API we don't need them anymore.
+- `Nvidia Apex`, `Fairscale`, `Albumentations`, `Nifti`, `Hydra` requiremets removed.
+- `OnnxCallback`, `PruningCallback`, `QuantizationCallback`, `TracingCallback` removed from callbacks API. Theese callbacks are under review now.
+
+If you have any questions on the Catalyst 22 edition updates, please join Catalyst slack for discussion.
+
+
 ## [21.12] - 2021-12-28
 
 ### Added

README.md

@@ -75,12 +75,9 @@ from catalyst.contrib.datasets import MNIST
 model = nn.Sequential(nn.Flatten(), nn.Linear(28 * 28, 10))
 criterion = nn.CrossEntropyLoss()
 optimizer = optim.Adam(model.parameters(), lr=0.02)
-
-train_data = MNIST(os.getcwd(), train=True)
-valid_data = MNIST(os.getcwd(), train=False)
 loaders = {
-    "train": DataLoader(train_data, batch_size=32),
-    "valid": DataLoader(valid_data, batch_size=32),
+    "train": DataLoader(MNIST(os.getcwd(), train=True), batch_size=32),
+    "valid": DataLoader(MNIST(os.getcwd(), train=False), batch_size=32),
 }
 
 runner = dl.SupervisedRunner(
@@ -110,21 +107,18 @@ metrics = runner.evaluate_loader(
     loader=loaders["valid"],
     callbacks=[dl.AccuracyCallback(input_key="logits", target_key="targets", topk=(1, 3, 5))],
 )
-assert "accuracy01" in metrics.keys()
 
 # model inference
 for prediction in runner.predict_loader(loader=loaders["valid"]):
     assert prediction["logits"].detach().cpu().numpy().shape[-1] == 10
 
-features_batch = next(iter(loaders["valid"]))[0]
-# model tracing
-utils.trace_model(model=runner.model.cpu(), batch=features_batch)
-# model quantization
-utils.quantize_model(model=runner.model)
-# model pruning
-utils.prune_model(model=runner.model, pruning_fn="l1_unstructured", amount=0.8)
-# onnx export
-utils.onnx_export(model=runner.model.cpu(), batch=features_batch, file="./logs/mnist.onnx", verbose=True)
+# model post-processing
+model = runner.model.cpu()
+batch = next(iter(loaders["valid"]))[0]
+utils.trace_model(model=model, batch=batch)
+utils.quantize_model(model=model)
+utils.prune_model(model=model, pruning_fn="l1_unstructured", amount=0.8)
+utils.onnx_export(model=model, batch=batch, file="./logs/mnist.onnx", verbose=True)
 ```
 
 ### Step-by-step Guide
@@ -188,6 +182,7 @@ Tested on Ubuntu 16.04/18.04/20.04, macOS 10.15, Windows 10, and Windows Subsyst
 
 ### Documentation
 - [master](https://catalyst-team.github.io/catalyst/)
+- [22.02](https://catalyst-team.github.io/catalyst/v22.02/index.html)
 
 - <details>
   <summary>2021 edition</summary>

catalyst/__version__.py

@@ -1 +1 @@
-__version__ = "22.02rc0"
+__version__ = "22.02"

catalyst/callbacks/backward.py

@@ -20,7 +20,7 @@ class BackwardCallback(IBackwardCallback):
     .. note::
         Please follow the `minimal examples`_ sections for more use cases.
 
-        .. _`minimal examples`: http://github.com/catalyst-team/catalyst#minimal-examples  # noqa: E501, W505
+        .. _`minimal examples`: https://github.com/catalyst-team/catalyst#minimal-examples  # noqa: E501, W505
     """
 
     def __init__(

catalyst/callbacks/criterion.py

@@ -17,7 +17,7 @@ class CriterionCallback(FunctionalMetricCallback, ICriterionCallback):
     .. note::
         Please follow the `minimal examples`_ sections for more use cases.
 
-        .. _`minimal examples`: http://github.com/catalyst-team/catalyst#minimal-examples  # noqa: E501, W505
+        .. _`minimal examples`: https://github.com/catalyst-team/catalyst#minimal-examples  # noqa: E501, W505
     """
 
     def __init__(

catalyst/callbacks/metrics/accuracy.py

@@ -88,7 +88,7 @@ class AccuracyCallback(BatchMetricCallback):
     .. note::
         Please follow the `minimal examples`_ sections for more use cases.
 
-        .. _`minimal examples`: http://github.com/catalyst-team/catalyst#minimal-examples  # noqa: E501, W505
+        .. _`minimal examples`: https://github.com/catalyst-team/catalyst#minimal-examples  # noqa: E501, W505
     """
 
     def __init__(
@@ -180,7 +180,7 @@ class MultilabelAccuracyCallback(BatchMetricCallback):
     .. note::
         Please follow the `minimal examples`_ sections for more use cases.
 
-        .. _`minimal examples`: http://github.com/catalyst-team/catalyst#minimal-examples  # noqa: E501, W505
+        .. _`minimal examples`: https://github.com/catalyst-team/catalyst#minimal-examples  # noqa: E501, W505
     """
 
     def __init__(

catalyst/callbacks/metrics/auc.py

@@ -76,7 +76,7 @@ class AUCCallback(LoaderMetricCallback):
     .. note::
         Please follow the `minimal examples`_ sections for more use cases.
 
-        .. _`minimal examples`: http://github.com/catalyst-team/catalyst#minimal-examples  # noqa: E501, W505
+        .. _`minimal examples`: https://github.com/catalyst-team/catalyst#minimal-examples  # noqa: E501, W505
     """
 
     def __init__(

catalyst/callbacks/metrics/classification.py

@@ -80,7 +80,7 @@ class PrecisionRecallF1SupportCallback(BatchMetricCallback):
     .. note::
         Please follow the `minimal examples`_ sections for more use cases.
 
-        .. _`minimal examples`: http://github.com/catalyst-team/catalyst#minimal-examples  # noqa: E501, W505
+        .. _`minimal examples`: https://github.com/catalyst-team/catalyst#minimal-examples  # noqa: E501, W505
     """
 
     def __init__(
@@ -187,7 +187,7 @@ class MultilabelPrecisionRecallF1SupportCallback(BatchMetricCallback):
     .. note::
         Please follow the `minimal examples`_ sections for more use cases.
 
-        .. _`minimal examples`: http://github.com/catalyst-team/catalyst#minimal-examples  # noqa: E501, W505
+        .. _`minimal examples`: https://github.com/catalyst-team/catalyst#minimal-examples  # noqa: E501, W505
     """
 
     def __init__(

catalyst/callbacks/metrics/cmc_score.py

@@ -145,7 +145,7 @@ def handle_batch(self, batch) -> None:
     .. note::
         Please follow the `minimal examples`_ sections for more use cases.
 
-        .. _`minimal examples`: http://github.com/catalyst-team/catalyst#minimal-examples  # noqa: E501, W505
+        .. _`minimal examples`: https://github.com/catalyst-team/catalyst#minimal-examples  # noqa: E501, W505
     """
 
     def __init__(

catalyst/callbacks/metrics/confusion_matrix.py

@@ -89,7 +89,7 @@ class ConfusionMatrixCallback(Callback):
     .. note::
         Please follow the `minimal examples`_ sections for more use cases.
 
-        .. _`minimal examples`: http://github.com/catalyst-team/catalyst#minimal-examples  # noqa: E501, W505
+        .. _`minimal examples`: https://github.com/catalyst-team/catalyst#minimal-examples  # noqa: E501, W505
     """
 
     def __init__(