Merge branch 'master' into model_size_bytes

.drone.jsonnet

@@ -0,0 +1,63 @@
+/*
+Copyright The PyTorch Lightning team.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+*/
+
+// https://github.com/drone/drone-jsonnet-config/blob/master/.drone.jsonnet
+
+local pipeline(name, image) = {
+  kind: "pipeline",
+  type: "docker",
+  name: name,
+  steps: [
+    {
+      name: "testing",
+      image: image,
+      environment: {
+        "CODECOV_TOKEN": {
+          from_secret: "codecov_token"
+        },
+        "MKL_THREADING_LAYER": "GNU",
+      },
+      commands: [
+        "python --version",
+        "pip --version",
+        "nvidia-smi",
+        "pip install -r ./requirements/devel.txt --upgrade-strategy only-if-needed -v --no-cache-dir",
+        "pip list",
+        "coverage run --source pytorch_lightning -m pytest pytorch_lightning tests -v -ra --color=yes --durations=25",
+        "python -m pytest benchmarks pl_examples -v -ra --color=yes --maxfail=2 --durations=0",
+        "coverage report",
+        "codecov --token $CODECOV_TOKEN --flags=gpu,pytest --name='GPU-coverage' --env=linux --build $DRONE_BUILD_NUMBER --commit $DRONE_COMMIT",
+        "python tests/collect_env_details.py"
+      ],
+    },
+  ],
+  trigger: {
+    branch: [
+      "master",
+      "release/*"
+    ],
+    event: [
+      "push",
+      "pull_request"
+    ]
+  },
+  depends_on: if name == "torch-GPU-nightly" then ["torch-GPU"]
+};
+
+[
+    pipeline("torch-GPU", "pytorchlightning/pytorch_lightning:base-cuda-py3.7-torch1.6"),
+    pipeline("torch-GPU-nightly", "pytorchlightning/pytorch_lightning:base-cuda-py3.7-torch1.7"),
+]

.github/CODEOWNERS

@@ -5,23 +5,48 @@
 # the repo. Unless a later match takes precedence,
 # @global-owner1 and @global-owner2 will be requested for
 # review when someone opens a pull request.
-* @williamfalcon @borda @teddykoker @awaelchli @nateraw @justusschock @tchaton @SeanNaren @ananyahjha93
+* @williamfalcon @borda @tchaton @SeanNaren @awaelchli @justusschock
 
 # Metrics
-/pytorch_lightning/metrics/*  @teddykoker @ananyahjha93 @justusschock
-/tests/metrics/*              @teddykoker @ananyahjha93 @justusschock
+/pytorch_lightning/metrics/   @teddykoker @ananyahjha93 @justusschock
+/tests/metrics/               @teddykoker @ananyahjha93 @justusschock
 /docs/source/metrics.rst      @teddykoker @ananyahjha93 @justusschock
 
 # API
-/pytorch_lightning/callbacks/base.py  @williamfalcon
-/pytorch_lightning/core/datamodule.py @williamfalcon
-/pytorch_lightning/trainer/trainer.py @williamfalcon
-/pytorch_lightning/core/hooks.py     @williamfalcon
-/pytorch_lightning/core/lightning.py  @williamfalcon
+/pytorch_lightning/callbacks/base.py           @williamfalcon
+/pytorch_lightning/core/datamodule.py          @williamfalcon
+/pytorch_lightning/trainer/trainer.py          @williamfalcon @tchaton
+/pytorch_lightning/core/hooks.py               @williamfalcon
+/pytorch_lightning/core/lightning.py           @williamfalcon @tchaton
+/pytorch_lightning/core/optimizer.py           @tchaton
+/pytorch_lightning/trainer/training_loop.py    @tchaton @SeanNaren
+/pytorch_lightning/trainer/evaluation_loop.py  @tchaton @SeanNaren
 
+# Connectors
+/pytorch_lightning/trainer/connectors/         @tchaton @SeanNaren
 
 # accelerators
-/pytorch_lightning/accelerators/*  @williamfalcon
+/pytorch_lightning/accelerators/               @williamfalcon @tchaton @SeanNaren @awaelchli @justusschock
 
 # owners
-/pytorch_lightning/.github/CODEOWNERS @williamfalcon
+/.github/CODEOWNERS   @williamfalcon
+# main
+/README.md            @williamfalcon @edenlightning
+# installation
+/setup.py             @borda @williamfalcon
+
+# CI/CD
+/.github/workflows/   @borda @tchaton
+/.github/*.py         @borda @tchaton
+/dockers/             @borda @tchaton
+# configs in root
+/*.yml                @borda @tchaton
+
+# Docs
+/docs/                          @edenlightning @tchaton @borda @awaelchli
+/.github/*.md                   @edenlightning @williamfalcon @borda
+/.github/ISSUE_TEMPLATE/*.md    @edenlightning @borda @tchaton
+/docs/source/conf.py            @borda @awaelchli
+
+# Testing
+/tests/base/boring_model.py @williamfalcon

CHANGELOG.md

@@ -4,8 +4,14 @@ All notable changes to this project will be documented in this file.
 
 The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
+## Unreleased
 
-## [1.1.0rc1] - 2020-12-02
+### Fixed
+
+- Fixed `LoggerConnector` to have logged metrics on root device in DP ([#4138](https://github.com/PyTorchLightning/pytorch-lightning/pull/4138))
+
+
+## [1.1.0rc] - 2020-12-02
 
 ### Added
 
@@ -50,6 +56,9 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Added optimizer refactors ([#4658](https://github.com/PyTorchLightning/pytorch-lightning/pull/4658))
 
 
+- Added `PrecisionRecallCurve, ROC, AveragePrecision` class metric ([#4549](https://github.com/PyTorchLightning/pytorch-lightning/pull/4549))
+
+
 - Added custom `Apex` and `NativeAMP` as `Precision plugins` ([#4355](https://github.com/PyTorchLightning/pytorch-lightning/pull/4355))
 
 
@@ -72,9 +81,14 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 ### Changed
 
+- Removed `multiclass_roc` and `multiclass_precision_recall_curve`, use `roc` and `precision_recall_curve` instead ([#4549](https://github.com/PyTorchLightning/pytorch-lightning/pull/4549))
+
+
+
 - Tuner algorithms will be skipped if `fast_dev_run=True` ([#3903](https://github.com/PyTorchLightning/pytorch-lightning/pull/3903))
 
 
+
 - WandbLogger does not force wandb `reinit` arg to True anymore and creates a run only when needed ([#4648](https://github.com/PyTorchLightning/pytorch-lightning/pull/4648))
 
 
@@ -89,6 +103,12 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Deprecated `prefix` argument in `ModelCheckpoint` ([#4765](https://github.com/PyTorchLightning/pytorch-lightning/pull/4765))
 
 
+- Deprecated the old way of assigning hyper-parameters through `self.hparams = ...` ([#4813](https://github.com/PyTorchLightning/pytorch-lightning/pull/4813))
+
+
+- Deprecated `mode='auto'` from `ModelCheckpoint` and `EarlyStopping` ([#4695](https://github.com/PyTorchLightning/pytorch-lightning/pull/4695))
+
+
 ### Removed
 
 
@@ -97,6 +117,10 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 - Added feature to move tensors to CPU before saving ([#4309](https://github.com/PyTorchLightning/pytorch-lightning/pull/4309))
 
+- Fixed `LoggerConnector` to have logged metrics on root device in DP ([#4138](https://github.com/PyTorchLightning/pytorch-lightning/pull/4138))
+
+
+- Auto convert tensors to contiguous format when `gather_all` ([#4907](https://github.com/PyTorchLightning/pytorch-lightning/pull/4907))
 
 
 ## [1.0.8] - 2020-11-24

MANIFEST.in

@@ -54,6 +54,7 @@ include pyproject.toml
 # Exclude build configs
 exclude *.yml
 exclude *.yaml
+exclude *.jsonnet
 
 # Exclude pyright config
 exclude .pyrightconfig.json

docs/source/hyperparameters.rst

@@ -167,8 +167,8 @@ improve readability and reproducibility.
             def train_dataloader(self):
                 return DataLoader(mnist_train, batch_size=self.hparams.batch_size)
 
-    .. warning:: Deprecated. This method of assigning hyperparameters to the LightningModule is no longer
-        recommended and will not be supported in future versions of Lightning.
+    .. warning:: Deprecated since v1.1.0. This method of assigning hyperparameters to the LightningModule
+        will no longer be supported from v1.3.0. Use the ``self.save_hyperparameters()`` method from above instead.
 
 
 4.  You can also save full objects such as `dict` or `Namespace` to the checkpoint.

docs/source/logging.rst

@@ -6,7 +6,7 @@
 
 .. role:: hidden
     :class: hidden-section
-    
+
 .. _logging:
 
 
@@ -57,9 +57,11 @@ Logging from a LightningModule
 
 Lightning offers automatic log functionalities for logging scalars, or manual logging for anything else.
 
-Automatic logging
+Automatic Logging
 =================
-Use the :func:`~~pytorch_lightning.core.lightning.LightningModule.log` method to log from anywhere in a :ref:`lightning_module`.
+Use the :func:`~~pytorch_lightning.core.lightning.LightningModule.log`
+method to log from anywhere in a :ref:`lightning_module` and :ref:`callbacks`
+except functions with `batch_start` in their names.
 
 .. code-block:: python
 
@@ -95,6 +97,9 @@ The :func:`~~pytorch_lightning.core.lightning.LightningModule.log` method has a
         argument of :class:`~pytorch_lightning.callbacks.model_checkpoint.ModelCheckpoint` or in the graphs plotted to the logger of your choice.
 
 
+If your work requires to log in an unsupported function, please open an issue with a clear description of why it is blocking you.
+
+
 Manual logging
 ==============
 If you want to log anything that is not a scalar, like histograms, text, images, etc... you may need to use the logger object directly.
@@ -144,8 +149,8 @@ Use the :func:`~pytorch_lightning.loggers.base.rank_zero_experiment` and :func:`
         def experiment(self):
             # Return the experiment object associated with this logger.
             pass
-         
-        @property 
+
+        @property
         def version(self):
             # Return the experiment version, int or str.
             return '0.1'
@@ -238,7 +243,7 @@ if you are using a logger. These defaults can be customized by overriding the
 :func:`~pytorch_lightning.core.lightning.LightningModule.get_progress_bar_dict` hook in your module.
 
 .. code-block:: python
-    
+
     def get_progress_bar_dict(self):
         # don't show the version number
         items = super().get_progress_bar_dict()

docs/source/metrics.rst

@@ -239,6 +239,24 @@ ConfusionMatrix
 .. autoclass:: pytorch_lightning.metrics.classification.ConfusionMatrix
     :noindex:
 
+PrecisionRecallCurve
+~~~~~~~~~~~~~~~~~~~~
+
+.. autoclass:: pytorch_lightning.metrics.classification.PrecisionRecallCurve
+    :noindex:
+
+AveragePrecision
+~~~~~~~~~~~~~~~~
+
+.. autoclass:: pytorch_lightning.metrics.classification.AveragePrecision
+    :noindex:
+
+ROC
+~~~
+
+.. autoclass:: pytorch_lightning.metrics.classification.ROC
+    :noindex:
+
 Regression Metrics
 ------------------
 
@@ -326,7 +344,7 @@ multiclass_auroc [func]
 average_precision [func]
 ~~~~~~~~~~~~~~~~~~~~~~~~
 
-.. autofunction:: pytorch_lightning.metrics.functional.classification.average_precision
+.. autofunction:: pytorch_lightning.metrics.functional.average_precision
     :noindex:
 
 
@@ -365,10 +383,10 @@ iou [func]
     :noindex:
 
 
-multiclass_roc [func]
+roc [func]
 ~~~~~~~~~~~~~~~~~~~~~
 
-.. autofunction:: pytorch_lightning.metrics.functional.classification.multiclass_roc
+.. autofunction:: pytorch_lightning.metrics.functional.roc
     :noindex:
 
 
@@ -389,7 +407,7 @@ precision_recall [func]
 precision_recall_curve [func]
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
-.. autofunction:: pytorch_lightning.metrics.functional.classification.precision_recall_curve
+.. autofunction:: pytorch_lightning.metrics.functional.precision_recall_curve
     :noindex:
 
 
@@ -400,13 +418,6 @@ recall [func]
     :noindex:
 
 
-roc [func]
-~~~~~~~~~~
-
-.. autofunction:: pytorch_lightning.metrics.functional.classification.roc
-    :noindex:
-
-
 stat_scores [func]
 ~~~~~~~~~~~~~~~~~~
 
@@ -424,14 +435,14 @@ stat_scores_multiple_classes [func]
 to_categorical [func]
 ~~~~~~~~~~~~~~~~~~~~~
 
-.. autofunction:: pytorch_lightning.metrics.functional.classification.to_categorical
+.. autofunction:: pytorch_lightning.metrics.utils.to_categorical
     :noindex:
 
 
 to_onehot [func]
 ~~~~~~~~~~~~~~~~
 
-.. autofunction:: pytorch_lightning.metrics.functional.classification.to_onehot
+.. autofunction:: pytorch_lightning.metrics.utils.to_onehot
     :noindex: