anthonytec2 · anthonytec2 · Jun 18, 2020 · Jun 18, 2020 · Jun 18, 2020 · Jun 18, 2020
diff --git a/.github/PULL_REQUEST_TEMPLATE.md b/.github/PULL_REQUEST_TEMPLATE.md
@@ -1,16 +1,24 @@
+
+## What does this PR do?
+
+<!--
+Please include a summary of the change and which issue is fixed. Please also include relevant motivation and context. List any dependencies that are required for this change.
+-->
+
+Fixes # (issue)
+
 # Before submitting
 
 - [ ] Was this discussed/approved via a Github issue? (no need for typos and docs improvements)
 - [ ] Did you read the [contributor guideline](https://github.com/PyTorchLightning/pytorch-lightning/blob/master/.github/CONTRIBUTING.md), Pull Request section?
-- [ ] Did you make sure to update the docs?   
-- [ ] Did you write any new necessary tests?  
+- [ ] Did you make sure your PR does only one thing, instead of bundling different changes together? Otherwise, we ask you create a separate PR for every change.
+- [ ] Did you make sure to update the documentation with your changes?
+- [ ] Did you write any new necessary tests? 
+- [ ] Did you verify new and existing tests pass locally with your changes?
 - [ ] If you made a notable change (that affects users), did you update the [CHANGELOG](https://github.com/PyTorchLightning/pytorch-lightning/blob/master/CHANGELOG.md)?
 
 <!-- For CHANGELOG separate each item in unreleased section by a blank line to reduce collisions -->
 
-## What does this PR do?
-Fixes # (issue).
-
 ## PR review    
 Anyone in the community is free to review the PR once the tests have passed.     
 If we didn't discuss your PR in Github issues there's a high chance it will not be merged.

diff --git a/CHANGELOG.md b/CHANGELOG.md
@@ -10,22 +10,45 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 ### Changed
 
+- Changed epoch indexing from 0 instead of 1 ([#2289](https://github.com/PyTorchLightning/pytorch-lightning/pull/2289))
+
 ### Deprecated
 
 ### Removed
 
 ### Fixed
 
+- Fixed parsing TPU arguments and TPU tests ([#2094](https://github.com/PyTorchLightning/pytorch-lightning/pull/2094))
+
+- Fixed number batches in case of multiple dataloaders and `limit_{*}_batches` ([#1920](https://github.com/PyTorchLightning/pytorch-lightning/pull/1920), [#2226](https://github.com/PyTorchLightning/pytorch-lightning/pull/2226))
+
+- Fixed an issue with forward hooks not being removed after model summary ([#2298](https://github.com/PyTorchLightning/pytorch-lightning/pull/2298))
+
+- Fixed ROC metric for CUDA tensors ([#2304](https://github.com/PyTorchLightning/pytorch-lightning/pull/2304))
+
+- Fixed `average_precision` metric ([#2319](https://github.com/PyTorchLightning/pytorch-lightning/pull/2319))
+
+- Fixed lost compatibility with custom datatypes implementing `.to` ([#2335](https://github.com/PyTorchLightning/pytorch-lightning/pull/2335))
 
-## [0.8.0] - 2020-06-DD
+## [0.8.1] - 2020-06-19
+
+### Fixed
+
+- Fixed the `load_from_checkpoint` path detected as URL bug ([#2244](https://github.com/PyTorchLightning/pytorch-lightning/pull/2244))
+- Fixed hooks - added barrier ([#2245](https://github.com/PyTorchLightning/pytorch-lightning/pull/2245), [#2257](https://github.com/PyTorchLightning/pytorch-lightning/pull/2257), [#2260](https://github.com/PyTorchLightning/pytorch-lightning/pull/220))
+- Fixed `hparams` - remove frame inspection on `self.hparams` ([#2253](https://github.com/PyTorchLightning/pytorch-lightning/pull/2253))
+- Fixed setup and on fit calls ([#2252](https://github.com/PyTorchLightning/pytorch-lightning/pull/2252))
+- Fixed GPU template ([#2255](https://github.com/PyTorchLightning/pytorch-lightning/pull/2255))
+
+## [0.8.0] - 2020-06-18
 
 ### Added
 
 - Added `overfit_batches`, `limit_{val|test}_batches` flags (overfit now uses training set for all three) ([#2213](https://github.com/PyTorchLightning/pytorch-lightning/pull/2213))
 - Added metrics 
   * Base classes ([#1326](https://github.com/PyTorchLightning/pytorch-lightning/pull/1326), [#1877](https://github.com/PyTorchLightning/pytorch-lightning/pull/1877))
   * Sklearn metrics classes ([#1327](https://github.com/PyTorchLightning/pytorch-lightning/pull/1327))
-  * Native torch metrics ([#1488](https://github.com/PyTorchLightning/pytorch-lightning/pull/1488))
+  * Native torch metrics ([#1488](https://github.com/PyTorchLightning/pytorch-lightning/pull/1488), [#2062](https://github.com/PyTorchLightning/pytorch-lightning/pull/2062))
   * docs for all Metrics ([#2184](https://github.com/PyTorchLightning/pytorch-lightning/pull/2184), [#2209](https://github.com/PyTorchLightning/pytorch-lightning/pull/2209))
   * Regression metrics ([#2221](https://github.com/PyTorchLightning/pytorch-lightning/pull/2221))
 - Added type hints in `Trainer.fit()` and `Trainer.test()` to reflect that also a list of dataloaders can be passed in ([#1723](https://github.com/PyTorchLightning/pytorch-lightning/pull/1723))
@@ -37,9 +60,11 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Added a model hook `transfer_batch_to_device` that enables moving custom data structures to the target device ([1756](https://github.com/PyTorchLightning/pytorch-lightning/pull/1756))
 - Added [black](https://black.readthedocs.io/en/stable/) formatter for the code with code-checker on pull ([1610](https://github.com/PyTorchLightning/pytorch-lightning/pull/1610))
 - Added back the slow spawn ddp implementation as `ddp_spawn` ([#2115](https://github.com/PyTorchLightning/pytorch-lightning/pull/2115))
-- Added loading checkpoints from URLs ([#1667](https://github.com/PyTorchLightning/pytorch-lightning/issues/1667))
+- Added loading checkpoints from URLs ([#1667](https://github.com/PyTorchLightning/pytorch-lightning/pull/1667))
 - Added a callback method `on_keyboard_interrupt` for handling KeyboardInterrupt events during training ([#2134](https://github.com/PyTorchLightning/pytorch-lightning/pull/2134))
 - Added a decorator `auto_move_data` that moves data to the correct device when using the LightningModule for inference ([#1905](https://github.com/PyTorchLightning/pytorch-lightning/pull/1905))
+- Added `ckpt_path` option to `LightningModule.test(...)` to load particular checkpoint ([#2190](https://github.com/PyTorchLightning/pytorch-lightning/pull/2190))
+- Added `setup` and `teardown` hooks for model ([#2229](https://github.com/PyTorchLightning/pytorch-lightning/pull/2229))
 
 ### Changed
 
@@ -50,18 +75,19 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Re-Enable Logger's `ImportError`s ([#1938](https://github.com/PyTorchLightning/pytorch-lightning/pull/1938))
 - Changed the default value of the Trainer argument `weights_summary` from `full` to `top` ([#2029](https://github.com/PyTorchLightning/pytorch-lightning/pull/2029))
 - Raise an error when lightning replaces an existing sampler ([#2020](https://github.com/PyTorchLightning/pytorch-lightning/pull/2020))
-- Enabled prepare_data from correct processes - clarify local vs global rank ([#2166](https://github.com/PyTorchLightning/pytorch-lightning/pull/2166))
+- Enabled `prepare_data` from correct processes - clarify local vs global rank ([#2166](https://github.com/PyTorchLightning/pytorch-lightning/pull/2166))
 - Remove explicit flush from tensorboard logger ([#2126](https://github.com/PyTorchLightning/pytorch-lightning/pull/2126))
-- Changed epoch/step indexing from 1 instead of 0 ([#2206](https://github.com/PyTorchLightning/pytorch-lightning/pull/2206))
+- Changed epoch indexing from 1 instead of 0 ([#2206](https://github.com/PyTorchLightning/pytorch-lightning/pull/2206))
 
 ### Deprecated
 
 - Deprecated flags: ([#2213](https://github.com/PyTorchLightning/pytorch-lightning/pull/2213))
-  * `overfit_pct` >> `overfit_batches`
-  * `val_percent_check` >> `limit_val_batches`
-  * `test_percent_check` >> `limit_test_batches`
+  * `overfit_pct` in favour of `overfit_batches`
+  * `val_percent_check` in favour of `limit_val_batches`
+  * `test_percent_check` in favour of `limit_test_batches`
 - Deprecated `ModelCheckpoint`'s attributes `best` and `kth_best_model` ([#1799](https://github.com/PyTorchLightning/pytorch-lightning/pull/1799))
 - Dropped official support/testing for older PyTorch versions <1.3 ([#1917](https://github.com/PyTorchLightning/pytorch-lightning/pull/1917))
+- Deprecated Trainer `proc_rank` in favour of `global_rank` ([#2166](https://github.com/PyTorchLightning/pytorch-lightning/pull/2166), [#2269](https://github.com/PyTorchLightning/pytorch-lightning/pull/2269))
 
 ### Removed
 
@@ -77,7 +103,7 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 - Run graceful training teardown on interpreter exit ([#1631](https://github.com/PyTorchLightning/pytorch-lightning/pull/1631))
 - Fixed user warning when apex was used together with learning rate schedulers ([#1873](https://github.com/PyTorchLightning/pytorch-lightning/pull/1873))
-- Fixed multiple calls of `EarlyStopping` callback ([#1751](https://github.com/PyTorchLightning/pytorch-lightning/issues/1751)) 
+- Fixed multiple calls of `EarlyStopping` callback ([#1863](https://github.com/PyTorchLightning/pytorch-lightning/pull/1863)) 
 - Fixed an issue with `Trainer.from_argparse_args` when passing in unknown Trainer args ([#1932](https://github.com/PyTorchLightning/pytorch-lightning/pull/1932))
 - Fixed bug related to logger not being reset correctly for model after tuner algorithms ([#1933](https://github.com/PyTorchLightning/pytorch-lightning/pull/1933))
 - Fixed root node resolution for SLURM cluster with dash in host name ([#1954](https://github.com/PyTorchLightning/pytorch-lightning/pull/1954))
@@ -89,8 +115,9 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Fixed an issue with `_auto_collect_arguments` collecting local variables that are not constructor arguments and not working for signatures that have the instance not named `self` ([#2048](https://github.com/PyTorchLightning/pytorch-lightning/pull/2048))
 - Fixed mistake in parameters' grad norm tracking ([#2012](https://github.com/PyTorchLightning/pytorch-lightning/pull/2012))
 - Fixed CPU and hanging GPU crash ([#2118](https://github.com/PyTorchLightning/pytorch-lightning/pull/2118))
-
 - Fixed an issue with the model summary and `example_input_array` depending on a specific ordering of the submodules in a LightningModule ([#1773](https://github.com/PyTorchLightning/pytorch-lightning/pull/1773))
+- Fixed Tpu logging ([#2230](https://github.com/PyTorchLightning/pytorch-lightning/pull/2230))
+- Fixed Pid port + duplicate `rank_zero` logging ([#2140](https://github.com/PyTorchLightning/pytorch-lightning/pull/2140), [#2231](https://github.com/PyTorchLightning/pytorch-lightning/pull/2231))
 
 ## [0.7.6] - 2020-05-16
 

diff --git a/README.md b/README.md
@@ -21,7 +21,13 @@
 -->
 </div>
 
+---   
+## Trending contributors
+
+[![](https://sourcerer.io/fame/williamFalcon/pytorchlightning/pytorch-lightning/images/0)](https://sourcerer.io/fame/williamFalcon/pytorchlightning/pytorch-lightning/links/0)[![](https://sourcerer.io/fame/williamFalcon/pytorchlightning/pytorch-lightning/images/1)](https://sourcerer.io/fame/williamFalcon/pytorchlightning/pytorch-lightning/links/1)[![](https://sourcerer.io/fame/williamFalcon/pytorchlightning/pytorch-lightning/images/2)](https://sourcerer.io/fame/williamFalcon/pytorchlightning/pytorch-lightning/links/2)[![](https://sourcerer.io/fame/williamFalcon/pytorchlightning/pytorch-lightning/images/3)](https://sourcerer.io/fame/williamFalcon/pytorchlightning/pytorch-lightning/links/3)[![](https://sourcerer.io/fame/williamFalcon/pytorchlightning/pytorch-lightning/images/4)](https://sourcerer.io/fame/williamFalcon/pytorchlightning/pytorch-lightning/links/4)[![](https://sourcerer.io/fame/williamFalcon/pytorchlightning/pytorch-lightning/images/5)](https://sourcerer.io/fame/williamFalcon/pytorchlightning/pytorch-lightning/links/5)[![](https://sourcerer.io/fame/williamFalcon/pytorchlightning/pytorch-lightning/images/6)](https://sourcerer.io/fame/williamFalcon/pytorchlightning/pytorch-lightning/links/6)[![](https://sourcerer.io/fame/williamFalcon/pytorchlightning/pytorch-lightning/images/7)](https://sourcerer.io/fame/williamFalcon/pytorchlightning/pytorch-lightning/links/7)
+
 ---
+
 ## Continuous Integration
 <center>
 
@@ -47,6 +53,8 @@ conda install pytorch-lightning -c conda-forge
 
 ## Docs
 - [master](https://pytorch-lightning.readthedocs.io/en/latest)
+- [stable](https://pytorch-lightning.readthedocs.io/en/stable)
+- [0.8.1](https://pytorch-lightning.readthedocs.io/en/0.8.1/)
 - [0.7.6](https://pytorch-lightning.readthedocs.io/en/0.7.6/)
 - [0.7.5](https://pytorch-lightning.readthedocs.io/en/0.7.5/)
 - [0.7.3](https://pytorch-lightning.readthedocs.io/en/0.7.3/)
@@ -357,6 +365,7 @@ Check out this awesome list of research papers and implementations done with Lig
 - [Transformers text classification](https://github.com/ricardorei/lightning-text-classification)
 - [VAE Library of over 18+ VAE flavors](https://github.com/AntixK/PyTorch-VAE)
 - [Finetune BERT, RoBERTa etc on QA Datasets like SQuAD](https://github.com/tshrjn/Finetune-QA/)
+- [Pytorch-Lightning + Microsoft NNI with Docker](https://github.com/davinnovation/pytorch-boilerplate)
 
 ## Tutorials
 Check out our [introduction guide](https://pytorch-lightning.readthedocs.io/en/latest/introduction_guide.html) to get started.
@@ -374,6 +383,7 @@ If you have any questions, feel free to:
 4. [Join our slack](https://join.slack.com/t/pytorch-lightning/shared_invite/zt-f6bl2l0l-JYMK3tbAgAmGRrlNr00f1A).
 
 ---
+
 ## FAQ
 **How do I use Lightning for rapid research?**    
 [Here's a walk-through](https://pytorch-lightning.readthedocs.io/en/latest/introduction_guide.html)
@@ -440,6 +450,8 @@ pip install https://github.com/PytorchLightning/pytorch-lightning/archive/0.X.Y.
 - Adrian Wälchli [(awaelchli)](https://github.com/awaelchli)
 - Nicki Skafte [(skaftenicki)](https://github.com/SkafteNicki)
 
+---
+
 #### Funding    
 Building open-source software with only a few part-time people is hard! We've secured funding to make sure we can
 hire a full-time staff, attend conferences, and move faster through implementing features you request.
@@ -456,7 +468,7 @@ If you want to cite the framework feel free to use this (but only if you loved i
 @article{falcon2019pytorch,
   title={PyTorch Lightning},
   author={Falcon, WA},
-  journal={GitHub. Note: https://github. com/williamFalcon/pytorch-lightning Cited by},
+  journal={GitHub. Note: https://github.com/PyTorchLightning/pytorch-lightning Cited by},
   volume={3},
   year={2019}
 }

diff --git a/docs/source/apex.rst b/docs/source/apex.rst
@@ -7,8 +7,10 @@
 =================
 Lightning offers 16-bit training for CPUs, GPUs and TPUs.
 
+----------
+
 GPU 16-bit
------------
+----------
 16 bit precision can cut your memory footprint by half.
 If using volta architecture GPUs it can give a dramatic training speed-up as well.
 
@@ -67,6 +69,8 @@ Enable 16-bit
 If you need to configure the apex init for your particular use case or want to use a different way of doing
 16-bit training, override   :meth:`pytorch_lightning.core.LightningModule.configure_apex`.
 
+----------
+
 TPU 16-bit
 ----------
 16-bit on TPus is much simpler. To use 16-bit with TPUs set precision to 16 when using the tpu flag

diff --git a/docs/source/callbacks.rst b/docs/source/callbacks.rst
@@ -46,7 +46,7 @@ Example:
 We successfully extended functionality without polluting our super clean
 :class:`~pytorch_lightning.core.LightningModule` research code.
 
----
+----------------
 
 .. automodule:: pytorch_lightning.callbacks.base
    :noindex:
@@ -56,7 +56,7 @@ We successfully extended functionality without polluting our super clean
         _abc_impl,
         check_monitor_top_k,
 
----
+----------------
 
 .. automodule:: pytorch_lightning.callbacks.early_stopping
    :noindex:
@@ -66,7 +66,7 @@ We successfully extended functionality without polluting our super clean
         _abc_impl,
         check_monitor_top_k,
 
----
+----------------
 
 .. automodule:: pytorch_lightning.callbacks.gradient_accumulation_scheduler
    :noindex:
@@ -76,15 +76,15 @@ We successfully extended functionality without polluting our super clean
         _abc_impl,
         check_monitor_top_k,
 
----
+----------------
 
 .. automodule:: pytorch_lightning.callbacks.lr_logger
     :noindex:
     :exclude-members:
         _extract_lr,
         _find_names
 
----
+----------------
 
 .. automodule:: pytorch_lightning.callbacks.model_checkpoint
    :noindex:
@@ -94,7 +94,7 @@ We successfully extended functionality without polluting our super clean
         _abc_impl,
         check_monitor_top_k,
 
----
+----------------
 
 .. automodule:: pytorch_lightning.callbacks.progress
    :noindex:

diff --git a/docs/source/child_modules.rst b/docs/source/child_modules.rst
@@ -43,7 +43,8 @@ that change in the `Autoencoder` model are the init, forward, training, validati
 
         def forward(self, x):
             generated = self.decoder(x)
-
+            return generated
+
         def training_step(self, batch, batch_idx):
             x, _ = batch
 

diff --git a/docs/source/debugging.rst b/docs/source/debugging.rst
@@ -6,7 +6,7 @@ Debugging
 =========
 The following are flags that make debugging much easier.
 
----
+----------------
 
 fast_dev_run
 ------------
@@ -21,7 +21,7 @@ argument of :class:`~pytorch_lightning.trainer.trainer.Trainer`)
 
     trainer = Trainer(fast_dev_run=True)
 
----
+----------------
 
 Inspect gradient norms
 ----------------------
@@ -35,7 +35,7 @@ argument of :class:`~pytorch_lightning.trainer.trainer.Trainer`)
     # the 2-norm
     trainer = Trainer(track_grad_norm=2)
 
----
+----------------
 
 Log GPU usage
 -------------
@@ -48,7 +48,7 @@ argument of :class:`~pytorch_lightning.trainer.trainer.Trainer`)
 
     trainer = Trainer(log_gpu_memory=True)
 
----
+----------------
 
 Make model overfit on subset of data
 ------------------------------------
@@ -61,7 +61,7 @@ argument of :class:`~pytorch_lightning.trainer.trainer.Trainer`)
 
 .. testcode::
 
-    # use only 1% of training data (and use the same training Dataloader (with shuffle off) in val and test)
+    # use only 1% of training data (and use the same training dataloader (with shuffle off) in val and test)
     trainer = Trainer(overfit_batches=0.01)
 
     # or overfit a number of batches
@@ -70,7 +70,7 @@ argument of :class:`~pytorch_lightning.trainer.trainer.Trainer`)
 With this flag, the train, val, and test sets will all be the same train set. We will also replace the sampler
 in the training set to turn off shuffle for you.
 
----
+----------------
 
 Print a summary of your LightningModule
 ---------------------------------------
@@ -99,7 +99,7 @@ See Also:
     - :paramref:`~pytorch_lightning.trainer.trainer.Trainer.weights_summary` Trainer argument
     - :class:`~pytorch_lightning.core.memory.ModelSummary`
 
----
+----------------
 
 Shorten epochs
 --------------
@@ -116,7 +116,7 @@ On larger datasets like Imagenet, this can help you debug or test a few things f
     # use 10 batches of train and 5 batches of val
     trainer = Trainer(limit_train_batches=10, limit_val_batches=5)
 
----
+----------------
 
 Set the number of validation sanity steps
 -----------------------------------------

diff --git a/docs/source/early_stopping.rst b/docs/source/early_stopping.rst
@@ -13,12 +13,16 @@ You can stop an epoch early by overriding :meth:`~pytorch_lightning.core.lightni
 
 If you do this repeatedly, for every epoch you had originally requested, then this will stop your entire run.
 
+----------
+
 Default Epoch End Callback Behavior
 -----------------------------------
 By default early stopping will be enabled if `'val_loss'`
 is found in :meth:`~pytorch_lightning.core.lightning.LightningModule.validation_epoch_end`'s
 return dict. Otherwise training will proceed with early stopping disabled.
 
+----------
+
 Enable Early Stopping using the EarlyStopping Callback
 ------------------------------------------------------
 The
@@ -81,6 +85,8 @@ and change where it is called:
     - :class:`~pytorch_lightning.trainer.trainer.Trainer`
     - :class:`~pytorch_lightning.callbacks.early_stopping.EarlyStopping`
 
+----------
+
 Disable Early Stopping with callbacks on epoch end
 --------------------------------------------------
 To disable early stopping pass ``False`` to the