changelog (#1616)

* changelog * warning * pull * typo * typo
2020-04-26 22:11:22 +02:00 · 2020-04-26 22:11:22 +02:00 · 80df5039f8
parent b989756c07
commit 80df5039f8
2 changed files with 36 additions and 57 deletions
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@ -8,86 +8,66 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).

 ### Added

- Added flag `replace_sampler_ddp` to manually disaple sampler replacement in ddp  ([#1513](https://github.com/PyTorchLightning/pytorch-lightning/pull/1513))
+### Changed

+### Deprecated
+
+### Removed
+
+### Fixed
+
+
+## [0.7.4] - 2020-04-26
+
+### Added
+
+- Added flag `replace_sampler_ddp` to manually disable sampler replacement in DDP  ([#1513](https://github.com/PyTorchLightning/pytorch-lightning/pull/1513))
 - Added speed parity tests (max 1 sec difference per epoch)([#1482](https://github.com/PyTorchLightning/pytorch-lightning/pull/1482))
-
 - Added `auto_select_gpus` flag to trainer that enables automatic selection of available GPUs on exclusive mode systems.
-
- Added learining rate finder ([#1347](https://github.com/PyTorchLightning/pytorch-lightning/pull/1347))
-
- Added support for ddp mode in clusters without SLURM ([#1345](https://github.com/PyTorchLightning/pytorch-lightning/issues/1345))
-
- Added `test_dataloaders` parameter to `Trainer.test()` ([#1393](https://github.com/PyTorchLightning/pytorch-lightning/issues/1393))
-
+- Added learning rate finder ([#1347](https://github.com/PyTorchLightning/pytorch-lightning/pull/1347))
+- Added support for ddp mode in clusters without SLURM ([#1387](https://github.com/PyTorchLightning/pytorch-lightning/pull/1387))
+- Added `test_dataloaders` parameter to `Trainer.test()` ([#1434](https://github.com/PyTorchLightning/pytorch-lightning/pull/1434))
 - Added `terminate_on_nan` flag to trainer that performs a NaN check with each training iteration when set to `True` ([#1475](https://github.com/PyTorchLightning/pytorch-lightning/pull/1475))
-
 - Added speed parity tests (max 1 sec difference per epoch)([#1482](https://github.com/PyTorchLightning/pytorch-lightning/pull/1482))
-
 - Added `terminate_on_nan` flag to trainer that performs a NaN check with each training iteration when set to `True`. ([#1475](https://github.com/PyTorchLightning/pytorch-lightning/pull/1475))
-
 - Added `ddp_cpu` backend for testing ddp without GPUs ([#1158](https://github.com/PyTorchLightning/pytorch-lightning/pull/1158))
-
 - Added [Horovod](http://horovod.ai) support as a distributed backend `Trainer(distributed_backend='horovod')` ([#1529](https://github.com/PyTorchLightning/pytorch-lightning/pull/1529))
-
 - Added support for 8 core distributed training on Kaggle TPU's ([#1568](https://github.com/PyTorchLightning/pytorch-lightning/pull/1568))
-
 - Added support for native AMP ([#1561](https://github.com/PyTorchLightning/pytorch-lightning/pull/1561), [#1580](https://github.com/PyTorchLightning/pytorch-lightning/pull/1580)) 

 ### Changed

 - Changed the default behaviour to no longer include a NaN check with each training iteration. ([#1475](https://github.com/PyTorchLightning/pytorch-lightning/pull/1475))
-
- Decoupled the progress bar from trainer. It is a callback now and can be customized or even be replaced entirely ([#1450](https://github.com/PyTorchLightning/pytorch-lightning/pull/1450)).
-
- Changed lr schedule step interval behavior to update every backwards pass instead of every forwards pass ([#1476](https://github.com/PyTorchLightning/pytorch-lightning/issues/1476))
-
+- Decoupled the progress bar from trainer` it is a callback now and can be customized or even be replaced entirely ([#1450](https://github.com/PyTorchLightning/pytorch-lightning/pull/1450)).
+- Changed lr schedule step interval behavior to update every backwards pass instead of every forwards pass ([#1477](https://github.com/PyTorchLightning/pytorch-lightning/pull/1477))
 - Defines shared proc. rank, remove rank from instances (e.g. loggers) ([#1408](https://github.com/PyTorchLightning/pytorch-lightning/pull/1408))
-
- Updated semantic segmentation example with custom u-net and logging ([#1371](https://github.com/PyTorchLightning/pytorch-lightning/pull/1371))
-
- Diabled val and test shuffling ([#1600](https://github.com/PyTorchLightning/pytorch-lightning/pull/1600))
-
+- Updated semantic segmentation example with custom U-Net and logging ([#1371](https://github.com/PyTorchLightning/pytorch-lightning/pull/1371))
+- Disabled val and test shuffling ([#1600](https://github.com/PyTorchLightning/pytorch-lightning/pull/1600))

 ### Deprecated

- Deprecatd `training_tqdm_dict` in favor of `progress_bar_dict` ([#1450](https://github.com/PyTorchLightning/pytorch-lightning/pull/1450)).
-
+- Deprecated `training_tqdm_dict` in favor of `progress_bar_dict` ([#1450](https://github.com/PyTorchLightning/pytorch-lightning/pull/1450)).

 ### Removed

- Removed `test_dataloaders` parameter from `Trainer.fit()` ([#1393](https://github.com/PyTorchLightning/pytorch-lightning/issues/1393))
-
+- Removed `test_dataloaders` parameter from `Trainer.fit()` ([#1434](https://github.com/PyTorchLightning/pytorch-lightning/pull/1434))

 ### Fixed

 - Added the possibility to pass nested metrics dictionaries to loggers ([#1582](https://github.com/PyTorchLightning/pytorch-lightning/pull/1582))
-
 - Fixed memory leak from opt return ([#1528](https://github.com/PyTorchLightning/pytorch-lightning/pull/1528))
-
 - Fixed saving checkpoint before deleting old ones ([#1453](https://github.com/PyTorchLightning/pytorch-lightning/pull/1453))
-
 - Fixed loggers - flushing last logged metrics even before continue, e.g. `trainer.test()` results ([#1459](https://github.com/PyTorchLightning/pytorch-lightning/pull/1459))
-
 - Fixed optimizer configuration when `configure_optimizers` returns dict without `lr_scheduler` ([#1443](https://github.com/PyTorchLightning/pytorch-lightning/pull/1443))
-
- Fixed LightningModule - Mixing hparams and arguments in `LightningModule.__init__()` crashes load_from_checkpoint() ([#1505](https://github.com/PyTorchLightning/pytorch-lightning/pull/1505))
-
+- Fixed `LightningModule` - mixing hparams and arguments in `LightningModule.__init__()` crashes load_from_checkpoint() ([#1505](https://github.com/PyTorchLightning/pytorch-lightning/pull/1505))
 - Added a missing call to the `on_before_zero_grad` model hook ([#1493](https://github.com/PyTorchLightning/pytorch-lightning/pull/1493)). 
-
- Allow use of sweeps with WandbLogger ([#1512](https://github.com/PyTorchLightning/pytorch-lightning/pull/1512))
-
+- Allow use of sweeps with `WandbLogger` ([#1512](https://github.com/PyTorchLightning/pytorch-lightning/pull/1512))
 - Fixed a bug that caused the `callbacks` Trainer argument to reference a global variable ([#1534](https://github.com/PyTorchLightning/pytorch-lightning/pull/1534)).
-
- Fixed a bug that set all boolean CLI arguments from Trainer.add_argparse_args always to True ([#1570](https://github.com/PyTorchLightning/pytorch-lightning/issues/1570))
-
- Fixed do not copy the batch when training on a single GPU ([#1576](https://github.com/PyTorchLightning/pytorch-lightning/issues/1576), [#1579](https://github.com/PyTorchLightning/pytorch-lightning/issues/1579))
-
+- Fixed a bug that set all boolean CLI arguments from `Trainer.add_argparse_args` always to True ([#1571](https://github.com/PyTorchLightning/pytorch-lightning/pull/1571))
+- Fixed do not copy the batch when training on a single GPU ([#1576](https://github.com/PyTorchLightning/pytorch-lightning/pull/1576), [#1579](https://github.com/PyTorchLightning/pytorch-lightning/pull/1579))
 - Fixed soft checkpoint removing on DDP ([#1408](https://github.com/PyTorchLightning/pytorch-lightning/pull/1408))
-
- Fixes automatic parser bug ([#1585](https://github.com/PyTorchLightning/pytorch-lightning/issues/1585))
-
- Fixed bool conversion from string ([#1606](https://github.com/PyTorchLightning/pytorch-lightning/issues/1606))
+- Fixed automatic parser bug ([#1585](https://github.com/PyTorchLightning/pytorch-lightning/pull/1585))
+- Fixed bool conversion from string ([#1606](https://github.com/PyTorchLightning/pytorch-lightning/pull/1606))

 ## [0.7.3] - 2020-04-09

@ -156,17 +136,17 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 ### Removed

 - Removed test for no test dataloader in .fit ([#1495](https://github.com/PyTorchLightning/pytorch-lightning/pull/1495))
- Removed duplicated module `pytorch_lightning.utilities.arg_parse` for loading CLI arguments ([#1167](https://github.com/PyTorchLightning/pytorch-lightning/issues/1167))
+- Removed duplicated module `pytorch_lightning.utilities.arg_parse` for loading CLI arguments ([#1167](https://github.com/PyTorchLightning/pytorch-lightning/pull/1167))
 - Removed wandb logger's `finalize` method ([#1193](https://github.com/PyTorchLightning/pytorch-lightning/pull/1193))
- Dropped `torchvision` dependency in tests and added own MNIST dataset class instead ([#986](https://github.com/PyTorchLightning/pytorch-lightning/issues/986))
+- Dropped `torchvision` dependency in tests and added own MNIST dataset class instead ([#986](https://github.com/PyTorchLightning/pytorch-lightning/pull/986))

 ### Fixed

 - Fixed `model_checkpoint` when saving all models ([#1359](https://github.com/PyTorchLightning/pytorch-lightning/pull/1359))
 - `Trainer.add_argparse_args` classmethod fixed. Now it adds a type for the arguments ([#1147](https://github.com/PyTorchLightning/pytorch-lightning/pull/1147))
- Fixed bug related to type checking of `ReduceLROnPlateau` lr schedulers([#1114](https://github.com/PyTorchLightning/pytorch-lightning/issues/1114))
+- Fixed bug related to type checking of `ReduceLROnPlateau` lr schedulers([#1126](https://github.com/PyTorchLightning/pytorch-lightning/pull/1126))
 - Fixed a bug to ensure lightning checkpoints to be backward compatible ([#1132](https://github.com/PyTorchLightning/pytorch-lightning/pull/1132))
- Fixed a bug that created an extra dataloader with active `reload_dataloaders_every_epoch` ([#1181](https://github.com/PyTorchLightning/pytorch-lightning/issues/1181))
+- Fixed a bug that created an extra dataloader with active `reload_dataloaders_every_epoch` ([#1196](https://github.com/PyTorchLightning/pytorch-lightning/pull/1196))
 - Fixed all warnings and errors in the docs build process ([#1191](https://github.com/PyTorchLightning/pytorch-lightning/pull/1191))
 - Fixed an issue where `val_percent_check=0` would not disable validation ([#1251](https://github.com/PyTorchLightning/pytorch-lightning/pull/1251))
 - Fixed average of incomplete `TensorRunningMean` ([#1309](https://github.com/PyTorchLightning/pytorch-lightning/pull/1309))
@ -185,7 +165,7 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Fixed `load_spawn_weights` only in proc rank 0 ([#1385](https://github.com/PyTorchLightning/pytorch-lightning/pull/1385))
 - Fixes `use_amp` issue ([#1145](https://github.com/PyTorchLightning/pytorch-lightning/pull/1145))
 - Fixes using deprecated `use_amp` attribute ([#1145](https://github.com/PyTorchLightning/pytorch-lightning/pull/1145))
- Fixed Tensorboard logger error: lightning_logs directory not exists in multi-node DDP on nodes with rank != 0 ([#1375](https://github.com/PyTorchLightning/pytorch-lightning/issues/1375))
+- Fixed Tensorboard logger error: lightning_logs directory not exists in multi-node DDP on nodes with rank != 0 ([#1377](https://github.com/PyTorchLightning/pytorch-lightning/pull/1377))
 - Fixed `Unimplemented backend XLA` error on TPU ([#1387](https://github.com/PyTorchLightning/pytorch-lightning/pull/1387))

 ## [0.7.1] - 2020-03-07
--- a/pytorch_lightning/callbacks/gradient_accumulation_scheduler.py
+++ b/pytorch_lightning/callbacks/gradient_accumulation_scheduler.py
@ -45,11 +45,10 @@ class GradientAccumulationScheduler(Callback):
                raise TypeError("All epoches and accumulation factor must be integers")

        minimal_epoch = min(scheduling.keys())
-        rank_zero_warn('Epochs indexing of `scheduling` starts from "1" until v0.6.x,'
-                       ' but will start from "0" in v0.8.0.', DeprecationWarning)
+        # rank_zero_warn('Epochs indexing of `scheduling` starts from "1" until v0.6.x,'
+        #                ' but will start from "0" in v0.8.0.', DeprecationWarning)
        if minimal_epoch < 1:
-            msg = f"Epochs indexing from 1, epoch {minimal_epoch} cannot be interpreted correct"
-            raise IndexError(msg)
+            raise IndexError(f"Epochs indexing from 1, epoch {minimal_epoch} cannot be interpreted correct")
        if minimal_epoch != 1:  # if user didnt define first epoch accumulation factor
            scheduling.update({1: 1})