Ignite是一个高级库,帮助你在PyTorch中训练神经网络
Ignite是一个高级库,帮助你在PyTorch中训练神经网络 vfdev-5 released this
PyTorch-Ignite 0.4.2 - Release Notes
Core
New Features and bug fixes
-
Added SSIM metric (#1217)
-
Added prebuilt Docker images (#1218)
-
Added distributed support for
EpochMetric
and related metrics (#1229) -
Added
required_output_keys
public attribute (#1291) -
Pre-built docker images for computer vision and nlp tasks
powered with Nvidia/Apex, Horovod, MS DeepSpeed (#1304 #1248 #1218 )
Handlers and utils
- Allow passing keyword arguments to save function on
Checkpoint
(#1245)
Distributed helper module
- Added support of Horovod (#1195)
- Added
idist.broadcast
(#1237) - Added
sync_bn
option toidist.auto_model
(#1265)
Contrib
New Features and bug fixes
- Added
EpochOutputStore
handler (#1226) - Improved displayed tag for tqdm progress bar (#1279)
- Fixed bug with
ParamGroupScheduler
with schedulers based on different optimizers (#1274)
And a lot of house-keeping Pre-September Hacktoberfest contributions
- Added initial Mypy check at CI step (#1296)
- Fixed typo in docs (concepts) (#1295)
- Fixed link to pytorch documents (#1294)
- Removed prints from tests (#1292)
- Downgraded tqdm version to stabilize the CI (#1293)
Acknowledgments
@M3L6H, @Tawishi, @WrRan, @ZhiliangWu, @benji011, @fco-dv, @kamahori, @kenjihiraoka, @kilsenp, @n2cholas, @nzare, @sdesrozis, @theodumont, @vfdev-5, @ydcjeff,
Assets
2
PyTorch-Ignite 0.4.1 - Release Notes
Core
New Features and bug fixes
- Improved docs for custom events (#1179)
Handlers and utils
- Added custom filename pattern for saving checkpoints (#1127)
Distributed helper module
- Improved namings in _XlaDistModel (#1173)
- Minor optimization for
idist.get_*
methods (#1196) - Fixed distributed proxy sampler runtime error (#1192)
- Fixes bug using
idist
with "nccl" backend and torch cuda is not available (#1166) - Fixed issue with logging XLA tensors (#1207)
Contrib
New Features and bug fixes
- Fixes warning about "TrainsLogger output_handler can not log metrics value" (#1170)
- Improved usage of contrib common methods with other save handlers (#1171)
Examples
- Improved Pascal Voc example (#1193)
Acknowledgments
@Joel-hanson, @WrRan, @jspisak, @marload, @ryanwongsa, @sdesrozis, @vfdev-5
Assets
2
Core
- Added State repr and input batch as engine.state.batch (#641)
- Adapted core metrics only to be used in distributed configuration (#635)
- Added fbeta metric as core metric (#653)
- Added event filtering feature (e.g. every/once/event filter logic) (#656)
- BC breaking change: Refactor ModelCheckpoint into Checkpoint + DiskSaver / ModelCheckpoint (#673)
- Added option
n_saved=None
to store all checkpoints (#703)
- Added option
- Improved accumulation metrics (#681)
- Early stopping min delta (#685)
- Droped Python 2.7 support (#699)
- Added feature: Metric can accept a dictionary (#689)
- Added Dice Coefficient metric (#680)
- Added helper method to simplify the setup of class loggers (#712)
Engine refactoring
Finally solved the issue #62 to resume training from an epoch or iteration
- Engine refactoring + features (#640)
- engine checkpointing
- variable epoch lenght defined by
epoch_length
- two additional events:
GET_BATCH_STARTED
andGET_BATCH_COMPLETED
- cifar10 example with save/resume in distributed conf
Contrib
- Improved
create_lr_scheduler_with_warmup
(#646) - Added helper method to plot param scheduler values with matplotlib (#650)
- BC Breaking change: with multiple optimizer's param groups (#690)
- Added state_dict/load_state_dict (#690)
- BC Breaking change: Let the user specify tqdm parameters for log_message (#695)
Examples
- Added an example of hyperparameters tuning with Ax on CIFAR10 (#652)
- Added CIFAR10 distributed example
Reproducible trainings as "References"
Inspired by torchvision/references, we provide several reproducible baselines for vision tasks:
Features:
- Distributed training with mixed precision by nvidia/apex
- Experiments tracking with MLflow or Polyaxon
Acknowledgments
Assets
2
Core
Various improvements in the core part of the library:
-
Add
epoch_bound
parameter toRunningAverage
(#488) -
Bug fixes with Confusion matrix, new implementation (#572) - BC breaking
-
Added
event_to_attr
in register_events (#523) -
Added accumulative single variable metrics (#524)
-
should_terminate
is reset between runs (#525) -
to_onehot
returns tensor with uint8 dtype (#571) - may be BC breaking -
Removable handle returned from
Engine.add_event_handler()
to enable single-shot events (#588) -
New documentation style
🎉
Distributed
We removed mnist distrib example as being misleading and provide distrib branch to adapt metrics for distributed computation. Code is working and is under testing. Please, try it in your use-case and leave us a feedback.
Now in Contributions module
- Added mlflow logger (#558)
- R-Squared Metric in regression metrics module (#496)
- Add tag field to OptimizerParamsHandler (#502)
- Improved ProgressBar with TerminateOnNan (#506)
- Support for layer freezing with Tensorboard integration (#515)
- Improved OutputHandler API (#531)
- Improved create_lr_scheduler_with_warmup (#556)
- Added "all" option to metric_names in contrib loggers (#565)
- Added GPU usage info as metric (#569)
- Other bug fixes
Notebook examples
- Added Cycle-GAN notebook (#500)
- Finetune EfficientNet-B0 on CIFAR100 (#544)
- Added Fashion MNIST jupyter notebook (#549)
Updated nighlty builds
From pip:
pip install --pre pytorch-ignite
From conda (this suggests to install pytorch nightly release instead of stable version as dependency):
conda install ignite -c pytorch-nightly
Acknowledgments
@ANUBHAVNATANI, @Bibonaut, @Evpok, @Hiroshiba, @JeroenDelcour, @Mxbonn, @anmolsjoshi, @asford, @bosr, @johnstill, @marrrcin, @vfdev-5, @willfrey
Assets
2
vfdev-5 released this
Core
-
We removed deprecated metric classes
BinaryAccuracy
andCategoricalAccuracy
and which are replaced byAccuracy
. -
Multilabel option for
Accuracy
,Precision
,Recall
metrics. -
Added other metrics:
-
Operations on metrics:
p = Precision(average=False)
- apply PyTorch operators:
mean_precision = p.mean()
- indexing:
precision_no_bg = p[1:]
- apply PyTorch operators:
-
Improved our docs with more examples.
-
Added FAQ section with best practices.
-
Bug fixes
Now in Contributions module
- added
TensorboardLogger
- added
VisdomLogger
- added
PolyaxonLogger
- improved
ProgressBar
- New regression metrics
- Median Absolute Error
- Median Relative Absolute Error
- Median Absolute Percentage Error
- Geometric Mean Relative Absolute Error
- Canberra Metric
- Fractional Absolute Error
- Wave Hedges Distance
- Geometric Mean Absolute Error
- added new parameter scheduling classes and improved parameters:
- PiecewiseLinear
- LRScheduler
- other helper methods
- added custom events support:
CustomPeriodicEvent
Notebook examples
- VAE on MNIST
- CNN for text classification
Nighlty builds with pytorch-nightly as dependency
We also provide pip/conda
nighlty builds with pytorch-nightly
as dependency:
pip install pytorch-ignite-nightly
or
conda install -c pytorch ignite-nightly
Acknowledgments
Bibonaut, IlyaOvodov, TheCodez, anmolsjoshi, fabianschilling, maaario, snowyday, vfdev-5, willprice, zasdfgbnm, zippeurfou
vfdev-5 would like also to thank his wife and newborn baby girl Nina for their support while working on this release !
Assets
2
vfdev-5 released this
Core
-
We removed deprecated metric classes
BinaryAccuracy
andCategoricalAccuracy
and which are replaced byAccuracy
. -
Multilabel option for
Accuracy
,Precision
,Recall
metrics. -
Added other metrics:
-
Operations on metrics:
p = Precision(average=False)
- apply PyTorch operators:
mean_precision = p.mean()
- indexing:
precision_no_bg = p[1:]
- apply PyTorch operators:
-
Improved our docs with more examples.
-
Added FAQ section with best practices.
-
Bug fixes
Now in Contributions module
- added
TensorboardLogger
- added
VisdomLogger
- added
PolyaxonLogger
- improved
ProgressBar
- New regression metrics
- Median Absolute Error
- Median Relative Absolute Error
- Median Absolute Percentage Error
- Geometric Mean Relative Absolute Error
- Canberra Metric
- Fractional Absolute Error
- Wave Hedges Distance
- Geometric Mean Absolute Error
- added new parameter scheduling classes and improved parameters:
- PiecewiseLinear
- LRScheduler
- other helper methods
- added custom events support:
CustomPeriodicEvent
Notebook examples
- VAE on MNIST
- CNN for text classification
Nighlty builds with pytorch-nightly as dependency
We also provide pip/conda
nighlty builds with pytorch-nightly
as dependency:
pip install pytorch-ignite-nightly
or
conda install -c pytorch ignite-nightly
Acknowledgments
Bibonaut, IlyaOvodov, TheCodez, anmolsjoshi, fabianschilling, maaario, snowyday, vfdev-5, willprice, zasdfgbnm, zippeurfou
vfdev-5 would like also to thank his wife and newborn baby girl Nina for their support while working on this release !
Assets
2
Assets
2
- Improve and fix bug with binary accuracy, precision, recall
- Metrics arithmetics
- ParamScheduler to support multiple optimizers/multiple parameter groups
Thanks to all our contributors !
Assets
2
What's new in this release:
- Contrib module with
- Parameter schedule
- TQDM ProgressBar
- ROC/AUC, AP, MaxAE metrics
- TBPTT Engine
- New handlers:
- Terminate on Nan
- New metrics:
- RunningAverage
- Merged Categorical/Binary -> Accuracy
- Refactor of examples
- New examples:
- Fast Neural Style
- RL
Thanks to all our contributors !
First release
vfdev-5 released this
Introduced Engine, Handlers and Metrics.
Metrics:
- BinaryAccuracy
- CategoricalAccuracy
- Loss
- Precision
- Recall
- etc
Handlers:
- ModelCheckpoint
- EarlyStopping
- Timer
Features:
- PyTorch 0.4 support
Examples:
- mnist.py
- mnist_with_tensorboardx.py
- mnist_with_visdom.py
- dcgan.py
Watchers:58 |
Star:3282 |
Fork:439 |
创建时间: 2017-11-24 01:31:21 |
最后Commits: 昨天 |
许可协议:BSD-3-Clause |
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PyTorch-Ignite 0.4.3 - Release Notes
Core
Metrics
Handlers
greater_or_equal
option to Checkpoint handler (#1597)Distributed helper module
Others
torch.cuda.manual_seed_all
toignite.utils.manual_seed
(#1444)to_onehot
function to be torch scriptable (#1592)Docker images
Examples
Contrib
Metrics
Handlers
HandlersTimeProfiler
which allows per handler time profiling (#1398, #1474)attach_opt_params_handler
to returnRemovableEventHandle
(#1502)TrainsLogger
toClearMLLogger
keeping BC (#1557, #1560)Documentation improvements
Codebase is MyPy checked
Acknowledgments
@1nF0rmed, @Amab, @BanzaiTokyo, @Devanshu24, @Nic-Ma, @RaviTezu, @SamuelMarks, @abdulelahsm, @afzal442, @ahmedo42, @dgarth, @fco-dv, @gruebel, @harsh8398, @ibotdotout, @isabela-pf, @jkhenning, @josselineperdomo, @jrieke, @n2cholas, @ramesht007, @rzats, @sdesrozis, @shngt, @sroy8091, @theodumont, @thescripted, @timgates42, @trsvchn, @uribgp, @vcarpani, @vfdev-5, @ydcjeff, @zhxxn