* Updated ImageNet example (pytorch#1138)

* [WIP] Updated ImageNet example
- minor fixes for Pascal VOC12

* Fixed flake8

* Updated pytorch-version-tests.yml to run cron every day at 00:00 UTC (pytorch#1141)

Co-authored-by: Sylvain Desroziers <[email protected]>

* Added check_compute_fn argument to EpochMetric and related metrics (pytorch#1140)

* Added check_compute_fn argument to EpochMetric and related functions.

* Updated docstrings

* Added check_compute_fn to _BaseRegressionEpoch

* Adding typing hints for check_compute_fn

* Update roc_auc.py

Co-authored-by: Sylvain Desroziers <[email protected]>
Co-authored-by: vfdev <[email protected]>

* Docs cosmetics (pytorch#1142)

* Updated docs, replaced single quote by double quote if is code
- fixed missing link to Engine
- cosmetics

* More doc updates

* More updates

* Fix batch size calculation error (pytorch#1137)

* Fix batch size calculation error

* Add tests for fixed batch size calculation

* Fix tests

* Test for num_workers

* Fix nproc comparison

* Improve docs

* Fixed docstring

Co-authored-by: vfdev <[email protected]>

* Docs updates (pytorch#1139)

* [WIP] Added teaser gif

* [WIP] Updated README

* [WIP] Updated README

* [WIP] Updated docs

* Reverted unintended pyproject.toml edits

* Updated README and examples parts

* More updates of README

* Added badge to check pytorch/python compatible versions

* Updated README

* Added ref to blog "Using Optuna to Optimize PyTorch Ignite Hyperparameters"

* Update README.md

* Fixed bad internal link in examples

* Updated README

* Fixes docs (pytorch#1147)

* Fixed bad link on teaser

* Added manual_seed into docs

* Issue pytorch#1115 : pbar persists due to specific rule in tqdm (notebook) when n < total (pytorch#1145)

* Issue pytorch#1115
pbar persists in notebook due to specific rules when n < total

* close pbar doesn't rise danger bar

* fix when pbar.total is None

Co-authored-by: vfdev <[email protected]>
Co-authored-by: Desroziers <[email protected]>

* Updated codebase such that torch>=1.3 (pytorch#1150)

Co-authored-by: vfdev <[email protected]>

* add wandb (pytorch#1152)

wandb integration already exists, just adding it to the requirements file

* Fixed typo and missing part of "Where to go next" (pytorch#1151)

* Fixes pytorch#1153 (pytorch#1154)

- temporary downgrade of scipy to 1.4.1 instead of 1.5.0

* Use global_step as priority, if it exists (pytorch#1155)

* Use global_step as priority, if it exists

* Fix flake8 error

* Style fix

Co-authored-by: vfdev <[email protected]>

* Fix TrainsSaver handling of Checkpoint's n_saved (pytorch#1135)

* Utilize Trains framework callbacks to better support checkpoint saving and respect Checkpoint.n_saved

* Update trains callbacks to new format

* autopep8 fix

* Fix trains mnist example (store checkpoints in local folder)

* Use trains 0.15.1rc0 until PR is approved

* Use CallbackType for Trains callback type resolution.
Add unit test for Trains callbacks

* Update trains version

* Updated test_trains_saver_callbacks

Co-authored-by: jkhenning <>
Co-authored-by: vfdev <[email protected]>

* Stateful handlers (pytorch#1156)

* Stateful handlers

* Added state_dict/load_state_dict tests for Checkpoint

* integration test

* Updated docstring and added include_self to ModelCheckpoint

* An integreation test for checkpointing with stateful handlers

* Black and flake8

Co-authored-by: vfdev-5 <[email protected]>

* Fixes pytorch#1162 (pytorch#1163)

* Fixes pytorch#1162
- relaxed check of optimizer type

* Updated docs

* Cosmetics (pytorch#1164)

* update ignite version to 0.5.0 in preparation of next release. (pytorch#1158)

Co-authored-by: vfdev <[email protected]>

* Create FUNDING.yml

* Update README.md

Added "Uncertainty Estimation Using a Single Deep Deterministic Neural Network" paper by @y0ast

* Issue 1124 (pytorch#1170)

* Fixes pytorch#1124

- Trains logger can log torch vectors

* Log vector as title=tag+key, series=str(index)

* Improved namings in _XlaDistModel (pytorch#1173)

* Issue 1123 - Improve usage of contrib common methods with other save handlers  (pytorch#1171)

* Added delegated_save_best_models_by_val_score

* Fixes pytorch#1123
- added save_handler arg to setup_common_training_handlers
- added method delegated_save_best_models_by_val_score

* Renamed delegated_save_best_models_by_val_score to gen_save_best_models_by_val_score

* Issue 1165 : nccl + torch.cuda not available (pytorch#1166)

* fix issue 1165

* Update ignite/distributed/comp_models/native.py

Co-authored-by: vfdev <[email protected]>

* add test for nccl /wo gpu

Co-authored-by: Desroziers <[email protected]>
Co-authored-by: vfdev <[email protected]>

* Fix typo in the docstring of ModelCheckpoint

* Fixes failing tests with native dist comp model (pytorch#1177)

- saves/restore env on init/finalize

* Set isort to 4.3.21 as it fails on 5.0 (pytorch#1180)

* improve docs for custom events (pytorch#1179)

* ValueError -> TypeError (pytorch#1175)

* ValueError -> TypeError

* refactor corresponeding unit-test

Co-authored-by: vfdev <[email protected]>

* Update cifar10  (pytorch#1181)

* Updated code to log models on Trains server

* Updated cifar10 example to log necessary things to Trains

* Fix Exception misuse in `ignite.contrib.handlers.base_logger.py` (pytorch#1183)

* ValueError -> TypeError

* NotImplementedError -> NotImplemented

* rollback ignite/engine/events [raise NotImplementedError]

* fix misuses of exceptions in ignite/contrib/handlers/base_logger.py

* refactor corresponding unit tests

Co-authored-by: Sylvain Desroziers <[email protected]>

* Fixed failing cifar10 test (pytorch#1184)

* Fix Exception misuse in `ignite.contrib.handlers.custom_events.py` (pytorch#1186)

* ValueError -> TypeError

* NotImplementedError -> NotImplemented

* rollback ignite/engine/events [raise NotImplementedError]

* fix misuses of exceptions in ignite/contrib/handlers/custom_events.py

* remove period in exceptions

* refactor corresponding unit tests

* Update tpu-tests.yml

* Fix Exception misuse in `ignite.contrib.engines.common.py` (pytorch#1182)

* ValueError -> TypeError

* NotImplementedError -> NotImplemented

* fix misuses of exceptions in ignite/contrib/engines/common.py

* rollback ignite/engine/events [raise NotImplementedError]

Co-authored-by: Sylvain Desroziers <[email protected]>
Co-authored-by: vfdev <[email protected]>

* Refactored test_utils.py into 3 files (pytorch#1185)

- we can better test new coming comp models

Co-authored-by: Sylvain Desroziers <[email protected]>

* Fix Exception misuse in `ignite.contrib.handlers.lr_finder.py` (pytorch#1187)

* ValueError -> TypeError

* NotImplementedError -> NotImplemented

* rollback ignite/engine/events [raise NotImplementedError]

* fix misuses of exceptions in ignite/contrib/handlers/lr_finder.py

* refactor corresponding unit tests

* fix typo

Co-authored-by: Desroziers <[email protected]>
Co-authored-by: Sylvain Desroziers <[email protected]>
Co-authored-by: vfdev <[email protected]>

* Fix Exception misuse in `ignite.contrib.handlers.mlflow_logger.py` (pytorch#1188)

* ValueError -> TypeError

* NotImplementedError -> NotImplemented

* rollback ignite/engine/events [raise NotImplementedError]

* fix misuses of exceptions in ignite/contrib/handlers/mlflow_logger.py & refactor corresponding unit tests

Co-authored-by: Sylvain Desroziers <[email protected]>
Co-authored-by: vfdev <[email protected]>

* Fix Exception misuse in `ignite.contrib.handlers.neptune_logger.py` (pytorch#1189)

* ValueError -> TypeError

* NotImplementedError -> NotImplemented

* rollback ignite/engine/events [raise NotImplementedError]

* fix misuses of exceptions in ignite/contrib/handlers/neptune_logger.py & refactor corresponding unit tests

Co-authored-by: Sylvain Desroziers <[email protected]>
Co-authored-by: vfdev <[email protected]>

* Update README.md (pytorch#1190)

* Update README.md

We are adding a disclaimer to all non-FB led repos in the PyTorch github org. Let me know if you have any concerns. Thanks!

* Update README.md

Co-authored-by: vfdev <[email protected]>

* fix for distributed proxy sampler runtime error (pytorch#1192)

* fix for distributed proxy sampler padding

* fixed formatting

* Updated timers to include fired hanlders' times (pytorch#1104) (pytorch#1194)

* update timers including fired handlers ones

* autopep8 fix

* fix measurement and add test

* rename fire_start_time to handlers_start_time

Co-authored-by: Desroziers <[email protected]>
Co-authored-by: AutoPEP8 <>

* Improve pascalvoc (pytorch#1193)

* Fixes pytorch#1124

- Trains logger can log torch vectors

* [WIP] Fixes issue with exp_trackin
- improved configs
- training script

* [WIP] Added explicit TrainsSaver setup

* Updated training script

* Fixed formatting

* Fixed bad merging

* Added missing rank dispatch for the progressbar

* Custom filename pattern for saving checkpoints (pytorch#1127)

* Custom filename pattern for saving checkpoints

* The suffix check be confused when adding name initially to the dict

* The filename prefix was updated which is not necessary was reverted

* The default filename pattern attribute was set instead of the `_filename_pattern`

* The redundant filename pattern to make filename was ugly, changed to something much more simple.

* The filename pattern implementation changed to have a new way to be initialized via an additional argument.

* - The extension given in the class has a dot infront of it, this can cause issues when having the latest filename pattern. have fixed it by assigning only the extension value not the dot
- The docsstring was updated to latest changes
- The assignment of name to filename pattern was missing

* The tests for checking the checkpoint filenames when a custom filename pattern is given.

* The formatting issue fixed

* - Added a function to get the filename pattern for the default to make it much more readable.
- Updated the current checkpoint __call__ to make filename based on the new function which has introduced
- Updated test_checkpoint_filename_pattern to have the exact values instead have a function.
- Updated a test case where it was failing due to the latest changes in a checkpoint __call__.

* - The _get_filename_pattern function updated to public and static setup_filename_pattern
- The setup_filename_pattern now takes updated arguments of with_score, with_score_name and with_global_step_transform

* The dostring and the static setup_filename_pattern were updated

- The docstring was updated with the filename_pattern also added a example
  for this as well.
- The static function `setup_filename_pattern` to get the default filename pattern
  of a checkpoint didn't have a proper typing. Have updated accordingly
- The `setup_filename_pattern` function accepted the custom filename pattern
  which was not required. Have updated this as well not to accept the custom
  filename pattern.

* The tests for the static function `Checkpoint.setup_filename_pattern`.

* The Docstring for setup_filename_pattern added and have updated the tests for this function.
- The docstring for the function used for making the default filename pattern for checkpoints is added.
- Added a new argument for filename prefix (`with_prefix`).
- The tests for the update is added

* Code clean up to have much more meaning to the code

* Simplified the code and tests

* fix quotes

* Revert "fix quotes"

This reverts commit 1b8d8e1.

Co-authored-by: Sylvain Desroziers <[email protected]>
Co-authored-by: vfdev <[email protected]>

* Docs update and auto_model change (pytorch#1197)

* Fixes pytorch#1174
- Updated docs
- auto_model puts params on device if they are not the device

* - Updated docs

* Update auto.py

* Minor optimization for idist.get_* (pytorch#1196)

* Minor optimization for idist.get_*

* Set overhead threshold to 1.9

* Keep only test_idist_methods_overhead_nccl

* Removed _sync_model_wrapper to implicitly check if we need to sync model
This also reduces time of idist.get_* method calls vs native calls

* Update test_native.py

* autopep8 fix

* Update test_native.py

Co-authored-by: AutoPEP8 <>
Co-authored-by: Sylvain Desroziers <[email protected]>

* Propagate spawn kwargs from parallel to model's spawn (pytorch#1201)

* Fixes pytorch#1199
- Updated code to propagate spawn kwargs
- start_method is fork by default

* Fixed bad syntax

* Fixes pytorch#1198 - bug with CM in PascalVOC example (pytorch#1200)

* Fixes pytorch#1198
- put CM to cpu before converting to numpy
- removed manual recall computation, put into CM definition

* Explicit CM compute by all proc and logging by 0 rank proc

* Added link to Discuss.PyTorch forum (pytorch#1205)

- Updated readme and FAQ

* Fixed wrong IoU computation in Pascal VOC (pytorch#1204)

* Fixed wrong IoU computation

* use black to fix lint check error

* Updated training code:
- added custom_event_filter to log images less frequently
- split events to avoid running validation twice in the end of the training

* Fixed formatting

Co-authored-by: Desroziers <[email protected]>

* Fix Typo in `ignite.handlers.timing` (pytorch#1208)

* ValueError -> TypeError

* NotImplementedError -> NotImplemented

* rollback ignite/engine/events [raise NotImplementedError]

* fix misuses of exceptions in ignite/contrib/handlers/custom_events.py

* remove period in exceptions

* refactor corresponding unit tests

* fix typo in ignite/handlers/timing.py

* Fixes issue with logging XLA tensors (pytorch#1207)

* [WIP] fixed typing

* Fixes pytorch#1136

- fixed problem when all_reduce does not put result tensor to original device

* REFACTOR: Early Return Pattern (if elif else -> if if return) (pytorch#1211)

* Issue 1133 - Fixes flaky Visdom tests (pytorch#1149)

* [WIP] inspect bug

* Attempt to fix flaky Visdom tests

* autopep8 fix

Co-authored-by: vfdev-5 <[email protected]>
Co-authored-by: AutoPEP8 <>

* Updated about page

* Replaced teaser code by a notebook runnable in Colab (pytorch#1216)

* Replaced teaser code by a notebook runnable in Colab

* Updated teaser (py, ipynb)

* Added support of Horovod (pytorch#1195)

* [WIP] Horovod comp model

* [WIP] Horovod comp model
- Implemented spawn
- Added comp model tests

* Refactored test_utils.py into 3 files
- we can better test new coming comp models

* [WIP] Run horovod tests

* [WIP] Horovod comp model + tests

* autopep8 fix

* [WIP] More tests

* Updated utils tests

* autopep8 fix

* [WIP] more tests

* Updated tests and code and cifar10 example

* autopep8 fix

* Fixed failing CI and updated code

* autopep8 fix

* Fixes failing test

* Fixed bug with new/old hvd API and the config

* Added metric tests

* Formatting and docs updated

* Updated frequency test

* Fixed formatting and a typo in idist.model_name docs

* Fixed failing test

* Docs updates and updated auto methods according to horovod API

* autopep8 fix

* Cosmetics

Co-authored-by: AutoPEP8 <>

* metrics: add SSIM (pytorch#1217)

* metrics: add SSIM

* add scikit-image dependency

* add distributed tests, fix docstring

* .gitignore back to normal

* Update ignite/metrics/ssim.py

Co-authored-by: vfdev <[email protected]>

* .format(), separate functions

* scalar input for kernel, sigma, fix py3.5 CI

* apply suggestions

* some fixes

* fixed tpu tests

* Minor code cosmetrics and raised err tolerance in tests

* used list comprehension convolution, fixed tests

* added uniform kernel, change tolerance, various image size tests

* Update ignite/metrics/ssim.py

Co-authored-by: vfdev <[email protected]>

* Update ignite/metrics/ssim.py

Co-authored-by: vfdev <[email protected]>

* Fix flake8

Co-authored-by: Sylvain Desroziers <[email protected]>
Co-authored-by: vfdev <[email protected]>

* add the EpochOutputStore with tests (pytorch#1226)

* add the EpochOutputStore with tests

* add correct import and unify the test cases

* fix checks from flake8 and isort

Co-authored-by: Zhiliang@siemens <[email protected]>

* add horovod test (pytorch#1230) (pytorch#1231)

Co-authored-by: Jeff Yang <[email protected]>

* Update README.md

* Added idist.broadcast (pytorch#1237)

* [WIP] Added idist.broadcast

* Removed unused code

* Added tests to increase coverage

* Docker for users pytorch#1214 (pytorch#1218)

* Docker for users pytorch#1214
- prebuilt docker image handling Ignite examples configuration

* Docker for users pytorch#1214
- more complete basic image based on pytorch 1.5.1-cuda10.1-cudnn7-devel
- with apex, opencv setups and pascal_voc2012 requirements
_ container running with non-privileged user

* Docker for users pytorch#1214
- improve Dockerfiles for vision and apex-vision (TORCH_CUDA_ARCH_LIST as argument)
- propose apex-vision with multi-stage build

* Docker for users pytorch#1214
- Dockerfiles for nlp and vision tasks with their apex version
- user as root, Ignite examples added

* Update README.md

Co-authored-by: Sylvain Desroziers <[email protected]>
Co-authored-by: vfdev <[email protected]>

* [BC-breaking] NotImplementedError -> NotImplemented (pytorch#1178)

* NotImplementedError -> NotImplemented

* returning NotImplemented, instead of raising it

* make type restriction inside  & add corresponding tests

* autopep8 fix

* remove extra spaces

* Updates according to the review

* Fixed unsupported f-string in 3.5
- added more tests

* Updated docs and tests

Co-authored-by: Sylvain Desroziers <[email protected]>
Co-authored-by: AutoPEP8 <>
Co-authored-by: vfdev-5 <[email protected]>

* Allow passing keyword arguments to save function on checkpoint. (pytorch#1245)

* Allow passing keyword arguments to save function on checkpoint.

* Change Docstring

* Add tests for keywords to DiskSaver

* autopep8 fix

* Use pytest.raises instead of xfail.

Co-authored-by: Sylvain Desroziers <[email protected]>
Co-authored-by: AutoPEP8 <>

* Docs updates and fix of black version (pytorch#1250)

* Update governance.rst

* Fix Exception misuse in `ignite.contrib.handlers.param_scheduler.py` (pytorch#1206)

* ValueError -> TypeError

* NotImplementedError -> NotImplemented

* rollback ignite/engine/events [raise NotImplementedError]

* fix misuses of exceptions in ignite/contrib/handlers/custom_events.py

* remove period in exceptions

* refactor corresponding unit tests

* fix misuses of exceptions in ignite/contrib/handlers/param_scheduler.py & refactor corresponding unit tests

* fix misuses of exceptions in ignite/contrib/handlers/param_scheduler.py & refactor corresponding unit tests (stricter: list/tuple -> TypeError & item of list/tuple -> ValueError)

* autopep8 fix

* remove extra spaces

* autopep8 fix

* add matches to pytest.raises

* add match to pytest.raises

* autopep8 fix

* add missing tests

* autopep8 fix

* Update param_scheduler.py

* revert previous modification

Co-authored-by: AutoPEP8 <>
Co-authored-by: Sylvain Desroziers <[email protected]>
Co-authored-by: vfdev <[email protected]>

* Issue pytorch#1247 (pytorch#1252)

* Delete test_custom_events.py

* Delete custom_events.py

* Removing depriciated CustomPeriodicEvent

* Remove deprecated CustomPeriodicEvent

* Update test_tqdm_logger.py

* Remove deprecated CustomPeriodicEvent

* Update test_tqdm_logger.py

Adding needed space.

* Removing CustomPeriodicEvent

* Update handlers.rst

* [WIP] Update readme for docker (pytorch#1254)

* [WIP] Update readme for docker

* Update README.md

Co-authored-by: vfdev <[email protected]>

* Update README.md

Co-authored-by: vfdev <[email protected]>

* [WIP] Update readme for docker
- fix rendering

* [WIP] Update readme for docker
- add DockerHub Ignite repo link and images list

* Updated readme

Co-authored-by: vfdev <[email protected]>

* Update README.md

* Update index.rst

* Update common.py

* Update CONTRIBUTING.md

* [WIP] Added sync_bn to auto_model with tests (pytorch#1265)

* Added dist support for EpochMetric and other similar metrics (pytorch#1229)

* [WIP] Added dist support for EpochMetric with tests

* Updated docs

* [WIP] Added idist.broadcast

* Removed unused code

* [WIP] Updated code

* Code and test updates

* autopep8 fix

* Replaced XLA unsupported type() method by attribute .dtype

* Updated code

Co-authored-by: AutoPEP8 <>

* Fixes pytorch#1258 (pytorch#1268)

- Replaced mp.spawn by mp.start_processes for native comp model

* Updated CONTRIBUTING.md (pytorch#1275)

* Updatd CONTRIBUTING.md

* Update CONTRIBUTING.md

* Rename Epoch to Iterations when using epoch_length with max_epochs=1 (pytorch#1279)

* Set default description as none

* Add test for description with max_epochs set to 1

* Change default description to use iterations when max_epochs=1

* Correct test_pbar_with_max_epochs_set_to_one

* Modify tests to reflect change from epochs to iterations

* Use engine.state.max_epochs instead of engine.state_dict()

* Change Iterations to Iteration

* Correct tests

* Update progress bar docstring

* Update tqdm_logger.py

Co-authored-by: vfdev <[email protected]>

* Update README.md

* [BC-breaking] Make Metrics accumulate values on device specified by user (pytorch#1232) (pytorch#1238)

* Make Metrics accumulate values on device specified by user (pytorch#1232)

* update accuracy to accumulate _num_correct in a tensor on the right device

* update loss metric to accumulate _sum in a tensor on the right device

* update mae metric to accumulate in a tensor on the right device

* update mpd metric to accumulate in a tensor on the right device

* update mse metric to accumulate in a tensor on the right device

* update top k accuracy  metric to accumulate in a tensor on the right device

* update precision and recall metrics to accumulate in tensors on the right device

* .....

* black formatting

* reverted run*.sh

* change all metrics default device to cpu except running_average

* Update ignite/metrics/precision.py

Co-authored-by: vfdev <[email protected]>

* remove Optional type from metric devices since default is cpu

* add comment explaining lack of detach in accuracy metrics

Co-authored-by: vfdev <[email protected]>

* Improved and fixed accuracy tests

* autopep8 fix

* update docs and docstrings for updated metrics (pytorch#1239)

* update accuracy to accumulate _num_correct in a tensor on the right device

* update loss metric to accumulate _sum in a tensor on the right device

* update mae metric to accumulate in a tensor on the right device

* update mpd metric to accumulate in a tensor on the right device

* update mse metric to accumulate in a tensor on the right device

* update top k accuracy  metric to accumulate in a tensor on the right device

* update precision and recall metrics to accumulate in tensors on the right device

* .....

* black formatting

* reverted run*.sh

* change all metrics default device to cpu except running_average

* Update ignite/metrics/precision.py

Co-authored-by: vfdev <[email protected]>

* remove Optional type from metric devices since default is cpu

* add comment explaining lack of detach in accuracy metrics

* update docstrings and docs

* Update ignite/metrics/accumulation.py

Co-authored-by: vfdev <[email protected]>

* Update ignite/metrics/accumulation.py

Co-authored-by: vfdev <[email protected]>

* Update ignite/metrics/accumulation.py

Co-authored-by: vfdev <[email protected]>

* Update ignite/metrics/accuracy.py

Co-authored-by: vfdev <[email protected]>

* Update ignite/metrics/fbeta.py

Co-authored-by: vfdev <[email protected]>

* Update ignite/metrics/loss.py

Co-authored-by: vfdev <[email protected]>

* Update ignite/metrics/metric.py

Co-authored-by: vfdev <[email protected]>

* Update ignite/metrics/precision.py

Co-authored-by: vfdev <[email protected]>

* Update ignite/metrics/recall.py

Co-authored-by: vfdev <[email protected]>

* add comment explaining lack of detach in metrics docs

* support device argument for running_average

* update support for device argumenet for accumulation

* fix and improve device tests for metrics

* fix and improve device tests for metrics

* fix TPU tests

* Apply suggestions from code review

* Apply suggestions from code review

Co-authored-by: vfdev <[email protected]>

* Updates to metrics_impl (pytorch#1266)

* update accuracy to accumulate _num_correct in a tensor on the right device

* update loss metric to accumulate _sum in a tensor on the right device

* update mae metric to accumulate in a tensor on the right device

* update mpd metric to accumulate in a tensor on the right device

* update mse metric to accumulate in a tensor on the right device

* update top k accuracy  metric to accumulate in a tensor on the right device

* update precision and recall metrics to accumulate in tensors on the right device

* .....

* black formatting

* reverted run*.sh

* change all metrics default device to cpu except running_average

* Update ignite/metrics/precision.py

Co-authored-by: vfdev <[email protected]>

* remove Optional type from metric devices since default is cpu

* add comment explaining lack of detach in accuracy metrics

* update docstrings and docs

* Update ignite/metrics/accumulation.py

Co-authored-by: vfdev <[email protected]>

* Update ignite/metrics/accumulation.py

Co-authored-by: vfdev <[email protected]>

* Update ignite/metrics/accumulation.py

Co-authored-by: vfdev <[email protected]>

* Update ignite/metrics/accuracy.py

Co-authored-by: vfdev <[email protected]>

* Update ignite/metrics/fbeta.py

Co-authored-by: vfdev <[email protected]>

* Update ignite/metrics/loss.py

Co-authored-by: vfdev <[email protected]>

* Update ignite/metrics/metric.py

Co-authored-by: vfdev <[email protected]>

* Update ignite/metrics/precision.py

Co-authored-by: vfdev <[email protected]>

* Update ignite/metrics/recall.py

Co-authored-by: vfdev <[email protected]>

* add comment explaining lack of detach in metrics docs

* support device argument for running_average

* update support for device argumenet for accumulation

* fix and improve device tests for metrics

* fix and improve device tests for metrics

* fix TPU tests

* Apply suggestions from code review

* Apply suggestions from code review

* detach tensors earlier in update

* remove redundant to() call

* ensure metrics aren't created on XLA devices

* Fixed isort

* move xla check to Metric.__init__ instead of individual metrics

* update xla tests

* replace deleted callable check

* remove redundant precision and recall __init__

* replace precision/recall __init__ for docs rendering

* add support for metrics_lambda with components on diff devices

Co-authored-by: vfdev <[email protected]>
Co-authored-by: n2cholas <[email protected]>

* Update metrics.rst

* Update metrics.rst

* Fix TPU tests for metrics_impl branch (pytorch#1277)

* update accuracy to accumulate _num_correct in a tensor on the right device

* update loss metric to accumulate _sum in a tensor on the right device

* update mae metric to accumulate in a tensor on the right device

* update mpd metric to accumulate in a tensor on the right device

* update mse metric to accumulate in a tensor on the right device

* update top k accuracy  metric to accumulate in a tensor on the right device

* update precision and recall metrics to accumulate in tensors on the right device

* .....

* black formatting

* reverted run*.sh

* change all metrics default device to cpu except running_average

* Update ignite/metrics/precision.py

Co-authored-by: vfdev <[email protected]>

* remove Optional type from metric devices since default is cpu

* add comment explaining lack of detach in accuracy metrics

* update docstrings and docs

* Update ignite/metrics/accumulation.py

Co-authored-by: vfdev <[email protected]>

* Update ignite/metrics/accumulation.py

Co-authored-by: vfdev <[email protected]>

* Update ignite/metrics/accumulation.py

Co-authored-by: vfdev <[email protected]>

* Update ignite/metrics/accuracy.py

Co-authored-by: vfdev <[email protected]>

* Update ignite/metrics/fbeta.py

Co-authored-by: vfdev <[email protected]>

* Update ignite/metrics/loss.py

Co-authored-by: vfdev <[email protected]>

* Update ignite/metrics/metric.py

Co-authored-by: vfdev <[email protected]>

* Update ignite/metrics/precision.py

Co-authored-by: vfdev <[email protected]>

* Update ignite/metrics/recall.py

Co-authored-by: vfdev <[email protected]>

* add comment explaining lack of detach in metrics docs

* support device argument for running_average

* update support for device argumenet for accumulation

* fix and improve device tests for metrics

* fix and improve device tests for metrics

* fix TPU tests

* Apply suggestions from code review

* Apply suggestions from code review

* detach tensors earlier in update

* remove redundant to() call

* ensure metrics aren't created on XLA devices

* Fixed isort

* move xla check to Metric.__init__ instead of individual metrics

* update xla tests

* replace deleted callable check

* remove redundant precision and recall __init__

* replace precision/recall __init__ for docs rendering

* add support for metrics_lambda with components on diff devices

* fix epoch_metric xla test

Co-authored-by: vfdev <[email protected]>
Co-authored-by: n2cholas <[email protected]>

* metrics_impl fix 2 gpu hvd tests and ensure consistent detaching (pytorch#1280)

* update accuracy to accumulate _num_correct in a tensor on the right device

* update loss metric to accumulate _sum in a tensor on the right device

* update mae metric to accumulate in a tensor on the right device

* update mpd metric to accumulate in a tensor on the right device

* update mse metric to accumulate in a tensor on the right device

* update top k accuracy  metric to accumulate in a tensor on the right device

* update precision and recall metrics to accumulate in tensors on the right device

* .....

* black formatting

* reverted run*.sh

* change all metrics default device to cpu except running_average

* Update ignite/metrics/precision.py

Co-authored-by: vfdev <[email protected]>

* remove Optional type from metric devices since default is cpu

* add comment explaining lack of detach in accuracy metrics

* update docstrings and docs

* Update ignite/metrics/accumulation.py

Co-authored-by: vfdev <[email protected]>

* Update ignite/metrics/accumulation.py

Co-authored-by: vfdev <[email protected]>

* Update ignite/metrics/accumulation.py

Co-authored-by: vfdev <[email protected]>

* Update ignite/metrics/accuracy.py

Co-authored-by: vfdev <[email protected]>

* Update ignite/metrics/fbeta.py

Co-authored-by: vfdev <[email protected]>

* Update ignite/metrics/loss.py

Co-authored-by: vfdev <[email protected]>

* Update ignite/metrics/metric.py

Co-authored-by: vfdev <[email protected]>

* Update ignite/metrics/precision.py

Co-authored-by: vfdev <[email protected]>

* Update ignite/metrics/recall.py

Co-authored-by: vfdev <[email protected]>

* add comment explaining lack of detach in metrics docs

* support device argument for running_average

* update support for device argumenet for accumulation

* fix and improve device tests for metrics

* fix and improve device tests for metrics

* fix TPU tests

* Apply suggestions from code review

* Apply suggestions from code review

* detach tensors earlier in update

* remove redundant to() call

* ensure metrics aren't created on XLA devices

* Fixed isort

* move xla check to Metric.__init__ instead of individual metrics

* update xla tests

* replace deleted callable check

* remove redundant precision and recall __init__

* replace precision/recall __init__ for docs rendering

* add support for metrics_lambda with components on diff devices

* fix epoch_metric xla test

* detach output consistently for all metrics

* fix horovod two gpu tests

* make confusion matrix detaches like other metrics

Co-authored-by: vfdev <[email protected]>
Co-authored-by: n2cholas <[email protected]>

* Fixes failing test on TPUs

Co-authored-by: Nicholas Vadivelu <[email protected]>
Co-authored-by: AutoPEP8 <>
Co-authored-by: Sylvain Desroziers <[email protected]>
Co-authored-by: n2cholas <[email protected]>

* Specify tqdm to be less than or equal to v4.48.0 (pytorch#1293)

* Fixes pytorch#1285 (pytorch#1290)

- use mp.spawn for pytorch < 1.5

* Issue 1249 : fix ParamGroupScheduler with schedulers based on different optimizers (pytorch#1274)

* remove **kwargs from LRScheduler

* revert ParamGroupScheduler inheritance : remove ParamScheduler base class

* use ParamGroupScheduler in ConcatScheduler

* add tests for ParamGroupScheduler with multiple optimizers

* autopep8 fix

* fix doc example

* fix from vfdev comments

* refactor list of optimizers and paranames

* add tests

* autopep8 fix

Co-authored-by: Desroziers <[email protected]>
Co-authored-by: AutoPEP8 <>
Co-authored-by: vfdev <[email protected]>

* remove prints (pytorch#1292)

* remove prints

* code formatting

Co-authored-by: vfdev <[email protected]>

* Fix link to pytorch documents (pytorch#1294)

* Fix link to pytorch documents

* Fix too long lines

Co-authored-by: vfdev <[email protected]>

* Added required_output_keys public attribute (1289) (pytorch#1291)

* Fixes pytorch#1289
- Promoted _required_output_keys to be public as user would like to override it.

* Updated docs

* Fixed typo in docs (concepts). (pytorch#1295)

* Setup Mypy check at CI step (pytorch#1296)

* add mypy file

* add mypy at CI step

* add mypy step at Contributing.md

Co-authored-by: vfdev <[email protected]>

* Update README.md

* Docker for users with Horovod (pytorch#1248)

* [WIP] Docker for users with Horovod
- base / vision / nlp
- with apex build

* [WIP] Docker for users with Horovod
- install horovod with .whl , add nccl in runtime image

* Docker for users with Horovod
- update Readmes for horovod images and configuration

* Docker for users with Horovod
- hvd tags/v0.20.0
- ignite examples with git sparse checkout

* Docker for users with Horovod
- update docs

Co-authored-by: Sylvain Desroziers <[email protected]>
Co-authored-by: vfdev <[email protected]>

* Added input data type check (pytorch#1301)

* Update metrics.rst

* Docker for users with MSDeepSpeed (pytorch#1304)

* Docker for users with DeepSpeed
- msdp-base | vision | nlp

* Docker for users with DeepSpeed
- rename images extensions to msdp-apex-*

Co-authored-by: Sylvain Desroziers <[email protected]>

* Update README.md

* Updated hvd images + scripts (pytorch#1306)

* Updated hvd images
- added scripts to auto build and push images

* Updated scripts according to the review

* Update BatchFiltered docstring

* Improve Canberra metric (pytorch#1312)

* Add abs on denominators in canberra metric and use sklearn in test

* autopep8 fix

* improve docstring

* use canberra on total computation

* Update canberra_metric.py

Co-authored-by: Desroziers <[email protected]>
Co-authored-by: AutoPEP8 <>
Co-authored-by: vfdev <[email protected]>

* Improve Canberra metric for DDP (pytorch#1314)

* refactor canberra metric for ddp

* improve canberra for ddp

* autopep8 fix

* use tensor for accumulation

* detach output

* remove useless item()

* add missing move to device

* refactor detach() and move

* refactor to remove useless view_as and to()

* do not expose reinit__is_reduced ad sync_all_reduce

Co-authored-by: Desroziers <[email protected]>
Co-authored-by: AutoPEP8 <>

* Improve ManhattanDistance metric for DDP  (pytorch#1320)

* fix manhattan distance and improve for ddp

* replace article by sklearn documentation

* Update ignite/contrib/metrics/regression/manhattan_distance.py

Co-authored-by: vfdev <[email protected]>

Co-authored-by: Desroziers <[email protected]>
Co-authored-by: vfdev <[email protected]>

* Update README.md

* Update about.rst

* Update Circle CI docker image to pytorch 1.6.0 (pytorch#1325)

* Update Circle CI docker image to pytorch 1.6. Closes pytorch#1225

* Update Circle CI docker image to pytorch 1.6. Closes pytorch#1225 (pytorch#1322)

* Revert "Update Circle CI docker image to pytorch 1.6. Closes pytorch#1225 (pytorch#1322)" (pytorch#1323)

This reverts commit 22ecac6.

* Update Circle CI docker image to pytorch 1.6.0 Closes pytorch#1225

Co-authored-by: vfdev <[email protected]>

* Update CONTRIBUTING.md

* Add new logo (pytorch#1324)

* Update Circle CI docker image to pytorch 1.6. Closes pytorch#1225 (pytorch#1322)

* Revert "Update Circle CI docker image to pytorch 1.6. Closes pytorch#1225 (pytorch#1322)" (pytorch#1323)

This reverts commit 22ecac6.

* add logos

* remove past logo from readme

* add logo guidelines

* Update README.md

Changed size to 512

* Updated docs logo

Co-authored-by: Juan Miguel Boyero Corral <[email protected]>
Co-authored-by: vfdev <[email protected]>

* Fixed CI on GPUs with pth 1.6.0 (pytorch#1326)

* Fixed CI on GPUs with pth 1.6.0
- updated tests/run_gpu_tests.sh file
- updated nccl version to 2.7 for Horovod build

* Fixed hvd failing tests

* Updated about us (pytorch#1327)

- Added CITATION file

* Improve R2Score metric for DDP (pytorch#1318)

* imrpove r2 for ddp

* autopep8 fix

* _num_examples type is scalar

* autopep8 fix

Co-authored-by: Desroziers <[email protected]>
Co-authored-by: AutoPEP8 <>
Co-authored-by: vfdev <[email protected]>

* Fix canberra docstring :  reference already in namespace (pytorch#1330)

Co-authored-by: Desroziers <[email protected]>
Co-authored-by: vfdev <[email protected]>

* Improve State and Engine docs pytorch#1259 (pytorch#1333)

- add State.restart() method
- add note in Engine.run() docstring / improve error message
- unit test for State.restart()

* pytorch#1336 missing link in doc fix (pytorch#1337)

* Make SSIM accumulate on specified device (pytorch#1328)

* make ssim accumulate on specified device

* keep output on original device until accumulation

* implement more efficient kernel creation

Co-authored-by: vfdev <[email protected]>

* Update documentation for terminate Events (pytorch#1338)

* Update documentation for terminate Events (pytorch#1332)

* Converted raw table in docstring to list table

* Update README.md

Co-authored-by: Anmol Joshi <[email protected]>
Co-authored-by: Sylvain Desroziers <[email protected]>
Co-authored-by: Marijan Smetko <[email protected]>
Co-authored-by: Desroziers <[email protected]>
Co-authored-by: Lavanya Shukla <[email protected]>
Co-authored-by: Akihiro Matsukawa <[email protected]>
Co-authored-by: Jake Henning <[email protected]>
Co-authored-by: Elijah Rippeth <[email protected]>
Co-authored-by: Wang Ran (汪然) <[email protected]>
Co-authored-by: Joseph Spisak <[email protected]>
Co-authored-by: Ryan Wong <[email protected]>
Co-authored-by: Joel Hanson <[email protected]>
Co-authored-by: Wansoo Kim <[email protected]>
Co-authored-by: Jeff Yang <[email protected]>
Co-authored-by: Zhiliang <[email protected]>
Co-authored-by: Zhiliang@siemens <[email protected]>
Co-authored-by: François COKELAER <[email protected]>
Co-authored-by: Kilian Pfeiffer <[email protected]>
Co-authored-by: Tawishi <[email protected]>
Co-authored-by: Michael Hollingworth <[email protected]>
Co-authored-by: Nicholas Vadivelu <[email protected]>
Co-authored-by: n2cholas <[email protected]>
Co-authored-by: Benjamin Lo <[email protected]>
Co-authored-by: Nidhi Zare <[email protected]>
Co-authored-by: Keisuke Kamahori <[email protected]>
Co-authored-by: Théo Dumont <[email protected]>
Co-authored-by: kenjihiraoka <[email protected]>
Co-authored-by: Juan Miguel Boyero Corral <[email protected]>
Co-authored-by: Isabela Presedo-Floyd <[email protected]>
Co-authored-by: Sumit Roy <[email protected]>
Co-authored-by: Shashank Gupta <[email protected]>