Files
pytorch-lightning/tests
3e8f2d99a9 Progress bar callback (#1450)
* squash and rebase

sanity check hooks


sanity check callback hook finish


moved core progress bar functionality into callback


wip


remove duplicate merge


clean up


imports


docs


sanity check progress bar main


sanity


move callback calls


init progrss bar callback


configuration and docs


changelog


rate decorator


pass process_position


disable on rank > 0


position index


is_enabled


remove decorator


refactor init tqdm bars


callback method ordering 


cannot reset when disabled


sequence -> list


default values


fix has no attr _time() 


move on_val_end to proper place


fix the pickle issue


update warning


properties


check for None


remove old comment


switch order


pull out non-tqdm functionality into base class


documentation for the base class


docs


fix refresh rate issue in validation


restrict type hint of trainer arg


more docs


update trainer docs


rst docs


fix lines too long


fix test


add missing type hints


fix typo


move docstring to __init__ solves doctest failures


remove doctest :(( can't fix the pickle error


fix example


simplify by saving trainer reference


fix docs errors


move docstring


initial value


multiple val checks per epoch


simpler handling of inf dataset sizes


update inf docs


renamed training_tqdm_dict


rename get_tqdm_dict


rename occurences of tqdm 


update changelog


fix doctest


fix formatting errors


added callback tests


progress bar on off test


more tests for progress bar


weird test fix?


add ignored property


disable default progress bar in LR finder


change enable/disable behavior


trying doctest in CI again


undo doctest pickle error


undo doctest pickle error :((


remove progress_bar_callback Trainer arg and fix tests


restore progress bar after auto lr find


update docs


fix rebase


fix wrong negation

* fix fast dev run total

* more thorough testing

* remove old args

* fix merge

* fix merge

* separate tests

* type hint total batches

* reduce if

Co-Authored-By: Jirka Borovec <Borda@users.noreply.github.com>

* is_disabled

Co-Authored-By: Jirka Borovec <Borda@users.noreply.github.com>

* is_enabled

Co-Authored-By: Jirka Borovec <Borda@users.noreply.github.com>

* rename enabled/disabled

* move deprecated api

* remove duplicated test from merge

* fix rename is_disabled

* newline

* test also testprogress for fast dev run

Co-authored-by: J. Borovec <jirka.borovec@seznam.cz>
Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>
2020-04-23 20:46:18 -04:00
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PyTorch-Lightning Tests

Most PL tests train a full MNIST model under various trainer conditions (ddp, ddp2+amp, etc...). This provides testing for most combinations of important settings. The tests expect the model to perform to a reasonable degree of testing accuracy to pass.

Running tests

The automatic travis tests ONLY run CPU-based tests. Although these cover most of the use cases, run on a 2-GPU machine to validate the full test-suite.

To run all tests do the following:

git clone https://github.com/PyTorchLightning/pytorch-lightning
cd pytorch-lightning

# install AMP support
bash tests/install_AMP.sh

# install dev deps
pip install -r tests/requirements-devel.txt

# run tests
py.test -v

To test models that require GPU make sure to run the above command on a GPU machine. The GPU machine must have:

  1. At least 2 GPUs.
  2. NVIDIA-apex installed.
  3. Horovod with NCCL support: HOROVOD_GPU_ALLREDUCE=NCCL HOROVOD_GPU_BROADCAST=NCCL pip install horovod

Running Coverage

Make sure to run coverage on a GPU machine with at least 2 GPUs and NVIDIA apex installed.

cd pytorch-lightning

# generate coverage (coverage is also installed as part of dev dependencies under tests/requirements-devel.txt)
coverage run --source pytorch_lightning -m py.test pytorch_lightning tests examples -v --doctest-modules

# print coverage stats
coverage report -m

# exporting results
coverage xml

Building test image

You can build it on your own, note it takes lots of time, be prepared.

git clone <git-repository>
docker image build -t pytorch_lightning:devel-pt_1_4 -f tests/Dockerfile --build-arg TORCH_VERSION=1.4 .

To build other versions, select different Dockerfile.

docker image list
docker run --rm -it pytorch_lightning:devel-pt_1_4 bash
docker image rm pytorch_lightning:devel-pt_1_4