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Decouple DataModules from Models - CPCV2 #386

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merged 2 commits into from Nov 26, 2020

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@akihironitta akihironitta commented Nov 20, 2020

What does this PR do?

Partial fix of #207.

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codecov bot commented Nov 20, 2020

Codecov Report

Merging #386 (f671de1) into master (70833f0) will decrease coverage by 0.84%.
The diff coverage is 0.00%.

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@@            Coverage Diff             @@
##           master     #386      +/-   ##
==========================================
- Coverage   82.03%   81.18%   -0.85%     
==========================================
  Files         100      100              
  Lines        5639     5714      +75     
==========================================
+ Hits         4626     4639      +13     
- Misses       1013     1075      +62     
Flag Coverage 螖
cpu 24.27% <0.00%> (-0.28%) 猬囷笍
pytest 24.27% <0.00%> (-0.28%) 猬囷笍
unittests 80.46% <0.00%> (-0.83%) 猬囷笍

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Impacted Files Coverage 螖
pl_bolts/models/self_supervised/cpc/cpc_module.py 20.31% <0.00%> (酶)
..._bolts/models/self_supervised/simclr/transforms.py 80.88% <0.00%> (-19.12%) 猬囷笍
...lts/models/self_supervised/simclr/simclr_module.py 71.49% <0.00%> (-11.32%) 猬囷笍
pl_bolts/losses/self_supervised_learning.py 71.33% <0.00%> (-6.37%) 猬囷笍
pl_bolts/datasets/base_dataset.py 95.45% <0.00%> (-4.55%) 猬囷笍
...l_bolts/models/self_supervised/byol/byol_module.py 83.90% <0.00%> (-1.04%) 猬囷笍
pl_bolts/models/self_supervised/resnets.py 92.04% <0.00%> (-0.74%) 猬囷笍
pl_bolts/models/self_supervised/byol/models.py 100.00% <0.00%> (酶)
.../models/self_supervised/simclr/simclr_finetuner.py 100.00% <0.00%> (酶)

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self.encoder = self.init_encoder()

# info nce loss
c, h = self.__compute_final_nb_c(self.hparams.patch_size)
self.contrastive_task = CPCTask(num_input_channels=c, target_dim=64, embed_scale=0.1)

self.z_dim = c * h * h
self.num_classes = self.datamodule.num_classes
self.num_classes = num_classes
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Since self.num_classes was already defined, I'm leaving it as is, but is this variable really necessary? As far as I understand the paper, it uses only images without any labels...

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Is this variable self.num_classes useful/necessary for downstream tasks...?

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lgtm cc: @ananyahjha93

@Borda Borda merged commit 2e903c3 into Lightning-Universe:master Nov 26, 2020
Self Supervised Learning automation moved this from In progress to Done Nov 26, 2020
chris-clem pushed a commit to chris-clem/pytorch-lightning-bolts that referenced this pull request Nov 27, 2020
chris-clem pushed a commit to chris-clem/pytorch-lightning-bolts that referenced this pull request Dec 9, 2020
Borda added a commit that referenced this pull request Jan 18, 2021
* Add DCGAN module

* Undo black on conf.py

* Add tests for DCGAN

* Fix flake8 and codefactor

* Add types and small refactoring

* Make image sampler callback work

* Upgrade DQN to use .log (#404)

* Upgrade DQN to use .log

* remove unused

* pep8

* fixed other dqn

* fix loss test case for batch size variation (#402)

* Decouple DataModules from Models - CPCV2 (#386)

* Decouple dms from CPCV2

* Update tests

* Add docstrings, fix import, and update changelog

* Update transforms

* bugfix: batch_size parameter for DataModules remaining (#344)

* bugfix: batch_size for DataModules remaining

* Update sklearn datamodule tests

* Fix default_transforms. Keep internal for every data module

* fix typo on binary_mnist_datamodule

thanks @akihironitta

Co-authored-by: Akihiro Nitta <nitta@akihironitta.com>

Co-authored-by: Akihiro Nitta <nitta@akihironitta.com>

* Fix a typo/copy paste error (#415)

* Just a Typo (#413)

missing a ' at the end of dataset='stl10

* Remove unused arguments (#418)

* tests: Use cached datasets in LitMNIST and the doctests (#414)

* Use cached datasets

* Use cached datasets in doctests

* clear replay buffer after trajectory (#425)

* stale: update label

* bugfix: Add missing imports to pl_bolts/__init__.py (#430)

* Add missing imports

* Add missing imports

* Apply isort

* Fix CIFAR num_samples (#432)

* Add static type checker mypy to the tests and pre-commit hooks (#433)

* Add mypy check to GitHub Actions

* Run mypy on pl_bolts only

* Add mypy check to pre-commit

* Add an empty line at the end of files

* Update mypy config

* Update mypy config

* Update mypy config

* show

Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>

* missing logo

* Add type annotations to pl_bolts/__init__.py (#435)

* Run mypy on pl_bolts only

* Update mypy config

* Add type hints to pl_bolts/__init__.py

* mypy

Co-authored-by: Jirka Borovec <jirka.borovec@seznam.cz>

* skip hanging (#437)

* Option to normalize latent interpolation images (#438)

* add option to normalize latent interpolation images

* linspace

* update

Co-authored-by: ananyahjha93 <ananya@pytorchlightning.ai>

* 0.2.6rc1

* Warnings fix (#449)

* Revert "Merge pull request #1 from ganprad/warnings_fix"

This reverts commit 7c5aaf0.

* Fixes warning related np.integer in SklearnDataModule

Fixes this warning:
```DeprecationWarning: Converting `np.integer` or `np.signedinteger` to a dtype is deprecated. The current result is `np.dtype(np.int_)` which is not strictly correct. Note that the result depends on the system. To ensure stable results use may want to use `np.int64` or `np.int32````

* Refactor datamodules/datasets (#338)

* Remove try: ... except: ...

* Fix experience_source

* Fix imagenet

* Fix kitti

* Fix sklearn

* Fix vocdetection

* Fix typo

* Remove duplicate

* Fix by flake8

* Add optional packages availability vars

* binary_mnist

* Use pl_bolts._SKLEARN_AVAILABLE

* Apply isort

* cifar10

* mnist

* cityscapes

* fashion mnist

* ssl_imagenet

* stl10

* cifar10

* dummy

* fix city

* fix stl10

* fix mnist

* ssl_amdim

* remove unused DataLoader and fix docs

* use from ... import ...

* fix pragma: no cover

* Fix forward reference in annotations

* binmnist

* Same order as imports

* Move vars from __init__ to utils/__init__

* Remove vars from __init__

* Update vars

* Apply isort

* update min requirements - PL 1.1.1 (#448)

* update min requirements

* rc0

* imports

* isort

* flake8

* 1.1.1

* flake8

* docs

* Add missing optional packages to `requirements/*.txt` (#450)

* Import matplotlib at the top

* Add missing optional packages

* Update wandb

* Add mypy to requirements

* update Isort (#457)

* Adding flags to datamodules (#388)

* Adding flags to datamodules

* Finishing up changes

* Fixing syntax error

* More syntax errors

* More

* Adding drop_last flag to sklearn test

* Adding drop_last flag to sklearn test

* Updating doc for reflect drop_last=False

* Adding flags to datamodules

* Finishing up changes

* Fixing syntax error

* More syntax errors

* More

* Adding drop_last flag to sklearn test

* Adding drop_last flag to sklearn test

* Updating doc for reflect drop_last=False

* Cleaning up parameters and docstring

* Fixing syntax error

* Fixing documentation

* Hardcoding shuffle=False for val and test

* Add DCGAN module

* Small fixes

* Remove DataModules

* Update docs

* Update docs

* Update torchvision import

* Import gym as optional package to build docs successfully (#458)

* Import gym as optional package

* Fix import

* Apply isort

* bugfix: batch_size parameter for DataModules remaining (#344)

* bugfix: batch_size for DataModules remaining

* Update sklearn datamodule tests

* Fix default_transforms. Keep internal for every data module

* fix typo on binary_mnist_datamodule

thanks @akihironitta

Co-authored-by: Akihiro Nitta <nitta@akihironitta.com>

Co-authored-by: Akihiro Nitta <nitta@akihironitta.com>

* Option to normalize latent interpolation images (#438)

* add option to normalize latent interpolation images

* linspace

* update

Co-authored-by: ananyahjha93 <ananya@pytorchlightning.ai>

* update min requirements - PL 1.1.1 (#448)

* update min requirements

* rc0

* imports

* isort

* flake8

* 1.1.1

* flake8

* docs

* Apply suggestions from code review

* Apply suggestions from code review

* Add docs

* Use LSUN instead of CIFAR10

* Update TensorboardGenerativeModelImageSampler

* Update docs with lsun

* Update test

* Revert TensorboardGenerativeModelImageSampler changes

* Remove ModelCheckpoint callback and nrow=5 arg

* Apply suggestions from code review

* Fix test_dcgan

* Apply yapf

* Apply suggestions from code review

Co-authored-by: Teddy Koker <teddy.koker@gmail.com>
Co-authored-by: Sidhant Sundrani <sidhant96@outlook.com>
Co-authored-by: Akihiro Nitta <nitta@akihironitta.com>
Co-authored-by: H茅ctor Laria <hector_laria@hotmail.com>
Co-authored-by: Bartol Karuza <bartol.k@gmail.com>
Co-authored-by: Happy Sugar Life <777Jonathansum@gmail.com>
Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>
Co-authored-by: Jirka Borovec <jirka.borovec@seznam.cz>
Co-authored-by: ananyahjha93 <ananya@pytorchlightning.ai>
Co-authored-by: Pradeep Ganesan <ganprad@users.noreply.github.com>
Co-authored-by: Brian Ko <briankosw@gmail.com>
Co-authored-by: Christoph Clement <christoph.clement@artorg.unibe.ch>
@Borda Borda added this to the v0.3 milestone Jan 18, 2021
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