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* delete

* Print Information Changes for AutoKeras v0.3 (#229) resolves #224

* Update CONTRIBUTING.md

* Develop (#187)

* merge (#128)

* 0.2.6 (#126)

* 0.2.5 setup.py (#111)

* [WIP] Attempts to Fix Memory Error  (#112)

* Add Website Badge in README.md, apply timeout in search function in search.py

* Add timeout in maximize_acq function in search.py

* Update unit test to allow timeout to raise TimeoutError

* Add unit test for timeout resume

* Remove TimeoutError from expectation

* Check Timeout exception in search() in search.py

* 0.2.5 setup.py (#110)

* Prevent gpu memory copy to main process after train() finished

* Cast loss from tensor to float

* Add pass() in MockProcess

* [MRG] Search Space limited to avoid out of memory (#121)

* limited the search space

* limited the search space

* reduce search space

* test added

* [MRG]Pytorch mp (#124)

* Change multiprcoessing to torch.multiprocessing

* Replace multiprocessing.Pool with torch.multiprocessing.Pool in tests

* 0.2.6 (#125)

* new release

* auto deploy

* auto deploy of docs

* fix the docs auto deploy

* Create CNAME

* deploy docs fixed

* update

* bug fix (#127)

* setup.py

* rm print

* Issue#37 and Issue #79 Save keras model/autokeras model (#122)

* Issue #37 Export Keras model

* Issue #79 Save autokeras model

* Issue #37 and Issue#79 Fixed comments

* Issue #37 and Issue #79

* Issue #37 and Issue #79

* Issue #37 and Issue #79 Fixed pytests

* Issue #37 and Issue #79

* quick fix test

* Progbar (#143)

* 0.2.6 (#126)

* 0.2.5 setup.py (#111)

* [WIP] Attempts to Fix Memory Error  (#112)

* Add Website Badge in README.md, apply timeout in search function in search.py

* Add timeout in maximize_acq function in search.py

* Update unit test to allow timeout to raise TimeoutError

* Add unit test for timeout resume

* Remove TimeoutError from expectation

* Check Timeout exception in search() in search.py

* 0.2.5 setup.py (#110)

* Prevent gpu memory copy to main process after train() finished

* Cast loss from tensor to float

* Add pass() in MockProcess

* [MRG] Search Space limited to avoid out of memory (#121)

* limited the search space

* limited the search space

* reduce search space

* test added

* [MRG]Pytorch mp (#124)

* Change multiprcoessing to torch.multiprocessing

* Replace multiprocessing.Pool with torch.multiprocessing.Pool in tests

* 0.2.6 (#125)

* new release

* auto deploy

* auto deploy of docs

* fix the docs auto deploy

* Create CNAME

* deploy docs fixed

* update

* bug fix (#127)

* setup.py

* contribute guide

* Add Progress Bar

* Update utils.py

* Update search.py

* update constant (#145)

* [WIP] Issue #158 Imageregressor (#159)

* Develop (#146)

* merge (#128)

* 0.2.6 (#126)

* 0.2.5 setup.py (#111)

* [WIP] Attempts to Fix Memory Error  (#112)

* Add Website Badge in README.md, apply timeout in search function in search.py

* Add timeout in maximize_acq function in search.py

* Update unit test to allow timeout to raise TimeoutError

* Add unit test for timeout resume

* Remove TimeoutError from expectation

* Check Timeout exception in search() in search.py

* 0.2.5 setup.py (#110)

* Prevent gpu memory copy to main process after train() finished

* Cast loss from tensor to float

* Add pass() in MockProcess

* [MRG] Search Space limited to avoid out of memory (#121)

* limited the search space

* limited the search space

* reduce search space

* test added

* [MRG]Pytorch mp (#124)

* Change multiprcoessing to torch.multiprocessing

* Replace multiprocessing.Pool with torch.multiprocessing.Pool in tests

* 0.2.6 (#125)

* new release

* auto deploy

* auto deploy of docs

* fix the docs auto deploy

* Create CNAME

* deploy docs fixed

* update

* bug fix (#127)

* setup.py

* rm print

* Issue#37 and Issue #79 Save keras model/autokeras model (#122)

* Issue #37 Export Keras model

* Issue #79 Save autokeras model

* Issue #37 and Issue#79 Fixed comments

* Issue #37 and Issue #79

* Issue #37 and Issue #79

* Issue #37 and Issue #79 Fixed pytests

* Issue #37 and Issue #79

* quick fix test

* Progbar (#143)

* 0.2.6 (#126)

* 0.2.5 setup.py (#111)

* [WIP] Attempts to Fix Memory Error  (#112)

* Add Website Badge in README.md, apply timeout in search function in search.py

* Add timeout in maximize_acq function in search.py

* Update unit test to allow timeout to raise TimeoutError

* Add unit test for timeout resume

* Remove TimeoutError from expectation

* Check Timeout exception in search() in search.py

* 0.2.5 setup.py (#110)

* Prevent gpu memory copy to main process after train() finished

* Cast loss from tensor to float

* Add pass() in MockProcess

* [MRG] Search Space limited to avoid out of memory (#121)

* limited the search space

* limited the search space

* reduce search space

* test added

* [MRG]Pytorch mp (#124)

* Change multiprcoessing to torch.multiprocessing

* Replace multiprocessing.Pool with torch.multiprocessing.Pool in tests

* 0.2.6 (#125)

* new release

* auto deploy

* auto deploy of docs

* fix the docs auto deploy

* Create CNAME

* deploy docs fixed

* update

* bug fix (#127)

* setup.py

* contribute guide

* Add Progress Bar

* Update utils.py

* Update search.py

* update constant (#145)

* Update setup.py (#147)

* Update setup.py

* Update setup.py

* Update setup.py (#155)

* requirements

* Issue #158 Export ImageRegressor model

* Memory (#161)

* aa

* limit memory

* refactor to_real_layer to member functions

* bug fix (#166)

* doc string changed for augment (#170)

I added proper documentation for class ImageSupervised  arg 'augment'. It is 'None' by default. However, if it is 'None', then it uses Constant.DATA_AUGMENTATION which is 'True'. This is misleading when trying things out.

* Update constant.py

* bug fix (#177)

* memory limit dynamically (#180)

* memory limit dynamically

* test

* test fixed

* [MRG]Dcgan (#175)

* Add Website Badge in README.md, apply timeout in search function in search.py

* Add timeout in maximize_acq function in search.py

* Update unit test to allow timeout to raise TimeoutError

* Add unit test for timeout resume

* Remove TimeoutError from expectation

* Check Timeout exception in search() in search.py

* finish workable version of gan

* add unit test and small refactoring

* add unsupervised super class

* Fix test_dcgan ran too long issue, put default param in unsupervised::generate(input_sample=None)

* remove examples/gan.py from repo

* add missing import

* correct model_trainer signature

* fixed the bug in return value of train_model()

* Update setup.py

* [WIP]Update CONTRIBUTING.md (#190)

* Update CONTRIBUTING.md

* Update CONTRIBUTING.md

* Update mkdocs.yml

* code_reuse_example

* Update CONTRIBUTING.md

* update develop (#206) (#207)

* Update CONTRIBUTING.md

* Develop (#187)

* merge (#128)

* 0.2.6 (#126)

* 0.2.5 setup.py (#111)

* [WIP] Attempts to Fix Memory Error  (#112)

* Add Website Badge in README.md, apply timeout in search function in search.py

* Add timeout in maximize_acq function in search.py

* Update unit test to allow timeout to raise TimeoutError

* Add unit test for timeout resume

* Remove TimeoutError from expectation

* Check Timeout exception in search() in search.py

* 0.2.5 setup.py (#110)

* Prevent gpu memory copy to main process after train() finished

* Cast loss from tensor to float

* Add pass() in MockProcess

* [MRG] Search Space limited to avoid out of memory (#121)

* limited the search space

* limited the search space

* reduce search space

* test added

* [MRG]Pytorch mp (#124)

* Change multiprcoessing to torch.multiprocessing

* Replace multiprocessing.Pool with torch.multiprocessing.Pool in tests

* 0.2.6 (#125)

* new release

* auto deploy

* auto deploy of docs

* fix the docs auto deploy

* Create CNAME

* deploy docs fixed

* update

* bug fix (#127)

* setup.py

* rm print

* Issue#37 and Issue #79 Save keras model/autokeras model (#122)

* Issue #37 Export Keras model

* Issue #79 Save autokeras model

* Issue #37 and Issue#79 Fixed comments

* Issue #37 and Issue #79

* Issue #37 and Issue #79

* Issue #37 and Issue #79 Fixed pytests

* Issue #37 and Issue #79

* quick fix test

* Progbar (#143)

* 0.2.6 (#126)

* 0.2.5 setup.py (#111)

* [WIP] Attempts to Fix Memory Error  (#112)

* Add Website Badge in README.md, apply timeout in search function in search.py

* Add timeout in maximize_acq function in search.py

* Update unit test to allow timeout to raise TimeoutError

* Add unit test for timeout resume

* Remove TimeoutError from expectation

* Check Timeout exception in search() in search.py

* 0.2.5 setup.py (#110)

* Prevent gpu memory copy to main process after train() finished

* Cast loss from tensor to float

* Add pass() in MockProcess

* [MRG] Search Space limited to avoid out of memory (#121)

* limited the search space

* limited the search space

* reduce search space

* test added

* [MRG]Pytorch mp (#124)

* Change multiprcoessing to torch.multiprocessing

* Replace multiprocessing.Pool with torch.multiprocessing.Pool in tests

* 0.2.6 (#125)

* new release

* auto deploy

* auto deploy of docs

* fix the docs auto deploy

* Create CNAME

* deploy docs fixed

* update

* bug fix (#127)

* setup.py

* contribute guide

* Add Progress Bar

* Update utils.py

* Update search.py

* update constant (#145)

* [WIP] Issue #158 Imageregressor (#159)

* Develop (#146)

* merge (#128)

* 0.2.6 (#126)

* 0.2.5 setup.py (#111)

* [WIP] Attempts to Fix Memory Error  (#112)

* Add Website Badge in README.md, apply timeout in search function in search.py

* Add timeout in maximize_acq function in search.py

* Update unit test to allow timeout to raise TimeoutError

* Add unit test for timeout resume

* Remove TimeoutError from expectation

* Check Timeout exception in search() in search.py

* 0.2.5 setup.py (#110)

* Prevent gpu memory copy to main process after train() finished

* Cast loss from tensor to float

* Add pass() in MockProcess

* [MRG] Search Space limited to avoid out of memory (#121)

* limited the search space

* limited the search space

* reduce search space

* test added

* [MRG]Pytorch mp (#124)

* Change multiprcoessing to torch.multiprocessing

* Replace multiprocessing.Pool with torch.multiprocessing.Pool in tests

* 0.2.6 (#125)

* new release

* auto deploy

* auto deploy of docs

* fix the docs auto deploy

* Create CNAME

* deploy docs fixed

* update

* bug fix (#127)

* setup.py

* rm print

* Issue#37 and Issue #79 Save keras model/autokeras model (#122)

* Issue #37 Export Keras model

* Issue #79 Save autokeras model

* Issue #37 and Issue#79 Fixed comments

* Issue #37 and Issue #79

* Issue #37 and Issue #79

* Issue #37 and Issue #79 Fixed pytests

* Issue #37 and Issue #79

* quick fix test

* Progbar (#143)

* 0.2.6 (#126)

* 0.2.5 setup.py (#111)

* [WIP] Attempts to Fix Memory Error  (#112)

* Add Website Badge in README.md, apply timeout in search function in search.py

* Add timeout in maximize_acq function in search.py

* Update unit test to allow timeout to raise TimeoutError

* Add unit test for timeout resume

* Remove TimeoutError from expectation

* Check Timeout exception in search() in search.py

* 0.2.5 setup.py (#110)

* Prevent gpu memory copy to main process after train() finished

* Cast loss from tensor to float

* Add pass() in MockProcess

* [MRG] Search Space limited to avoid out of memory (#121)

* limited the search space

* limited the search space

* reduce search space

* test added

* [MRG]Pytorch mp (#124)

* Change multiprcoessing to torch.multiprocessing

* Replace multiprocessing.Pool with torch.multiprocessing.Pool in tests

* 0.2.6 (#125)

* new release

* auto deploy

* auto deploy of docs

* fix the docs auto deploy

* Create CNAME

* deploy docs fixed

* update

* bug fix (#127)

* setup.py

* contribute guide

* Add Progress Bar

* Update utils.py

* Update search.py

* update constant (#145)

* Update setup.py (#147)

* Update setup.py

* Update setup.py

* Update setup.py (#155)

* requirements

* Issue #158 Export ImageRegressor model

* Memory (#161)

* aa

* limit memory

* refactor to_real_layer to member functions

* bug fix (#166)

* doc string changed for augment (#170)

I added proper documentation for class ImageSupervised  arg 'augment'. It is 'None' by default. However, if it is 'None', then it uses Constant.DATA_AUGMENTATION which is 'True'. This is misleading when trying things out.

* Update constant.py

* bug fix (#177)

* memory limit dynamically (#180)

* memory limit dynamically

* test

* test fixed

* [MRG]Dcgan (#175)

* Add Website Badge in README.md, apply timeout in search function in search.py

* Add timeout in maximize_acq function in search.py

* Update unit test to allow timeout to raise TimeoutError

* Add unit test for timeout resume

* Remove TimeoutError from expectation

* Check Timeout exception in search() in search.py

* finish workable version of gan

* add unit test and small refactoring

* add unsupervised super class

* Fix test_dcgan ran too long issue, put default param in unsupervised::generate(input_sample=None)

* remove examples/gan.py from repo

* add missing import

* correct model_trainer signature

* fixed the bug in return value of train_model()

* Update setup.py

* [WIP]Update CONTRIBUTING.md (#190)

* Update CONTRIBUTING.md

* Update CONTRIBUTING.md

* Update mkdocs.yml

* code_reuse_example

* Update CONTRIBUTING.md

* Update search.py

* Develop (#215)

* update develop (#206)

* Update CONTRIBUTING.md

* Develop (#187)

* merge (#128)

* 0.2.6 (#126)

* 0.2.5 setup.py (#111)

* [WIP] Attempts to Fix Memory Error  (#112)

* Add Website Badge in README.md, apply timeout in search function in search.py

* Add timeout in maximize_acq function in search.py

* Update unit test to allow timeout to raise TimeoutError

* Add unit test for timeout resume

* Remove TimeoutError from expectation

* Check Timeout exception in search() in search.py

* 0.2.5 setup.py (#110)

* Prevent gpu memory copy to main process after train() finished

* Cast loss from tensor to float

* Add pass() in MockProcess

* [MRG] Search Space limited to avoid out of memory (#121)

* limited the search space

* limited the search space

* reduce search space

* test added

* [MRG]Pytorch mp (#124)

* Change multiprcoessing to torch.multiprocessing

* Replace multiprocessing.Pool with torch.multiprocessing.Pool in tests

* 0.2.6 (#125)

* new release

* auto deploy

* auto deploy of docs

* fix the docs auto deploy

* Create CNAME

* deploy docs fixed

* update

* bug fix (#127)

* setup.py

* rm print

* Issue#37 and Issue #79 Save keras model/autokeras model (#122)

* Issue #37 Export Keras model

* Issue #79 Save autokeras model

* Issue #37 and Issue#79 Fixed comments

* Issue #37 and Issue #79

* Issue #37 and Issue #79

* Issue #37 and Issue #79 Fixed pytests

* Issue #37 and Issue #79

* quick fix test

* Progbar (#143)

* 0.2.6 (#126)

* 0.2.5 setup.py (#111)

* [WIP] Attempts to Fix Memory Error  (#112)

* Add Website Badge in README.md, apply timeout in search function in search.py

* Add timeout in maximize_acq function in search.py

* Update unit test to allow timeout to raise TimeoutError

* Add unit test for timeout resume

* Remove TimeoutError from expectation

* Check Timeout exception in search() in search.py

* 0.2.5 setup.py (#110)

* Prevent gpu memory copy to main process after train() finished

* Cast loss from tensor to float

* Add pass() in MockProcess

* [MRG] Search Space limited to avoid out of memory (#121)

* limited the search space

* limited the search space

* reduce search space

* test added

* [MRG]Pytorch mp (#124)

* Change multiprcoessing to torch.multiprocessing

* Replace multiprocessing.Pool with torch.multiprocessing.Pool in tests

* 0.2.6 (#125)

* new release

* auto deploy

* auto deploy of docs

* fix the docs auto deploy

* Create CNAME

* deploy docs fixed

* update

* bug fix (#127)

* setup.py

* contribute guide

* Add Progress Bar

* Update utils.py

* Update search.py

* update constant (#145)

* [WIP] Issue #158 Imageregressor (#159)

* Develop (#146)

* merge (#128)

* 0.2.6 (#126)

* 0.2.5 setup.py (#111)

* [WIP] Attempts to Fix Memory Error  (#112)

* Add Website Badge in README.md, apply timeout in search function in search.py

* Add timeout in maximize_acq function in search.py

* Update unit test to allow timeout to raise TimeoutError

* Add unit test for timeout resume

* Remove TimeoutError from expectation

* Check Timeout exception in search() in search.py

* 0.2.5 setup.py (#110)

* Prevent gpu memory copy to main process after train() finished

* Cast loss from tensor to float

* Add pass() in MockProcess

* [MRG] Search Space limited to avoid out of memory (#121)

* limited the search space

* limited the search space

* reduce search space

* test added

* [MRG]Pytorch mp (#124)

* Change multiprcoessing to torch.multiprocessing

* Replace multiprocessing.Pool with torch.multiprocessing.Pool in tests

* 0.2.6 (#125)

* new release

* auto deploy

* auto deploy of docs

* fix the docs auto deploy

* Create CNAME

* deploy docs fixed

* update

* bug fix (#127)

* setup.py

* rm print

* Issue#37 and Issue #79 Save keras model/autokeras model (#122)

* Issue #37 Export Keras model

* Issue #79 Save autokeras model

* Issue #37 and Issue#79 Fixed comments

* Issue #37 and Issue #79

* Issue #37 and Issue #79

* Issue #37 and Issue #79 Fixed pytests

* Issue #37 and Issue #79

* quick fix test

* Progbar (#143)

* 0.2.6 (#126)

* 0.2.5 setup.py (#111)

* [WIP] Attempts to Fix Memory Error  (#112)

* Add Website Badge in README.md, apply timeout in search function in search.py

* Add timeout in maximize_acq function in search.py

* Update unit test to allow timeout to raise TimeoutError

* Add unit test for timeout resume

* Remove TimeoutError from expectation

* Check Timeout exception in search() in search.py

* 0.2.5 setup.py (#110)

* Prevent gpu memory copy to main process after train() finished

* Cast loss from tensor to float

* Add pass() in MockProcess

* [MRG] Search Space limited to avoid out of memory (#121)

* limited the search space

* limited the search space

* reduce search space

* test added

* [MRG]Pytorch mp (#124)

* Change multiprcoessing to torch.multiprocessing

* Replace multiprocessing.Pool with torch.multiprocessing.Pool in tests

* 0.2.6 (#125)

* new release

* auto deploy

* auto deploy of docs

* fix the docs auto deploy

* Create CNAME

* deploy docs fixed

* update

* bug fix (#127)

* setup.py

* contribute guide

* Add Progress Bar

* Update utils.py

* Update search.py

* update constant (#145)

* Update setup.py (#147)

* Update setup.py

* Update setup.py

* Update setup.py (#155)

* requirements

* Issue #158 Export ImageRegressor model

* Memory (#161)

* aa

* limit memory

* refactor to_real_layer to member functions

* bug fix (#166)

* doc string changed for augment (#170)

I added proper documentation for class ImageSupervised  arg 'augment'. It is 'None' by default. However, if it is 'None', then it uses Constant.DATA_AUGMENTATION which is 'True'. This is misleading when trying things out.

* Update constant.py

* bug fix (#177)

* memory limit dynamically (#180)

* memory limit dynamically

* test

* test fixed

* [MRG]Dcgan (#175)

* Add Website Badge in README.md, apply timeout in search function in search.py

* Add timeout in maximize_acq function in search.py

* Update unit test to allow timeout to raise TimeoutError

* Add unit test for timeout resume

* Remove TimeoutError from expectation

* Check Timeout exception in search() in search.py

* finish workable version of gan

* add unit test and small refactoring

* add unsupervised super class

* Fix test_dcgan ran too long issue, put default param in unsupervised::generate(input_sample=None)

* remove examples/gan.py from repo

* add missing import

* correct model_trainer signature

* fixed the bug in return value of train_model()

* Update setup.py

* [WIP]Update CONTRIBUTING.md (#190)

* Update CONTRIBUTING.md

* Update CONTRIBUTING.md

* Update mkdocs.yml

* code_reuse_example

* Update CONTRIBUTING.md

* bug_fix (#208)

* bug_fix (#214) resolves #212

* Update CONTRIBUTING.md

* Update setup.py

* delete (#217)

* Print Information Changes for AutoKeras v0.3

* readme

* contributing
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25 changes: 8 additions & 17 deletions CONTRIBUTING.md
Expand Up @@ -80,30 +80,21 @@ to ensure your merge request meet our requirements.
## Pull Request Guide
Before you submit a pull request, check that it meets these guidelines:

1. Submit the pull request from the first day when you started your development and mark it as **[WIP]**
1. Submit the pull request from the first day when you started your development and prefix the title of the pull request with **[WIP]**

2. Give your pull request a **helpful title** that summarizing your contribution.
2. Give your pull request title and branch name should contain **helpful** information summarizing your contribution.

3. Give your branch a **helpful name** summarizing your contribution (fork the repo and create a new branch for pull request).
3. Include "resolves #issue_number" in the title and the description of the pull request.

4. Also, **add the issue number** which it addresses.
If there is no associated issue, feel free to [create one](https://github.com/jhfjhfj1/autokeras/issues).

5. If merging the pull requests resolve one or more other issues.
In both the title and the description of the pull request, write "resolves #issue_number" to link the issue.

6. For the case of bug fixes, at the time of the PR,
4. For the case of bug fixes, at the time of the PR,
the test case should fail for the code base in the master branch and pass for the PR code.

7. Please prefix the title of your pull request with [MRG] if the contribution is complete and should be subjected to a detailed review.
An incomplete contribution – where you expect to do more work before receiving a full review – should be prefixed [WIP] (to indicate a work in progress) and changed to [MRG] when it matures.

8. When the status change from WIP to MRG, set the reviewer to
[@jhfjhfj1](https://github.com/jhfjhfj1). After the code review, @jhfjhfj1 will set the assign the assignee back to the contributor. The assignee will be set back to @jhfjhfj1 after the contributor has addressed all the code review comments and ready to be merged. This may go back and forth for several times.
5. The contribution is complete, change the **[WIP]** to **[MRG]**,
set the reviewer to
[@jhfjhfj1](https://github.com/jhfjhfj1).

9. Checkout from and pull request to the right branch.
6. Checkout from and pull request to the develop branch.
If it is a very urgent bug fix, checkout from master and pull request to both master and develop.
Otherwise, checkout from develop and pull request to develop.

## Code Style Guide
This project tries to closely follow the official Python Style Guide detailed in [PEP8](https://www.python.org/dev/peps/pep-0008/).
Expand Down
6 changes: 5 additions & 1 deletion README.md
Expand Up @@ -6,7 +6,6 @@
<a href="https://coveralls.io/github/jhfjhfj1/autokeras?branch=master"><img alt="Coverage Status" src="https://coveralls.io/repos/github/jhfjhfj1/autokeras/badge.svg?branch=master" style="width: 99px"/></a>
<a href="https://badge.fury.io/py/autokeras"><img src="https://badge.fury.io/py/autokeras.svg" alt="PyPI version" style="width: 125px"></a>
<a href="https://autokeras.com"><img src="https://readthedocs.org/projects/pip/badge/?version=latest&style=flat" alt="AutoKeras Official Website" style="width: 86px"></a>
<a href="https://gitter.im/autokeras/Lobby?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge"><img src="https://badges.gitter.im/autokeras/Lobby.svg" alt="Join the chat at https://gitter.im/autokeras/Lobby" style="width: 92px"></a>
</p>
</div>

Expand Down Expand Up @@ -35,6 +34,11 @@ Here is a short example of using the package.
clf.fit(x_train, y_train)
results = clf.predict(x_test)

## Community

You can use Gitter to communicate with people who also interested in Auto-Keras.

<a href="https://gitter.im/autokeras/Lobby?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge"><img src="https://badges.gitter.im/autokeras/Lobby.svg" alt="Join the chat at https://gitter.im/autokeras/Lobby" style="width: 92px"></a>

## Citing this work

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