0.2.17 (#231) · keras-team/autokeras@c74731b

Commit

0.2.17 (#231)

* 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

* 0.2.17

Loading branch information

haifeng-jin committed Oct 1, 2018

1 parent 82962a4 commit c74731b

autokeras/image_supervised.py

            
                      Original file line number
                      Diff line number
                      Diff line change
                  
    @@ -248,7 +248,7 @@ def fit(self, x_train=None, y_train=None, time_limit=None):
  
                if len(self.load_searcher().history) == 0:

                    raise TimeoutError("Search Time too short. No model was found during the search time.")

                elif self.verbose:

                    print('Time is out.')

                    print('\nTime limit for model search is reached. Ending the model search.')

        @abstractmethod

        def get_n_output_node(self):

    @@ -315,6 +315,8 @@ def final_fit(self, x_train, y_train, x_test, y_test, trainer_args=None, retrain
  
            searcher = self.load_searcher()

            graph = searcher.load_best_model()

            if self.verbose:

                print('\nLoading and training the best model recorded from the search.')

            if retrain:

                graph.weighted = False

autokeras/model_trainer.py

            
                      Original file line number
                      Diff line number
                      Diff line change
                  
    @@ -64,6 +64,8 @@ def __init__(self, model, **kwargs):
  
            self.model.to(self.device)

            self.optimizer = None

            self.early_stop = None

            self.current_epoch = 0

            self.current_metric_value = 0

        def train_model(self,

                        max_iter_num=None,

    @@ -89,55 +91,33 @@ def train_model(self,
  
            test_loss_list = []

            self.optimizer = torch.optim.Adam(self.model.parameters())

            progress_bar = None

            if self.verbose:

                progress_bar = tqdm(total=max_iter_num,

                                    desc='    Model    ',

                                    file=sys.stdout,

                                    leave=False,

                                    ncols=75,

                                    position=1,

                                    unit=' epoch')

            for epoch in range(max_iter_num):

                self._train()

                test_loss, metric_value = self._test()

                self.current_metric_value = metric_value

                test_metric_value_list.append(metric_value)

                test_loss_list.append(test_loss)

                if self.verbose:

                    progress_bar.update(1)

                    if epoch == 0:

                        header = ['Epoch', 'Loss', 'Accuracy']

                        line = '|'.join(x.center(24) for x in header)

                        progress_bar.write('+' + '-' * len(line) + '+')

                        progress_bar.write('|' + line + '|')

                        progress_bar.write('+' + '-' * len(line) + '+')

                    r = [epoch + 1, test_loss, metric_value]

                    line = '|'.join(str(x).center(24) for x in r)

                    progress_bar.write('|' + line + '|')

                    progress_bar.write('+' + '-' * len(line) + '+')

                decreasing = self.early_stop.on_epoch_end(test_loss)

                if not decreasing:

                    if self.verbose:

                        print('\nNo loss decrease after {} epochs.\n'.format(max_no_improvement_num))

                    break

            if self.verbose:

                progress_bar.close()

            last_num = min(max_no_improvement_num, max_iter_num)

            return (sum(test_loss_list[-last_num:]) / last_num,

                    sum(test_metric_value_list[-last_num:]) / last_num)

        def _train(self):

            self.model.train()

            loader = self.train_loader

            self.current_epoch += 1

            cp_loader = deepcopy(loader)

            if self.verbose:

                progress_bar = tqdm(total=len(cp_loader),

                                    desc='Current Epoch',

                                    desc='Epoch-' + str(self.current_epoch) + ', Current Metric - ' + str(self.current_metric_value),

                                    file=sys.stdout,

                                    leave=False,

                                    ncols=75,

                                    ncols=100,

                                    position=0,

                                    unit=' batch')

autokeras/search.py

            
                      Original file line number
                      Diff line number
                      Diff line change
                  
    @@ -129,7 +129,9 @@ def add_model(self, metric_value, loss, graph, model_id):
  
                line = '|'.join(x.center(24) for x in header)

                print('+' + '-' * len(line) + '+')

                print('|' + line + '|')

                for i, r in enumerate(self.history):

                if self.history:

                    r = self.history[-1]

                    print('+' + '-' * len(line) + '+')

                    line = '|'.join(str(r[x]).center(24) for x in idx)

                    print('|' + line + '|')

    @@ -219,7 +221,7 @@ def search(self, train_data, test_data, timeout=60 * 60 * 24):
  
                if not re.search('out of memory', str(e)):

                    raise e

                if self.verbose:

                    print('out of memory')

                    print('\nCurrent model size is too big. Discontinuing training this model to search for other models.')

                Constant.MAX_MODEL_SIZE = graph.size() - 1

                return

            finally:

setup.py

            
                      Original file line number
                      Diff line number
                      Diff line change
                  
    @@ -5,12 +5,12 @@
  
        packages=['autokeras'],  # this must be the same as the name above

        install_requires=['torch==0.4.1', 'torchvision==0.2.1', 'numpy>=1.14.5', 'keras==2.2.2', 'scikit-learn==0.19.1',

                          'tensorflow>=1.10.0', 'tqdm==4.25.0'],

        version='0.2.15',

        version='0.2.17',

        description='AutoML for deep learning',

        author='Haifeng Jin',

        author_email='jhfjhfj1@gmail.com',

        url='http://autokeras.com',

        download_url='https://github.com/jhfjhfj1/autokeras/archive/0.2.15.tar.gz',

        download_url='https://github.com/jhfjhfj1/autokeras/archive/0.2.17.tar.gz',

        keywords=['automl'],  # arbitrary keywords

        classifiers=[]

    )

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