We are currently solving the following issue within our repository. Here is the issue text:
--- BEGIN ISSUE ---
"numpy.linalg.linalg.LinAlgError: N-th leading minor of the array is not positive definite" exception while training ImageClassifier
<!---
**If you are reporting a bug:**
*  Verify that your issue is not being currently addressed by other issues or pull requests.
*  Please note that Auto-Keras is only compatible with **Python 3.6**.
*  Tag the issue with the `bug report` tag.
-->

### Bug Description

When training ImageClassifier on float inputs of shape 80x92x24 on a binary classification task, this exception is thrown when AutoKeras lists all created models until this point and their respected losses and metrics. Here is a more complete log + stack trace:  http://termbin.com/gb3n

### Reproducing Steps

* Create a dataset of noise shaped 80x92x24 with ~360 or so samples
*  Respective binary labels.

In my case, some values of the dataset are quite large (they vary between 0 and 1_000_000, but I'm not sure that this is related since AutoKeras performs normalization).

* Have it train on a GTX 1070Ti or equivalent in terms of vram for about an hour (can't confirm that it's GPU-related either).
* Wait for the exception


### Expected Behavior

It should work.

### Setup Details
 - OS type and version: Ubuntu 18.04
 - Python: 3.6
 - autokeras: 0.2.14 (installed manually from git)
- all dependencies are installed as stated in requirements.txt for this release, unless for:
- tensorflow 1.10, compiled locally. 


--- END ISSUE ---

Below are some code segments, each from a relevant file. One or more of these files may contain bugs.
--- BEGIN FILES ---
Path: `setup.py`
Content:
```
1 from distutils.core import setup
2 
3 setup(
4     name='autokeras',
5     packages=['autokeras'],  # this must be the same as the name above
6     install_requires=['torch==0.4.1', 'torchvision==0.2.1', 'numpy>=1.14.5', 'keras==2.2.2', 'scikit-learn==0.19.1',
7                       'tensorflow>=1.10.0', 'tqdm==4.25.0'],
8     version='0.2.17',
9     description='AutoML for deep learning',
10     author='Haifeng Jin',
11     author_email='jhfjhfj1@gmail.com',
12     url='http://autokeras.com',
13     download_url='https://github.com/jhfjhfj1/autokeras/archive/0.2.17.tar.gz',
14     keywords=['automl'],  # arbitrary keywords
15     classifiers=[]
16 )
17
```
--- END FILES ---

Please first localize the bug based on the issue statement, and then generate a patch according to the `git diff` format fenced by three backticks.

Here is an example:

```diff
diff --git a/examples/server_async.py b/examples/server_async.py
--- a/examples/server_async.py
+++ b/examples/server_async.py
@@ -313,4 +313,4 @@
 
 
 if __name__ == "__main__":
-    asyncio.run(run_async_server("."), debug=True)
+    asyncio.run(run_async_server(), debug=True)
diff --git a/examples/server_sync.py b/examples/server_sync.py
--- a/examples/server_sync.py
+++ b/examples/server_sync.py
@@ -313,5 +313,5 @@
 
 
 if __name__ == "__main__":
-    server = run_sync_server(".")
+    server = run_sync_server()
     server.shutdown()

```

diff --git a/setup.py b/setup.py
--- a/setup.py
+++ b/setup.py
@@ -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='0.2.17',
+    version='0.2.18',
     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/0.2.17.tar.gz',
+    download_url='https://github.com/jhfjhfj1/autokeras/archive/0.2.18.tar.gz',
     keywords=['automl'],  # arbitrary keywords
     classifiers=[]
 )

{"golden_diff": "diff --git a/setup.py b/setup.py\n--- a/setup.py\n+++ b/setup.py\n@@ -5,12 +5,12 @@\n     packages=['autokeras'],  # this must be the same as the name above\n     install_requires=['torch==0.4.1', 'torchvision==0.2.1', 'numpy>=1.14.5', 'keras==2.2.2', 'scikit-learn==0.19.1',\n                       'tensorflow>=1.10.0', 'tqdm==4.25.0'],\n-    version='0.2.17',\n+    version='0.2.18',\n     description='AutoML for deep learning',\n     author='Haifeng Jin',\n     author_email='jhfjhfj1@gmail.com',\n     url='http://autokeras.com',\n-    download_url='https://github.com/jhfjhfj1/autokeras/archive/0.2.17.tar.gz',\n+    download_url='https://github.com/jhfjhfj1/autokeras/archive/0.2.18.tar.gz',\n     keywords=['automl'],  # arbitrary keywords\n     classifiers=[]\n )\n", "issue": "\"numpy.linalg.linalg.LinAlgError: N-th leading minor of the array is not positive definite\" exception while training ImageClassifier\n<!---\r\n**If you are reporting a bug:**\r\n*  Verify that your issue is not being currently addressed by other issues or pull requests.\r\n*  Please note that Auto-Keras is only compatible with **Python 3.6**.\r\n*  Tag the issue with the `bug report` tag.\r\n-->\r\n\r\n### Bug Description\r\n\r\nWhen training ImageClassifier on float inputs of shape 80x92x24 on a binary classification task, this exception is thrown when AutoKeras lists all created models until this point and their respected losses and metrics. Here is a more complete log + stack trace:  http://termbin.com/gb3n\r\n\r\n### Reproducing Steps\r\n\r\n* Create a dataset of noise shaped 80x92x24 with ~360 or so samples\r\n*  Respective binary labels.\r\n\r\nIn my case, some values of the dataset are quite large (they vary between 0 and 1_000_000, but I'm not sure that this is related since AutoKeras performs normalization).\r\n\r\n* Have it train on a GTX 1070Ti or equivalent in terms of vram for about an hour (can't confirm that it's GPU-related either).\r\n* Wait for the exception\r\n\r\n\r\n### Expected Behavior\r\n\r\nIt should work.\r\n\r\n### Setup Details\r\n - OS type and version: Ubuntu 18.04\r\n - Python: 3.6\r\n - autokeras: 0.2.14 (installed manually from git)\r\n- all dependencies are installed as stated in requirements.txt for this release, unless for:\r\n- tensorflow 1.10, compiled locally. \r\n\n", "before_files": [{"content": "from distutils.core import setup\n\nsetup(\n    name='autokeras',\n    packages=['autokeras'],  # this must be the same as the name above\n    install_requires=['torch==0.4.1', 'torchvision==0.2.1', 'numpy>=1.14.5', 'keras==2.2.2', 'scikit-learn==0.19.1',\n                      'tensorflow>=1.10.0', 'tqdm==4.25.0'],\n    version='0.2.17',\n    description='AutoML for deep learning',\n    author='Haifeng Jin',\n    author_email='jhfjhfj1@gmail.com',\n    url='http://autokeras.com',\n    download_url='https://github.com/jhfjhfj1/autokeras/archive/0.2.17.tar.gz',\n    keywords=['automl'],  # arbitrary keywords\n    classifiers=[]\n)\n", "path": "setup.py"}], "after_files": [{"content": "from distutils.core import setup\n\nsetup(\n    name='autokeras',\n    packages=['autokeras'],  # this must be the same as the name above\n    install_requires=['torch==0.4.1', 'torchvision==0.2.1', 'numpy>=1.14.5', 'keras==2.2.2', 'scikit-learn==0.19.1',\n                      'tensorflow>=1.10.0', 'tqdm==4.25.0'],\n    version='0.2.18',\n    description='AutoML for deep learning',\n    author='Haifeng Jin',\n    author_email='jhfjhfj1@gmail.com',\n    url='http://autokeras.com',\n    download_url='https://github.com/jhfjhfj1/autokeras/archive/0.2.18.tar.gz',\n    keywords=['automl'],  # arbitrary keywords\n    classifiers=[]\n)\n", "path": "setup.py"}]}