Removing all code that has been moved to Tensorflow (#169)

* Removing all code that has been moved to Tensorflow. Import skflow from tensorflow now.

* update travis script to use TF 0.8

* Updated readme

* cleanup extra imports in __init__

* corrected version of py3 tensorflow

Author: ilblackdragon

README.rst

@@ -4,52 +4,19 @@ SkFlow has been moved to Tensorflow.
 SkFlow has been moved to http://github.com/tensorflow/tensorflow into contrib folder specifically located `here <https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/learn/python/learn>`__.
 The development will continue there. Please submit any issues and pull requests to Tensorflow repository instead. 
 
-This repository will ramp down, including after next Tensorflow release we will wind down code here. Please see instructions on most recent installation `here <https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/learn/python/learn>`__.
-
-Previously:
-
-|Travis-CI Build Status| |Codecov Status| |License| |PyPI version| |Join the chat at
-https://gitter.im/tensorflow/skflow|
-
-Scikit Flow
-===========
-
-This is a simplified interface for TensorFlow, to get people started on predictive analytics and data mining.
-
-Library covers variety of needs from linear models to *Deep Learning* applications like text and image understanding.
-
-Why *TensorFlow*? 
------------------
-- TensorFlow provides a good backbone for building different shapes of machine learning applications. 
-- It will continue to evolve both in the distributed direction and as general pipelinining machinery.
-
-Why *Scikit Flow*? 
------------------
-- To smooth the transition from the Scikit Learn world of one-liner machine learning into the more open world of building different shapes of ML models. You can start by using fit/predict and slide into TensorFlow APIs as you are getting comfortable. 
-- To provide a set of reference models that would be easy to integrate with existing code.
+This repository will ramp down, including after next Tensorflow release we will wind down code here. 
+Please see instructions on most recent installation `here <https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/learn/python/learn>`__.
 
 Installation
-============
+------------
 
-Dependencies
------------
-- Python: 2.7, 3.4+ 
-- Scikit learn: 0.16, 0.17, 0.18+ 
-- Tensorflow: 0.7+
+No installation needed, SkFlow has been moved into Tensorflow 0.8+.
+Make sure you have Tensorflow 0.8+ version and you can start using SkFlow right away by importing like this:
 
-First, you need to make sure you have `TensorFlow <https://github.com/tensorflow/tensorflow#installation>`__ and `Scikit Learn <http://scikit-learn.org/stable/install.html>`__ installed. 
-
-Run the following to install the stable version from PyPI:
-
-.. code:: bash
-
-    pip install skflow
-
-Or run the following to install from the development version from Github:
+.. code:: python
 
-.. code:: bash
+    import tensorflow.contrib.learn as skflow
 
-    pip install git+git://github.com/tensorflow/skflow.git
 
 Tutorial
 --------
@@ -90,7 +57,7 @@ Simple linear classification:
 
 .. code:: python
 
-    import skflow
+    import tensorflow.contrib.learn as skflow
     from sklearn import datasets, metrics
 
     iris = datasets.load_iris()
@@ -106,7 +73,7 @@ Simple linear regression:
 
 .. code:: python
 
-    import skflow
+    import tensorflow.contrib.learn as skflow
     from sklearn import datasets, metrics, preprocessing
 
     boston = datasets.load_boston()
@@ -123,7 +90,7 @@ Example of 3 layer network with 10, 20 and 10 hidden units respectively:
 
 .. code:: python
 
-    import skflow
+    import tensorflow.contrib.learn as skflow
     from sklearn import datasets, metrics
 
     iris = datasets.load_iris()
@@ -139,7 +106,7 @@ Example of how to pass a custom model to the TensorFlowEstimator:
 
 .. code:: python
 
-    import skflow
+    import tensorflow.contrib.learn as skflow
     from sklearn import datasets, metrics
 
     iris = datasets.load_iris()
@@ -163,7 +130,7 @@ Some example code:
 
 .. code:: python
 
-    import skflow
+    import tensorflow.contrib.learn as skflow
 
     classifier = skflow.TensorFlowLinearRegression()
     classifier.fit(...)

scripts/travis_install.sh

@@ -39,15 +39,15 @@ case "$TASK" in
             "linux")
                 case "$TRAVIS_PYTHON_VERSION" in
                     "2.7")
-                        TENSORFLOW_PACKAGE_URL="https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.7.1-cp27-none-linux_x86_64.whl"
+                        TENSORFLOW_PACKAGE_URL="https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.8.0rc0-cp27-none-linux_x86_64.whl"
                     ;;
                     "3.4")
-                        TENSORFLOW_PACKAGE_URL="https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.7.1-cp34-none-linux_x86_64.whl"
+                        TENSORFLOW_PACKAGE_URL="https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.8.0rc0-cp34-cp34m-linux_x86_64.whl"
                     ;;
                 esac
             ;;
             "osx")
-                TENSORFLOW_PACKAGE_URL="https://storage.googleapis.com/tensorflow/mac/tensorflow-0.7.1-py2-none-any.whl"
+                TENSORFLOW_PACKAGE_URL="https://storage.googleapis.com/tensorflow/mac/tensorflow-0.8.0rc0-py2-none-any.whl"
             ;;
         esac
         pip install "$TENSORFLOW_PACKAGE_URL"  --ignore-installed six

skflow/__init__.py

@@ -13,24 +13,12 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 
-import pkg_resources as pkg_rs
-import numpy as np
-import tensorflow as tf
+import warnings
 
-from skflow.io import *
-from skflow.estimators import *
-from skflow import ops
-from skflow import preprocessing
-from skflow.io import data_feeder
-from skflow import models
-from skflow.trainer import TensorFlowTrainer
+try:
+    from tensorflow.contrib.learn import *
+    warnings.warn("skflow as separate library is deprecated. "
+                  "Use import tensorflow.contrib.learn as skflow instead.", DeprecationWarning)
+except ImportError:
+    raise ImportError("Update your Tensorflow to 0.8+ to use latest skflow.")
 
-__version__, SKLEARN_VERSION, TF_VERSION = \
-[pkg_rs.get_distribution(pkg).version for pkg in ['skflow', 'scikit-learn', 'tensorflow']]
-
-if SKLEARN_VERSION < '0.16.0':
-    raise ImportError("Your scikit-learn version needs to be at least 0.16. "
-                      "Your current version is %s. " % SKLEARN_VERSION)
-if TF_VERSION < '0.7.0':
-    raise ImportError("Your tensorflow version needs to be at least 0.7. "
-                      "Your current version is %s. " % TF_VERSION)