Added helper class for getting tf variables from loss function (#184)

* Added helper class for getting tf variables from loss function

* Updated usage and documentation

* Removed try-catches

* Added futures

* Added documentation

* fixes and tests

* more tests

* install tensorflow in travis

test/tensorflow_test.py

@@ -0,0 +1,53 @@
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
+import unittest
+import tensorflow as tf
+import ray
+
+class TensorFlowTest(unittest.TestCase):
+
+  def testTensorFlowVariables(self):
+    ray.init(start_ray_local=True, num_workers=2)
+
+    x_data = tf.placeholder(tf.float32, shape=[100])
+    y_data = tf.placeholder(tf.float32, shape=[100])
+
+    w = tf.Variable(tf.random_uniform([1], -1.0, 1.0))
+    b = tf.Variable(tf.zeros([1]))
+    y = w * x_data + b
+    loss = tf.reduce_mean(tf.square(y - y_data))
+
+    sess = tf.Session()
+    sess.run(tf.global_variables_initializer())
+
+    variables = ray.experimental.TensorFlowVariables(loss, sess)
+    weights = variables.get_weights()
+
+    for (name, val) in weights.items():
+      weights[name] += 1.0
+
+    variables.set_weights(weights)
+    self.assertEqual(weights, variables.get_weights())
+
+    w2 = tf.Variable(tf.random_uniform([1], -1.0, 1.0), name="w")
+    b2 = tf.Variable(tf.zeros([1]), name="b")
+    y2 = w2 * x_data + b2
+    loss2 = tf.reduce_mean(tf.square(y2 - y_data))
+
+    sess.run(tf.global_variables_initializer())
+
+    variables2 = ray.experimental.TensorFlowVariables(loss2, sess)
+    weights2 = variables2.get_weights()
+
+    for (name, val) in weights2.items():
+      weights2[name] += 2.0
+
+    variables2.set_weights(weights2)
+    self.assertEqual(weights2, variables2.get_weights())
+
+    ray.worker.cleanup()
+
+if __name__ == "__main__":
+  unittest.main(verbosity=2)