Changes for tf0.12 (GPflow#307)

* Changes for tf0.12.

* Modified tests as well, updated readme & version.

* Update .travis.yml

.travis.yml

@@ -17,7 +17,7 @@ install:
   # Replace dep1 dep2 ... with your dependencies
   - conda create -q -n test-environment python=3.5 numpy scipy pandas nose
   - source activate test-environment
-  - pip install https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.11.0-cp35-cp35m-linux_x86_64.whl
+  - pip install https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.12.1-cp35-cp35m-linux_x86_64.whl
   - python setup.py install
 script:
   - nosetests --nologcapture testing

GPflow/_version.py

@@ -13,4 +13,4 @@
 # limitations under the License.
 
 
-__version__ = "0.3.4"
+__version__ = "0.3.5"

GPflow/kernels.py

@@ -77,7 +77,7 @@ def __init__(self, input_dim, active_dims=None):
         """
         Parameterized.__init__(self)
         self.scoped_keys.extend(['K', 'Kdiag'])
-        self.input_dim = input_dim
+        self.input_dim = int(input_dim)
         if active_dims is None:
             self.active_dims = slice(input_dim)
         elif type(active_dims) is slice:

GPflow/model.py

@@ -138,7 +138,7 @@ def _compile(self, optimizer=None):
             else:
                 opt_step = optimizer.minimize(self._minusF,
                                               var_list=[self._free_vars])
-            init = tf.initialize_all_variables()
+            init = tf.global_variables_initializer()
         self._session.run(init)
 
         # build tensorflow functions for computing the likelihood

GPflow/param.py

@@ -206,7 +206,7 @@ def get_samples_df(self, samples):
         end = start + self.size
         samples = samples[:, start:end]
         samples = samples.reshape((samples.shape[0],) + self.shape)
-        samples = self.transform.forward(samples)
+        samples = np.atleast_1d(self.transform.forward(samples))
         return pd.Series([v for v in samples], name=self.long_name)
 
     def make_tf_array(self, free_array):
@@ -529,7 +529,7 @@ def runnable(instance, *np_args):
                     storage['feed_dict_keys'] = instance.get_feed_dict_keys()
                     feed_dict = {}
                     instance.update_feed_dict(storage['feed_dict_keys'], feed_dict)
-                    storage['session'].run(tf.initialize_all_variables(), feed_dict=feed_dict)
+                    storage['session'].run(tf.global_variables_initializer(), feed_dict=feed_dict)
             feed_dict = dict(zip(storage['tf_args'], np_args))
             feed_dict[storage['free_vars']] = instance.get_free_state()
             instance.update_feed_dict(storage['feed_dict_keys'], feed_dict)

README.md

@@ -15,7 +15,7 @@ GPflow implements modern Gaussian process inference for composable kernels and l
 # Install
 
 ## 1) Install TensorFlow. 
-Please see instructions on the main TensorFlow [webpage](https://www.tensorflow.org/versions/r0.11/get_started/os_setup.html#download-and-setup). You will need version 0.11. We find that for most users pip installation is the fastest way to get going.
+Please see instructions on the main TensorFlow [webpage](https://www.tensorflow.org/versions/r0.12/get_started/os_setup.html#download-and-setup). You will need version 0.12. We find that for most users pip installation is the fastest way to get going.
 
 ## 2) install package
 GPflow includes some tensorflow extensions that are compiled when you run setup.py.  For those interested in modifying the source of GPflow, we recommend  

RELEASE.md

@@ -1,3 +1,6 @@
+# Release 0.3.5
+ - Update to work with TensorFlow 0.12.1.
+
 # Release 0.3.4
  - Changes to stop computations all being done on the default graph.
  - Update list of GPflow contributors and other small changes to front page.

setup.py

@@ -46,7 +46,7 @@
       package_dir={'GPflow': 'GPflow'},
       py_modules=['GPflow.__init__'],
       test_suite='testing',
-      install_requires=['numpy>=1.9', 'scipy>=0.16', 'tensorflow>=0.11.0rc1', 'pandas>=0.18.1'],
+      install_requires=['numpy>=1.9', 'scipy>=0.16', 'tensorflow==0.12.1', 'pandas>=0.18.1'],
       classifiers=['License :: OSI Approved :: BSD License',
                    'Natural Language :: English',
                    'Operating System :: MacOS :: MacOS X',

testing/test_likelihoods.py

@@ -235,7 +235,7 @@ def setUp(self):
         self.sess = tf.Session()
         free_array = self.switched_likelihood.get_free_state()
         self.switched_likelihood.make_tf_array(free_array)
-        self.sess.run(tf.initialize_all_variables())
+        self.sess.run(tf.global_variables_initializer())
 
     def test_logp(self):
         # switchedlikelihood
@@ -258,7 +258,7 @@ def test_predict_density(self):
         # likelihood
         rslts = []
         for lik, y, f, fvar in zip(self.likelihoods, self.Y_list, self.F_list, self.Fvar_list):
-            self.sess.run(tf.initialize_all_variables())
+            self.sess.run(tf.global_variables_initializer())
             with lik.tf_mode():
                 rslts.append(self.sess.run(lik.predict_density(f, fvar, y)))
 
@@ -273,7 +273,7 @@ def test_variational_expectations(self):
         # likelihood
         rslts = []
         for lik, y, f, fvar in zip(self.likelihoods, self.Y_list, self.F_list, self.Fvar_list):
-            self.sess.run(tf.initialize_all_variables())
+            self.sess.run(tf.global_variables_initializer())
             with lik.tf_mode():
                 rslts.append(self.sess.run(lik.variational_expectations(f, fvar, y)))
 

testing/test_mean_functions.py

@@ -222,7 +222,7 @@ def test(self):
         sess = tf.Session()
         tf_array = switched_mean.get_free_state()
         switched_mean.make_tf_array(tf_array)
-        sess.run(tf.initialize_all_variables())
+        sess.run(tf.global_variables_initializer())
         fd = {}
         switched_mean.update_feed_dict(switched_mean.get_feed_dict_keys(), fd)
         with switched_mean.tf_mode():