GPflow 2.0 notebook update: GPs for big data (#1048)

notebooks2/ci_utils.py → gpflow/ci_utils.py

@@ -1,4 +1,4 @@
-# Copyright 2017 Artem Artemev @awav
+# Copyright 2017-2019 GPflow
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.

gpflow/inducing_variables/inducing_variables.py

@@ -22,23 +22,19 @@
 
 class InducingVariables(tf.Module):
     """
-    Abstract base class for inducing inducing.
+    Abstract base class for inducing variables.
     """
 
     @abc.abstractmethod
     def __len__(self) -> int:
         """
-        Returns the number of inducing, relevant for example to determine the
-        size of the variational distribution.
+        Returns the number of inducing variables, relevant for example
+        to determine the size of the variational distribution.
         """
         pass
 
 
-class InducingPoints(InducingVariables):
-    """
-    Real-space inducing points
-    """
-
+class InducingPointsBase(InducingVariables):
     def __init__(self, Z):
         """
         :param Z: the initial positions of the inducing points, size [M, D]
@@ -50,9 +46,16 @@ def __len__(self):
         return self.Z.shape[0]
 
 
-class Multiscale(InducingPoints):
+class InducingPoints(InducingPointsBase):
+    """
+    Real-space inducing points
+    """
+
+
+class Multiscale(InducingPointsBase):
     """
-    Multi-scale inducing inducing
+    Multi-scale inducing variables
+
     Originally proposed in
 
     ::

gpflow/models/svgp.py

@@ -43,27 +43,24 @@ class SVGP(GPModel):
     def __init__(self,
                  kernel,
                  likelihood,
-                 inducing_variable=None,
+                 inducing_variable,
                  mean_function=None,
-                 num_latent=1,
-                 q_diag=False,
+                 *,
+                 num_latent: int=1,
+                 q_diag: bool=False,
                  q_mu=None,
                  q_sqrt=None,
-                 whiten=True,
+                 whiten: bool=True,
                  num_data=None):
         """
-        - X is a data matrix, size [N, D]
-        - Y is a data matrix, size [N, P]
-        - kernel, likelihood, mean_function are appropriate GPflow objects
-        - Z is a matrix of pseudo inputs, size [M, D]
-        - num_latent is the number of latent process to use, default to
-          Y.shape[1]
+        - kernel, likelihood, inducing_variables, mean_function are appropriate
+          GPflow objects
+        - num_latent is the number of latent processes to use, defaults to 1
         - q_diag is a boolean. If True, the covariance is approximated by a
           diagonal matrix.
         - whiten is a boolean. If True, we use the whitened representation of
           the inducing points.
-        - minibatch_size, if not None, turns on mini-batching with that size.
-        - num_data is the total number of observations, default to X.shape[0]
+        - num_data is the total number of observations, defaults to X.shape[0]
           (relevant when feeding in external minibatches)
         """
         # init the super class, accept args

notebooks2/advanced/multioutput.ipynb

@@ -69,14 +69,7 @@
     "import gpflow as gpf\n",
     "\n",
     "from gpflow.utilities import print_summary\n",
-    "\n",
-    "import sys\n",
-    "from pathlib import Path\n",
-    "module_path = str(Path(\"..\").absolute().resolve())\n",
-    "if module_path not in sys.path:\n",
-    "    sys.path.append(module_path)\n",
-    "\n",
-    "from ci_utils import ci_niter\n",
+    "from gpflow.ci_utils import ci_niter\n",
     "\n",
     "gpf.config.set_default_float(np.float64)\n",
     "gpf.config.set_summary_fmt(\"notebook\")\n",

notebooks2/basics/gplvm.ipynb

@@ -28,14 +28,7 @@
     "import gpflow\n",
     "from gpflow.utilities import ops, print_summary\n",
     "from gpflow.config import set_default_float, default_float, set_summary_fmt\n",
-    "\n",
-    "import sys\n",
-    "from pathlib import Path\n",
-    "module_path = str(Path(\"..\").absolute().resolve())\n",
-    "if module_path not in sys.path:\n",
-    "    sys.path.append(module_path)\n",
-    "\n",
-    "from ci_utils import ci_niter\n",
+    "from gpflow.ci_utils import ci_niter\n",
     "\n",
     "set_default_float(np.float64)\n",
     "set_summary_fmt(\"notebook\")\n",