[WIP] Update tutorial examples (#342)

* Remove transitional print import.

* Add example for multiple GPUs in python.

* Add example on GPU in C++.

* Add example on multiple GPUs in C++.

* Add IVFFlat example on GPU in python.

* Add Makefile for C++ tutorial examples.

* Add IVF index on GPU example in C++.

tutorial/python/1-Flat.py

@@ -4,7 +4,6 @@
 # This source code is licensed under the BSD+Patents license found in the
 # LICENSE file in the root directory of this source tree.
 
-from __future__ import print_function
 import numpy as np
 
 d = 64                           # dimension

tutorial/python/2-IVFFlat.py

@@ -4,7 +4,6 @@
 # This source code is licensed under the BSD+Patents license found in the
 # LICENSE file in the root directory of this source tree.
 
-from __future__ import print_function
 import numpy as np
 
 d = 64                           # dimension

tutorial/python/3-IVFPQ.py

@@ -4,7 +4,6 @@
 # This source code is licensed under the BSD+Patents license found in the
 # LICENSE file in the root directory of this source tree.
 
-from __future__ import print_function
 import numpy as np
 
 d = 64                           # dimension

tutorial/python/4-GPU.py

@@ -4,7 +4,6 @@
 # This source code is licensed under the BSD+Patents license found in the
 # LICENSE file in the root directory of this source tree.
 
-from __future__ import print_function
 import numpy as np
 
 d = 64                           # dimension
@@ -16,20 +15,46 @@ xb[:, 0] += np.arange(nb) / 1000.
 xq = np.random.random((nq, d)).astype('float32')
 xq[:, 0] += np.arange(nq) / 1000.
 
-import faiss                   # make faiss available
+import faiss                     # make faiss available
 
 print("number of GPUs:", faiss.get_num_gpus())
 
-index = faiss.IndexFlatL2(d)   # build the index
+res = faiss.StandardGpuResources()  # use a single GPU
 
-res = faiss.StandardGpuResources()
+## Using a flat index
 
-index = faiss.index_cpu_to_gpu(res, 0, index)
+index_flat = faiss.IndexFlatL2(d)  # build a flat (CPU) index
 
-index.add(xb)                  # add vectors to the index
-print(index.ntotal)
+# make it a flat GPU index
+gpu_index_flat = faiss.index_cpu_to_gpu(res, 0, index_flat)
+
+gpu_index_flat.add(xb)         # add vectors to the index
+print(gpu_index_flat.ntotal)
 
 k = 4                          # we want to see 4 nearest neighbors
-D, I = index.search(xq, k)     # actual search
+D, I = gpu_index_flat.search(xq, k)  # actual search
+print(I[:5])                   # neighbors of the 5 first queries
+print(I[-5:])                  # neighbors of the 5 last queries
+
+
+## Using an IVF index
+
+nlist = 100
+quantizer = faiss.IndexFlatL2(d)  # the other index
+index_ivf = faiss.IndexIVFFlat(quantizer, d, nlist, faiss.METRIC_L2)
+# here we specify METRIC_L2, by default it performs inner-product search
+
+# make it an IVF GPU index
+gpu_index_ivf = faiss.index_cpu_to_gpu(res, 0, index_ivf)
+
+assert not gpu_index_ivf.is_trained
+gpu_index_ivf.train(xb)        # add vectors to the index
+assert gpu_index_ivf.is_trained
+
+gpu_index_ivf.add(xb)          # add vectors to the index
+print(gpu_index_ivf.ntotal)
+
+k = 4                          # we want to see 4 nearest neighbors
+D, I = gpu_index_ivf.search(xq, k)  # actual search
 print(I[:5])                   # neighbors of the 5 first queries
 print(I[-5:])                  # neighbors of the 5 last queries

tutorial/python/5-Multiple-GPUs.py

@@ -0,0 +1,34 @@
+# Copyright (c) 2015-present, Facebook, Inc.
+# All rights reserved.
+#
+# This source code is licensed under the BSD+Patents license found in the
+# LICENSE file in the root directory of this source tree.
+
+import numpy as np
+
+d = 64                           # dimension
+nb = 100000                      # database size
+nq = 10000                       # nb of queries
+np.random.seed(1234)             # make reproducible
+xb = np.random.random((nb, d)).astype('float32')
+xb[:, 0] += np.arange(nb) / 1000.
+xq = np.random.random((nq, d)).astype('float32')
+xq[:, 0] += np.arange(nq) / 1000.
+
+import faiss                     # make faiss available
+
+ngpus = faiss.get_num_gpus()
+
+print("number of GPUs:", ngpus)
+
+index = faiss.index_cpu_to_all_gpus( # build the index
+    faiss.IndexFlatL2(d)
+)
+
+index.add(xb)                  # add vectors to the index
+print(index.ntotal)
+
+k = 4                          # we want to see 4 nearest neighbors
+D, I = index.search(xq, k)     # actual search
+print(I[:5])                   # neighbors of the 5 first queries
+print(I[-5:])                  # neighbors of the 5 last queries