ADD: glove and deep1b

.gitattributes

@@ -53,3 +53,9 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.jpg filter=lfs diff=lfs merge=lfs -text
 *.jpeg filter=lfs diff=lfs merge=lfs -text
 *.webp filter=lfs diff=lfs merge=lfs -text
+deep1b/base.10M.fbin filter=lfs diff=lfs merge=lfs -text
+glove/glove_50k_50.txt filter=lfs diff=lfs merge=lfs -text
+sift1m/sift_learn.fvecs filter=lfs diff=lfs merge=lfs -text
+sift1m/sift_base.fvecs filter=lfs diff=lfs merge=lfs -text
+sift1m/sift_query.fvecs filter=lfs diff=lfs merge=lfs -text
+sift1m/sift_groundtruth.ivecs filter=lfs diff=lfs merge=lfs -text

deep1b/base.10M.fbin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:290b341abc7ba570541e013fd20fd6d38c5873490ef395b512de5ed8dee18ce7
+size 3840000008

deep1b/loading.py

@@ -0,0 +1,23 @@
+import numpy as np
+
+def read_fbin(filename, start_idx=0, chunk_size=None):
+    """ Read *.fbin file that contains float32 vectors
+    Args:
+        :param filename (str): path to *.fbin file
+        :param start_idx (int): start reading vectors from this index
+        :param chunk_size (int): number of vectors to read.
+                                 If None, read all vectors
+    Returns:
+        Array of float32 vectors (numpy.ndarray)
+    """
+    with open(filename, "rb") as f:
+        nvecs, dim = np.fromfile(f, count=2, dtype=np.int32)
+        nvecs = (nvecs - start_idx) if chunk_size is None else chunk_size
+        arr = np.fromfile(f, count=nvecs * dim, dtype=np.float32,
+                          offset=start_idx * 4 * dim)
+    return arr.reshape(nvecs, dim)
+
+
+# read data
+# chunk_size = 50000
+# dataset = read_fbin('deep1B/base.10M.fbin', chunk_size=chunk_size)

glove/glove_50k_50.txt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a146f296bb010d2e4660c0dfd38ee85ba4830799a9efc633fcc0d3f80dda4a9d
+size 21328184

glove/loading.py

@@ -0,0 +1,2 @@
+from gensim.models import KeyedVectors
+dataset = KeyedVectors.load_word2vec_format('glove_50k_50.txt')