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mihaicmihaic
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Update SVS parameters
WS_SEARCH is now SEARCH_WINDOW_SIZE. NUM_THREADS was removed.
1 parent 340c9e6 commit 97f2105

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2 files changed

+11
-19
lines changed

2 files changed

+11
-19
lines changed

‎engine/clients/redis/search.py‎

Lines changed: 2 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -38,7 +38,7 @@ def init_client(cls, host, distance, connection_params: dict, search_params: dic
3838
if cls.hybrid_policy != "ADHOC_BF":
3939
cls.knn_conditions = "EF_RUNTIME $EF"
4040
elif cls.algorithm == "SVS-VAMANA":
41-
cls.knn_conditions = "WS_SEARCH $WS_SEARCH"
41+
cls.knn_conditions = "SEARCH_WINDOW_SIZE $SEARCH_WINDOW_SIZE"
4242
cls.data_type = "FLOAT32"
4343
if "search_params" in cls.search_params:
4444
cls.data_type = (
@@ -97,7 +97,7 @@ def search_one(cls, vector, meta_conditions, top) -> List[Tuple[int, float]]:
9797
if cls.hybrid_policy != "ADHOC_BF":
9898
params_dict["EF"] = cls.search_params["search_params"]["ef"]
9999
if cls.algorithm == "SVS-VAMANA":
100-
params_dict["WS_SEARCH"] = cls.search_params["search_params"]["WS_SEARCH"]
100+
params_dict["SEARCH_WINDOW_SIZE"] = cls.search_params["search_params"]["SEARCH_WINDOW_SIZE"]
101101
results = cls._ft.search(q, query_params=params_dict)
102102

103103
return [(int(result.id), float(result.vector_score)) for result in results.docs]

‎experiments/configurations/dbpedia-calibration.json‎

Lines changed: 9 additions & 17 deletions
Original file line numberDiff line numberDiff line change
@@ -67,7 +67,6 @@
6767
"algorithm": "svs-vamana",
6868
"data_type": "FLOAT16",
6969
"svs-vamana_config": {
70-
"NUM_THREADS": 16,
7170
"DISTANCE_METRIC": "L2",
7271
"GRAPH_MAX_DEGREE": 32,
7372
"CONSTRUCTION_WINDOW_SIZE": 200
@@ -78,7 +77,7 @@
7877
"algorithm": "svs-vamana",
7978
"parallel": 100,
8079
"top": 100,
81-
"calibration_param": "WS_SEARCH",
80+
"calibration_param": "SEARCH_WINDOW_SIZE",
8281
"calibration_precision": 0.95,
8382
"search_params": {
8483
"data_type": "FLOAT16"
@@ -99,7 +98,6 @@
9998
"algorithm": "svs-vamana",
10099
"data_type": "FLOAT32",
101100
"svs-vamana_config": {
102-
"NUM_THREADS": 16,
103101
"DISTANCE_METRIC": "L2",
104102
"GRAPH_MAX_DEGREE": 32,
105103
"CONSTRUCTION_WINDOW_SIZE": 200
@@ -110,7 +108,7 @@
110108
"algorithm": "svs-vamana",
111109
"parallel": 100,
112110
"top": 100,
113-
"calibration_param": "WS_SEARCH",
111+
"calibration_param": "SEARCH_WINDOW_SIZE",
114112
"calibration_precision": 0.95,
115113
"search_params": {
116114
"data_type": "FLOAT32"
@@ -131,7 +129,6 @@
131129
"algorithm": "svs-vamana",
132130
"data_type": "FLOAT16",
133131
"svs-vamana_config": {
134-
"NUM_THREADS": 16,
135132
"DISTANCE_METRIC": "L2",
136133
"GRAPH_MAX_DEGREE": 32,
137134
"CONSTRUCTION_WINDOW_SIZE": 200,
@@ -143,7 +140,7 @@
143140
"algorithm": "svs-vamana",
144141
"parallel": 100,
145142
"top": 100,
146-
"calibration_param": "WS_SEARCH",
143+
"calibration_param": "SEARCH_WINDOW_SIZE",
147144
"calibration_precision": 0.95,
148145
"search_params": {
149146
"data_type": "FLOAT16"
@@ -164,7 +161,6 @@
164161
"algorithm": "svs-vamana",
165162
"data_type": "FLOAT32",
166163
"svs-vamana_config": {
167-
"NUM_THREADS": 16,
168164
"DISTANCE_METRIC": "L2",
169165
"GRAPH_MAX_DEGREE": 32,
170166
"CONSTRUCTION_WINDOW_SIZE": 200,
@@ -176,7 +172,7 @@
176172
"algorithm": "svs-vamana",
177173
"parallel": 100,
178174
"top": 100,
179-
"calibration_param": "WS_SEARCH",
175+
"calibration_param": "SEARCH_WINDOW_SIZE",
180176
"calibration_precision": 0.95,
181177
"search_params": {
182178
"data_type": "FLOAT32"
@@ -197,7 +193,6 @@
197193
"algorithm": "svs-vamana",
198194
"data_type": "FLOAT32",
199195
"svs-vamana_config": {
200-
"NUM_THREADS": 16,
201196
"DISTANCE_METRIC": "L2",
202197
"GRAPH_MAX_DEGREE": 32,
203198
"CONSTRUCTION_WINDOW_SIZE": 200,
@@ -209,7 +204,7 @@
209204
"algorithm": "svs-vamana",
210205
"parallel": 100,
211206
"top": 100,
212-
"calibration_param": "WS_SEARCH",
207+
"calibration_param": "SEARCH_WINDOW_SIZE",
213208
"calibration_precision": 0.95,
214209
"search_params": {
215210
"data_type": "FLOAT32"
@@ -230,7 +225,6 @@
230225
"algorithm": "svs-vamana",
231226
"data_type": "FLOAT16",
232227
"svs-vamana_config": {
233-
"NUM_THREADS": 16,
234228
"DISTANCE_METRIC": "L2",
235229
"GRAPH_MAX_DEGREE": 32,
236230
"CONSTRUCTION_WINDOW_SIZE": 200,
@@ -242,7 +236,7 @@
242236
"algorithm": "svs-vamana",
243237
"parallel": 100,
244238
"top": 100,
245-
"calibration_param": "WS_SEARCH",
239+
"calibration_param": "SEARCH_WINDOW_SIZE",
246240
"calibration_precision": 0.95,
247241
"search_params": {
248242
"data_type": "FLOAT16"
@@ -263,7 +257,6 @@
263257
"algorithm": "svs-vamana",
264258
"data_type": "FLOAT16",
265259
"svs-vamana_config": {
266-
"NUM_THREADS": 16,
267260
"DISTANCE_METRIC": "L2",
268261
"GRAPH_MAX_DEGREE": 32,
269262
"CONSTRUCTION_WINDOW_SIZE": 200,
@@ -275,7 +268,7 @@
275268
"algorithm": "svs-vamana",
276269
"parallel": 100,
277270
"top": 100,
278-
"calibration_param": "WS_SEARCH",
271+
"calibration_param": "SEARCH_WINDOW_SIZE",
279272
"calibration_precision": 0.95,
280273
"search_params": {
281274
"data_type": "FLOAT16"
@@ -296,7 +289,6 @@
296289
"algorithm": "svs-vamana",
297290
"data_type": "FLOAT32",
298291
"svs-vamana_config": {
299-
"NUM_THREADS": 16,
300292
"DISTANCE_METRIC": "L2",
301293
"GRAPH_MAX_DEGREE": 32,
302294
"CONSTRUCTION_WINDOW_SIZE": 200,
@@ -308,7 +300,7 @@
308300
"algorithm": "svs-vamana",
309301
"parallel": 100,
310302
"top": 100,
311-
"calibration_param": "WS_SEARCH",
303+
"calibration_param": "SEARCH_WINDOW_SIZE",
312304
"calibration_precision": 0.95,
313305
"search_params": {
314306
"data_type": "FLOAT32"
@@ -321,4 +313,4 @@
321313
"algorithm": "svs-vamana"
322314
}
323315
}
324-
]
316+
]

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