Add l2 normalization if needed when setting vector as target

MTG · Dec 11, 2024 · 8f29b21 · 8f29b21
1 parent 9f0fba6
commit 8f29b21
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Showing 2 changed files with 12 additions and 4 deletions.
diff --git a/utils/search/backends/solr555pysolr.py b/utils/search/backends/solr555pysolr.py
@@ -33,7 +33,7 @@
 from utils.text import remove_control_chars
 from utils.search import SearchEngineBase, SearchResults, SearchEngineException
 from utils.search.backends.solr_common import SolrQuery, SolrResponseInterpreter
-from utils.similarity_utilities import get_similarity_search_target_vector
+from utils.similarity_utilities import get_similarity_search_target_vector, get_l2_normalized_vector
 
 
 SOLR_FORUM_URL = f"{settings.SOLR5_BASE_URL}/forum"
@@ -278,9 +278,7 @@ def add_similarity_vectors_to_documents(self, sound_objects, documents):
 
                         if config_options.get('l2_norm', False):
                             # Normalize the vector to have unit length
-                            norm = math.sqrt(sum([v*v for v in vector_data]))
-                            if norm > 0:
-                                vector_data = [v/norm for v in vector_data]
+                            vector_data = get_l2_normalized_vector(vector_data)
 
                         sim_vector_document_data = {
                             'content_type': SOLR_DOC_CONTENT_TYPES['similarity_vector'],

diff --git a/utils/similarity_utilities.py b/utils/similarity_utilities.py
@@ -19,6 +19,7 @@
 #
 
 import logging
+import math
 import traceback
 
 from django.conf import settings
@@ -170,6 +171,13 @@ def hash_cache_key(key):
     return create_hash(key, limit=32)
 
 
+def get_l2_normalized_vector(vector):
+    norm = math.sqrt(sum([v*v for v in vector]))
+    if norm > 0:
+        vector = [v/norm for v in vector]
+    return vector
+
+
 def get_similarity_search_target_vector(sound_id, analyzer=settings.SEARCH_ENGINE_DEFAULT_SIMILARITY_ANALYZER):
     # If the sound has been analyzed for similarity, returns the vector to be used for similarity search
     sa = sounds.models.SoundAnalysis.objects.filter(sound_id=sound_id, analyzer=analyzer, analysis_status="OK")
@@ -180,5 +188,7 @@ def get_similarity_search_target_vector(sound_id, analyzer=settings.SEARCH_ENGIN
             if data is not None:
                 vector_raw = data[config_options['vector_property_name']]
                 if vector_raw is not None:
+                    if config_options['l2_norm']:
+                        vector_raw = get_l2_normalized_vector(vector_raw)
                     return vector_raw
     return None