Merge 7380e27c93 into 72eda9a24f

cr-mixer/server/src/main/scala/com/twitter/cr_mixer/CrMixerServer.scala

@@ -40,7 +40,7 @@ import com.twitter.cr_mixer.module.similarity_engine.ProducerBasedUnifiedSimilar
 import com.twitter.cr_mixer.module.similarity_engine.SimClustersANNSimilarityEngineModule
 import com.twitter.cr_mixer.module.similarity_engine.TweetBasedUnifiedSimilarityEngineModule
 import com.twitter.cr_mixer.module.similarity_engine.TweetBasedQigSimilarityEngineModule
-import com.twitter.cr_mixer.module.similarity_engine.TweetBasedTwHINSimlarityEngineModule
+import com.twitter.cr_mixer.module.similarity_engine.TweetBasedTwHINSimilarityEngineModule
 import com.twitter.cr_mixer.module.similarity_engine.TweetBasedUserAdGraphSimilarityEngineModule
 import com.twitter.cr_mixer.module.similarity_engine.TweetBasedUserTweetGraphSimilarityEngineModule
 import com.twitter.cr_mixer.module.similarity_engine.TweetBasedUserVideoGraphSimilarityEngineModule
@@ -180,7 +180,7 @@ class CrMixerServer extends ThriftServer with Mtls with HttpServer with HttpMtls
         TripCandidateStoreModule,
         TwiceClustersMembersStoreModule,
         TweetBasedQigSimilarityEngineModule,
-        TweetBasedTwHINSimlarityEngineModule,
+        TweetBasedTwHINSimilarityEngineModule,
         TweetBasedUnifiedSimilarityEngineModule,
         TweetBasedUserAdGraphSimilarityEngineModule,
         TweetBasedUserTweetGraphSimilarityEngineModule,

cr-mixer/server/src/main/scala/com/twitter/cr_mixer/module/similarity_engine/TweetBasedTwHINSimlarityEngineModule.scala

@@ -21,7 +21,7 @@ import com.twitter.cr_mixer.similarity_engine.SimilarityEngine.SimilarityEngineC
 import com.twitter.cr_mixer.thriftscala.SimilarityEngineType
 import com.twitter.finagle.memcached.{Client => MemcachedClient}
 
-object TweetBasedTwHINSimlarityEngineModule extends TwitterModule {
+object TweetBasedTwHINSimilarityEngineModule extends TwitterModule {
   @Provides
   @Named(ModuleNames.TweetBasedTwHINANNSimilarityEngine)
   def providesTweetBasedTwHINANNSimilarityEngine(

navi/thrift_bpr_adapter/thrift/src/decoder.rs

@@ -6,7 +6,7 @@ enum FeatureVal {
   FloatVector(Vec<f32>),
 }
 
-// A Feture has a name and a value
+// A Feature has a name and a value
 // The name for now is 'id' of type string
 // Eventually this needs to be flexible - example to accomodate feature-id
 struct Feature {

src/java/com/twitter/search/earlybird_root/common/EarlybirdFeatureSchemaMerger.java

@@ -149,7 +149,7 @@ public class EarlybirdFeatureSchemaMerger {
    * (This is done inside superroot)
    * @param requestContext the search request context
    * @param mergedResponse the merged result inside the superroot
-   * @param realtimeResponse the realtime tier resposne
+   * @param realtimeResponse the realtime tier response
    * @param protectedResponse the protected tier response
    * @param fullArchiveResponse the full archive tier response
    * @param statsPrefix

twml/libtwml/src/lib/TensorRecordReader.cpp

@@ -178,7 +178,7 @@ RawTensor TensorRecordReader::readStringTensor() {
         CHECK_THRIFT_TYPE(readByte(), TTYPE_STRING, "data_type");
         length = readInt32();
         // Store the current location of the byte stream.
-        // Use this at to "deocde strings" at a later point.
+        // Use this at to "decode strings" at a later point.
         data = getBuffer();
         for (int32_t i = 0; i < length; i++) {
           // Skip reading the strings

twml/twml/contrib/utils/math_fns.py

@@ -7,7 +7,7 @@ from tensorflow.python.ops import array_ops, math_ops
 def safe_div(numerator, denominator, name=None):
   """
   Example usage: calculating NDCG = DCG / IDCG to handle cases when
-  IDCG = 0 returns 0 instead of Infinity 
+  IDCG = 0 returns 0 instead of Infinity
   Do not use this dividing funciton unless it makes sense to your problem
   Divides two tensors element-wise, returns 0 if the denominator is <= 0.
   Args:
@@ -56,7 +56,7 @@ def cal_swapped_ndcg(label_scores, predicted_scores, top_k_int):
   Args:
     label_scores: a real `Tensor`.
     predicted_scores: a real `Tensor`, with dtype matching label_scores
-    top_k_int: An int or an int `Tensor`. 
+    top_k_int: An int or an int `Tensor`.
   Returns:
     a `Tensor` that holds swapped NDCG by .
   """
@@ -100,7 +100,7 @@ def _dcg_idcg(relevance_scores, cg_discount):
     relevance_scores: a real `Tensor`.
     cg_discount: a real `Tensor`, with dtype matching relevance_scores
   Returns:
-    a `Tensor` that holds \\sum_{i=1}^k \frac{relevance_scores_k}{cg_discount}  
+    a `Tensor` that holds \\sum_{i=1}^k \frac{relevance_scores_k}{cg_discount}
   """
   # cg_discount is safe
   dcg_k = relevance_scores / cg_discount
@@ -115,8 +115,8 @@ def _get_ranking_orders(label_scores, predicted_scores, top_k_int=1):
     predicted_scores: a real `Tensor`, with dtype matching label_scores
     top_k_int: an integer or an int `Tensor`.
   Returns:
-    two `Tensors` that hold sorted_labels: the ground truth relevance socres
-    and predicted_order: relevance socres based on sorted predicted_scores
+    two `Tensors` that hold sorted_labels: the ground truth relevance scores
+    and predicted_order: relevance scores based on sorted predicted_scores
   """
   # sort predictions_scores and label_scores
   # size [batch_size/num of DataRecords, 1]
@@ -141,7 +141,7 @@ def _get_cg_discount(top_k_int=1):
   Args:
     top_k_int: An int or an int `Tensor`.
   Returns:
-    a `Tensor` that holds \log_{2}(i + 1), i \in [1, k] 
+    a `Tensor` that holds \log_{2}(i + 1), i \in [1, k]
   """
   log_2 = tf.log(tf.constant(2.0, dtype=tf.float32))
   # top_k_range needs to start from 1 to top_k_int