fix: sparse weights iterator end->end

VowpalWabbit · Sep 29, 2023 · 443f31b · 443f31b
1 parent de52303
commit 443f31b
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Showing 6 changed files with 75 additions and 2 deletions.
diff --git a/test/core.vwtest.json b/test/core.vwtest.json
@@ -6017,5 +6017,33 @@
     "input_files": [
       "train-sets/single_empty_lines.txt"
     ]
+  },
+  {
+    "id": 465,
+    "desc": "cb_explore_adf with epsilon-greedy exploration using --sparse_weights and saving model",
+    "vw_command": "--cb_explore_adf --epsilon 0.1 -d train-sets/cb_test.ldf --noconstant --sparse_weights -f standard_sparse_model.vw",
+    "diff_files": {
+      "stderr": "train-sets/ref/sparse_save_check.stderr",
+      "stdout": "train-sets/ref/sparse_save_check.stdout"
+    },
+    "input_files": [
+      "train-sets/cb_test.ldf"
+    ]
+  },
+  {
+    "id": 466,
+    "desc": "cb_explore_adf with epsilon-greedy exploration using --sparse_weights and loading model",
+    "vw_command": "--cb_explore_adf --epsilon 0.1 -d train-sets/cb_test.ldf --noconstant --sparse_weights -i standard_sparse_model.vw",
+    "diff_files": {
+      "stderr": "train-sets/ref/sparse_load_check.stderr",
+      "stdout": "train-sets/ref/sparse_load_check.stdout"
+    },
+    "input_files": [
+      "train-sets/cb_test.ldf",
+      "standard_sparse_model.vw"
+    ],
+    "depends_on": [
+      465
+    ]
   }
 ]
diff --git a/test/train-sets/ref/sparse_load_check.stderr b/test/train-sets/ref/sparse_load_check.stderr
@@ -0,0 +1,22 @@
+using no cache
+Reading datafile = train-sets/cb_test.ldf
+num sources = 1
+Num weight bits = 18
+learning rate = 0.5
+initial_t = 3
+power_t = 0.5
+cb_type = mtr
+Enabled learners: gd, scorer-identity, csoaa_ldf-rank, cb_adf, cb_explore_adf_greedy, shared_feature_merger
+Input label = CB
+Output pred = ACTION_PROBS
+average  since         example        example        current        current  current
+loss     last          counter         weight          label        predict features
+0.066667 0.066667            1            1.0        0:1:0.5         1:0.48       15
+0.033333 0.000000            2            2.0        1:0:0.5         1:0.95        6
+
+finished run
+number of examples = 3
+weighted example sum = 3.000000
+weighted label sum = 0.000000
+average loss = 0.033333
+total feature number = 27
diff --git a/test/train-sets/ref/sparse_load_check.stdout b/test/train-sets/ref/sparse_load_check.stdout
diff --git a/test/train-sets/ref/sparse_save_check.stderr b/test/train-sets/ref/sparse_save_check.stderr
@@ -0,0 +1,23 @@
+final_regressor = standard_sparse_model.vw
+using no cache
+Reading datafile = train-sets/cb_test.ldf
+num sources = 1
+Num weight bits = 18
+learning rate = 0.5
+initial_t = 0
+power_t = 0.5
+cb_type = mtr
+Enabled learners: gd, scorer-identity, csoaa_ldf-rank, cb_adf, cb_explore_adf_greedy, shared_feature_merger
+Input label = CB
+Output pred = ACTION_PROBS
+average  since         example        example        current        current  current
+loss     last          counter         weight          label        predict features
+0.666667 0.666667            1            1.0        0:1:0.5         0:0.33       15
+0.333333 0.000000            2            2.0        1:0:0.5         1:0.95        6
+
+finished run
+number of examples = 3
+weighted example sum = 3.000000
+weighted label sum = 0.000000
+average loss = 0.333333
+total feature number = 27
diff --git a/test/train-sets/ref/sparse_save_check.stdout b/test/train-sets/ref/sparse_save_check.stdout
diff --git a/vowpalwabbit/core/include/vw/core/array_parameters_sparse.h b/vowpalwabbit/core/include/vw/core/array_parameters_sparse.h
@@ -75,11 +75,11 @@ class sparse_parameters
 
   // iterator with stride
   iterator begin() { return iterator(_map.begin()); }
-  iterator end() { return iterator(_map.begin()); }
+  iterator end() { return iterator(_map.end()); }
 
   // const iterator
   const_iterator cbegin() const { return const_iterator(_map.begin()); }
-  const_iterator cend() const { return const_iterator(_map.begin()); }
+  const_iterator cend() const { return const_iterator(_map.end()); }
 
   inline VW::weight& operator[](size_t i) { return *(get_or_default_and_get(i)); }