Fix smoke tests

Signed-off-by: Jun Ki Min <[email protected]>
recommenders-team · Dec 19, 2023 · 9ecf302 · 9ecf302
1 parent 649f1b2
commit 9ecf302
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Showing 3 changed files with 20 additions and 26 deletions.
diff --git a/examples/02_model_collaborative_filtering/baseline_deep_dive.ipynb b/examples/02_model_collaborative_filtering/baseline_deep_dive.ipynb
@@ -78,7 +78,7 @@
                 "    mae,\n",
                 "    rsquared,\n",
                 "    exp_var,\n",
-                "    map_at_k,\n",
+                "    map,\n",
                 "    ndcg_at_k,\n",
                 "    precision_at_k,\n",
                 "    recall_at_k,\n",
@@ -689,7 +689,7 @@
             "source": [
                 "cols[\"col_prediction\"] = \"Count\"\n",
                 "\n",
-                "eval_map = map_at_k(test, baseline_recommendations, k=TOP_K, **cols)\n",
+                "eval_map = map(test, baseline_recommendations, k=TOP_K, **cols)\n",
                 "eval_ndcg = ndcg_at_k(test, baseline_recommendations, k=TOP_K, **cols)\n",
                 "eval_precision = precision_at_k(test, baseline_recommendations, k=TOP_K, **cols)\n",
                 "eval_recall = recall_at_k(test, baseline_recommendations, k=TOP_K, **cols)\n",

diff --git a/examples/02_model_collaborative_filtering/cornac_bpr_deep_dive.ipynb b/examples/02_model_collaborative_filtering/cornac_bpr_deep_dive.ipynb
@@ -49,7 +49,7 @@
                 "\n",
                 "from recommenders.datasets import movielens\n",
                 "from recommenders.datasets.python_splitters import python_random_split\n",
-                "from recommenders.evaluation.python_evaluation import map_at_k, ndcg_at_k, precision_at_k, recall_at_k\n",
+                "from recommenders.evaluation.python_evaluation import map, ndcg_at_k, precision_at_k, recall_at_k\n",
                 "from recommenders.models.cornac.cornac_utils import predict_ranking\n",
                 "from recommenders.utils.timer import Timer\n",
                 "from recommenders.utils.constants import SEED\n",
@@ -557,7 +557,7 @@
             ],
             "source": [
                 "k = 10\n",
-                "eval_map = map_at_k(test, all_predictions, col_prediction='prediction', k=k)\n",
+                "eval_map = map(test, all_predictions, col_prediction='prediction', k=k)\n",
                 "eval_ndcg = ndcg_at_k(test, all_predictions, col_prediction='prediction', k=k)\n",
                 "eval_precision = precision_at_k(test, all_predictions, col_prediction='prediction', k=k)\n",
                 "eval_recall = recall_at_k(test, all_predictions, col_prediction='prediction', k=k)\n",

diff --git a/tests/smoke/examples/test_notebooks_gpu.py b/tests/smoke/examples/test_notebooks_gpu.py
@@ -43,9 +43,7 @@ def test_ncf_deep_dive_smoke(notebooks, output_notebook, kernel_name):
         notebook_path,
         output_notebook,
         kernel_name=kernel_name,
-        parameters=dict(
-            TOP_K=10, MOVIELENS_DATA_SIZE="100k", EPOCHS=1, BATCH_SIZE=1024
-        ),
+        parameters=dict(TOP_K=10, MOVIELENS_DATA_SIZE="100k", EPOCHS=1, BATCH_SIZE=1024),
     )
     results = read_notebook(output_notebook)
 
@@ -91,19 +89,15 @@ def test_xdeepfm_smoke(notebooks, output_notebook, kernel_name):
         output_notebook,
         kernel_name=kernel_name,
         parameters=dict(
-            EPOCHS_FOR_SYNTHETIC_RUN=1,
-            EPOCHS_FOR_CRITEO_RUN=1,
-            BATCH_SIZE_SYNTHETIC=128,
-            BATCH_SIZE_CRITEO=512,
+            EPOCHS=1,
+            BATCH_SIZE=512,
             RANDOM_SEED=42,
         ),
     )
     results = read_notebook(output_notebook)
 
-    assert results["res_syn"]["auc"] == pytest.approx(0.5043, rel=TOL, abs=ABS_TOL)
-    assert results["res_syn"]["logloss"] == pytest.approx(0.7046, rel=TOL, abs=ABS_TOL)
-    assert results["res_real"]["auc"] == pytest.approx(0.7251, rel=TOL, abs=ABS_TOL)
-    assert results["res_real"]["logloss"] == pytest.approx(0.508, rel=TOL, abs=ABS_TOL)
+    assert results["auc"] == pytest.approx(0.7251, rel=TOL, abs=ABS_TOL)
+    assert results["logloss"] == pytest.approx(0.508, rel=TOL, abs=ABS_TOL)
 
 
 @pytest.mark.notebooks
@@ -140,14 +134,14 @@ def test_naml_smoke(notebooks, output_notebook, kernel_name):
         notebook_path,
         output_notebook,
         kernel_name=kernel_name,
-        parameters=dict(epochs=1, seed=42, MIND_type="demo"),
+        parameters=dict(epochs=1, batch_size=64, seed=42, MIND_type="demo"),
     )
     results = read_notebook(output_notebook)
 
-    assert results["res_syn"]["group_auc"] == pytest.approx(
+    assert results["group_auc"] == pytest.approx(
         0.5801, rel=TOL, abs=ABS_TOL
     )
-    assert results["res_syn"]["mean_mrr"] == pytest.approx(0.2512, rel=TOL, abs=ABS_TOL)
+    assert results["mean_mrr"] == pytest.approx(0.2512, rel=TOL, abs=ABS_TOL)
 
 
 @pytest.mark.notebooks
@@ -162,10 +156,10 @@ def test_nrms_smoke(notebooks, output_notebook, kernel_name):
     )
     results = read_notebook(output_notebook)
 
-    assert results["res_syn"]["group_auc"] == pytest.approx(
+    assert results["group_auc"] == pytest.approx(
         0.5768, rel=TOL, abs=ABS_TOL
     )
-    assert results["res_syn"]["mean_mrr"] == pytest.approx(0.2457, rel=TOL, abs=ABS_TOL)
+    assert results["mean_mrr"] == pytest.approx(0.2457, rel=TOL, abs=ABS_TOL)
 
 
 @pytest.mark.notebooks
@@ -176,14 +170,14 @@ def test_npa_smoke(notebooks, output_notebook, kernel_name):
         notebook_path,
         output_notebook,
         kernel_name=kernel_name,
-        parameters=dict(epochs=1, seed=42, MIND_type="demo"),
+        parameters=dict(epochs=1, batch_size=64, seed=42, MIND_type="demo"),
     )
     results = read_notebook(output_notebook)
 
-    assert results["res_syn"]["group_auc"] == pytest.approx(
+    assert results["group_auc"] == pytest.approx(
         0.5861, rel=TOL, abs=ABS_TOL
     )
-    assert results["res_syn"]["mean_mrr"] == pytest.approx(0.255, rel=TOL, abs=ABS_TOL)
+    assert results["mean_mrr"] == pytest.approx(0.255, rel=TOL, abs=ABS_TOL)
 
 
 @pytest.mark.notebooks
@@ -194,14 +188,14 @@ def test_lstur_smoke(notebooks, output_notebook, kernel_name):
         notebook_path,
         output_notebook,
         kernel_name=kernel_name,
-        parameters=dict(epochs=1, seed=40, MIND_type="demo"),
+        parameters=dict(epochs=1, batch_size=64, seed=40, MIND_type="demo"),
     )
     results = read_notebook(output_notebook)
 
-    assert results["res_syn"]["group_auc"] == pytest.approx(
+    assert results["group_auc"] == pytest.approx(
         0.5977, rel=TOL, abs=ABS_TOL
     )
-    assert results["res_syn"]["mean_mrr"] == pytest.approx(0.2618, rel=TOL, abs=ABS_TOL)
+    assert results["mean_mrr"] == pytest.approx(0.2618, rel=TOL, abs=ABS_TOL)
 
 
 @pytest.mark.notebooks