Fix deep_recommender KerasRS example. (#2114)

Rank of cross feature was incorrect.

Author: hertschuh

examples/keras_rs/deep_recommender.py

@@ -433,7 +433,9 @@ def preprocess_rating(x):
             "raw_user_age": features["raw_user_age"],
             "user_gender": features["user_gender"],
             "user_occupation_label": features["user_occupation_label"],
-            "user_gender_X_raw_user_age": features["user_gender_X_raw_user_age"],
+            "user_gender_X_raw_user_age": tf.squeeze(
+                features["user_gender_X_raw_user_age"], axis=-1
+            ),
             # Movie inputs are movie ID, vectorized title and genres
             "movie_id": int(x["movie_id"]),
             "movie_title_vector": features["movie_title"],

examples/keras_rs/ipynb/deep_recommender.ipynb

@@ -745,7 +745,9 @@
     "            \"raw_user_age\": features[\"raw_user_age\"],\n",
     "            \"user_gender\": features[\"user_gender\"],\n",
     "            \"user_occupation_label\": features[\"user_occupation_label\"],\n",
-    "            \"user_gender_X_raw_user_age\": features[\"user_gender_X_raw_user_age\"],\n",
+    "            \"user_gender_X_raw_user_age\": tf.squeeze(\n",
+    "                features[\"user_gender_X_raw_user_age\"], axis=-1\n",
+    "            ),\n",
     "            # Movie inputs are movie ID, vectorized title and genres\n",
     "            \"movie_id\": int(x[\"movie_id\"]),\n",
     "            \"movie_title_vector\": features[\"movie_title\"],\n",

examples/keras_rs/md/deep_recommender.md

@@ -497,7 +497,9 @@ def preprocess_rating(x):
             "raw_user_age": features["raw_user_age"],
             "user_gender": features["user_gender"],
             "user_occupation_label": features["user_occupation_label"],
-            "user_gender_X_raw_user_age": features["user_gender_X_raw_user_age"],
+            "user_gender_X_raw_user_age": tf.squeeze(
+                features["user_gender_X_raw_user_age"], axis=-1
+            ),
             # Movie inputs are movie ID, vectorized title and genres
             "movie_id": int(x["movie_id"]),
             "movie_title_vector": features["movie_title"],