forecaster docs bugfix

docs/source/forecaster.rst

@@ -73,9 +73,9 @@ Unless otherwise specified, the performance is reported using the ThresholdDecis
 +=====================+===================================+=======+======+=======+=======+======+==========+=========================+
 | Gemma2 9B           | ThresholdDecisionPolicy           | 71.0  | 69.1 | 76.1  | 72.3  | 34.2 | 3.9      | +1.8 (8.4 - 6.6)        |
 +---------------------+-----------------------------------+-------+------+-------+-------+------+----------+-------------------------+
-| Gemma2 9B           | DeferralDecisionPolicy            | 70.9  | 72.0 | 68.4  | 70.1  | 26.7 | 3.8      | -0.1 (7.0 - 7.1)        |
+| Gemma2 9B           | DeferralDecisionPolicy            | 70.9  | 72.1 | 68.4  | 70.2  | 26.7 | 3.8      | -0.1 (7.0 - 7.1)        |
 +---------------------+-----------------------------------+-------+------+-------+-------+------+----------+-------------------------+
-| Gemma2 9B           | SimulationAverageDecisionPolicy   | 70.2  | 68.1 | 76.6  | 72.0  | 36.1 | 4.0      | -1.2 (9.3 - 10.5)       |
+| Gemma2 9B           | SimulationAverageDecisionPolicy   | 70.2  | 68.1 | 76.6  | 72.0  | 36.2 | 4.0      | -1.2 (9.3 - 10.5)       |
 +---------------------+-----------------------------------+-------+------+-------+-------+------+----------+-------------------------+
 | Mistral 7B          | ThresholdDecisionPolicy           | 70.7  | 68.8 | 76.0  | 72.1  | 34.6 | 4.0      | +2.9 (8.1 - 5.2)        |
 +---------------------+-----------------------------------+-------+------+-------+-------+------+----------+-------------------------+

examples/forecaster/Run Transformer Fine-tuned Models.ipynb

@@ -12,7 +12,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [
     {
@@ -26,26 +26,29 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "2026-06-27 20:18:39.864582: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.\n",
-      "2026-06-27 20:18:39.887405: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n",
+      "/reef/lyk25/ConvoKit/dist/.venv/lib/python3.12/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
+      "  from .autonotebook import tqdm as notebook_tqdm\n",
       "WARNING: All log messages before absl::InitializeLog() is called are written to STDERR\n",
-      "E0000 00:00:1782591519.912052  859600 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n",
-      "E0000 00:00:1782591519.919822  859600 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n",
-      "W0000 00:00:1782591519.938735  859600 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.\n",
-      "W0000 00:00:1782591519.938755  859600 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.\n",
-      "W0000 00:00:1782591519.938757  859600 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.\n",
-      "W0000 00:00:1782591519.938760  859600 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.\n",
-      "2026-06-27 20:18:39.944875: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n",
-      "To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n"
+      "I0000 00:00:1782619476.409075 1013993 port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.\n",
+      "I0000 00:00:1782619476.481779 1013993 cpu_feature_guard.cc:227] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n",
+      "To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n",
+      "WARNING: All log messages before absl::InitializeLog() is called are written to STDERR\n",
+      "I0000 00:00:1782619477.990444 1013993 port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.\n"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "INFO 06-27 20:18:48 [__init__.py:216] Automatically detected platform cuda.\n",
       "🦥 Unsloth Zoo will now patch everything to make training faster!\n"
      ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Unable to import `torchao` Tensor objects. This may affect loading checkpoints serialized with `torchao`\n"
+     ]
     }
    ],
    "source": [
@@ -78,16 +81,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [],
    "source": [
     "# CPU mode (noting that it will be slower)\n",
     "DEVICE = \"cuda\"\n",
     "\n",
-    "corpus_name = \"cga-wikiconv\"\n",
+    "# corpus_name = \"cga-wikiconv\"\n",
     "# corpus_name = \"cga-cmv-legacy\"\n",
-    "# corpus_name = \"cga-cmv-large\"\n",
+    "corpus_name = \"cga-cmv-large\"\n",
     "label_metadata = \"has_removed_comment\" if 'cmv' in corpus_name else 'conversation_has_personal_attack'\n",
     "\n",
     "YOUR_MODEL_DIRECTORY = \"YOUR_MODEL_DIRECTORY\"\n",
@@ -96,7 +99,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [
     {
@@ -125,7 +128,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -223,11 +226,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [],
    "source": [
-    "def transform_selector(context_tuple, corpus_name):\n",
+    "def transform_selector(context_tuple):\n",
     "    \"\"\"\n",
     "    For transform we only need to check that the conversation is in the test split\n",
     "    \"\"\"\n",
@@ -238,7 +241,7 @@
     "    matches_split = (context_tuple.current_utterance.get_conversation().meta[\"split\"] == \"test\")\n",
     "    is_end = (len(context_tuple.context) == convo_length)\n",
     "\n",
-    "    if corpus_name.contains(\"cmv\"):\n",
+    "    if \"cmv\" in corpus_name:\n",
     "        return (matches_split)\n",
     "    else:\n",
     "        return (matches_split and not is_end)\n",
@@ -505,7 +508,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [
     {
@@ -813,7 +816,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": ".venv",
    "language": "python",
    "name": "python3"
   },
@@ -827,7 +830,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.11"
+   "version": "3.12.4"
   }
  },
  "nbformat": 4,