commit-message.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "264797cf-c1d0-4041-aa49-842324522403",
   "metadata": {},
   "source": [
    "# Common Constants"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "30c905ae-b80d-4d65-ac58-c39afdcb196a",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "from run_battery import BatteryRunner, BatteryConfigs\n",
    "\n",
    "runner = BatteryRunner.of(BatteryConfigs.CommitMessageGeneration)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "0659b8a4-71d9-4e8c-aba0-d58cb62e60ce",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loaded 100 cases!\n"
     ]
    }
   ],
   "source": [
    "runner.load_cases()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "0f0a6c8c-a366-48de-8348-5a019cd0222e",
   "metadata": {},
   "outputs": [],
   "source": [
    "from model_wrapper import ModelFamily"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "750f419d-f179-42bc-ae6d-1476d01d4299",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true
   },
   "source": [
    "# Generate Output"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "6b9f4ab3-f30e-473c-8e5b-3543e750c791",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "34e66e22cc3744a2994951bd2728c578",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HTML(value=\"<h1 style='font-weight: bold; border-bottom: 1px solid;'>Testing prompt index 0</h1>\")"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "# Testing prompt index 0\n",
      "Prompt to be tested:\n",
      "/* diff of changes\n",
      "{prompt}\n",
      "*/\n",
      "// a summary of the above diff is:\n",
      "// -\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "6cbf9735106e49d29e3e13f519f5e371",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HTML(value=\"<h2 style='font-weight: bold; border-bottom: 1px dotted;'>Loading 350M (Salesforce/codegen-350M-mu…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "## Loading 350M (Salesforce/codegen-350M-multi)\n",
      "[2024-06-01@20:50:44|model.device] Starting timer.\n",
      "Configuring torch device...\n",
      "Using device: cuda:0 aka cuda:0\n",
      "[2024-06-01@20:50:44|model.device] Time elapsed: 38ms\n",
      "[2024-06-01@20:50:44|model.tokenizer] Starting timer.\n",
      "[2024-06-01@20:50:44|model.tokenizer] Time elapsed: 336ms\n",
      "[2024-06-01@20:50:44|model.model] Starting timer.\n",
      "Obtaining model...\n",
      "[2024-06-01@20:50:51|model.model] Time elapsed: 6s 637ms\n",
      "Opening ./output/commit/prompt0/codegen1-multi-350M.output...\n",
      "95 entries found already, skipping that many...\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "b0234dbd00334bc6a6698f5769e4887a",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "VBox(children=(IntProgress(value=0, description='Progress:'), Label(value='Estimated time remaining: calculati…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "!! max size might be exceeded !!\n",
      "inputs so far: /* diff of changes\n",
      "diff --git a/guava-gwt/src-super/com/google/common/base/super/com/google/common/base/Stopwatch.java b/guava-gwt/src-super/com/google/common/base/super/com/google/common/base/Stopwatch.java\n",
      "index 73ce24e..531a0f3 100644\n",
      "--- a/guava-gwt/src-super/com/google/common/base/super/com/google/common/base/Stopwatch.java\n",
      "+++ b/guava-gwt/src-super/com/google/common/base/super/com/google/com [ ... 1913 bytes abbreviated ... ]    */\n",
      "   @Deprecated\n",
      "   public Stopwatch(Ticker ticker) {\n",
      "*/\n",
      "// a summary of the above diff is:\n",
      "// -\n",
      "Warning: Model returned no output (prompt may have been too large)\n",
      "!! max size might be exceeded !!\n",
      "inputs so far: /* diff of changes\n",
      "diff --git a/sql/src/main/java/io/crate/lucene/match/OptionParser.java b/sql/src/main/java/io/crate/lucene/match/OptionParser.java\n",
      "index 09047c4ff..171555a11 100644\n",
      "--- a/sql/src/main/java/io/crate/lucene/match/OptionParser.java\n",
      "+++ b/sql/src/main/java/io/crate/lucene/match/OptionParser.java\n",
      "@@ -161,7 +161,7 @@ public class OptionParser {\n",
      "         if (fuzziness == null) {\n",
      "       [ ... 1893 bytes abbreviated ... ]  assertThat(TestingHelpers.printedTable(response.rows()),\n",
      "*/\n",
      "// a summary of the above diff is:\n",
      "// -\n",
      "Warning: Model returned no output (prompt may have been too large)\n",
      "Done, 6s 66ms elapsed.\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "5a06030e045049c4abe8e005f9e659c8",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HTML(value=\"<h2 style='font-weight: bold; border-bottom: 1px dotted;'>Loading 2B (Salesforce/codegen-2B-multi)…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "## Loading 2B (Salesforce/codegen-2B-multi)\n",
      "[2024-06-01@20:50:57|model.device] Starting timer.\n",
      "Configuring torch device...\n",
      "Using device: cuda:0 aka cuda:0\n",
      "[2024-06-01@20:50:57|model.device] Time elapsed: ~0s\n",
      "[2024-06-01@20:50:57|model.tokenizer] Starting timer.\n",
      "[2024-06-01@20:50:57|model.tokenizer] Time elapsed: 178ms\n",
      "[2024-06-01@20:50:57|model.model] Starting timer.\n",
      "Obtaining model...\n",
      "[2024-06-01@20:51:32|model.model] Time elapsed: 35s 92ms\n",
      "Opening ./output/commit/prompt0/codegen1-multi-2B.output...\n",
      "95 entries found already, skipping that many...\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "2cf2d9a9bc114a13886aba43e0e230d0",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "VBox(children=(IntProgress(value=0, description='Progress:'), Label(value='Estimated time remaining: calculati…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "!! max size might be exceeded !!\n",
      "inputs so far: /* diff of changes\n",
      "diff --git a/guava-gwt/src-super/com/google/common/base/super/com/google/common/base/Stopwatch.java b/guava-gwt/src-super/com/google/common/base/super/com/google/common/base/Stopwatch.java\n",
      "index 73ce24e..531a0f3 100644\n",
      "--- a/guava-gwt/src-super/com/google/common/base/super/com/google/common/base/Stopwatch.java\n",
      "+++ b/guava-gwt/src-super/com/google/common/base/super/com/google/com [ ... 1913 bytes abbreviated ... ]    */\n",
      "   @Deprecated\n",
      "   public Stopwatch(Ticker ticker) {\n",
      "*/\n",
      "// a summary of the above diff is:\n",
      "// -\n",
      "Warning: Model returned no output (prompt may have been too large)\n",
      "!! max size might be exceeded !!\n",
      "inputs so far: /* diff of changes\n",
      "diff --git a/sql/src/main/java/io/crate/lucene/match/OptionParser.java b/sql/src/main/java/io/crate/lucene/match/OptionParser.java\n",
      "index 09047c4ff..171555a11 100644\n",
      "--- a/sql/src/main/java/io/crate/lucene/match/OptionParser.java\n",
      "+++ b/sql/src/main/java/io/crate/lucene/match/OptionParser.java\n",
      "@@ -161,7 +161,7 @@ public class OptionParser {\n",
      "         if (fuzziness == null) {\n",
      "       [ ... 1893 bytes abbreviated ... ]  assertThat(TestingHelpers.printedTable(response.rows()),\n",
      "*/\n",
      "// a summary of the above diff is:\n",
      "// -\n",
      "Warning: Model returned no output (prompt may have been too large)\n",
      "Done, 9s 551ms elapsed.\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "bb5598ad22b44e908aa7abc5d508ebe7",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HTML(value=\"<h2 style='font-weight: bold; border-bottom: 1px dotted;'>Loading 6B (Salesforce/codegen-6B-multi)…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "## Loading 6B (Salesforce/codegen-6B-multi)\n",
      "[2024-06-01@20:51:42|model.device] Starting timer.\n",
      "Configuring torch device...\n",
      "Using device: cuda:0 aka cuda:0\n",
      "[2024-06-01@20:51:42|model.device] Time elapsed: ~0s\n",
      "[2024-06-01@20:51:42|model.tokenizer] Starting timer.\n",
      "[2024-06-01@20:51:43|model.tokenizer] Time elapsed: 163ms\n",
      "[2024-06-01@20:51:43|model.model] Starting timer.\n",
      "Obtaining model...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:root:Some parameters are on the meta device device because they were offloaded to the cpu.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[2024-06-01@20:53:08|model.model] Time elapsed: 1min 25s\n",
      "Opening ./output/commit/prompt0/codegen1-multi-6B.output...\n",
      "95 entries found already, skipping that many...\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "c1705e1c2abf48dba9f8500db466bf0a",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "VBox(children=(IntProgress(value=0, description='Progress:'), Label(value='Estimated time remaining: calculati…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "!! max size might be exceeded !!\n",
      "inputs so far: /* diff of changes\n",
      "diff --git a/guava-gwt/src-super/com/google/common/base/super/com/google/common/base/Stopwatch.java b/guava-gwt/src-super/com/google/common/base/super/com/google/common/base/Stopwatch.java\n",
      "index 73ce24e..531a0f3 100644\n",
      "--- a/guava-gwt/src-super/com/google/common/base/super/com/google/common/base/Stopwatch.java\n",
      "+++ b/guava-gwt/src-super/com/google/common/base/super/com/google/com [ ... 1913 bytes abbreviated ... ]    */\n",
      "   @Deprecated\n",
      "   public Stopwatch(Ticker ticker) {\n",
      "*/\n",
      "// a summary of the above diff is:\n",
      "// -\n",
      "Warning: Model returned no output (prompt may have been too large)\n",
      "!! max size might be exceeded !!\n",
      "inputs so far: /* diff of changes\n",
      "diff --git a/sql/src/main/java/io/crate/lucene/match/OptionParser.java b/sql/src/main/java/io/crate/lucene/match/OptionParser.java\n",
      "index 09047c4ff..171555a11 100644\n",
      "--- a/sql/src/main/java/io/crate/lucene/match/OptionParser.java\n",
      "+++ b/sql/src/main/java/io/crate/lucene/match/OptionParser.java\n",
      "@@ -161,7 +161,7 @@ public class OptionParser {\n",
      "         if (fuzziness == null) {\n",
      "       [ ... 1893 bytes abbreviated ... ]  assertThat(TestingHelpers.printedTable(response.rows()),\n",
      "*/\n",
      "// a summary of the above diff is:\n",
      "// -\n",
      "Warning: Model returned no output (prompt may have been too large)\n",
      "Done, 1min 40s elapsed.\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "c5785cf0e1f34dee9e5d936b6e96bd5d",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HTML(value=\"<h2 style='font-weight: bold; border-bottom: 1px dotted;'>Loading 16B (Salesforce/codegen-16B-mult…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "## Loading 16B (Salesforce/codegen-16B-multi)\n",
      "[2024-06-01@20:54:49|model.device] Starting timer.\n",
      "Configuring torch device...\n",
      "Using device: cuda:0 aka cuda:0\n",
      "[2024-06-01@20:54:49|model.device] Time elapsed: ~0s\n",
      "[2024-06-01@20:54:49|model.tokenizer] Starting timer.\n",
      "[2024-06-01@20:54:49|model.tokenizer] Time elapsed: 160ms\n",
      "[2024-06-01@20:54:49|model.model] Starting timer.\n",
      "Obtaining model...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:root:Some parameters are on the meta device device because they were offloaded to the cpu.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[2024-06-01@20:58:04|model.model] Time elapsed: 3min 15s\n",
      "Opening ./output/commit/prompt0/codegen1-multi-16B.output...\n",
      "95 entries found already, skipping that many...\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "519c54c26d3b4277b1d3ab3c958a831f",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "VBox(children=(IntProgress(value=0, description='Progress:'), Label(value='Estimated time remaining: calculati…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "!! max size might be exceeded !!\n",
      "inputs so far: /* diff of changes\n",
      "diff --git a/guava-gwt/src-super/com/google/common/base/super/com/google/common/base/Stopwatch.java b/guava-gwt/src-super/com/google/common/base/super/com/google/common/base/Stopwatch.java\n",
      "index 73ce24e..531a0f3 100644\n",
      "--- a/guava-gwt/src-super/com/google/common/base/super/com/google/common/base/Stopwatch.java\n",
      "+++ b/guava-gwt/src-super/com/google/common/base/super/com/google/com [ ... 1913 bytes abbreviated ... ]    */\n",
      "   @Deprecated\n",
      "   public Stopwatch(Ticker ticker) {\n",
      "*/\n",
      "// a summary of the above diff is:\n",
      "// -\n",
      "Warning: Model returned no output (prompt may have been too large)\n",
      "!! max size might be exceeded !!\n",
      "inputs so far: /* diff of changes\n",
      "diff --git a/sql/src/main/java/io/crate/lucene/match/OptionParser.java b/sql/src/main/java/io/crate/lucene/match/OptionParser.java\n",
      "index 09047c4ff..171555a11 100644\n",
      "--- a/sql/src/main/java/io/crate/lucene/match/OptionParser.java\n",
      "+++ b/sql/src/main/java/io/crate/lucene/match/OptionParser.java\n",
      "@@ -161,7 +161,7 @@ public class OptionParser {\n",
      "         if (fuzziness == null) {\n",
      "       [ ... 1893 bytes abbreviated ... ]  assertThat(TestingHelpers.printedTable(response.rows()),\n",
      "*/\n",
      "// a summary of the above diff is:\n",
      "// -\n",
      "Warning: Model returned no output (prompt may have been too large)\n",
      "Done, 11min 5s elapsed.\n"
     ]
    }
   ],
   "source": [
    "runner.run_battery(\n",
    "    family=ModelFamily.CodeGen1.multi,\n",
    "    max_size=800,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a4addc95-67ae-44ff-8e6e-6ce1a3f10ba5",
   "metadata": {},
   "source": [
    "# Interpret Output"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "33696339-2ba0-4676-8c17-6de39f3d09da",
   "metadata": {},
   "outputs": [],
   "source": [
    "import metric\n",
    "runner.init_render(family=ModelFamily.CodeGen1.multi)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "cde85bce-3343-4d77-9d2f-235fbd46280b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saved figure to ./figs/pdf/cmg-all.pdf\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "[{'prompt0': [0.0, 0.0, 0.0, 0.0]},\n",
       " {'prompt0': [0.005091944041387383,\n",
       "   0.0014133822836740583,\n",
       "   0.00625229882485127,\n",
       "   0.005881310913068362]}]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "runner.render_metric_multi(\n",
    "    [ metric.BMoses, metric.BNorm ],\n",
    "    save=\"./figs/pdf/cmg-all.pdf\",\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b8c970eb-9447-4e78-9ac6-8493523ec8f3",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true
   },
   "source": [
    "## Metric: BLEU"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "eaaf82d9-c966-4659-8914-516ca3030de4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saved figure to figs/cmg-1.png\n"
     ]
    },
    {
     "data": {
      "image/png": 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1DPrqGPTVMdypr2fPntUtt9ySp1xQYENWaGiojh07Zjd27NgxBQUF5XoWS5J8fX3l6+ubY7xkyZIKCgpySJ1mycjIUEBAgEqVKpXvX6Duht46Bn11DPrqGPTVMeirY9BXx6CvjuFOfc2uLy8fI3KbuwveqMjISK1evdpuLD4+XpGRkS6qCAAAAEBh4DYh69y5c0pKSlJSUpKkrFu0JyUl6cCBA5KyLvWLiYmxzX/00Uf1v//9T08//bT++OMPvfnmm/roo480fPhwV5QPAAAAoJBwm5D1008/qW7duqpbt64kKS4uTnXr1tWYMWMkSUeOHLEFLkm65ZZbtGzZMsXHx6t27dp67bXX9M477yg6Otol9QMAAAAoHNzmM1mtWrXStb7Sa8GCBblu8/PPPzuwKgAAAODaDMPQpUuXlJmZ6epS8p2MjAx5eXnp4sWL+aI/3t7e8vT0vOn9uE3IAgAAANxNenq6jhw5otTUVFeXki8ZhqHQ0FAdPHgwX3wvrcViUfny5RUYGHhT+yFkAQAAAA5gtVq1d+9eeXp6KiwsTD4+PvkiSOQnVqtV586dU2Bg4HW/4NfRDMPQiRMndOjQIVWpUuWmzmgRsgAAAAAHSE9Pl9VqVXh4uAICAlxdTr5ktVqVnp4uPz8/l4csSQoODta+ffuUkZFxUyHL9c8EAAAAKMDyQ3hA3ph1ppEzWQAAAEA+tm+flJAgnTkjFSsmtWolRUS4tiZcGyELAAAAyIc2b5bGj5eWL5euvMm2xSK1ayeNHSs1bOi6+nB1nLsEAAAA8pnPPpOaN5eWLbMPWFLW8rJlWes/+8w19eHaCFkAAABAPrJ5s9Szp5SenrUcHp511ur997N+li+fNZ6enjVv82bX1ZpfjBs3TnXq1MkxfvHiRQ0ePFilSpVSYGCgunbtqmPHjjm8HkIWAAAAkI+MH385YMXESLt3S+PGSb16Zf3cs0fq2zdrfXq69Pzzrqr0svTsgvOZ4cOH66uvvtLHH3+stWvX6s8//1SXLl0cflxCFgAAAOAkhiGdP3/1x++/Z30GS8o6YzVtmpSRYT8nI0N6/XWpXLmsecuWSdu3X3u//7zk8HpatWqlIUOGaMiQISpWrJhKly6t0aNHy/h7RxEREZowYYJiYmIUFBSkRx55RJL06aefqkaNGvL19VVERIRee+01u/1GRETohRdeUExMjAIDA3XLLbdo+fLlOnHihDp16qTAwEDVqlVLP/30k22bBQsWqHjx4lqyZImqVKkiPz8/RUdH6+DBg7b148eP1y+//CKLxSKLxaIFCxbozJkzmjt3rqZMmaK77rpL9evX1/z587V+/Xpt3Ljxxv94N4CQBQAAADhJaqoUGHj1R40alwPRoUNSyZK5zytZUjp8OGueYUi3337t/aam3nitCxculJeXlzZt2qTXX39dU6ZM0TvvvGNb/+qrr6p27dr6+eefNXr0aG3ZskXdunVTjx49tHXrVo0bN06jR4/WggUL7PY7depUNWvWTD///LPatWunRx99VLGxserTp48SExNVqVIlxcTE2AJdVt9S9eKLL+rdd9/VunXrlJycrB49ekiSunfvrieffFI1atTQkSNHdOTIEXXv3l1btmxRRkaGoqKibPupVq2aKlSooA0bNtx4Q24AdxcEAAAAkEN4eLimTp0qi8Wi2267TVu3btXUqVM1YMAASdJdd92lJ5980ja/d+/euvvuuzV69GhJUtWqVfX777/rlVdeUb9+/Wzz2rVrp4EDB0qSRo8erdmzZ6thw4b6z3/+I0kaOXKkIiMjdezYMYWGhkqSMjIyNGPGDDVu3FhSVgCsXr26Nm3apEaNGikwMFBeXl62+ZJ09OhR+fj4qHjx4nbPKyQkREePHjW3Wf/AmSwAAADASQICpHPnrv6YPfvy3FGjrj33mWcuz33rrWvPDQi48VqbNGli9+W8kZGR2rVrlzIzMyVJDRo0sJu/fft2NWvWzG6sWbNmdttIUq1atWy/h4SESJLuuOOOHGPHjx+3jXl5eanhFferr1atmooXL67t27ff+BNzAs5kAQAAAE5isUhFilx9fXR01hzDkP7v/7JudOHjk3NeenrW+ux9Rkdfe7+OUORfHtDb29v2e3aIy23MarXeRHVSaGio0tPTlZycbHc268ozZI7CmSwAAAAgn4iIyPqiYUk6eFB6+OHLdxrMlp6eNX7oUNZy+/ZSxYrm1/Ljjz/aLW/cuFFVqlSRp6dnrvOrV6+udevW2Y2tW7dOVatWveo2eXXp0iW7m2Hs2LFDycnJql69uiTJx8fH7myZJNWvX1/e3t5avXq13XYHDhxQZGTkTdVzPZzJAgAAAPKRsWOl+PisMPXee9KaNdKDD0pVq0o7d0rz5l0OWD4+0pgxjqnjwIEDiouL08CBA5WYmKg33ngjx90Cr/Tkk0+qYcOGmjBhgrp3764NGzZoxowZevPNN2+6Fm9vbz3++OOaPn26vLy8NGTIEDVp0kSNGjWSlHXXwr179yopKUnly5dX0aJFVaxYMT300EOKi4tTyZIlFRQUpMcff1yRkZFq0qTJTdd0LYQsAAAAIB9p2FD64IPLX0h86FDu34Xl45M174qPKpkqJiZGFy5cUKNGjeTp6amhQ4fabtWem3r16umjjz7SmDFjNGHCBJUtW1bPP/+83U0v/q2AgACNHDlSvXr10uHDh9WiRQvNnTvXtr5r16767LPP1Lp1ayUnJ2v+/Pnq16+fpk6dKg8PD3Xt2lVpaWmKjo42JfRdDyELAAAAyGe6dJF++CErXC1bZv89VxZL1iWCY8Y4LmBJWWePpk2bplmzZuVYt2/fvly36dq1q7p27XrVfea23enTpxUUFGRbjoiIsLt9e7YuXbpc9YuEfX199cknn+QY9/Pz08yZMzVz5syr1uQIhCwAAAAgH2rYUPrqK2nfPmntWunMGalYMalVK8d8BgvmIWQBAAAA+VhERNYD7oOQBQAAAMBOQkKCq0uw6devnymf63ImbuEOAAAAACYiZAEAAAAOlNtNHJA/mfW3ImQBAAAADuDt7S1JSk1NdXElyKv0v7/5+Wa/PJnPZAEAAAAO4OnpqeLFi+v48eOSsr7ryWKxuLiq/MVqtSo9PV0XL16Uh4drz/9YrVadOHFCAQEB8vK6uZhEyAIAAAAcJDQ0VJJsQQv2DMPQhQsX5O/vny8CqIeHhypUqHDTtRCyAAAAAAexWCwqW7asypQpo4yMDFeXk+9kZGTou+++05133mm7vNKVfHx8TDmjRsgCAAAAHMzT0/OmP+dTEHl6eurSpUvy8/PLFyHLLNz4AgAAAABMRMgCAAAAABMRsgAAAADARIQsAAAAADARIQsAAAAATETIAgAAAAATEbIAAAAAwESELAAAAAAwESELAAAAAExEyAIAAAAAExGyAAAAAMBEhCwAAAAAMBEhCwAAAABMRMgCAAAAABMRsgAAAADARIQsAAAAADARIQsAAAAATETIAgAAAAATEbIAAAAAwESELAAAAAAwESELAAAAAExEyAIAAAAAExGyAAAAAMBEhCwAAAAAMBEhCwAAAABMRMgCAAAAABMRsgAAAADARIQsAAAAADARIQsAAAAATETIAgAAAAATEbIAAAAAwESELAAAAAAwESELAAAAAExEyAIAAAAAExGyAAAAAMBEhCwAAAAAMBEhCwAAAABMRMgCAAAAABMRsgAAAADARIQsAAAAADARIQsAAAAATETIAgAAAAATEbIAAAAAwESELAAAAAAwESELAAAAAExEyAIAAAAAExGyAAAAAMBEhCwAAAAAMBEhCwAAAABMRMgCAAAAABMRsgAAAADARIQsAAAAADARIQsAAAAATOR2IWvmzJmKiIiQn5+fGjdurE2bNl1z/rRp03TbbbfJ399f4eHhGj58uC5evOikagEAAAAUNm4VshYvXqy4uDiNHTtWiYmJql27tqKjo3X8+PFc5y9atEjPPPOMxo4dq+3bt2vu3LlavHix/vvf/zq5cgAAAACFhVuFrClTpmjAgAHq37+/br/9ds2ePVsBAQGaN29ervPXr1+vZs2aqVevXoqIiFCbNm3Us2fP6579AgAAAIB/y8vVBeRVenq6tmzZolGjRtnGPDw8FBUVpQ0bNuS6TdOmTfV///d/2rRpkxo1aqT//e9/Wr58ufr27Zvr/LS0NKWlpdmWU1JSJEkZGRnKyMgw8dmYL7u+/F6nO6K3jkFfHYO+OgZ9dQz66hj01THoq2O4U19vpEaLYRiGA2sxzZ9//qly5cpp/fr1ioyMtI0//fTTWrt2rX788cdct5s+fbqeeuopGYahS5cu6dFHH9WsWbNynTtu3DiNHz8+x/iiRYsUEBBgzhMBAAAA4HZSU1PVq1cvnTlzRkFBQdec6zZnsv6NhIQEvfTSS3rzzTfVuHFj7d69W0OHDtWECRM0evToHPNHjRqluLg423JKSorCw8PVpk2b6zbS1TIyMhQfH6977rlH3t7eri6nQKG3jkFfHYO+OgZ9dQz66hj01THoq2O4U1+zr3LLC7cJWaVLl5anp6eOHTtmN37s2DGFhobmus3o0aPVt29fPfzww5KkmjVr6vz583rkkUf07LPPysPD/iNpvr6+8vX1zbEfb2/vfP9Hz+ZOtbobeusY9NUx6Ktj0FfHoK+OQV8dg746hjv09Ubqc5sbX/j4+Kh+/fpavXq1bcxqtWr16tV2lw9eKTU1NUeQ8vT0lCS5yVWSAAAAANyM25zJkqS4uDjFxsaqQYMGatSokaZNm6bz58+rf//+kqSYmBiVK1dOEydOlCR16NBBU6ZMUd26dW2XC44ePVodOnSwhS0AAAAAMJNbhazu3bvrxIkTGjNmjI4ePao6depoxYoVCgkJkSQdOHDA7szVc889J4vFoueee06HDx9WcHCwOnTooBdffNFVTwEAAABAAedWIUuShgwZoiFDhuS6LiEhwW7Zy8tLY8eO1dixY51QGQAAAAC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\n",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saved figure to figs/cmg-2.png\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "b_moses_metrics = runner.render_metric(metric.BMoses, save=\"figs/cmg-1.png\")\n",
    "b_norm_metrics = runner.render_metric(metric.BNorm, save=\"figs/cmg-2.png\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "ac9e8acc-bbf4-4add-b24d-83fd01f60728",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saved figure to ./figs/cmg-3.png\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from render_output import OutputRenderer\n",
    "combined_renderer = OutputRenderer(\n",
    "    baseline=0.0,\n",
    "    metric=\"B-Moses vs B-Norm\",\n",
    ")\n",
    "\n",
    "combined_renderer.render(\n",
    "    ys={\n",
    "        \"B-Moses\": b_moses_metrics[\"prompt0\"],\n",
    "        \"B-Norm\": b_norm_metrics[\"prompt0\"],\n",
    "    },\n",
    "    y_max=0.01,\n",
    "    save=\"./figs/cmg-3.png\",\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ef5cc3a5-a2a6-48a1-87f1-c0c1e133acc6",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4ad6b6eb-9372-46d8-9ec3-9b3e0822af65",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}