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hans/main-whitelisting.ipynb

Created December 3, 2019 22:32
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SyntaxGym results 2019-12-03, with PPL whitelisting
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main-whitelisting.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import json\n",
"import operator\n",
"import os\n",
"from pathlib import Path\n",
"from pprint import pprint\n",
"import re\n",
"\n",
"import matplotlib.pyplot as plt\n",
"import numpy as np\n",
"import pandas as pd\n",
"import seaborn as sns\n",
"%matplotlib inline"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Load data and preprocess"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Metadata"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"# Map from test suite tag to high-level circuit.\n",
"circuits = {\n",
" \"Licensing\": [\"npi\", \"reflexive\"],\n",
" \"Long-Distance Dependencies\": [\"fgd\", \"position\", \"embed\", \"number\", \"comparison\"],\n",
" \"Garden-Path Effects\": [\"gardenpath\", \"npz\", \"mvrr\"],\n",
" \"Gross Syntactic State\": [\"subordination\"],\n",
" \"Center Embedding\": [\"center\"],\n",
" \"Transformations\": [\"passive\", \"cleft\"],\n",
"}\n",
"\n",
"tag_to_circuit = {tag: circuit\n",
" for circuit, tags in circuits.items()\n",
" for tag in tags}"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"# Exclusions\n",
"exclude_suite_re = re.compile(r\"^cleft_modifier|^fgd-embed[34]|^npz_(ambig)\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Load"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"os.chdir(\"..\")\n",
"ppl_data_path = Path(\"data/raw/perplexity.csv\")\n",
"test_suite_results_path = Path(\"data/raw/test_suite_results\")"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/opt/conda/lib/python3.6/site-packages/ipykernel_launcher.py:15: UserWarning: This pattern has match groups. To actually get the groups, use str.extract.\n",
" from ipykernel import kernelapp as app\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Dropping 7373 results / 5 suites due to exclusions.\n",
"Tags missing circuit: nn\n"
]
}
],
"source": [
"perplexity_df = pd.read_csv(ppl_data_path, index_col=[\"model\", \"corpus\", \"seed\"])\n",
"perplexity_df.index.set_names(\"model_name\", level=0, inplace=True)\n",
"\n",
"results_df = pd.concat([pd.read_csv(f) for f in test_suite_results_path.glob(\"*.csv\")])\n",
"\n",
"# Split model_id into constituent parts\n",
"model_ids = results_df.model.str.split(\"_\", expand=True).rename(columns={0: \"model_name\", 1: \"corpus\", 2: \"seed\"})\n",
"results_df = results_df.join(model_ids).drop(columns=[\"model\"])\n",
"results_df[\"seed\"] = results_df.seed.astype(int)\n",
"\n",
"# Manual fixes\n",
"results_df.loc[results_df.model_name.isin((\"bllip-lg\", \"bllip-md\", \"bllip-sm\", \"bllip-xs\")), \"model_name\"] = \"vanilla\"\n",
"\n",
"# Exclude test suites\n",
"exclude_filter = results_df.suite.str.contains(exclude_suite_re)\n",
"print(\"Dropping %i results / %i suites due to exclusions.\"\n",
" % (exclude_filter.sum(), len(results_df[exclude_filter].suite.unique())))\n",
"results_df = results_df[~exclude_filter]\n",
"\n",
"# Add tags\n",
"results_df[\"tag\"] = results_df.suite.transform(lambda s: re.split(r\"[-_0-9]\", s)[0])\n",
"results_df[\"circuit\"] = results_df.tag.map(tag_to_circuit)\n",
"tags_missing_circuit = set(results_df.tag.unique()) - set(tag_to_circuit.keys())\n",
"if tags_missing_circuit:\n",
" print(\"Tags missing circuit: \", \", \".join(tags_missing_circuit))"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>suite</th>\n",
" <th>item</th>\n",
" <th>correct</th>\n",
" <th>model_name</th>\n",
" <th>corpus</th>\n",
" <th>seed</th>\n",
" <th>tag</th>\n",
" <th>circuit</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>reflexive_orc_fem</td>\n",
" <td>0</td>\n",
" <td>False</td>\n",
" <td>ordered-neurons</td>\n",
" <td>bllip-lg</td>\n",
" <td>111</td>\n",
" <td>reflexive</td>\n",
" <td>Licensing</td>\n",
" </tr>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>reflexive_orc_fem</td>\n",
" <td>0</td>\n",
" <td>False</td>\n",
" <td>ordered-neurons</td>\n",
" <td>bllip-md</td>\n",
" <td>111</td>\n",
" <td>reflexive</td>\n",
" <td>Licensing</td>\n",
" </tr>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>reflexive_orc_fem</td>\n",
" <td>0</td>\n",
" <td>False</td>\n",
" <td>ordered-neurons</td>\n",
" <td>bllip-sm</td>\n",
" <td>120</td>\n",
" <td>reflexive</td>\n",
" <td>Licensing</td>\n",
" </tr>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>reflexive_orc_fem</td>\n",
" <td>0</td>\n",
" <td>False</td>\n",
" <td>ordered-neurons</td>\n",
" <td>bllip-xs</td>\n",
" <td>922</td>\n",
" <td>reflexive</td>\n",
" <td>Licensing</td>\n",
" </tr>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>reflexive_orc_fem</td>\n",
" <td>0</td>\n",
" <td>False</td>\n",
" <td>vanilla</td>\n",
" <td>bllip-lg</td>\n",
" <td>111</td>\n",
" <td>reflexive</td>\n",
" <td>Licensing</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" suite item correct model_name corpus seed \\\n",
"0 reflexive_orc_fem 0 False ordered-neurons bllip-lg 111 \n",
"0 reflexive_orc_fem 0 False ordered-neurons bllip-md 111 \n",
"0 reflexive_orc_fem 0 False ordered-neurons bllip-sm 120 \n",
"0 reflexive_orc_fem 0 False ordered-neurons bllip-xs 922 \n",
"0 reflexive_orc_fem 0 False vanilla bllip-lg 111 \n",
"\n",
" tag circuit \n",
"0 reflexive Licensing \n",
"0 reflexive Licensing \n",
"0 reflexive Licensing \n",
"0 reflexive Licensing \n",
"0 reflexive Licensing "
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"results_df.head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Checks"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"# Each model--corpus--seed should have perplexity data.\n",
"ids_from_results = results_df.set_index([\"model_name\", \"corpus\", \"seed\"]).sort_index().index\n",
"ids_from_ppl = perplexity_df.sort_index().index\n",
"diff = set(ids_from_results) - set(ids_from_ppl)\n",
"if diff:\n",
" print(\"Missing perplexity results for:\")\n",
" pprint(diff)\n",
" #raise ValueError(\"Each model--corpus--seed must have perplexity data.\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Main analyses\n",
"\n",
"1. barplot ranking model accuracies\n",
"2. scatter plot with ppl on x-axis and SG score on y-axis (for a given dataset size -- or maybe all of them together?)\n",
"3. variance in ppl vs variance in SG score for a single model across seeds and/or sizes\n",
"\n",
"Test suite analyses\n",
"\n",
"1. within-tag/circuit ppl-SG correlations\n",
"2. circuit-circuit coordination heatmap\n",
"3. robustness to stability modification}"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Global settings\n",
"\n",
"e.g. to maintain consistent hues across model graphs, etc."
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"model_order = sorted(set(results_df.model_name))\n",
"corpus_order = [\"bllip-lg\", \"bllip-md\", \"bllip-sm\", \"bllip-xs\"]\n",
"circuit_order = sorted([c for c in results_df.circuit.dropna().unique()])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Data prep"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"suites_df = results_df.groupby([\"model_name\", \"corpus\", \"seed\", \"suite\"]).correct.mean().reset_index()\n",
"suites_df[\"tag\"] = suites_df.suite.transform(lambda s: re.split(r\"[-_0-9]\", s)[0])\n",
"suites_df[\"circuit\"] = suites_df.tag.map(tag_to_circuit)"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>model_name</th>\n",
" <th>corpus</th>\n",
" <th>seed</th>\n",
" <th>correct</th>\n",
" <th>pid</th>\n",
" <th>test_loss</th>\n",
" <th>test_ppl</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>ordered-neurons</td>\n",
" <td>bllip-lg</td>\n",
" <td>111</td>\n",
" <td>0.359028</td>\n",
" <td>NaN</td>\n",
" <td>4.61</td>\n",
" <td>100.84</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>ordered-neurons</td>\n",
" <td>bllip-md</td>\n",
" <td>111</td>\n",
" <td>0.359028</td>\n",
" <td>NaN</td>\n",
" <td>4.47</td>\n",
" <td>87.39</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>ordered-neurons</td>\n",
" <td>bllip-sm</td>\n",
" <td>111</td>\n",
" <td>0.381460</td>\n",
" <td>NaN</td>\n",
" <td>3.72</td>\n",
" <td>41.27</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>ordered-neurons</td>\n",
" <td>bllip-sm</td>\n",
" <td>120</td>\n",
" <td>0.359037</td>\n",
" <td>NaN</td>\n",
" <td>3.72</td>\n",
" <td>41.47</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>ordered-neurons</td>\n",
" <td>bllip-xs</td>\n",
" <td>111</td>\n",
" <td>0.371505</td>\n",
" <td>NaN</td>\n",
" <td>4.06</td>\n",
" <td>58.15</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" model_name corpus seed correct pid test_loss test_ppl\n",
"0 ordered-neurons bllip-lg 111 0.359028 NaN 4.61 100.84\n",
"1 ordered-neurons bllip-md 111 0.359028 NaN 4.47 87.39\n",
"2 ordered-neurons bllip-sm 111 0.381460 NaN 3.72 41.27\n",
"3 ordered-neurons bllip-sm 120 0.359037 NaN 3.72 41.47\n",
"4 ordered-neurons bllip-xs 111 0.371505 NaN 4.06 58.15"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Join PPL and accuracy data.\n",
"joined_data = suites_df.groupby([\"model_name\", \"corpus\", \"seed\"]).correct.agg(\"mean\")\n",
"joined_data = pd.DataFrame(joined_data).join(perplexity_df).reset_index()\n",
"joined_data.head()"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
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" vertical-align: top;\n",
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"\n",
" .dataframe thead th {\n",
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" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>model_name</th>\n",
" <th>corpus</th>\n",
" <th>seed</th>\n",
" <th>circuit</th>\n",
" <th>correct</th>\n",
" <th>pid</th>\n",
" <th>test_loss</th>\n",
" <th>test_ppl</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>ordered-neurons</td>\n",
" <td>bllip-lg</td>\n",
" <td>111</td>\n",
" <td>Center Embedding</td>\n",
" <td>0.630792</td>\n",
" <td>NaN</td>\n",
" <td>4.61</td>\n",
" <td>100.84</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>ordered-neurons</td>\n",
" <td>bllip-lg</td>\n",
" <td>111</td>\n",
" <td>Garden-Path Effects</td>\n",
" <td>0.460169</td>\n",
" <td>NaN</td>\n",
" <td>4.61</td>\n",
" <td>100.84</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>ordered-neurons</td>\n",
" <td>bllip-lg</td>\n",
" <td>111</td>\n",
" <td>Gross Syntactic State</td>\n",
" <td>0.362319</td>\n",
" <td>NaN</td>\n",
" <td>4.61</td>\n",
" <td>100.84</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>ordered-neurons</td>\n",
" <td>bllip-lg</td>\n",
" <td>111</td>\n",
" <td>Licensing</td>\n",
" <td>0.114165</td>\n",
" <td>NaN</td>\n",
" <td>4.61</td>\n",
" <td>100.84</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>ordered-neurons</td>\n",
" <td>bllip-lg</td>\n",
" <td>111</td>\n",
" <td>Long-Distance Dependencies</td>\n",
" <td>0.434109</td>\n",
" <td>NaN</td>\n",
" <td>4.61</td>\n",
" <td>100.84</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" model_name corpus seed circuit correct pid \\\n",
"0 ordered-neurons bllip-lg 111 Center Embedding 0.630792 NaN \n",
"1 ordered-neurons bllip-lg 111 Garden-Path Effects 0.460169 NaN \n",
"2 ordered-neurons bllip-lg 111 Gross Syntactic State 0.362319 NaN \n",
"3 ordered-neurons bllip-lg 111 Licensing 0.114165 NaN \n",
"4 ordered-neurons bllip-lg 111 Long-Distance Dependencies 0.434109 NaN \n",
"\n",
" test_loss test_ppl \n",
"0 4.61 100.84 \n",
"1 4.61 100.84 \n",
"2 4.61 100.84 \n",
"3 4.61 100.84 \n",
"4 4.61 100.84 "
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Join PPL and accuracy data, splitting on circuit.\n",
"joined_data_circuits = suites_df.groupby([\"model_name\", \"corpus\", \"seed\", \"circuit\"]).correct.agg(\"mean\")\n",
"joined_data_circuits = pd.DataFrame(joined_data_circuits).reset_index().set_index([\"model_name\", \"corpus\", \"seed\"]).join(perplexity_df).reset_index()\n",
"joined_data_circuits.head()"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/opt/conda/lib/python3.6/site-packages/ipykernel_launcher.py:16: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
" app.launch_new_instance()\n"
]
},
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
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"\n",
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>suite</th>\n",
" <th>item</th>\n",
" <th>correct</th>\n",
" <th>model_name</th>\n",
" <th>corpus</th>\n",
" <th>seed</th>\n",
" <th>tag</th>\n",
" <th>circuit</th>\n",
" <th>has_modifier</th>\n",
" <th>test_suite_base</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>mvrr_mod</td>\n",
" <td>0</td>\n",
" <td>False</td>\n",
" <td>ordered-neurons</td>\n",
" <td>bllip-lg</td>\n",
" <td>111</td>\n",
" <td>mvrr</td>\n",
" <td>Garden-Path Effects</td>\n",
" <td>True</td>\n",
" <td>v</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>mvrr_mod</td>\n",
" <td>0</td>\n",
" <td>False</td>\n",
" <td>ordered-neurons</td>\n",
" <td>bllip-md</td>\n",
" <td>111</td>\n",
" <td>mvrr</td>\n",
" <td>Garden-Path Effects</td>\n",
" <td>True</td>\n",
" <td>v</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>mvrr_mod</td>\n",
" <td>0</td>\n",
" <td>False</td>\n",
" <td>ordered-neurons</td>\n",
" <td>bllip-sm</td>\n",
" <td>120</td>\n",
" <td>mvrr</td>\n",
" <td>Garden-Path Effects</td>\n",
" <td>True</td>\n",
" <td>v</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>mvrr_mod</td>\n",
" <td>0</td>\n",
" <td>False</td>\n",
" <td>ordered-neurons</td>\n",
" <td>bllip-xs</td>\n",
" <td>922</td>\n",
" <td>mvrr</td>\n",
" <td>Garden-Path Effects</td>\n",
" <td>True</td>\n",
" <td>v</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>mvrr_mod</td>\n",
" <td>0</td>\n",
" <td>False</td>\n",
" <td>vanilla</td>\n",
" <td>bllip-lg</td>\n",
" <td>111</td>\n",
" <td>mvrr</td>\n",
" <td>Garden-Path Effects</td>\n",
" <td>True</td>\n",
" <td>v</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" suite item correct model_name corpus seed tag \\\n",
"21 mvrr_mod 0 False ordered-neurons bllip-lg 111 mvrr \n",
"21 mvrr_mod 0 False ordered-neurons bllip-md 111 mvrr \n",
"21 mvrr_mod 0 False ordered-neurons bllip-sm 120 mvrr \n",
"21 mvrr_mod 0 False ordered-neurons bllip-xs 922 mvrr \n",
"21 mvrr_mod 0 False vanilla bllip-lg 111 mvrr \n",
"\n",
" circuit has_modifier test_suite_base \n",
"21 Garden-Path Effects True v \n",
"21 Garden-Path Effects True v \n",
"21 Garden-Path Effects True v \n",
"21 Garden-Path Effects True v \n",
"21 Garden-Path Effects True v "
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Analyze stability to modification.\n",
"def has_modifier(ts):\n",
" if ts.endswith((\"_modifier\", \"_mod\")):\n",
" return True\n",
" else:\n",
" return None\n",
"results_df[\"has_modifier\"] = results_df.suite.transform(has_modifier)\n",
"\n",
"# Mark \"non-modifier\" test suites\n",
"modifier_ts = results_df[results_df.has_modifier == True].suite.unique()\n",
"no_modifier_ts = [re.sub(r\"_mod(ifier)?$\", \"\", ts) for ts in modifier_ts]\n",
"results_df.loc[results_df.suite.isin(no_modifier_ts), \"has_modifier\"] = False\n",
"# Store subset of test suites which have definite modifier/no-modifier marking\n",
"results_df_mod = results_df[~(results_df.has_modifier.isna())]\n",
"# Get base test suite (without modifier/no-modifier marking)\n",
"results_df_mod[\"test_suite_base\"] = results_df_mod.suite.transform(lambda ts: ts.strip(\"_no-modifier\").strip(\"_modifier\"))\n",
"results_df_mod.head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Accuracy across models"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/opt/conda/lib/python3.6/site-packages/scipy/stats/stats.py:1713: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.\n",
" return np.add.reduce(sorted[indexer] * weights, axis=axis) / sumval\n"
]
},
{
"data": {
"text/plain": [
"Text(0,0.5,'Accuracy')"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"sns.barplot(data=results_df.reset_index(), x=\"model_name\", y=\"correct\")\n",
"\n",
"plt.xlabel(\"Model\")\n",
"plt.ylabel(\"Accuracy\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Accuracy vs perplexity"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [],
"source": [
"corpus_to_size = {\n",
" \"bllip-xs\": 2,\n",
" \"bllip-sm\": 8,\n",
" \"bllip-md\": 14,\n",
" \"bllip-lg\": 20,\n",
"}\n",
"\n",
"model_colors = dict(zip(model_order,\n",
" ['#1f77b4', '#ff7f0e', '#2ca02c', '#d62728', '#9467bd', '#8c564b', '#e377c2', '#7f7f7f', '#bcbd22', '#17becf']))"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.legend.Legend at 0x2ba93c7d4c18>"
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 720x720 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"f, ax = plt.subplots(figsize=(10, 10))\n",
"# sns.regplot(data=graph_data, x=\"test_ppl\", y=\"correct\",\n",
"# scatter_kws={\"s\": graph_data[\"corpus\"].map(corpus_to_size),\n",
"# \"facecolors\": graph_data.model.map(model_colors)})\n",
"sns.scatterplot(data=joined_data, x=\"test_ppl\", y=\"correct\",\n",
" hue=\"model_name\", size=\"corpus\",\n",
" hue_order=model_order, size_order=corpus_order)\n",
"plt.xlabel(\"Test corpus perplexity\")\n",
"plt.ylabel(\"SyntaxGym score\")\n",
"plt.legend(bbox_to_anchor=(1.04,1), loc=\"upper left\")"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<seaborn.axisgrid.FacetGrid at 0x2ba93e1989b0>"
]
},
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 436.75x360 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"sns.lmplot(data=joined_data, x=\"test_ppl\", y=\"correct\",\n",
" hue=\"corpus\", truncate=True)"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<seaborn.axisgrid.FacetGrid at 0x2ba93e1c0d30>"
]
},
"execution_count": 17,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1296x216 with 6 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"g = sns.FacetGrid(data=joined_data_circuits, col=\"circuit\")\n",
"g.map(sns.scatterplot, \"test_ppl\", \"correct\", \"model_name\",\n",
" hue_order=model_order)"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"model_name corpus circuit \n",
"ordered-neurons bllip-lg Center Embedding 0.630792\n",
" Garden-Path Effects 0.460169\n",
" Gross Syntactic State 0.362319\n",
" Licensing 0.114165\n",
" Long-Distance Dependencies 0.434109\n",
" Transformations 0.932143\n",
" bllip-md Center Embedding 0.630792\n",
" Garden-Path Effects 0.460169\n",
" Gross Syntactic State 0.362319\n",
" Licensing 0.114165\n",
" Long-Distance Dependencies 0.434109\n",
" Transformations 0.932143\n",
" bllip-sm Center Embedding 0.623237\n",
" Garden-Path Effects 0.464840\n",
" Gross Syntactic State 0.404622\n",
" Licensing 0.135399\n",
" Long-Distance Dependencies 0.419527\n",
" Transformations 0.921905\n",
" bllip-xs Center Embedding 0.642430\n",
" Garden-Path Effects 0.521296\n",
" Gross Syntactic State 0.365386\n",
" Licensing 0.125586\n",
" Long-Distance Dependencies 0.410803\n",
" Transformations 0.883909\n",
"vanilla bllip-lg Center Embedding 0.624386\n",
" Garden-Path Effects 0.463641\n",
" Gross Syntactic State 0.410628\n",
" Licensing 0.112460\n",
" Long-Distance Dependencies 0.439241\n",
" Transformations 0.929630\n",
" bllip-md Center Embedding 0.630357\n",
" Garden-Path Effects 0.455322\n",
" Gross Syntactic State 0.394928\n",
" Licensing 0.119484\n",
" Long-Distance Dependencies 0.424937\n",
" Transformations 0.932143\n",
" bllip-sm Center Embedding 0.630357\n",
" Garden-Path Effects 0.455322\n",
" Gross Syntactic State 0.394928\n",
" Licensing 0.119484\n",
" Long-Distance Dependencies 0.424937\n",
" Transformations 0.932143\n",
" bllip-xs Center Embedding 0.648206\n",
" Garden-Path Effects 0.471096\n",
" Gross Syntactic State 0.343460\n",
" Licensing 0.131103\n",
" Long-Distance Dependencies 0.412647\n",
" Transformations 0.874564\n",
"Name: correct, dtype: float64"
]
},
"execution_count": 18,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"joined_data_circuits.groupby([\"model_name\", \"corpus\", \"circuit\"]).correct.mean()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Variance in accuracy vs variance in perplexity"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 479.5x360 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"catplot_ticks = [\"correct\", \"test_ppl\"]\n",
"catplot_data = joined_data.copy()\n",
"catplot_data[\"correct\"] *= 100\n",
"catplot_data = catplot_data.melt(id_vars=set(catplot_data.columns) - set(catplot_ticks))\n",
"catplot_data[\"corpus_size\"] = catplot_data.corpus.map(corpus_to_size)\n",
"\n",
"g = sns.catplot(data=catplot_data,\n",
" x=\"variable\", y=\"value\", hue=\"model_name\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Circuit–circuit correlations"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/opt/conda/lib/python3.6/site-packages/ipykernel_launcher.py:10: FutureWarning: using a dict on a Series for aggregation\n",
"is deprecated and will be removed in a future version\n",
" # Remove the CWD from sys.path while we load stuff.\n",
"/opt/conda/lib/python3.6/site-packages/ipykernel_launcher.py:11: FutureWarning: using a dict on a Series for aggregation\n",
"is deprecated and will be removed in a future version\n",
" # This is added back by InteractiveShellApp.init_path()\n"
]
},
{
"data": {
"text/plain": [
"Text(0.5,0.98,'Circuit--circuit correlations')"
]
},
"execution_count": 20,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1440x1440 with 36 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"f, axs = plt.subplots(len(circuit_order), len(circuit_order), figsize=(20, 20))\n",
"plt.subplots_adjust(hspace=0.5, wspace=0.5)\n",
"\n",
"for c1, row in zip(circuit_order, axs):\n",
" for c2, ax in zip(circuit_order, row):\n",
" if c1 <= c2:\n",
" ax.axis(\"off\")\n",
" continue\n",
" \n",
" xs = results_df[results_df.circuit == c1].groupby([\"model_name\", \"corpus\", \"seed\"]).correct.agg({c1: \"mean\"})\n",
" ys = results_df[results_df.circuit == c2].groupby([\"model_name\", \"corpus\", \"seed\"]).correct.agg({c2: \"mean\"})\n",
" df = pd.concat([xs, ys], axis=1)\n",
" ax.set_title(\"%s /\\n %s\" % (c1, c2))\n",
" sns.regplot(data=df, x=c1, y=c2, ax=ax)\n",
" \n",
"plt.suptitle(\"Circuit--circuit correlations\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Stability to modification"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Text(0.5,1,'Stability to modification')"
]
},
"execution_count": 21,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1080x720 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.subplots(figsize=(15, 10))\n",
"sns.barplot(data=results_df_mod, x=\"model_name\", y=\"correct\", hue=\"has_modifier\")\n",
"plt.title(\"Stability to modification\")"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Text(0.5,1,'Stability to modification')"
]
},
"execution_count": 22,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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\n",
"text/plain": [
"<Figure size 1080x720 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.subplots(figsize=(15, 10))\n",
"sns.barplot(data=results_df_mod, x=\"corpus\", y=\"correct\", hue=\"has_modifier\")\n",
"plt.title(\"Stability to modification\")"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/opt/conda/lib/python3.6/site-packages/ipykernel_launcher.py:1: FutureWarning: using a dict on a Series for aggregation\n",
"is deprecated and will be removed in a future version\n",
" \"\"\"Entry point for launching an IPython kernel.\n"
]
},
{
"data": {
"text/plain": [
"Text(0.5,1,'Change in accuracy due to modification')"
]
},
"execution_count": 23,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1080x720 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"avg_mod_results = results_df_mod.groupby([\"model_name\", \"test_suite_base\", \"has_modifier\"]).correct.agg({\"correct\": \"mean\"}).sort_index()\n",
"avg_mod_diffs = avg_mod_results.xs(True, level=\"has_modifier\") - avg_mod_results.xs(False, level=\"has_modifier\")\n",
"\n",
"plt.subplots(figsize=(15, 10))\n",
"sns.boxplot(data=avg_mod_diffs.reset_index(), x=\"model_name\", y=\"correct\")\n",
"plt.title(\"Change in accuracy due to modification\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"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": "3.6.8"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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