Toolbox Features

README.md

@@ -1,4 +1,4 @@
-<img src="./docs/source/_static/images/nnsigt.png" alt="drawing" style="width:200px;float:left"/>
+<img src="./docs/source/_static/images/nnsight_logo.svg" alt="drawing" style="width:200px;float:left"/>
 
 # nnsight 
 ![PyPI - Version](https://img.shields.io/pypi/v/nnsight)

docs/source/_static/css/custom.css

@@ -21,7 +21,10 @@
 }
 
 html[data-theme="light"] {
-    --pst-color-secondary: #64ccdc;
+    --pst-color-secondary: #b676b2;
+    --pst-color-primary: #4ca4d2;
+    --pst-color-primary-highlight: #b676b2;
+
 }
 
 

docs/source/_templates/ndif_status.html

@@ -0,0 +1,27 @@
+<style>
+    #ndif_status {
+        height: 18px;
+        width: 18px;
+        background-color: red;
+        border-radius: 50%;
+        display: inline-block;
+        margin-left: 10px;
+    }
+</style>
+
+<div>NDIF Status: </div><span id="ndif_status"></span>
+
+<script>
+    console.log()
+    fetch("{{ndif_url}}")
+        .then((response) => {
+            if (response.status == 200) {
+                document.getElementById("ndif_status").style.backgroundColor = "green"
+            }
+            else {
+                document.getElementById("ndif_status").style.backgroundColor = "red"
+            }
+        })
+        .catch((response) => document.getElementById("ndif_status").style.backgroundColor = "red")
+
+</script>

docs/source/conf.py

@@ -4,15 +4,11 @@
 project = 'nnsight'
 copyright = '2023, NDIF'
 author = 'Jaden Fiotto-Kaufman'
-release = '0.0.6'
+release = '0.0.7'
 
 
 
 # General Configuration
-
-import sys
-sys.path.append('/home/caden/Programming/nnsight/src/nnsight')
-
 extensions = [
     'sphinx.ext.autodoc', # Auto documentation from docstrings
     'sphinx.ext.napoleon', # Support for NumPy and Google style docstrings
@@ -39,7 +35,7 @@
 html_theme_options = {
   "logo": {"text":"nnsight"},
   "show_nav_level": 2,
-  "navbar_end": ["navbar-icon-links"],
+  "navbar_end": ["navbar-icon-links", "ndif_status"],
   "navbar_align": "left",
   "icon_links": [
         {
@@ -51,7 +47,8 @@
 }
 
 html_context = {
-   "default_mode": "light"
+   "default_mode": "light",
+   "ndif_url" : "https://ndif.baulab.us/ping"
 }
 
 html_css_files = [

docs/source/index.rst

@@ -19,7 +19,9 @@ nnsight
     .. grid-item:: 
         .. div:: 
 
-          .. image:: _static/images/nnsigt.png
+          .. image:: _static/images/nnsight_logo.svg
+            :width: 400
+            :height: 276
 
     .. grid-item:: 
 

docs/source/tutorials.rst

@@ -1,7 +1,35 @@
 Tutorials
 =========
 
+Check out the :bdg-link-primary:`main demo <tutorials/notebooks/main_demo.ipynb>` for a quick walkthrough of important nnsight functionality. You can also check out more tutorials for the package below! 
+
+.. grid:: 2
+   :gutter: 3
+
+   .. grid-item-card::  Basics
+      :link: basics
+
+      Walk through the basic functionality of the package.
+
+   .. grid-item-card::  Features
+      :link: features
+
+      Learn some more advanced features of the package.
+
+   .. grid-item-card::  Toolkit
+
+      Familiarize yourself with the tools that come with the package. (Coming soon!)
+
+   .. grid-item-card::  Papers
+
+      See how nnsight can be applied through key papers in interpretability. (Coming soon!)
+
+
+
+
 .. toctree::
+   :hidden:
    :maxdepth: 1
 
-   tutorials/main_demo.ipynb
+   tutorials/basics
+   tutorials/features

docs/source/tutorials/basics.rst

@@ -0,0 +1,7 @@
+Basics
+======
+
+.. toctree::
+   :maxdepth: 1
+
+   notebooks/main_demo.ipynb

docs/source/tutorials/features.rst

@@ -0,0 +1,9 @@
+Features
+========
+
+.. toctree::
+   :maxdepth: 1
+
+   notebooks/cross_prompt.ipynb
+   notebooks/multiple_token.ipynb
+   notebooks/token_indexing.ipynb

docs/source/tutorials/notebooks/cross_prompt.ipynb

@@ -0,0 +1,133 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "5873a43e-e181-47d3-8ba9-2f6c9e7a7d61",
+   "metadata": {},
+   "source": [
+    "# Cross-Prompt Intervention"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1fb6417c-53dd-43d4-900b-7fdb9616591c",
+   "metadata": {},
+   "source": [
+    "Intervention operations work cross prompt! Use two invocations within the same generation block and operations can work between them.\n",
+    "\n",
+    "In this case, we grab the token embeddings coming from the first prompt, \"Madison square garden is located in the city of New\" and replace the embeddings of the second prompt with them."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "455cfa6f-54d6-43b7-befd-6754d6baa9e8",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from nnsight import LanguageModel\n",
+    "\n",
+    "model = LanguageModel('gpt2', device_map='cuda')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "50c3b04f-a9dc-4f01-9010-a93751745a47",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "You're using a GPT2TokenizerFast tokenizer. Please note that with a fast tokenizer, using the `__call__` method is faster than using a method to encode the text followed by a call to the `pad` method to get a padded encoding.\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Madison square garden is located in the city of New York City.\n",
+      "_ _ _ _ _ _ _ _ _ _ York City.\n"
+     ]
+    }
+   ],
+   "source": [
+    "with model.generate(max_new_tokens=3) as generator:\n",
+    "    \n",
+    "    with generator.invoke(\"Madison square garden is located in the city of New\") as invoker:\n",
+    "\n",
+    "        embeddings = model.transformer.wte.output\n",
+    "\n",
+    "    with generator.invoke(\"_ _ _ _ _ _ _ _ _ _\") as invoker:\n",
+    "\n",
+    "        model.transformer.wte.output = embeddings\n",
+    "\n",
+    "print(model.tokenizer.decode(generator.output[0]))\n",
+    "print(model.tokenizer.decode(generator.output[1]))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5c70184c-239d-4964-94bc-56f5d4fea363",
+   "metadata": {},
+   "source": [
+    "We also could have entered a pre-saved embedding tensor as shown here:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "808f77a3-a43c-4564-a47b-0f1b1da6c79b",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Madison square garden is located in the city of New York City.\n",
+      "_ _ _ _ _ _ _ _ _ _ York City.\n"
+     ]
+    }
+   ],
+   "source": [
+    "with model.generate(max_new_tokens=3) as generator:\n",
+    "    \n",
+    "    with generator.invoke(\"Madison square garden is located in the city of New\") as invoker:\n",
+    "\n",
+    "        embeddings = model.transformer.wte.output.save()\n",
+    "\n",
+    "print(model.tokenizer.decode(generator.output[0]))\n",
+    "\n",
+    "with model.generate(max_new_tokens=3) as generator:\n",
+    "\n",
+    "    with generator.invoke(\"_ _ _ _ _ _ _ _ _ _\") as invoker:\n",
+    "\n",
+    "        model.transformer.wte.output = embeddings.value\n",
+    "\n",
+    "print(model.tokenizer.decode(generator.output[0]))"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "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": "3.8.18"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}