From 2b3882cbba32421ec7b05aa37445b6cd70d0a5b9 Mon Sep 17 00:00:00 2001
From: Diane Adjavon <adjavond@hhmi.org>
Date: Mon, 26 Aug 2024 17:52:32 -0400
Subject: [PATCH 1/4] Remove erroneous text instructions

---
 assets/diff_class.png            | Bin 0 -> 93934 bytes
 assets/same_class.png            | Bin 0 -> 92646 bytes
 assets/same_class_diff_color.png | Bin 11402 -> 0 bytes
 assets/same_color_diff_class.png | Bin 9904 -> 0 bytes
 solution.py                      |  23 +++++++++++------------
 5 files changed, 11 insertions(+), 12 deletions(-)
 create mode 100644 assets/diff_class.png
 create mode 100644 assets/same_class.png
 delete mode 100644 assets/same_class_diff_color.png
 delete mode 100644 assets/same_color_diff_class.png

diff --git a/assets/diff_class.png b/assets/diff_class.png
new file mode 100644
index 0000000000000000000000000000000000000000..a74239537fd8a88cee88f4d117c03deac724dc8c
GIT binary patch
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diff --git a/solution.py b/solution.py
index c70861b..a5f0c6f 100644
--- a/solution.py
+++ b/solution.py
@@ -967,7 +967,7 @@ def visualize_color_attribution_and_counterfactual(
 # %%
 for idx in range(batch_size):
     print("Source class:", y[idx].item())
-    print("Target class:", 0)
+    print("Target class:", target_class)
     visualize_color_attribution_and_counterfactual(
         attributions[idx].cpu().numpy(), x[idx].cpu().numpy(), x_fake[idx].cpu().numpy()
     )
@@ -980,6 +980,16 @@ def visualize_color_attribution_and_counterfactual(
 # </ul>
 # </div>
 # %% [markdown]
+# By now you will have hopefully noticed that it isn't the exact color of the image that determines its class, but that two images with a very similar color can be of different classes!
+#
+# Here are two examples of image-counterfactual-attribution triplets.
+# You'll notice that they are *very* similar in every way! But one set is different classes, and one set is the same class!
+# 
+# ![same_class](assets/same_class.png)
+# ![diff_class](assets/diff_class.png)
+#
+# We are missing a crucial step of the explanation pipeline: a quantification of how the class changes over the interpolation. 
+#
 # In the lecture, we used the attribution to act as a mask, to gradually go from the original image to the counterfactual image.
 # This allowed us to classify all of the intermediate images, and learn how the class changed over the interpolation.
 # Here we have a much simpler task so we have some advantages:
@@ -1053,17 +1063,6 @@ def visualize_color_attribution_and_counterfactual(
 #
 # %% [markdown]
 # # Part 5: Exploring the Style Space, finding the answer
-# By now you will have hopefully noticed that it isn't the exact color of the image that determines its class, but that two images with a very similar color can be of different classes!
-#
-# Here is an example of two images that are very similar in color, but are of different classes.
-# ![same_color_diff_class](assets/same_color_diff_class.png)
-# While both of the images are yellow, the attribution tells us (if you squint!) that one of the yellows has slightly more blue in it!
-#
-# Conversely, here is an example of two images with very different colors, but that are of the same class:
-# ![same_class_diff_color](assets/same_class_diff_color.png)
-# Here the attribution is empty! Using the discriminative attribution we can see that the significant color change doesn't matter at all!
-#
-#
 # So color is important... but not always? What's going on!?
 # There is a final piece of information that we can use to solve the puzzle: the style space.
 # %% [markdown]

From 7ddbb1104d49a3d56dc74c6358b0b7dd9528b77c Mon Sep 17 00:00:00 2001
From: adjavon <adjavon@users.noreply.github.com>
Date: Mon, 26 Aug 2024 21:53:21 +0000
Subject: [PATCH 2/4] Commit from GitHub Actions (Build Notebooks)

---
 exercise.ipynb | 227 ++++++++++++++++++++++++------------------------
 solution.ipynb | 231 ++++++++++++++++++++++++-------------------------
 2 files changed, 228 insertions(+), 230 deletions(-)

diff --git a/exercise.ipynb b/exercise.ipynb
index 1f76626..4a0a4a5 100644
--- a/exercise.ipynb
+++ b/exercise.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "2cec6e2e",
+   "id": "1b3bf19e",
    "metadata": {
     "lines_to_next_cell": 0,
     "tags": []
@@ -29,7 +29,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "c9faff54",
+   "id": "067e738b",
    "metadata": {
     "lines_to_next_cell": 0
    },
@@ -41,7 +41,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "8b2714f2",
+   "id": "b913b71a",
    "metadata": {},
    "source": [
     "\n",
@@ -54,7 +54,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "196887ff",
+   "id": "98283047",
    "metadata": {
     "lines_to_next_cell": 0
    },
@@ -68,7 +68,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "dc029ece",
+   "id": "1afbe1b3",
    "metadata": {
     "lines_to_next_cell": 0
    },
@@ -84,7 +84,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "3f76a8a6",
+   "id": "5bef908b",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -102,7 +102,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "9ec21db3",
+   "id": "3e27811b",
    "metadata": {
     "lines_to_next_cell": 0
    },
@@ -113,7 +113,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "06793f28",
+   "id": "c554ff65",
    "metadata": {
     "lines_to_next_cell": 0
    },
@@ -130,7 +130,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "1bc9ae08",
+   "id": "0f8465d5",
    "metadata": {
     "lines_to_next_cell": 0,
     "tags": [
@@ -155,7 +155,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "e0d3e182",
+   "id": "9460ef99",
    "metadata": {
     "lines_to_next_cell": 0
    },
@@ -166,7 +166,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "0bd2cb1e",
+   "id": "e35f652a",
    "metadata": {
     "lines_to_next_cell": 0
    },
@@ -195,7 +195,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "88a42af2",
+   "id": "714d0118",
    "metadata": {
     "lines_to_next_cell": 0
    },
@@ -212,7 +212,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "72fbabcd",
+   "id": "2b3080ec",
    "metadata": {},
    "source": [
     "# Part 2: Using Integrated Gradients to find what the classifier knows\n",
@@ -222,7 +222,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "5a41df80",
+   "id": "42bf258c",
    "metadata": {},
    "source": [
     "## Attributions through integrated gradients\n",
@@ -235,7 +235,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "c7615db3",
+   "id": "9dc58dab",
    "metadata": {
     "tags": []
    },
@@ -253,7 +253,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f8bc4307",
+   "id": "50185c99",
    "metadata": {
     "tags": []
    },
@@ -269,7 +269,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "36075e2c",
+   "id": "e960ab8b",
    "metadata": {
     "tags": [
      "task"
@@ -290,7 +290,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "8ebbe326",
+   "id": "eed52045",
    "metadata": {
     "tags": []
    },
@@ -303,7 +303,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "2de7d44e",
+   "id": "be5a007b",
    "metadata": {
     "lines_to_next_cell": 2,
     "tags": []
@@ -315,7 +315,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "c484acb2",
+   "id": "5c0780f6",
    "metadata": {
     "tags": []
    },
@@ -343,7 +343,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "898595ea",
+   "id": "30041689",
    "metadata": {
     "tags": []
    },
@@ -356,7 +356,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "5b66372f",
+   "id": "c0d46960",
    "metadata": {
     "lines_to_next_cell": 2
    },
@@ -370,7 +370,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f26f6f42",
+   "id": "477cd87c",
    "metadata": {
     "lines_to_next_cell": 0
    },
@@ -383,7 +383,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "69cf5669",
+   "id": "ed247a59",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -408,7 +408,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "9642568b",
+   "id": "746de08d",
    "metadata": {
     "lines_to_next_cell": 0
    },
@@ -422,7 +422,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "2891c43d",
+   "id": "8c5ea46b",
    "metadata": {},
    "source": [
     "\n",
@@ -448,7 +448,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "357966b5",
+   "id": "eaacace4",
    "metadata": {},
    "source": [
     "<div class=\"alert alert-block alert-info\"><h4>Task 2.3: Use random noise as a baseline</h4>\n",
@@ -460,7 +460,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "8e4e92d0",
+   "id": "bbbe47bb",
    "metadata": {
     "tags": [
      "task"
@@ -482,7 +482,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f9b5fba2",
+   "id": "bb810907",
    "metadata": {
     "tags": []
    },
@@ -496,7 +496,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "58262250",
+   "id": "5b379c73",
    "metadata": {
     "tags": [
      "task"
@@ -520,7 +520,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "ccedb79c",
+   "id": "342b9336",
    "metadata": {
     "tags": []
    },
@@ -536,7 +536,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "68893afb",
+   "id": "96d713fd",
    "metadata": {},
    "source": [
     "<div class=\"alert alert-block alert-info\"><h2>BONUS Task: Using different attributions.</h2>\n",
@@ -550,7 +550,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "849fa319",
+   "id": "f6118ade",
    "metadata": {},
    "source": [
     "<div class=\"alert alert-block alert-success\"><h2>Checkpoint 2</h2>\n",
@@ -570,7 +570,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "876bdd3b",
+   "id": "12781ee6",
    "metadata": {
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@@ -598,7 +598,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "5a1c2a34",
+   "id": "6dd2e900",
    "metadata": {
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     "tags": []
@@ -621,7 +621,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "85aa4a15",
+   "id": "e489a340",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -653,7 +653,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "2b95f3e8",
+   "id": "d77aa8d1",
    "metadata": {
     "lines_to_next_cell": 0
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@@ -668,7 +668,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "ac1205e5",
+   "id": "974e17d8",
    "metadata": {
     "lines_to_next_cell": 0,
     "tags": [
@@ -689,7 +689,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "9c976d43",
+   "id": "50f5d295",
    "metadata": {
     "tags": []
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@@ -704,7 +704,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "881575de",
+   "id": "f4dd16b3",
    "metadata": {
     "lines_to_next_cell": 0,
     "tags": []
@@ -721,7 +721,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "e43f27f1",
+   "id": "ccf31a3c",
    "metadata": {
     "lines_to_next_cell": 0,
     "tags": [
@@ -735,7 +735,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "d29d8d58",
+   "id": "49ff9e3a",
    "metadata": {
     "lines_to_next_cell": 0
    },
@@ -746,7 +746,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "f51b15fc",
+   "id": "b0f0fb98",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -756,7 +756,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "73814dae",
+   "id": "23b21a32",
    "metadata": {
     "lines_to_next_cell": 0,
     "tags": []
@@ -774,7 +774,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "5fc36682",
+   "id": "29678f3b",
    "metadata": {
     "lines_to_next_cell": 0
    },
@@ -786,7 +786,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "e07edb85",
+   "id": "6c069dc6",
    "metadata": {
     "lines_to_next_cell": 0,
     "tags": []
@@ -805,7 +805,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "5082b8ab",
+   "id": "321515da",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -814,7 +814,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "43ef8a2d",
+   "id": "060fd784",
    "metadata": {
     "lines_to_next_cell": 0,
     "tags": []
@@ -830,7 +830,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "468fe88f",
+   "id": "8c85a285",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -839,7 +839,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "6dd0f856",
+   "id": "511db0c6",
    "metadata": {
     "lines_to_next_cell": 0,
     "tags": []
@@ -851,7 +851,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "89da32d6",
+   "id": "6c3dfe27",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -864,7 +864,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "2b894eac",
+   "id": "aca01927",
    "metadata": {
     "lines_to_next_cell": 0,
     "tags": []
@@ -878,7 +878,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "b25e284e",
+   "id": "c0bb0943",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -890,7 +890,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "72125f93",
+   "id": "1c17e308",
    "metadata": {
     "lines_to_next_cell": 0,
     "tags": []
@@ -910,7 +910,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "41cf9baf",
+   "id": "c378d7f9",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -934,7 +934,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "a5b1fb2e",
+   "id": "07f4fecf",
    "metadata": {
     "lines_to_next_cell": 2
    },
@@ -946,7 +946,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "421a4724",
+   "id": "452728c7",
    "metadata": {
     "lines_to_next_cell": 0,
     "tags": []
@@ -968,7 +968,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "d375c071",
+   "id": "9a73a3eb",
    "metadata": {
     "lines_to_next_cell": 0,
     "tags": []
@@ -980,7 +980,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "f782b7f0",
+   "id": "01ddb9f7",
    "metadata": {
     "lines_to_next_cell": 0,
     "tags": [
@@ -1091,7 +1091,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "bf2700e1",
+   "id": "2b1901cd",
    "metadata": {
     "lines_to_next_cell": 0,
     "tags": []
@@ -1103,7 +1103,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "93af3047",
+   "id": "32eebf00",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1119,7 +1119,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "65452041",
+   "id": "fd98dc27",
    "metadata": {
     "tags": []
    },
@@ -1134,7 +1134,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "db668256",
+   "id": "c74e6127",
    "metadata": {
     "lines_to_next_cell": 0,
     "tags": []
@@ -1146,7 +1146,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "f76c5e65",
+   "id": "d38a9dfd",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1168,7 +1168,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "573bb9d9",
+   "id": "bd940bab",
    "metadata": {
     "tags": []
    },
@@ -1184,7 +1184,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "26dfd88b",
+   "id": "24e48cf3",
    "metadata": {
     "tags": []
    },
@@ -1194,7 +1194,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f48126ab",
+   "id": "1f56a54f",
    "metadata": {
     "tags": []
    },
@@ -1211,7 +1211,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "4305090b",
+   "id": "8f572d41",
    "metadata": {
     "title": "Loading the test dataset"
    },
@@ -1231,7 +1231,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "154db796",
+   "id": "dc260633",
    "metadata": {
     "lines_to_next_cell": 0,
     "tags": []
@@ -1243,7 +1243,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "ebbcd12d",
+   "id": "0429a766",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1256,7 +1256,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "61d5d4bc",
+   "id": "80f4b326",
    "metadata": {
     "lines_to_next_cell": 0
    },
@@ -1266,7 +1266,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "7ae07350",
+   "id": "8443a95a",
    "metadata": {
     "lines_to_next_cell": 0
    },
@@ -1284,7 +1284,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "bca04b2a",
+   "id": "012af37d",
    "metadata": {
     "lines_to_next_cell": 0,
     "tags": [
@@ -1320,7 +1320,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "bebb99c9",
+   "id": "9a2a6a90",
    "metadata": {
     "lines_to_next_cell": 0,
     "tags": []
@@ -1332,7 +1332,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "c87df0c0",
+   "id": "ca2d44e7",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1345,7 +1345,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "2fbc38e9",
+   "id": "63966675",
    "metadata": {
     "tags": []
    },
@@ -1360,7 +1360,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "baf8c83a",
+   "id": "413852c4",
    "metadata": {
     "tags": []
    },
@@ -1371,7 +1371,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "2465c04b",
+   "id": "65d61fc4",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1385,7 +1385,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "35613805",
+   "id": "b926cdc6",
    "metadata": {
     "tags": []
    },
@@ -1400,7 +1400,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "321fcad6",
+   "id": "4aaf7349",
    "metadata": {
     "lines_to_next_cell": 0
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@@ -1415,7 +1415,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "1c45c814",
+   "id": "ac005791",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1436,7 +1436,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "584f13f4",
+   "id": "8f3faac4",
    "metadata": {
     "title": "Another visualization function"
    },
@@ -1465,7 +1465,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "df33dd4a",
+   "id": "956658ca",
    "metadata": {
     "lines_to_next_cell": 0
    },
@@ -1473,7 +1473,7 @@
    "source": [
     "for idx in range(batch_size):\n",
     "    print(\"Source class:\", y[idx].item())\n",
-    "    print(\"Target class:\", 0)\n",
+    "    print(\"Target class:\", target_class)\n",
     "    visualize_color_attribution_and_counterfactual(\n",
     "        attributions[idx].cpu().numpy(), x[idx].cpu().numpy(), x_fake[idx].cpu().numpy()\n",
     "    )"
@@ -1481,7 +1481,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f2bdfa5d",
+   "id": "8df09e0c",
    "metadata": {
     "lines_to_next_cell": 0
    },
@@ -1497,11 +1497,21 @@
   },
   {
    "cell_type": "markdown",
-   "id": "da87745e",
+   "id": "59557649",
    "metadata": {
     "lines_to_next_cell": 0
    },
    "source": [
+    "By now you will have hopefully noticed that it isn't the exact color of the image that determines its class, but that two images with a very similar color can be of different classes!\n",
+    "\n",
+    "Here are two examples of image-counterfactual-attribution triplets.\n",
+    "You'll notice that they are *very* similar in every way! But one set is different classes, and one set is the same class!\n",
+    "\n",
+    "![same_class](assets/same_class.png)\n",
+    "![diff_class](assets/diff_class.png)\n",
+    "\n",
+    "We are missing a crucial step of the explanation pipeline: a quantification of how the class changes over the interpolation. \n",
+    "\n",
     "In the lecture, we used the attribution to act as a mask, to gradually go from the original image to the counterfactual image.\n",
     "This allowed us to classify all of the intermediate images, and learn how the class changed over the interpolation.\n",
     "Here we have a much simpler task so we have some advantages:\n",
@@ -1512,7 +1522,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "88f10203",
+   "id": "0e01c5da",
    "metadata": {
     "lines_to_next_cell": 0
    },
@@ -1526,7 +1536,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "2e79affe",
+   "id": "a9b88599",
    "metadata": {
     "lines_to_next_cell": 0
    },
@@ -1546,7 +1556,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "70f9846e",
+   "id": "f402e79a",
    "metadata": {
     "lines_to_next_cell": 0
    },
@@ -1582,7 +1592,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "386a9f4c",
+   "id": "fcefb0bb",
    "metadata": {
     "lines_to_next_cell": 0
    },
@@ -1596,7 +1606,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "ae25a656",
+   "id": "01f9a614",
    "metadata": {
     "lines_to_next_cell": 0
    },
@@ -1612,7 +1622,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "53c7b041",
+   "id": "3bb20dcd",
    "metadata": {
     "lines_to_next_cell": 0
    },
@@ -1628,30 +1638,19 @@
   },
   {
    "cell_type": "markdown",
-   "id": "c75ed748",
+   "id": "d546c694",
    "metadata": {
     "lines_to_next_cell": 0
    },
    "source": [
     "# Part 5: Exploring the Style Space, finding the answer\n",
-    "By now you will have hopefully noticed that it isn't the exact color of the image that determines its class, but that two images with a very similar color can be of different classes!\n",
-    "\n",
-    "Here is an example of two images that are very similar in color, but are of different classes.\n",
-    "![same_color_diff_class](assets/same_color_diff_class.png)\n",
-    "While both of the images are yellow, the attribution tells us (if you squint!) that one of the yellows has slightly more blue in it!\n",
-    "\n",
-    "Conversely, here is an example of two images with very different colors, but that are of the same class:\n",
-    "![same_class_diff_color](assets/same_class_diff_color.png)\n",
-    "Here the attribution is empty! Using the discriminative attribution we can see that the significant color change doesn't matter at all!\n",
-    "\n",
-    "\n",
     "So color is important... but not always? What's going on!?\n",
     "There is a final piece of information that we can use to solve the puzzle: the style space."
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "45dcb17b",
+   "id": "bc3ed726",
    "metadata": {},
    "source": [
     "<div class=\"alert alert-block alert-info\"><h3>Task 5.1: Explore the style space</h3>\n",
@@ -1663,7 +1662,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "11309f0a",
+   "id": "718ce53b",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1698,7 +1697,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "e7e0f8d4",
+   "id": "ca7a48a9",
    "metadata": {
     "lines_to_next_cell": 0
    },
@@ -1714,7 +1713,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "cc183548",
+   "id": "e814f376",
    "metadata": {
     "lines_to_next_cell": 0
    },
@@ -1741,7 +1740,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "9f34f021",
+   "id": "bbdc2fa9",
    "metadata": {
     "lines_to_next_cell": 0
    },
@@ -1755,7 +1754,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "5d29071b",
+   "id": "3fe20ca4",
    "metadata": {
     "lines_to_next_cell": 0
    },
@@ -1772,7 +1771,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "366dd45c",
+   "id": "ff536dd4",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1794,7 +1793,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "b657a0f5",
+   "id": "d19016ff",
    "metadata": {},
    "source": [
     "<div class=\"alert alert-block alert-warning\"><h3>Questions</h3>\n",
@@ -1806,7 +1805,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "35b0a886",
+   "id": "24c11487",
    "metadata": {},
    "source": [
     "<div class=\"alert alert-block alert-success\"><h2>Checkpoint 5</h2>\n",
@@ -1824,7 +1823,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "c7f12c18",
+   "id": "36582123",
    "metadata": {},
    "source": [
     "# Bonus!\n",
diff --git a/solution.ipynb b/solution.ipynb
index b8d9964..e1f331f 100644
--- a/solution.ipynb
+++ b/solution.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "2cec6e2e",
+   "id": "1b3bf19e",
    "metadata": {
     "lines_to_next_cell": 0,
     "tags": []
@@ -29,7 +29,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "c9faff54",
+   "id": "067e738b",
    "metadata": {
     "lines_to_next_cell": 0
    },
@@ -41,7 +41,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "8b2714f2",
+   "id": "b913b71a",
    "metadata": {},
    "source": [
     "\n",
@@ -54,7 +54,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "196887ff",
+   "id": "98283047",
    "metadata": {
     "lines_to_next_cell": 0
    },
@@ -68,7 +68,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "dc029ece",
+   "id": "1afbe1b3",
    "metadata": {
     "lines_to_next_cell": 0
    },
@@ -84,7 +84,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "3f76a8a6",
+   "id": "5bef908b",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -102,7 +102,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "9ec21db3",
+   "id": "3e27811b",
    "metadata": {
     "lines_to_next_cell": 0
    },
@@ -113,7 +113,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "06793f28",
+   "id": "c554ff65",
    "metadata": {
     "lines_to_next_cell": 0
    },
@@ -130,7 +130,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "becee066",
+   "id": "885618d6",
    "metadata": {
     "tags": [
      "solution"
@@ -154,7 +154,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "e0d3e182",
+   "id": "9460ef99",
    "metadata": {
     "lines_to_next_cell": 0
    },
@@ -165,7 +165,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "0bd2cb1e",
+   "id": "e35f652a",
    "metadata": {
     "lines_to_next_cell": 0
    },
@@ -194,7 +194,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "88a42af2",
+   "id": "714d0118",
    "metadata": {
     "lines_to_next_cell": 0
    },
@@ -211,7 +211,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "72fbabcd",
+   "id": "2b3080ec",
    "metadata": {},
    "source": [
     "# Part 2: Using Integrated Gradients to find what the classifier knows\n",
@@ -221,7 +221,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "5a41df80",
+   "id": "42bf258c",
    "metadata": {},
    "source": [
     "## Attributions through integrated gradients\n",
@@ -234,7 +234,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "c7615db3",
+   "id": "9dc58dab",
    "metadata": {
     "tags": []
    },
@@ -252,7 +252,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f8bc4307",
+   "id": "50185c99",
    "metadata": {
     "tags": []
    },
@@ -268,7 +268,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "300ad40e",
+   "id": "a8bce89a",
    "metadata": {
     "tags": [
      "solution"
@@ -292,7 +292,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "8ebbe326",
+   "id": "eed52045",
    "metadata": {
     "tags": []
    },
@@ -305,7 +305,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "2de7d44e",
+   "id": "be5a007b",
    "metadata": {
     "lines_to_next_cell": 2,
     "tags": []
@@ -317,7 +317,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "c484acb2",
+   "id": "5c0780f6",
    "metadata": {
     "tags": []
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@@ -345,7 +345,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "898595ea",
+   "id": "30041689",
    "metadata": {
     "tags": []
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@@ -358,7 +358,7 @@
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   {
    "cell_type": "markdown",
-   "id": "5b66372f",
+   "id": "c0d46960",
    "metadata": {
     "lines_to_next_cell": 2
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@@ -372,7 +372,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f26f6f42",
+   "id": "477cd87c",
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@@ -385,7 +385,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "69cf5669",
+   "id": "ed247a59",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -410,7 +410,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "9642568b",
+   "id": "746de08d",
    "metadata": {
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@@ -424,7 +424,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "2891c43d",
+   "id": "8c5ea46b",
    "metadata": {},
    "source": [
     "\n",
@@ -450,7 +450,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "357966b5",
+   "id": "eaacace4",
    "metadata": {},
    "source": [
     "<div class=\"alert alert-block alert-info\"><h4>Task 2.3: Use random noise as a baseline</h4>\n",
@@ -462,7 +462,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "99c5b515",
+   "id": "35062d2c",
    "metadata": {
     "tags": [
      "solution"
@@ -488,7 +488,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f9b5fba2",
+   "id": "bb810907",
    "metadata": {
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@@ -502,7 +502,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "2ba867e8",
+   "id": "367cb0b3",
    "metadata": {
     "tags": [
      "solution"
@@ -532,7 +532,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "ccedb79c",
+   "id": "342b9336",
    "metadata": {
     "tags": []
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@@ -548,7 +548,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "68893afb",
+   "id": "96d713fd",
    "metadata": {},
    "source": [
     "<div class=\"alert alert-block alert-info\"><h2>BONUS Task: Using different attributions.</h2>\n",
@@ -562,7 +562,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "849fa319",
+   "id": "f6118ade",
    "metadata": {},
    "source": [
     "<div class=\"alert alert-block alert-success\"><h2>Checkpoint 2</h2>\n",
@@ -582,7 +582,7 @@
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   {
    "cell_type": "markdown",
-   "id": "876bdd3b",
+   "id": "12781ee6",
    "metadata": {
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@@ -610,7 +610,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "5a1c2a34",
+   "id": "6dd2e900",
    "metadata": {
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     "tags": []
@@ -633,7 +633,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "85aa4a15",
+   "id": "e489a340",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -665,7 +665,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "2b95f3e8",
+   "id": "d77aa8d1",
    "metadata": {
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@@ -680,7 +680,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "ff8cbb81",
+   "id": "8ec9d68a",
    "metadata": {
     "tags": [
      "solution"
@@ -697,7 +697,7 @@
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   {
    "cell_type": "markdown",
-   "id": "9c976d43",
+   "id": "50f5d295",
    "metadata": {
     "tags": []
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@@ -712,7 +712,7 @@
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   {
    "cell_type": "markdown",
-   "id": "881575de",
+   "id": "f4dd16b3",
    "metadata": {
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     "tags": []
@@ -729,7 +729,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "de64cf3c",
+   "id": "7152c016",
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     "tags": [
@@ -743,7 +743,7 @@
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   {
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-   "id": "d29d8d58",
+   "id": "49ff9e3a",
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@@ -754,7 +754,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "f51b15fc",
+   "id": "b0f0fb98",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -764,7 +764,7 @@
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   {
    "cell_type": "markdown",
-   "id": "73814dae",
+   "id": "23b21a32",
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     "tags": []
@@ -782,7 +782,7 @@
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-   "id": "5fc36682",
+   "id": "29678f3b",
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@@ -794,7 +794,7 @@
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   {
    "cell_type": "markdown",
-   "id": "e07edb85",
+   "id": "6c069dc6",
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     "tags": []
@@ -813,7 +813,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "5082b8ab",
+   "id": "321515da",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -822,7 +822,7 @@
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   {
    "cell_type": "markdown",
-   "id": "43ef8a2d",
+   "id": "060fd784",
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     "tags": []
@@ -838,7 +838,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "468fe88f",
+   "id": "8c85a285",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -847,7 +847,7 @@
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   {
    "cell_type": "markdown",
-   "id": "6dd0f856",
+   "id": "511db0c6",
    "metadata": {
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     "tags": []
@@ -859,7 +859,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "89da32d6",
+   "id": "6c3dfe27",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -872,7 +872,7 @@
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   {
    "cell_type": "markdown",
-   "id": "2b894eac",
+   "id": "aca01927",
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     "tags": []
@@ -886,7 +886,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "b25e284e",
+   "id": "c0bb0943",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -898,7 +898,7 @@
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   {
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-   "id": "72125f93",
+   "id": "1c17e308",
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     "tags": []
@@ -918,7 +918,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "41cf9baf",
+   "id": "c378d7f9",
    "metadata": {},
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@@ -942,7 +942,7 @@
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    "cell_type": "code",
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-   "id": "a5b1fb2e",
+   "id": "07f4fecf",
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@@ -954,7 +954,7 @@
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-   "id": "421a4724",
+   "id": "452728c7",
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@@ -976,7 +976,7 @@
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-   "id": "d375c071",
+   "id": "9a73a3eb",
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     "tags": []
@@ -988,7 +988,7 @@
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-   "id": "c79ac460",
+   "id": "a32e6ffb",
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     "tags": [
@@ -1058,7 +1058,7 @@
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-   "id": "bf2700e1",
+   "id": "2b1901cd",
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     "tags": []
@@ -1070,7 +1070,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "93af3047",
+   "id": "32eebf00",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1086,7 +1086,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "65452041",
+   "id": "fd98dc27",
    "metadata": {
     "tags": []
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@@ -1101,7 +1101,7 @@
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   {
    "cell_type": "markdown",
-   "id": "db668256",
+   "id": "c74e6127",
    "metadata": {
     "lines_to_next_cell": 0,
     "tags": []
@@ -1113,7 +1113,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "f76c5e65",
+   "id": "d38a9dfd",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1135,7 +1135,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "573bb9d9",
+   "id": "bd940bab",
    "metadata": {
     "tags": []
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@@ -1151,7 +1151,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "26dfd88b",
+   "id": "24e48cf3",
    "metadata": {
     "tags": []
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@@ -1161,7 +1161,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f48126ab",
+   "id": "1f56a54f",
    "metadata": {
     "tags": []
    },
@@ -1178,7 +1178,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "4305090b",
+   "id": "8f572d41",
    "metadata": {
     "title": "Loading the test dataset"
    },
@@ -1198,7 +1198,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "154db796",
+   "id": "dc260633",
    "metadata": {
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     "tags": []
@@ -1210,7 +1210,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "ebbcd12d",
+   "id": "0429a766",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1223,7 +1223,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "61d5d4bc",
+   "id": "80f4b326",
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@@ -1233,7 +1233,7 @@
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   {
    "cell_type": "markdown",
-   "id": "7ae07350",
+   "id": "8443a95a",
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@@ -1251,7 +1251,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "ede3165e",
+   "id": "e448e313",
    "metadata": {
     "tags": [
      "solution"
@@ -1288,7 +1288,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "bebb99c9",
+   "id": "9a2a6a90",
    "metadata": {
     "lines_to_next_cell": 0,
     "tags": []
@@ -1300,7 +1300,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "c87df0c0",
+   "id": "ca2d44e7",
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    "outputs": [],
    "source": [
@@ -1313,7 +1313,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "2fbc38e9",
+   "id": "63966675",
    "metadata": {
     "tags": []
    },
@@ -1328,7 +1328,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "baf8c83a",
+   "id": "413852c4",
    "metadata": {
     "tags": []
    },
@@ -1339,7 +1339,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "2465c04b",
+   "id": "65d61fc4",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1353,7 +1353,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "35613805",
+   "id": "b926cdc6",
    "metadata": {
     "tags": []
    },
@@ -1368,7 +1368,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "321fcad6",
+   "id": "4aaf7349",
    "metadata": {
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@@ -1383,7 +1383,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "1c45c814",
+   "id": "ac005791",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1404,7 +1404,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "584f13f4",
+   "id": "8f3faac4",
    "metadata": {
     "title": "Another visualization function"
    },
@@ -1433,7 +1433,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "df33dd4a",
+   "id": "956658ca",
    "metadata": {
     "lines_to_next_cell": 0
    },
@@ -1441,7 +1441,7 @@
    "source": [
     "for idx in range(batch_size):\n",
     "    print(\"Source class:\", y[idx].item())\n",
-    "    print(\"Target class:\", 0)\n",
+    "    print(\"Target class:\", target_class)\n",
     "    visualize_color_attribution_and_counterfactual(\n",
     "        attributions[idx].cpu().numpy(), x[idx].cpu().numpy(), x_fake[idx].cpu().numpy()\n",
     "    )"
@@ -1449,7 +1449,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f2bdfa5d",
+   "id": "8df09e0c",
    "metadata": {
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    },
@@ -1465,11 +1465,21 @@
   },
   {
    "cell_type": "markdown",
-   "id": "da87745e",
+   "id": "59557649",
    "metadata": {
     "lines_to_next_cell": 0
    },
    "source": [
+    "By now you will have hopefully noticed that it isn't the exact color of the image that determines its class, but that two images with a very similar color can be of different classes!\n",
+    "\n",
+    "Here are two examples of image-counterfactual-attribution triplets.\n",
+    "You'll notice that they are *very* similar in every way! But one set is different classes, and one set is the same class!\n",
+    "\n",
+    "![same_class](assets/same_class.png)\n",
+    "![diff_class](assets/diff_class.png)\n",
+    "\n",
+    "We are missing a crucial step of the explanation pipeline: a quantification of how the class changes over the interpolation. \n",
+    "\n",
     "In the lecture, we used the attribution to act as a mask, to gradually go from the original image to the counterfactual image.\n",
     "This allowed us to classify all of the intermediate images, and learn how the class changed over the interpolation.\n",
     "Here we have a much simpler task so we have some advantages:\n",
@@ -1480,7 +1490,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "88f10203",
+   "id": "0e01c5da",
    "metadata": {
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@@ -1494,7 +1504,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "2e79affe",
+   "id": "a9b88599",
    "metadata": {
     "lines_to_next_cell": 0
    },
@@ -1514,7 +1524,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "70f9846e",
+   "id": "f402e79a",
    "metadata": {
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@@ -1550,7 +1560,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "386a9f4c",
+   "id": "fcefb0bb",
    "metadata": {
     "lines_to_next_cell": 0
    },
@@ -1564,7 +1574,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "ae25a656",
+   "id": "01f9a614",
    "metadata": {
     "lines_to_next_cell": 0
    },
@@ -1580,7 +1590,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "53c7b041",
+   "id": "3bb20dcd",
    "metadata": {
     "lines_to_next_cell": 0
    },
@@ -1596,30 +1606,19 @@
   },
   {
    "cell_type": "markdown",
-   "id": "c75ed748",
+   "id": "d546c694",
    "metadata": {
     "lines_to_next_cell": 0
    },
    "source": [
     "# Part 5: Exploring the Style Space, finding the answer\n",
-    "By now you will have hopefully noticed that it isn't the exact color of the image that determines its class, but that two images with a very similar color can be of different classes!\n",
-    "\n",
-    "Here is an example of two images that are very similar in color, but are of different classes.\n",
-    "![same_color_diff_class](assets/same_color_diff_class.png)\n",
-    "While both of the images are yellow, the attribution tells us (if you squint!) that one of the yellows has slightly more blue in it!\n",
-    "\n",
-    "Conversely, here is an example of two images with very different colors, but that are of the same class:\n",
-    "![same_class_diff_color](assets/same_class_diff_color.png)\n",
-    "Here the attribution is empty! Using the discriminative attribution we can see that the significant color change doesn't matter at all!\n",
-    "\n",
-    "\n",
     "So color is important... but not always? What's going on!?\n",
     "There is a final piece of information that we can use to solve the puzzle: the style space."
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "45dcb17b",
+   "id": "bc3ed726",
    "metadata": {},
    "source": [
     "<div class=\"alert alert-block alert-info\"><h3>Task 5.1: Explore the style space</h3>\n",
@@ -1631,7 +1630,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "11309f0a",
+   "id": "718ce53b",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1666,7 +1665,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "e7e0f8d4",
+   "id": "ca7a48a9",
    "metadata": {
     "lines_to_next_cell": 0
    },
@@ -1682,7 +1681,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "cc183548",
+   "id": "e814f376",
    "metadata": {
     "lines_to_next_cell": 0
    },
@@ -1709,7 +1708,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "9f34f021",
+   "id": "bbdc2fa9",
    "metadata": {
     "lines_to_next_cell": 0
    },
@@ -1723,7 +1722,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "5d29071b",
+   "id": "3fe20ca4",
    "metadata": {
     "lines_to_next_cell": 0
    },
@@ -1740,7 +1739,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "366dd45c",
+   "id": "ff536dd4",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1762,7 +1761,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "b657a0f5",
+   "id": "d19016ff",
    "metadata": {},
    "source": [
     "<div class=\"alert alert-block alert-warning\"><h3>Questions</h3>\n",
@@ -1774,7 +1773,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "35b0a886",
+   "id": "24c11487",
    "metadata": {},
    "source": [
     "<div class=\"alert alert-block alert-success\"><h2>Checkpoint 5</h2>\n",
@@ -1792,7 +1791,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "c7f12c18",
+   "id": "36582123",
    "metadata": {},
    "source": [
     "# Bonus!\n",
@@ -1807,7 +1806,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "93aa15d5",
+   "id": "44f3ac5f",
    "metadata": {
     "tags": [
      "solution"
@@ -1821,7 +1820,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "ac995812",
+   "id": "3144a680",
    "metadata": {
     "tags": [
      "solution"

From 622745633df48a2a97cb1040584d5ee8798e00af Mon Sep 17 00:00:00 2001
From: Diane Adjavon <adjavond@hhmi.org>
Date: Mon, 26 Aug 2024 17:58:26 -0400
Subject: [PATCH 3/4] Fix lists in checkpoints

---
 solution.py | 25 ++++++++++++++-----------
 1 file changed, 14 insertions(+), 11 deletions(-)

diff --git a/solution.py b/solution.py
index a5f0c6f..1111482 100644
--- a/solution.py
+++ b/solution.py
@@ -1055,12 +1055,13 @@ def visualize_color_attribution_and_counterfactual(
 # %% [markdown]
 # <div class="alert alert-block alert-success"><h2>Checkpoint 4</h2>
 # At this point you have:
-# - Created a StarGAN that can change the class of an image
-# - Evaluated the StarGAN on unseen data
-# - Used the StarGAN to create counterfactual images
-# - Used the counterfactual images to highlight the differences between classes
-# - Interpolated between the images to see how the classifier behaves
-#
+# <ul>
+# <li> Created a StarGAN that can change the class of an image </li>
+# <li> Evaluated the StarGAN on unseen data </li>
+# <li> Used the StarGAN to create counterfactual images </li>
+# <li> Used the counterfactual images to highlight the differences between classes </li>
+# <li> Interpolated between the images to see how the classifier behaves </li>
+# </ul>
 # %% [markdown]
 # # Part 5: Exploring the Style Space, finding the answer
 # So color is important... but not always? What's going on!?
@@ -1166,11 +1167,13 @@ def visualize_color_attribution_and_counterfactual(
 # <div class="alert alert-block alert-success"><h2>Checkpoint 5</h2>
 # Congratulations! You have made it to the end of the exercise!
 # You have:
-# - Created a StarGAN that can change the class of an image
-# - Evaluated the StarGAN on unseen data
-# - Used the StarGAN to create counterfactual images
-# - Used the counterfactual images to highlight the differences between classes
-# - Used the style space to understand the differences between classes
+# <ul>
+# <li> Created a StarGAN that can change the class of an image </li>
+# <li> Evaluated the StarGAN on unseen data </li>
+# <li> Used the StarGAN to create counterfactual images </li>
+# <li> Used the counterfactual images to highlight the differences between classes </li>
+# <li> Used the style space to understand the differences between classes </li>
+# </ul>
 #
 # If you have any questions, feel free to ask them in the chat!
 # And check the Solutions exercise for a definite answer to how these classes are defined!

From 4749b5f4b8f8a8328373404cd9550afe6be7ce61 Mon Sep 17 00:00:00 2001
From: adjavon <adjavon@users.noreply.github.com>
Date: Mon, 26 Aug 2024 21:59:13 +0000
Subject: [PATCH 4/4] Commit from GitHub Actions (Build Notebooks)

---
 exercise.ipynb | 228 ++++++++++++++++++++++++------------------------
 solution.ipynb | 232 +++++++++++++++++++++++++------------------------
 2 files changed, 234 insertions(+), 226 deletions(-)

diff --git a/exercise.ipynb b/exercise.ipynb
index 4a0a4a5..1c05f30 100644
--- a/exercise.ipynb
+++ b/exercise.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "1b3bf19e",
+   "id": "508f55c4",
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     "tags": []
@@ -29,7 +29,7 @@
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@@ -41,7 +41,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "b913b71a",
+   "id": "62e6288c",
    "metadata": {},
    "source": [
     "\n",
@@ -54,7 +54,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "98283047",
+   "id": "524e722d",
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@@ -68,7 +68,7 @@
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@@ -84,7 +84,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "5bef908b",
+   "id": "25fb11b9",
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@@ -102,7 +102,7 @@
   },
   {
    "cell_type": "markdown",
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+   "id": "cc3c08e3",
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@@ -113,7 +113,7 @@
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@@ -130,7 +130,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "0f8465d5",
+   "id": "44819937",
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@@ -155,7 +155,7 @@
   },
   {
    "cell_type": "markdown",
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@@ -166,7 +166,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "e35f652a",
+   "id": "4ffba779",
    "metadata": {
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@@ -195,7 +195,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "714d0118",
+   "id": "7be4250a",
    "metadata": {
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@@ -212,7 +212,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "2b3080ec",
+   "id": "5f8c898d",
    "metadata": {},
    "source": [
     "# Part 2: Using Integrated Gradients to find what the classifier knows\n",
@@ -222,7 +222,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "42bf258c",
+   "id": "a284d49b",
    "metadata": {},
    "source": [
     "## Attributions through integrated gradients\n",
@@ -235,7 +235,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "9dc58dab",
+   "id": "925ce3e7",
    "metadata": {
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@@ -253,7 +253,7 @@
   },
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-   "id": "50185c99",
+   "id": "b72a7b5a",
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@@ -269,7 +269,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "e960ab8b",
+   "id": "9c1f5411",
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@@ -290,7 +290,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "eed52045",
+   "id": "3a0c2413",
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@@ -303,7 +303,7 @@
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@@ -315,7 +315,7 @@
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-   "id": "5c0780f6",
+   "id": "3c89c686",
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@@ -343,7 +343,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "30041689",
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@@ -356,7 +356,7 @@
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@@ -370,7 +370,7 @@
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@@ -383,7 +383,7 @@
   {
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-   "id": "ed247a59",
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@@ -408,7 +408,7 @@
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@@ -422,7 +422,7 @@
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-   "id": "8c5ea46b",
+   "id": "05d0cef7",
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@@ -448,7 +448,7 @@
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   {
    "cell_type": "markdown",
-   "id": "eaacace4",
+   "id": "43b62c80",
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     "<div class=\"alert alert-block alert-info\"><h4>Task 2.3: Use random noise as a baseline</h4>\n",
@@ -460,7 +460,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "bbbe47bb",
+   "id": "b6dd00a1",
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@@ -482,7 +482,7 @@
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@@ -496,7 +496,7 @@
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    "execution_count": null,
-   "id": "5b379c73",
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@@ -520,7 +520,7 @@
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@@ -536,7 +536,7 @@
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-   "id": "96d713fd",
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@@ -550,7 +550,7 @@
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-   "id": "f6118ade",
+   "id": "b08a5590",
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@@ -570,7 +570,7 @@
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@@ -653,7 +653,7 @@
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@@ -746,7 +746,7 @@
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@@ -756,7 +756,7 @@
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@@ -774,7 +774,7 @@
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@@ -786,7 +786,7 @@
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@@ -805,7 +805,7 @@
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@@ -814,7 +814,7 @@
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@@ -830,7 +830,7 @@
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@@ -839,7 +839,7 @@
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@@ -864,7 +864,7 @@
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@@ -1119,7 +1119,7 @@
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@@ -1168,7 +1168,7 @@
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@@ -1231,7 +1231,7 @@
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@@ -1436,7 +1436,7 @@
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-   "id": "8f3faac4",
+   "id": "3d722e25",
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@@ -1465,7 +1465,7 @@
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@@ -1556,7 +1556,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "f402e79a",
+   "id": "a6039426",
    "metadata": {
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    },
@@ -1592,7 +1592,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "fcefb0bb",
+   "id": "62c10f55",
    "metadata": {
     "lines_to_next_cell": 0
    },
@@ -1606,7 +1606,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "01f9a614",
+   "id": "f35c78d1",
    "metadata": {
     "lines_to_next_cell": 0
    },
@@ -1622,23 +1622,25 @@
   },
   {
    "cell_type": "markdown",
-   "id": "3bb20dcd",
+   "id": "ce0defa7",
    "metadata": {
     "lines_to_next_cell": 0
    },
    "source": [
     "<div class=\"alert alert-block alert-success\"><h2>Checkpoint 4</h2>\n",
     "At this point you have:\n",
-    "- Created a StarGAN that can change the class of an image\n",
-    "- Evaluated the StarGAN on unseen data\n",
-    "- Used the StarGAN to create counterfactual images\n",
-    "- Used the counterfactual images to highlight the differences between classes\n",
-    "- Interpolated between the images to see how the classifier behaves\n"
+    "<ul>\n",
+    "<li> Created a StarGAN that can change the class of an image </li>\n",
+    "<li> Evaluated the StarGAN on unseen data </li>\n",
+    "<li> Used the StarGAN to create counterfactual images </li>\n",
+    "<li> Used the counterfactual images to highlight the differences between classes </li>\n",
+    "<li> Interpolated between the images to see how the classifier behaves </li>\n",
+    "</ul>"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "d546c694",
+   "id": "bbd7820d",
    "metadata": {
     "lines_to_next_cell": 0
    },
@@ -1650,7 +1652,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "bc3ed726",
+   "id": "141b4181",
    "metadata": {},
    "source": [
     "<div class=\"alert alert-block alert-info\"><h3>Task 5.1: Explore the style space</h3>\n",
@@ -1662,7 +1664,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "718ce53b",
+   "id": "b6e9c103",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1697,7 +1699,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "ca7a48a9",
+   "id": "c01c00f7",
    "metadata": {
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@@ -1713,7 +1715,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "e814f376",
+   "id": "11b7d4c9",
    "metadata": {
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    },
@@ -1740,7 +1742,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "bbdc2fa9",
+   "id": "2c53c235",
    "metadata": {
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@@ -1754,7 +1756,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "3fe20ca4",
+   "id": "9d81df42",
    "metadata": {
     "lines_to_next_cell": 0
    },
@@ -1771,7 +1773,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "ff536dd4",
+   "id": "081a67e4",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1793,7 +1795,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "d19016ff",
+   "id": "1d74498c",
    "metadata": {},
    "source": [
     "<div class=\"alert alert-block alert-warning\"><h3>Questions</h3>\n",
@@ -1805,17 +1807,19 @@
   },
   {
    "cell_type": "markdown",
-   "id": "24c11487",
+   "id": "1efd608c",
    "metadata": {},
    "source": [
     "<div class=\"alert alert-block alert-success\"><h2>Checkpoint 5</h2>\n",
     "Congratulations! You have made it to the end of the exercise!\n",
     "You have:\n",
-    "- Created a StarGAN that can change the class of an image\n",
-    "- Evaluated the StarGAN on unseen data\n",
-    "- Used the StarGAN to create counterfactual images\n",
-    "- Used the counterfactual images to highlight the differences between classes\n",
-    "- Used the style space to understand the differences between classes\n",
+    "<ul>\n",
+    "<li> Created a StarGAN that can change the class of an image </li>\n",
+    "<li> Evaluated the StarGAN on unseen data </li>\n",
+    "<li> Used the StarGAN to create counterfactual images </li>\n",
+    "<li> Used the counterfactual images to highlight the differences between classes </li>\n",
+    "<li> Used the style space to understand the differences between classes </li>\n",
+    "</ul>\n",
     "\n",
     "If you have any questions, feel free to ask them in the chat!\n",
     "And check the Solutions exercise for a definite answer to how these classes are defined!"
@@ -1823,7 +1827,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "36582123",
+   "id": "4f71144a",
    "metadata": {},
    "source": [
     "# Bonus!\n",
diff --git a/solution.ipynb b/solution.ipynb
index e1f331f..b2359d5 100644
--- a/solution.ipynb
+++ b/solution.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "1b3bf19e",
+   "id": "508f55c4",
    "metadata": {
     "lines_to_next_cell": 0,
     "tags": []
@@ -29,7 +29,7 @@
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   {
    "cell_type": "markdown",
-   "id": "067e738b",
+   "id": "88480b87",
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@@ -41,7 +41,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "b913b71a",
+   "id": "62e6288c",
    "metadata": {},
    "source": [
     "\n",
@@ -54,7 +54,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "98283047",
+   "id": "524e722d",
    "metadata": {
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@@ -68,7 +68,7 @@
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   {
    "cell_type": "markdown",
-   "id": "1afbe1b3",
+   "id": "c9c22ad8",
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@@ -84,7 +84,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "5bef908b",
+   "id": "25fb11b9",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -102,7 +102,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "3e27811b",
+   "id": "cc3c08e3",
    "metadata": {
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@@ -113,7 +113,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "c554ff65",
+   "id": "254aef78",
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@@ -130,7 +130,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "885618d6",
+   "id": "469219c6",
    "metadata": {
     "tags": [
      "solution"
@@ -154,7 +154,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "9460ef99",
+   "id": "61dbe630",
    "metadata": {
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@@ -165,7 +165,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "e35f652a",
+   "id": "4ffba779",
    "metadata": {
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@@ -194,7 +194,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "714d0118",
+   "id": "7be4250a",
    "metadata": {
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@@ -211,7 +211,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "2b3080ec",
+   "id": "5f8c898d",
    "metadata": {},
    "source": [
     "# Part 2: Using Integrated Gradients to find what the classifier knows\n",
@@ -221,7 +221,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "42bf258c",
+   "id": "a284d49b",
    "metadata": {},
    "source": [
     "## Attributions through integrated gradients\n",
@@ -234,7 +234,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "9dc58dab",
+   "id": "925ce3e7",
    "metadata": {
     "tags": []
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@@ -252,7 +252,7 @@
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   {
    "cell_type": "markdown",
-   "id": "50185c99",
+   "id": "b72a7b5a",
    "metadata": {
     "tags": []
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@@ -268,7 +268,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "a8bce89a",
+   "id": "9a722cf0",
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      "solution"
@@ -292,7 +292,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "eed52045",
+   "id": "3a0c2413",
    "metadata": {
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@@ -305,7 +305,7 @@
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   {
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-   "id": "be5a007b",
+   "id": "1941efec",
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@@ -317,7 +317,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "5c0780f6",
+   "id": "3c89c686",
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@@ -345,7 +345,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "30041689",
+   "id": "e10dc24d",
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@@ -358,7 +358,7 @@
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@@ -372,7 +372,7 @@
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@@ -385,7 +385,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "ed247a59",
+   "id": "598a1f0a",
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@@ -410,7 +410,7 @@
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   {
    "cell_type": "markdown",
-   "id": "746de08d",
+   "id": "d873aa39",
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@@ -424,7 +424,7 @@
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   {
    "cell_type": "markdown",
-   "id": "8c5ea46b",
+   "id": "05d0cef7",
    "metadata": {},
    "source": [
     "\n",
@@ -450,7 +450,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "eaacace4",
+   "id": "43b62c80",
    "metadata": {},
    "source": [
     "<div class=\"alert alert-block alert-info\"><h4>Task 2.3: Use random noise as a baseline</h4>\n",
@@ -462,7 +462,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "35062d2c",
+   "id": "1988179e",
    "metadata": {
     "tags": [
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@@ -488,7 +488,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "bb810907",
+   "id": "f3c3e97c",
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@@ -502,7 +502,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "367cb0b3",
+   "id": "5370fe7e",
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@@ -532,7 +532,7 @@
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   {
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-   "id": "342b9336",
+   "id": "7abf9f27",
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@@ -548,7 +548,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "96d713fd",
+   "id": "c37b4cc9",
    "metadata": {},
    "source": [
     "<div class=\"alert alert-block alert-info\"><h2>BONUS Task: Using different attributions.</h2>\n",
@@ -562,7 +562,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f6118ade",
+   "id": "b08a5590",
    "metadata": {},
    "source": [
     "<div class=\"alert alert-block alert-success\"><h2>Checkpoint 2</h2>\n",
@@ -582,7 +582,7 @@
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-   "id": "12781ee6",
+   "id": "13b502ee",
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@@ -610,7 +610,7 @@
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@@ -633,7 +633,7 @@
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-   "id": "e489a340",
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@@ -665,7 +665,7 @@
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@@ -680,7 +680,7 @@
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    "execution_count": null,
-   "id": "8ec9d68a",
+   "id": "f0b9e1fa",
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@@ -697,7 +697,7 @@
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-   "id": "50f5d295",
+   "id": "8cc42dea",
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@@ -712,7 +712,7 @@
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@@ -743,7 +743,7 @@
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-   "id": "b0f0fb98",
+   "id": "fb6eecc1",
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@@ -764,7 +764,7 @@
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+   "id": "c79251f6",
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@@ -782,7 +782,7 @@
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-   "id": "29678f3b",
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@@ -794,7 +794,7 @@
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@@ -813,7 +813,7 @@
   {
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-   "id": "321515da",
+   "id": "8eb2fe39",
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@@ -822,7 +822,7 @@
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@@ -838,7 +838,7 @@
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-   "id": "8c85a285",
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@@ -847,7 +847,7 @@
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@@ -859,7 +859,7 @@
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-   "id": "6c3dfe27",
+   "id": "e957ad43",
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@@ -872,7 +872,7 @@
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@@ -886,7 +886,7 @@
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-   "id": "c0bb0943",
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@@ -898,7 +898,7 @@
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@@ -918,7 +918,7 @@
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-   "id": "c378d7f9",
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@@ -942,7 +942,7 @@
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-   "id": "07f4fecf",
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@@ -954,7 +954,7 @@
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@@ -976,7 +976,7 @@
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@@ -988,7 +988,7 @@
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@@ -1058,7 +1058,7 @@
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@@ -1070,7 +1070,7 @@
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@@ -1086,7 +1086,7 @@
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@@ -1101,7 +1101,7 @@
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@@ -1113,7 +1113,7 @@
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-   "id": "d38a9dfd",
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@@ -1135,7 +1135,7 @@
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-   "id": "bd940bab",
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@@ -1151,7 +1151,7 @@
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-   "id": "24e48cf3",
+   "id": "b3c5bbd0",
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@@ -1161,7 +1161,7 @@
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@@ -1178,7 +1178,7 @@
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    "cell_type": "code",
    "execution_count": null,
-   "id": "8f572d41",
+   "id": "3d4f212c",
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@@ -1198,7 +1198,7 @@
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-   "id": "dc260633",
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@@ -1210,7 +1210,7 @@
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@@ -1223,7 +1223,7 @@
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@@ -1233,7 +1233,7 @@
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@@ -1251,7 +1251,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "e448e313",
+   "id": "25cc00c8",
    "metadata": {
     "tags": [
      "solution"
@@ -1288,7 +1288,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "9a2a6a90",
+   "id": "255934ec",
    "metadata": {
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     "tags": []
@@ -1300,7 +1300,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "ca2d44e7",
+   "id": "6daca8ca",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1313,7 +1313,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "63966675",
+   "id": "18186b93",
    "metadata": {
     "tags": []
    },
@@ -1328,7 +1328,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "413852c4",
+   "id": "29b63b00",
    "metadata": {
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@@ -1339,7 +1339,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "65d61fc4",
+   "id": "411b8730",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1353,7 +1353,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "b926cdc6",
+   "id": "dcce6a0c",
    "metadata": {
     "tags": []
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@@ -1368,7 +1368,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "4aaf7349",
+   "id": "106316e5",
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@@ -1383,7 +1383,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "ac005791",
+   "id": "152bed37",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1404,7 +1404,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "8f3faac4",
+   "id": "3d722e25",
    "metadata": {
     "title": "Another visualization function"
    },
@@ -1433,7 +1433,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "956658ca",
+   "id": "04eabebc",
    "metadata": {
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@@ -1449,7 +1449,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "8df09e0c",
+   "id": "46e50c88",
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@@ -1465,7 +1465,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "59557649",
+   "id": "a9b101b6",
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@@ -1490,7 +1490,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "0e01c5da",
+   "id": "246fda63",
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@@ -1504,7 +1504,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "a9b88599",
+   "id": "2e9602ae",
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@@ -1524,7 +1524,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "f402e79a",
+   "id": "a6039426",
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@@ -1560,7 +1560,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "fcefb0bb",
+   "id": "62c10f55",
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@@ -1574,7 +1574,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "01f9a614",
+   "id": "f35c78d1",
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@@ -1590,23 +1590,25 @@
   },
   {
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-   "id": "3bb20dcd",
+   "id": "ce0defa7",
    "metadata": {
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    },
    "source": [
     "<div class=\"alert alert-block alert-success\"><h2>Checkpoint 4</h2>\n",
     "At this point you have:\n",
-    "- Created a StarGAN that can change the class of an image\n",
-    "- Evaluated the StarGAN on unseen data\n",
-    "- Used the StarGAN to create counterfactual images\n",
-    "- Used the counterfactual images to highlight the differences between classes\n",
-    "- Interpolated between the images to see how the classifier behaves\n"
+    "<ul>\n",
+    "<li> Created a StarGAN that can change the class of an image </li>\n",
+    "<li> Evaluated the StarGAN on unseen data </li>\n",
+    "<li> Used the StarGAN to create counterfactual images </li>\n",
+    "<li> Used the counterfactual images to highlight the differences between classes </li>\n",
+    "<li> Interpolated between the images to see how the classifier behaves </li>\n",
+    "</ul>"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "d546c694",
+   "id": "bbd7820d",
    "metadata": {
     "lines_to_next_cell": 0
    },
@@ -1618,7 +1620,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "bc3ed726",
+   "id": "141b4181",
    "metadata": {},
    "source": [
     "<div class=\"alert alert-block alert-info\"><h3>Task 5.1: Explore the style space</h3>\n",
@@ -1630,7 +1632,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "718ce53b",
+   "id": "b6e9c103",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1665,7 +1667,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "ca7a48a9",
+   "id": "c01c00f7",
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@@ -1681,7 +1683,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "e814f376",
+   "id": "11b7d4c9",
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@@ -1708,7 +1710,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "bbdc2fa9",
+   "id": "2c53c235",
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@@ -1722,7 +1724,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "3fe20ca4",
+   "id": "9d81df42",
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@@ -1739,7 +1741,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "ff536dd4",
+   "id": "081a67e4",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1761,7 +1763,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "d19016ff",
+   "id": "1d74498c",
    "metadata": {},
    "source": [
     "<div class=\"alert alert-block alert-warning\"><h3>Questions</h3>\n",
@@ -1773,17 +1775,19 @@
   },
   {
    "cell_type": "markdown",
-   "id": "24c11487",
+   "id": "1efd608c",
    "metadata": {},
    "source": [
     "<div class=\"alert alert-block alert-success\"><h2>Checkpoint 5</h2>\n",
     "Congratulations! You have made it to the end of the exercise!\n",
     "You have:\n",
-    "- Created a StarGAN that can change the class of an image\n",
-    "- Evaluated the StarGAN on unseen data\n",
-    "- Used the StarGAN to create counterfactual images\n",
-    "- Used the counterfactual images to highlight the differences between classes\n",
-    "- Used the style space to understand the differences between classes\n",
+    "<ul>\n",
+    "<li> Created a StarGAN that can change the class of an image </li>\n",
+    "<li> Evaluated the StarGAN on unseen data </li>\n",
+    "<li> Used the StarGAN to create counterfactual images </li>\n",
+    "<li> Used the counterfactual images to highlight the differences between classes </li>\n",
+    "<li> Used the style space to understand the differences between classes </li>\n",
+    "</ul>\n",
     "\n",
     "If you have any questions, feel free to ask them in the chat!\n",
     "And check the Solutions exercise for a definite answer to how these classes are defined!"
@@ -1791,7 +1795,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "36582123",
+   "id": "4f71144a",
    "metadata": {},
    "source": [
     "# Bonus!\n",
@@ -1806,7 +1810,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "44f3ac5f",
+   "id": "9a7ef223",
    "metadata": {
     "tags": [
      "solution"
@@ -1820,7 +1824,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "3144a680",
+   "id": "ce759160",
    "metadata": {
     "tags": [
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