From dc52d141fc6954c5947c9fff138c1c6cd09b7713 Mon Sep 17 00:00:00 2001
From: Dibya Ghosh <dibya.ghosh@berkeley.edu>
Date: Wed, 13 Dec 2023 22:45:46 -0800
Subject: [PATCH] Fix pre-commit

---
 examples/01_inference_pretrained.ipynb | 29 +++++++++++++-------------
 1 file changed, 14 insertions(+), 15 deletions(-)

diff --git a/examples/01_inference_pretrained.ipynb b/examples/01_inference_pretrained.ipynb
index 1440005d..5e4262ad 100644
--- a/examples/01_inference_pretrained.ipynb
+++ b/examples/01_inference_pretrained.ipynb
@@ -14,7 +14,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": null,
    "id": "7229ce10",
    "metadata": {},
    "outputs": [],
@@ -25,7 +25,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": null,
    "id": "83d34283",
    "metadata": {},
    "outputs": [],
@@ -38,7 +38,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": null,
    "id": "15fca0dd",
    "metadata": {},
    "outputs": [
@@ -48,7 +48,7 @@
        "<matplotlib.image.AxesImage at 0x7f6b4b99c040>"
       ]
      },
-     "execution_count": 5,
+     "execution_count": null,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -76,7 +76,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": null,
    "id": "e669650f",
    "metadata": {},
    "outputs": [
@@ -118,7 +118,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": null,
    "id": "a51eb166",
    "metadata": {},
    "outputs": [
@@ -167,7 +167,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": null,
    "id": "8b0f7fd1-5b43-480f-b00f-766248d7f9af",
    "metadata": {},
    "outputs": [],
@@ -193,7 +193,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": null,
    "id": "42c04953-869d-48a8-a2df-e601324e97e6",
    "metadata": {},
    "outputs": [],
@@ -214,7 +214,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": null,
    "id": "392bd127",
    "metadata": {},
    "outputs": [
@@ -274,7 +274,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": null,
    "id": "9ad64434",
    "metadata": {},
    "outputs": [],
@@ -291,7 +291,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": null,
    "id": "74d6b20f",
    "metadata": {},
    "outputs": [],
@@ -337,7 +337,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": null,
    "id": "7a79775d",
    "metadata": {},
    "outputs": [
@@ -347,7 +347,7 @@
        "<matplotlib.legend.Legend at 0x7f6ae428b820>"
       ]
      },
-     "execution_count": 13,
+     "execution_count": null,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -410,8 +410,7 @@
    "mimetype": "text/x-python",
    "name": "python",
    "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.10.13"
+   "pygments_lexer": "ipython3"
   }
  },
  "nbformat": 4,