11{
22 "cells": [
3- {
4- "cell_type": "markdown",
5- "metadata": {
6- "id": "view-in-github",
7- "colab_type": "text"
8- },
9- "source": [
10- "<a href=\"https://colab.research.google.com/github/ssec/WAF_ML_Tutorial_Part2/blob/main/colab_notebooks/Notebook08_UNets_PyTorch.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
11- ]
12- },
133 {
144 "cell_type": "markdown",
155 "metadata": {
4232 },
4333 {
4434 "cell_type": "code",
45- "execution_count": 1 ,
35+ "execution_count": null ,
4636 "metadata": {
4737 "colab": {
4838 "base_uri": "https://localhost:8080/"
9181 }
9282 ],
9383 "source": [
94- "#@title Install and unpack files [this will take some time]\n",
95- "\n",
84+ "# Install and unpack files [this will take some time]\n",
9685 "print('installing dependencies')\n",
9786 "!pip -q install zenodo-get\n",
9887 "!pip -q install zarr\n",
99- "# Note: We are removing the keras-unet-collection install as we will implement UNet in PyTorch manually\n",
10088 "print('grabbing sub-sevir')\n",
10189 "!zenodo_get 7011372\n",
10290 "print('unpacking sub-sevir')\n",
10593 "!tar -xf sub-sevir/sub-sevir-val.tar.gz -C sub-sevir/\n",
10694 "!tar -xf sub-sevir/sub-sevir-test.tar.gz -C sub-sevir/\n",
10795 "print('grabbing the Github repo')\n",
108- "!git clone https://github.com/ai2es /WAF_ML_Tutorial_Part2.git\n",
109- "print('done')\n "
96+ "!git clone https://github.com/ssec /WAF_ML_Tutorial_Part2.git\n",
97+ "print('done')"
11098 ]
11199 },
112100 {
124112 },
125113 {
126114 "cell_type": "code",
127- "execution_count": 2 ,
115+ "execution_count": null ,
128116 "metadata": {
129117 "colab": {
130118 "base_uri": "https://localhost:8080/"
196184 },
197185 {
198186 "cell_type": "code",
199- "execution_count": 3 ,
187+ "execution_count": null ,
200188 "metadata": {
201189 "id": "D2ldW9wxWIXZ"
202190 },
314302 },
315303 {
316304 "cell_type": "code",
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318306 "metadata": {
319307 "id": "3uUHGmceWIXZ"
320308 },
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348336 {
349337 "cell_type": "code",
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352340 "id": "dPB1W6_aWIXb"
353341 },
405393 },
406394 {
407395 "cell_type": "code",
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409397 "metadata": {
410398 "id": "ca6JduBbWIXc"
411399 },
418406 },
419407 {
420408 "cell_type": "code",
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409+ "execution_count": null ,
422410 "metadata": {
423411 "colab": {
424412 "base_uri": "https://localhost:8080/",
512500 },
513501 {
514502 "cell_type": "code",
515- "execution_count": 8 ,
503+ "execution_count": null ,
516504 "metadata": {
517505 "colab": {
518506 "base_uri": "https://localhost:8080/"
677665 },
678666 {
679667 "cell_type": "code",
680- "execution_count": 9 ,
668+ "execution_count": null ,
681669 "metadata": {
682670 "colab": {
683671 "base_uri": "https://localhost:8080/",
744732 },
745733 {
746734 "cell_type": "code",
747- "execution_count": 10 ,
735+ "execution_count": null ,
748736 "metadata": {
749737 "colab": {
750738 "base_uri": "https://localhost:8080/",
833821 },
834822 {
835823 "cell_type": "code",
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824+ "execution_count": null ,
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838826 "colab": {
839827 "base_uri": "https://localhost:8080/"
917905 },
918906 {
919907 "cell_type": "code",
920- "execution_count": 12 ,
908+ "execution_count": null ,
921909 "metadata": {
922910 "colab": {
923911 "base_uri": "https://localhost:8080/",
973961 },
974962 {
975963 "cell_type": "code",
976- "execution_count": 13 ,
964+ "execution_count": null ,
977965 "metadata": {
978966 "colab": {
979967 "base_uri": "https://localhost:8080/",
10621050 },
10631051 {
10641052 "cell_type": "code",
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1053+ "execution_count": null ,
10661054 "metadata": {
10671055 "id": "PKkRFd2hWIXg"
10681056 },
10811069 },
10821070 {
10831071 "cell_type": "code",
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10871075 },
11251113 },
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11291117 "metadata": {
11301118 "colab": {
11311119 "base_uri": "https://localhost:8080/",
12051193 },
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12071195 "cell_type": "code",
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1196+ "execution_count": null ,
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12101198 "id": "oZJObUj1WIXh"
12111199 },
12191207 },
12201208 {
12211209 "cell_type": "code",
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1210+ "execution_count": null ,
12231211 "metadata": {
12241212 "colab": {
12251213 "base_uri": "https://localhost:8080/"
12641252 },
12651253 {
12661254 "cell_type": "code",
1267- "execution_count": 38 ,
1255+ "execution_count": null ,
12681256 "metadata": {
12691257 "colab": {
12701258 "base_uri": "https://localhost:8080/",
13201308 },
13211309 {
13221310 "cell_type": "code",
1323- "execution_count": 37 ,
1311+ "execution_count": null ,
13241312 "metadata": {
13251313 "colab": {
13261314 "base_uri": "https://localhost:8080/",
14161404 "id": "7zN9Dr4nWaRC",
14171405 "outputId": "67f8c8c0-f22e-4b44-965a-6163dc202526"
14181406 },
1419- "execution_count": 22 ,
1407+ "execution_count": null ,
14201408 "outputs": [
14211409 {
14221410 "output_type": "execute_result",
14801468 "id": "SYJb35PlW-VY",
14811469 "outputId": "7dc57abd-f62f-4c4b-c034-507e3de22e85"
14821470 },
1483- "execution_count": 32 ,
1471+ "execution_count": null ,
14841472 "outputs": [
14851473 {
14861474 "output_type": "execute_result",
15751563 "id": "XjdLGzUoeulg",
15761564 "outputId": "df681a0e-ef7c-42f8-eefd-f7e25c2f3ec1"
15771565 },
1578- "execution_count": 33 ,
1566+ "execution_count": null ,
15791567 "outputs": [
15801568 {
15811569 "output_type": "display_data",
16391627 "height": 1000
16401628 }
16411629 },
1642- "execution_count": 35 ,
1630+ "execution_count": null ,
16431631 "outputs": [
16441632 {
16451633 "output_type": "display_data",
16801668 },
16811669 "colab": {
16821670 "provenance": [],
1683- "gpuType": "T4",
1684- "include_colab_link": true
1671+ "gpuType": "T4"
16851672 },
16861673 "kernelspec": {
16871674 "name": "python3",
16911678 },
16921679 "nbformat": 4,
16931680 "nbformat_minor": 0
1694- }
1681+ }
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