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71 changes: 29 additions & 42 deletions colab_notebooks/Notebook08_UNets_PyTorch.ipynb
Original file line number Diff line number Diff line change
@@ -1,15 +1,5 @@
{
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "view-in-github",
"colab_type": "text"
},
"source": [
"<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>"
]
},
{
"cell_type": "markdown",
"metadata": {
Expand Down Expand Up @@ -42,7 +32,7 @@
},
{
"cell_type": "code",
"execution_count": 1,
"execution_count": null,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
Expand Down Expand Up @@ -91,12 +81,10 @@
}
],
"source": [
"#@title Install and unpack files [this will take some time]\n",
"\n",
"# Install and unpack files [this will take some time]\n",
"print('installing dependencies')\n",
"!pip -q install zenodo-get\n",
"!pip -q install zarr\n",
"# Note: We are removing the keras-unet-collection install as we will implement UNet in PyTorch manually\n",
"print('grabbing sub-sevir')\n",
"!zenodo_get 7011372\n",
"print('unpacking sub-sevir')\n",
Expand All @@ -105,8 +93,8 @@
"!tar -xf sub-sevir/sub-sevir-val.tar.gz -C sub-sevir/\n",
"!tar -xf sub-sevir/sub-sevir-test.tar.gz -C sub-sevir/\n",
"print('grabbing the Github repo')\n",
"!git clone https://github.com/ai2es/WAF_ML_Tutorial_Part2.git\n",
"print('done')\n"
"!git clone https://github.com/ssec/WAF_ML_Tutorial_Part2.git\n",
"print('done')"
]
},
{
Expand All @@ -124,7 +112,7 @@
},
{
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"metadata": {
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Expand Down Expand Up @@ -196,7 +184,7 @@
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Expand Down Expand Up @@ -314,7 +302,7 @@
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Expand Down Expand Up @@ -347,7 +335,7 @@
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Expand Down Expand Up @@ -405,7 +393,7 @@
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Expand All @@ -418,7 +406,7 @@
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Expand Down Expand Up @@ -512,7 +500,7 @@
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Expand Down Expand Up @@ -677,7 +665,7 @@
},
{
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"metadata": {
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"base_uri": "https://localhost:8080/",
Expand Down Expand Up @@ -744,7 +732,7 @@
},
{
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"metadata": {
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"base_uri": "https://localhost:8080/",
Expand Down Expand Up @@ -833,7 +821,7 @@
},
{
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"metadata": {
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"base_uri": "https://localhost:8080/"
Expand Down Expand Up @@ -917,7 +905,7 @@
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{
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"execution_count": null,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
Expand Down Expand Up @@ -973,7 +961,7 @@
},
{
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"execution_count": null,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
Expand Down Expand Up @@ -1062,7 +1050,7 @@
},
{
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"metadata": {
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},
Expand All @@ -1081,7 +1069,7 @@
},
{
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"metadata": {
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},
Expand Down Expand Up @@ -1125,7 +1113,7 @@
},
{
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"execution_count": null,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
Expand Down Expand Up @@ -1205,7 +1193,7 @@
},
{
"cell_type": "code",
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"execution_count": null,
"metadata": {
"id": "oZJObUj1WIXh"
},
Expand All @@ -1219,7 +1207,7 @@
},
{
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"execution_count": null,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
Expand Down Expand Up @@ -1264,7 +1252,7 @@
},
{
"cell_type": "code",
"execution_count": 38,
"execution_count": null,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
Expand Down Expand Up @@ -1320,7 +1308,7 @@
},
{
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"execution_count": 37,
"execution_count": null,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
Expand Down Expand Up @@ -1416,7 +1404,7 @@
"id": "7zN9Dr4nWaRC",
"outputId": "67f8c8c0-f22e-4b44-965a-6163dc202526"
},
"execution_count": 22,
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
Expand Down Expand Up @@ -1480,7 +1468,7 @@
"id": "SYJb35PlW-VY",
"outputId": "7dc57abd-f62f-4c4b-c034-507e3de22e85"
},
"execution_count": 32,
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
Expand Down Expand Up @@ -1575,7 +1563,7 @@
"id": "XjdLGzUoeulg",
"outputId": "df681a0e-ef7c-42f8-eefd-f7e25c2f3ec1"
},
"execution_count": 33,
"execution_count": null,
"outputs": [
{
"output_type": "display_data",
Expand Down Expand Up @@ -1639,7 +1627,7 @@
"height": 1000
}
},
"execution_count": 35,
"execution_count": null,
"outputs": [
{
"output_type": "display_data",
Expand Down Expand Up @@ -1680,8 +1668,7 @@
},
"colab": {
"provenance": [],
"gpuType": "T4",
"include_colab_link": true
"gpuType": "T4"
},
"kernelspec": {
"name": "python3",
Expand All @@ -1691,4 +1678,4 @@
},
"nbformat": 4,
"nbformat_minor": 0
}
}
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