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"model_module_version": "1.5.0", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } } } } }, "cells": [ { "cell_type": "code", "execution_count": null, "metadata": { "id": "R7xc_rqnwQyE" }, "outputs": [], "source": [ "from google.colab import auth\n", "\n", "\n" ] }, { "cell_type": "code", "source": [ "auth.authenticate_user()\n" ], "metadata": { "id": "G_qxaCmS6a9Q" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "\n", "!curl https://sdk.cloud.google.com | bash\n" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "e0ND5g9X6dEP", "outputId": "c206ae59-16d0-4270-93aa-2415ab94b06f" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "\u001b[1;30;43mStreaming output truncated to the last 5000 lines.\u001b[0m\n", "google-cloud-sdk/lib/surface/service_directory/services/__init__.py\n", "google-cloud-sdk/lib/surface/service_directory/services/add_iam_policy_binding.py\n", "google-cloud-sdk/lib/surface/service_directory/services/create.py\n", "google-cloud-sdk/lib/surface/service_directory/services/delete.py\n", "google-cloud-sdk/lib/surface/service_directory/services/describe.py\n", "google-cloud-sdk/lib/surface/service_directory/services/get_iam_policy.py\n", "google-cloud-sdk/lib/surface/service_directory/services/list.py\n", "google-cloud-sdk/lib/surface/service_directory/services/remove_iam_policy_binding.py\n", "google-cloud-sdk/lib/surface/service_directory/services/resolve.py\n", "google-cloud-sdk/lib/surface/service_directory/services/set_iam_policy.py\n", "google-cloud-sdk/lib/surface/service_directory/services/update.py\n", "google-cloud-sdk/lib/surface/service_extensions/__init__.py\n", 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"google-cloud-sdk/lib/third_party/pytz/zoneinfo/America/Miquelon\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/America/Moncton\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/America/Monterrey\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/America/Montevideo\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/America/Montreal\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/America/Montserrat\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/America/Nassau\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/America/New_York\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/America/Nipigon\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/America/Nome\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/America/Noronha\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/America/North_Dakota/Beulah\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/America/North_Dakota/Center\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/America/North_Dakota/New_Salem\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/America/Nuuk\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/America/Ojinaga\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/America/Panama\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/America/Pangnirtung\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/America/Paramaribo\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/America/Phoenix\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/America/Port-au-Prince\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/America/Port_of_Spain\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/America/Porto_Acre\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/America/Porto_Velho\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/America/Puerto_Rico\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/America/Punta_Arenas\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/America/Rainy_River\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/America/Rankin_Inlet\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/America/Recife\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/America/Regina\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/America/Resolute\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/America/Rio_Branco\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/America/Rosario\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/America/Santa_Isabel\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/America/Santarem\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/America/Santiago\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/America/Santo_Domingo\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/America/Sao_Paulo\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/America/Scoresbysund\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/America/Shiprock\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/America/Sitka\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/America/St_Barthelemy\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/America/St_Johns\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/America/St_Kitts\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/America/St_Lucia\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/America/St_Thomas\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/America/St_Vincent\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/America/Swift_Current\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/America/Tegucigalpa\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/America/Thule\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/America/Thunder_Bay\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/America/Tijuana\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/America/Toronto\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/America/Tortola\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/America/Vancouver\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/America/Virgin\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/America/Whitehorse\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/America/Winnipeg\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/America/Yakutat\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/America/Yellowknife\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Antarctica/Casey\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Antarctica/Davis\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Antarctica/DumontDUrville\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Antarctica/Macquarie\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Antarctica/Mawson\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Antarctica/McMurdo\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Antarctica/Palmer\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Antarctica/Rothera\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Antarctica/South_Pole\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Antarctica/Syowa\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Antarctica/Troll\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Antarctica/Vostok\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Arctic/Longyearbyen\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Aden\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Almaty\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Amman\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Anadyr\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Aqtau\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Aqtobe\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Ashgabat\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Ashkhabad\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Atyrau\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Baghdad\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Bahrain\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Baku\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Bangkok\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Barnaul\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Beirut\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Bishkek\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Brunei\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Calcutta\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Chita\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Choibalsan\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Chongqing\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Chungking\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Colombo\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Dacca\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Damascus\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Dhaka\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Dili\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Dubai\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Dushanbe\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Famagusta\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Gaza\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Harbin\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Hebron\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Ho_Chi_Minh\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Hong_Kong\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Hovd\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Irkutsk\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Istanbul\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Jakarta\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Jayapura\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Jerusalem\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Kabul\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Kamchatka\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Karachi\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Kashgar\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Kathmandu\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Katmandu\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Khandyga\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Kolkata\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Krasnoyarsk\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Kuala_Lumpur\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Kuching\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Kuwait\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Macao\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Macau\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Magadan\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Makassar\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Manila\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Muscat\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Nicosia\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Novokuznetsk\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Novosibirsk\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Omsk\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Oral\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Phnom_Penh\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Pontianak\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Pyongyang\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Qatar\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Qostanay\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Qyzylorda\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Rangoon\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Riyadh\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Saigon\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Sakhalin\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Samarkand\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Seoul\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Shanghai\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Singapore\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Srednekolymsk\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Taipei\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Tashkent\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Tbilisi\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Tehran\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Tel_Aviv\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Thimbu\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Thimphu\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Tokyo\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Tomsk\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Ujung_Pandang\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Ulaanbaatar\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Ulan_Bator\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Urumqi\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Ust-Nera\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Vientiane\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Vladivostok\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Yakutsk\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Yangon\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Yekaterinburg\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Asia/Yerevan\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Atlantic/Azores\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Atlantic/Bermuda\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Atlantic/Canary\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Atlantic/Cape_Verde\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Atlantic/Faeroe\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Atlantic/Faroe\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Atlantic/Jan_Mayen\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Atlantic/Madeira\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Atlantic/Reykjavik\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Atlantic/South_Georgia\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Atlantic/St_Helena\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Atlantic/Stanley\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Australia/ACT\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Australia/Adelaide\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Australia/Brisbane\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Australia/Broken_Hill\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Australia/Canberra\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Australia/Currie\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Australia/Darwin\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Australia/Eucla\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Australia/Hobart\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Australia/LHI\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Australia/Lindeman\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Australia/Lord_Howe\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Australia/Melbourne\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Australia/NSW\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Australia/North\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Australia/Perth\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Australia/Queensland\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Australia/South\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Australia/Sydney\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Australia/Tasmania\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Australia/Victoria\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Australia/West\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Australia/Yancowinna\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Brazil/Acre\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Brazil/DeNoronha\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Brazil/East\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Brazil/West\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/CET\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/CST6CDT\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Canada/Atlantic\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Canada/Central\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Canada/Eastern\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Canada/Mountain\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Canada/Newfoundland\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Canada/Pacific\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Canada/Saskatchewan\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Canada/Yukon\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Chile/Continental\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Chile/EasterIsland\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Cuba\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/EET\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/EST\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/EST5EDT\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Egypt\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Eire\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Etc/GMT\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Etc/GMT+0\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Etc/GMT+1\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Etc/GMT+10\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Etc/GMT+11\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Etc/GMT+12\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Etc/GMT+2\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Etc/GMT+3\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Etc/GMT+4\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Etc/GMT+5\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Etc/GMT+6\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Etc/GMT+7\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Etc/GMT+8\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Etc/GMT+9\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Etc/GMT-0\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Etc/GMT-1\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Etc/GMT-10\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Etc/GMT-11\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Etc/GMT-12\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Etc/GMT-13\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Etc/GMT-14\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Etc/GMT-2\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Etc/GMT-3\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Etc/GMT-4\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Etc/GMT-5\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Etc/GMT-6\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Etc/GMT-7\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Etc/GMT-8\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Etc/GMT-9\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Etc/GMT0\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Etc/Greenwich\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Etc/UCT\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Etc/UTC\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Etc/Universal\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Etc/Zulu\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Europe/Amsterdam\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Europe/Andorra\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Europe/Astrakhan\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Europe/Athens\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Europe/Belfast\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Europe/Belgrade\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Europe/Berlin\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Europe/Bratislava\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Europe/Brussels\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Europe/Bucharest\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Europe/Budapest\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Europe/Busingen\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Europe/Chisinau\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Europe/Copenhagen\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Europe/Dublin\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Europe/Gibraltar\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Europe/Guernsey\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Europe/Helsinki\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Europe/Isle_of_Man\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Europe/Istanbul\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Europe/Jersey\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Europe/Kaliningrad\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Europe/Kiev\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Europe/Kirov\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Europe/Lisbon\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Europe/Ljubljana\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Europe/London\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Europe/Luxembourg\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Europe/Madrid\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Europe/Malta\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Europe/Mariehamn\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Europe/Minsk\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Europe/Monaco\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Europe/Moscow\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Europe/Nicosia\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Europe/Oslo\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Europe/Paris\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Europe/Podgorica\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Europe/Prague\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Europe/Riga\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Europe/Rome\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Europe/Samara\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Europe/San_Marino\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Europe/Sarajevo\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Europe/Saratov\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Europe/Simferopol\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Europe/Skopje\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Europe/Sofia\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Europe/Stockholm\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Europe/Tallinn\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Europe/Tirane\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Europe/Tiraspol\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Europe/Ulyanovsk\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Europe/Uzhgorod\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Europe/Vaduz\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Europe/Vatican\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Europe/Vienna\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Europe/Vilnius\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Europe/Volgograd\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Europe/Warsaw\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Europe/Zagreb\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Europe/Zaporozhye\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Europe/Zurich\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Factory\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/GB\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/GB-Eire\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/GMT\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/GMT+0\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/GMT-0\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/GMT0\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Greenwich\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/HST\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Hongkong\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Iceland\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Indian/Antananarivo\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Indian/Chagos\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Indian/Christmas\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Indian/Cocos\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Indian/Comoro\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Indian/Kerguelen\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Indian/Mahe\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Indian/Maldives\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Indian/Mauritius\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Indian/Mayotte\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Indian/Reunion\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Iran\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Israel\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Jamaica\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Japan\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Kwajalein\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Libya\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/MET\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/MST\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/MST7MDT\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Mexico/BajaNorte\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Mexico/BajaSur\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Mexico/General\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/NZ\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/NZ-CHAT\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Navajo\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/PRC\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/PST8PDT\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Pacific/Apia\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Pacific/Auckland\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Pacific/Bougainville\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Pacific/Chatham\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Pacific/Chuuk\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Pacific/Easter\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Pacific/Efate\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Pacific/Enderbury\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Pacific/Fakaofo\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Pacific/Fiji\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Pacific/Funafuti\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Pacific/Galapagos\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Pacific/Gambier\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Pacific/Guadalcanal\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Pacific/Guam\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Pacific/Honolulu\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Pacific/Johnston\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Pacific/Kiritimati\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Pacific/Kosrae\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Pacific/Kwajalein\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Pacific/Majuro\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Pacific/Marquesas\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Pacific/Midway\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Pacific/Nauru\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Pacific/Niue\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Pacific/Norfolk\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Pacific/Noumea\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Pacific/Pago_Pago\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Pacific/Palau\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Pacific/Pitcairn\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Pacific/Pohnpei\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Pacific/Ponape\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Pacific/Port_Moresby\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Pacific/Rarotonga\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Pacific/Saipan\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Pacific/Samoa\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Pacific/Tahiti\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Pacific/Tarawa\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Pacific/Tongatapu\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Pacific/Truk\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Pacific/Wake\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Pacific/Wallis\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Pacific/Yap\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Poland\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Portugal\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/ROC\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/ROK\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Singapore\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Turkey\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/UCT\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/US/Alaska\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/US/Aleutian\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/US/Arizona\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/US/Central\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/US/East-Indiana\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/US/Eastern\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/US/Hawaii\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/US/Indiana-Starke\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/US/Michigan\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/US/Mountain\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/US/Pacific\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/US/Samoa\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/UTC\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Universal\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/W-SU\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/WET\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/Zulu\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/iso3166.tab\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/leapseconds\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/posixrules\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/tzdata.zi\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/zone.tab\n", "google-cloud-sdk/lib/third_party/pytz/zoneinfo/zone1970.tab\n", "google-cloud-sdk/lib/third_party/pyu2f/LICENSE\n", "google-cloud-sdk/lib/third_party/pyu2f/__init__.py\n", "google-cloud-sdk/lib/third_party/pyu2f/apdu.py\n", "google-cloud-sdk/lib/third_party/pyu2f/convenience/__init__.py\n", "google-cloud-sdk/lib/third_party/pyu2f/convenience/authenticator.py\n", "google-cloud-sdk/lib/third_party/pyu2f/convenience/baseauthenticator.py\n", "google-cloud-sdk/lib/third_party/pyu2f/convenience/customauthenticator.py\n", "google-cloud-sdk/lib/third_party/pyu2f/convenience/localauthenticator.py\n", "google-cloud-sdk/lib/third_party/pyu2f/errors.py\n", "google-cloud-sdk/lib/third_party/pyu2f/hardware.py\n", "google-cloud-sdk/lib/third_party/pyu2f/hid/__init__.py\n", "google-cloud-sdk/lib/third_party/pyu2f/hid/base.py\n", "google-cloud-sdk/lib/third_party/pyu2f/hid/linux.py\n", "google-cloud-sdk/lib/third_party/pyu2f/hid/macos.py\n", "google-cloud-sdk/lib/third_party/pyu2f/hid/windows.py\n", "google-cloud-sdk/lib/third_party/pyu2f/hidtransport.py\n", "google-cloud-sdk/lib/third_party/pyu2f/model.py\n", "google-cloud-sdk/lib/third_party/pyu2f/u2f.py\n", "google-cloud-sdk/lib/third_party/requests/LICENSE\n", "google-cloud-sdk/lib/third_party/requests/NOTICE\n", "google-cloud-sdk/lib/third_party/requests/__init__.py\n", "google-cloud-sdk/lib/third_party/requests/__version__.py\n", "google-cloud-sdk/lib/third_party/requests/_internal_utils.py\n", "google-cloud-sdk/lib/third_party/requests/adapters.py\n", "google-cloud-sdk/lib/third_party/requests/api.py\n", "google-cloud-sdk/lib/third_party/requests/auth.py\n", "google-cloud-sdk/lib/third_party/requests/certs.py\n", "google-cloud-sdk/lib/third_party/requests/compat.py\n", "google-cloud-sdk/lib/third_party/requests/cookies.py\n", "google-cloud-sdk/lib/third_party/requests/exceptions.py\n", "google-cloud-sdk/lib/third_party/requests/help.py\n", "google-cloud-sdk/lib/third_party/requests/hooks.py\n", "google-cloud-sdk/lib/third_party/requests/models.py\n", "google-cloud-sdk/lib/third_party/requests/packages.py\n", "google-cloud-sdk/lib/third_party/requests/sessions.py\n", "google-cloud-sdk/lib/third_party/requests/status_codes.py\n", "google-cloud-sdk/lib/third_party/requests/structures.py\n", 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"google-cloud-sdk/platform/ext-runtime/ruby/templates/dockerignore.template\n", "google-cloud-sdk/platform/ext-runtime/ruby/test/runtime_test.py\n", "google-cloud-sdk/rpm/mapping/command_mapping.yaml\n", "google-cloud-sdk/rpm/mapping/component_mapping.yaml\n", "\n", "/root/google-cloud-sdk/install.sh\n", "Welcome to the Google Cloud CLI!\n", "WARNING: You appear to be running this script as root. This may cause \n", "the installation to be inaccessible to users other than the root user.\n", "\n", "To help improve the quality of this product, we collect anonymized usage data\n", "and anonymized stacktraces when crashes are encountered; additional information\n", "is available at . This data is\n", "handled in accordance with our privacy policy\n", ". You may choose to opt in this\n", "collection now (by choosing 'Y' at the below prompt), or at any time in the\n", "future by running the following command:\n", "\n", " gcloud config set disable_usage_reporting false\n", "\n", "\n", "This will install all the core command line tools necessary for working with\n", "the Google Cloud Platform.\n", "\n", "Beginning update. This process may take several minutes.\n", "\n", "\n", "Your current Google Cloud CLI version is: 449.0.0\n", "Installing components from version: 449.0.0\n", "\n", "┌─────────────────────────────────────────────────────────────────────────────┐\n", "│ These components will be installed. │\n", "├─────────────────────────────────────────────────────┬────────────┬──────────┤\n", "│ Name │ Version │ Size │\n", "├─────────────────────────────────────────────────────┼────────────┼──────────┤\n", "│ BigQuery Command Line Tool │ 2.0.98 │ 1.6 MiB │\n", "│ BigQuery Command Line Tool (Platform Specific) │ 2.0.98 │ < 1 MiB │\n", "│ Bundled Python 3.9 │ 3.9.16 │ 63.6 MiB │\n", "│ Cloud Storage Command Line Tool │ 5.26 │ 11.3 MiB │\n", "│ Cloud Storage Command Line Tool (Platform Specific) │ 5.25 │ < 1 MiB │\n", "│ Google Cloud CLI Core Libraries (Platform Specific) │ 2023.09.15 │ < 1 MiB │\n", "│ Google Cloud CRC32C Hash Tool │ 1.0.0 │ 1.2 MiB │\n", "│ anthoscli │ 0.2.40 │ 68.7 MiB │\n", "│ gcloud cli dependencies │ 2021.04.16 │ < 1 MiB │\n", "└─────────────────────────────────────────────────────┴────────────┴──────────┘\n", "\n", "For the latest full release notes, please visit:\n", " https://cloud.google.com/sdk/release_notes\n", "\n", "╔════════════════════════════════════════════════════════════╗\n", "╠═ Creating update staging area ═╣\n", "╚════════════════════════════════════════════════════════════╝\n", "╔════════════════════════════════════════════════════════════╗\n", "╠═ Installing: BigQuery Command Line Tool ═╣\n", "╚════════════════════════════════════════════════════════════╝\n", "╔════════════════════════════════════════════════════════════╗\n", "╠═ Installing: BigQuery Command Line Tool (Platform Spec... ═╣\n", "╚════════════════════════════════════════════════════════════╝\n", "╔════════════════════════════════════════════════════════════╗\n", "╠═ Installing: Bundled Python 3.9 ═╣\n", "╚════════════════════════════════════════════════════════════╝\n", "╔════════════════════════════════════════════════════════════╗\n", "╠═ Installing: Bundled Python 3.9 ═╣\n", "╚════════════════════════════════════════════════════════════╝\n", "╔════════════════════════════════════════════════════════════╗\n", "╠═ Installing: Cloud Storage Command Line Tool ═╣\n", "╚════════════════════════════════════════════════════════════╝\n", "╔════════════════════════════════════════════════════════════╗\n", "╠═ Installing: Cloud Storage Command Line Tool (Platform... ═╣\n", "╚════════════════════════════════════════════════════════════╝\n", "╔════════════════════════════════════════════════════════════╗\n", "╠═ Installing: Default set of gcloud commands ═╣\n", "╚════════════════════════════════════════════════════════════╝\n", "╔════════════════════════════════════════════════════════════╗\n", "╠═ Installing: Google Cloud CLI Core Libraries (Platform... ═╣\n", "╚════════════════════════════════════════════════════════════╝\n", "╔════════════════════════════════════════════════════════════╗\n", "╠═ Installing: Google Cloud CRC32C Hash Tool ═╣\n", "╚════════════════════════════════════════════════════════════╝\n", "╔════════════════════════════════════════════════════════════╗\n", "╠═ Installing: Google Cloud CRC32C Hash Tool ═╣\n", "╚════════════════════════════════════════════════════════════╝\n", "╔════════════════════════════════════════════════════════════╗\n", "╠═ Installing: anthoscli ═╣\n", "╚════════════════════════════════════════════════════════════╝\n", "╔════════════════════════════════════════════════════════════╗\n", "╠═ Installing: anthoscli ═╣\n", "╚════════════════════════════════════════════════════════════╝\n", "╔════════════════════════════════════════════════════════════╗\n", "╠═ Installing: gcloud cli dependencies ═╣\n", "╚════════════════════════════════════════════════════════════╝\n", "╔════════════════════════════════════════════════════════════╗\n", "╠═ Creating backup and activating new installation ═╣\n", "╚════════════════════════════════════════════════════════════╝\n", "\n", "\n", "Update done!\n", "\n", "\u001b[1;33mWARNING:\u001b[0m There are other instances of Google Cloud tools on your system PATH.\n", " Please remove the following to avoid confusion or accidental invocation:\n", "\n", " /tools/google-cloud-sdk/bin/gcloud-crc32c\n", "/tools/google-cloud-sdk/bin/anthoscli\n", "/tools/google-cloud-sdk/bin/java_dev_appserver.sh\n", "/tools/google-cloud-sdk/bin/git-credential-gcloud.sh\n", "/tools/google-cloud-sdk/bin/dev_appserver.py\n", "/tools/google-cloud-sdk/bin/gcloud\n", "/tools/google-cloud-sdk/bin/gsutil\n", "/tools/google-cloud-sdk/bin/docker-credential-gcloud\n", "/tools/google-cloud-sdk/bin/bq\n", "\n", " \n", "==> Source [/root/google-cloud-sdk/completion.bash.inc] in your profile to enable shell command completion for gcloud.\n", "==> Source [/root/google-cloud-sdk/path.bash.inc] in your profile to add the Google Cloud SDK command line tools to your $PATH.\n", "\n", "For more information on how to get started, please visit:\n", " https://cloud.google.com/sdk/docs/quickstarts\n", "\n", "\n" ] } ] }, { "cell_type": "code", "source": [ "!ls /root/google-cloud-sdk" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "yGH2vgRj6yjb", "outputId": "9d00db5e-86fe-4704-ffe6-d031b6e76d53" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "bin\t\t deb\t LICENSE\t platform\trpm\n", "completion.bash.inc install.bat path.bash.inc properties\tVERSION\n", "completion.zsh.inc install.sh path.fish.inc README\n", "data\t\t lib\t path.zsh.inc\t RELEASE_NOTES\n" ] } ] }, { "cell_type": "code", "source": [ "!rm -rf /root/google-cloud-sdk" ], "metadata": { "id": "_iaKJTtR6zH7" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "!gcloud init" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "59a5JEOE6f2Y", "outputId": "648c10fc-3c20-4ca8-f12b-11e9c1e469d1" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Welcome! This command will take you through the configuration of gcloud.\n", "\n", "Settings from your current configuration [default] are:\n", "component_manager:\n", " disable_update_check: 'True'\n", "core:\n", " account: harshchandrahc5@gmail.com\n", "\n", "Pick configuration to use:\n", " [1] Re-initialize this configuration [default] with new settings \n", " [2] Create a new configuration\n", "Please enter your numeric choice: \n", "\n", "Command killed by keyboard interrupt\n", "\n", "^C\n" ] } ] }, { "cell_type": "code", "source": [ "!gcloud init --no-launch-browser" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "BHfW8zum7KF-", "outputId": "3ed24dfb-efc6-4d52-b021-e93adc25c5f1" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Welcome! This command will take you through the configuration of gcloud.\n", "\n", "Settings from your current configuration [default] are:\n", "component_manager:\n", " disable_update_check: 'True'\n", "core:\n", " account: harshchandrahc5@gmail.com\n", "\n", "Pick configuration to use:\n", " [1] Re-initialize this configuration [default] with new settings \n", " [2] Create a new configuration\n", "Please enter your numeric choice: 1\n", "\n", "Your current configuration has been set to: [default]\n", "\n", "You can skip diagnostics next time by using the following flag:\n", " gcloud init --skip-diagnostics\n", "\n", "Network diagnostic detects and fixes local network connection issues.\n", "Reachability Check passed.\n", "Network diagnostic passed (1/1 checks passed).\n", "\n", "Choose the account you would like to use to perform operations for this \n", "configuration:\n", " [1] harshchandrahc5@gmail.com\n", " [2] Log in with a new account\n", "Please enter your numeric choice: 1\n", "\n", "You are logged in as: [harshchandrahc5@gmail.com].\n", "\n", "Pick cloud project to use: \n", " [1] careersxp-web\n", " [2] cv-builder-56c7e\n", " [3] electronicslovers-45b40\n", " [4] electronicslovers-f6b4a\n", " [5] friendly-chat-53e1c\n", " [6] harshhc-portfolio\n", " [7] hc-test-bot\n", " [8] hc-vision-944f6\n", " [9] hive-app-buzz\n", " [10] hive-eia\n", " [11] instagram-stickers\n", " [12] lotopop-app\n", " [13] mapstest-1526137790413\n", " [14] news-app-356a0\n", " [15] online-electronics-store-ff686\n", " [16] proud-outrider-401316\n", " [17] quality-stickers\n", " [18] sessionstorm-web\n", " [19] snapshotcv-c5be7\n", " [20] sticker-test-6a239\n", " [21] study-pomodoro\n", " [22] webdev-project-261713\n", " [23] whatsapp-stickers-eb4f8\n", " [24] Enter a project ID\n", " [25] Create a new project\n", "Please enter numeric choice or text value (must exactly match list item): 25\n", "\n", "Enter a Project ID. Note that a Project ID CANNOT be changed later.\n", "Project IDs must be 6-30 characters (lowercase ASCII, digits, or\n", "hyphens) in length and start with a lowercase letter. nasa-challenge2023\n", "Your current project has been set to: [nasa-challenge2023].\n", "\n", "Not setting default zone/region (this feature makes it easier to use\n", "[gcloud compute] by setting an appropriate default value for the\n", "--zone and --region flag).\n", "See https://cloud.google.com/compute/docs/gcloud-compute section on how to set\n", "default compute region and zone manually. If you would like [gcloud init] to be\n", "able to do this for you the next time you run it, make sure the\n", "Compute Engine API is enabled for your project on the\n", "https://console.developers.google.com/apis page.\n", "\n", "Your Google Cloud SDK is configured and ready to use!\n", "\n", "* Commands that require authentication will use harshchandrahc5@gmail.com by default\n", "* Commands will reference project `nasa-challenge2023` by default\n", "Run `gcloud help config` to learn how to change individual settings\n", "\n", "This gcloud configuration is called [default]. You can create additional configurations if you work with multiple accounts and/or projects.\n", "Run `gcloud topic configurations` to learn more.\n", "\n", "Some things to try next:\n", "\n", "* Run `gcloud --help` to see the Cloud Platform services you can interact with. And run `gcloud help COMMAND` to get help on any gcloud command.\n", "* Run `gcloud topic --help` to learn about advanced features of the SDK like arg files and output formatting\n", "* Run `gcloud cheat-sheet` to see a roster of go-to `gcloud` commands.\n" ] } ] }, { "cell_type": "code", "source": [ "!echo \"deb http://packages.cloud.google.com/apt gcsfuse-bionic main\" > /etc/apt/sources.list.d/gcsfuse.list\n", "!curl https://packages.cloud.google.com/apt/doc/apt-key.gpg | apt-key add -\n", "!apt -qq update\n", "!apt -qq install gcsfuse" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "YCcG8huz5Di9", "outputId": "a4b547f2-7205-492a-f70a-93f3fdfb90f6" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ " % Total % Received % Xferd Average Speed Time Time Time Current\n", " Dload Upload Total Spent Left Speed\n", "\r 0 0 0 0 0 0 0 0 --:--:-- --:--:-- --:--:-- 0\r100 2659 100 2659 0 0 18841 0 --:--:-- --:--:-- --:--:-- 18992\n", "Warning: apt-key is deprecated. Manage keyring files in trusted.gpg.d instead (see apt-key(8)).\n", "OK\n", "18 packages can be upgraded. Run 'apt list --upgradable' to see them.\n", "\u001b[1;33mW: \u001b[0mhttp://packages.cloud.google.com/apt/dists/gcsfuse-bionic/InRelease: Key is stored in legacy trusted.gpg keyring (/etc/apt/trusted.gpg), see the DEPRECATION section in apt-key(8) for details.\u001b[0m\n", "The following NEW packages will be installed:\n", " gcsfuse\n", "0 upgraded, 1 newly installed, 0 to remove and 18 not upgraded.\n", "Need to get 5,558 kB of archives.\n", "After this operation, 0 B of additional disk space will be used.\n", "Selecting previously unselected package gcsfuse.\n", "(Reading database ... 120875 files and directories currently installed.)\n", "Preparing to unpack .../gcsfuse_1.2.0_amd64.deb ...\n", "Unpacking gcsfuse (1.2.0) ...\n", "Setting up gcsfuse (1.2.0) ...\n" ] } ] }, { "cell_type": "code", "source": [ "!pip3 install tf2onnx" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "c4ktABlsukGi", "outputId": "4aea120f-2804-4327-a9b0-646346ff6239" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Collecting tf2onnx\n", " Downloading tf2onnx-1.15.1-py3-none-any.whl (454 kB)\n", "\u001b[?25l \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m0.0/454.7 kB\u001b[0m \u001b[31m?\u001b[0m eta \u001b[36m-:--:--\u001b[0m\r\u001b[2K \u001b[91m━━━━━━━━━━━━━\u001b[0m\u001b[90m╺\u001b[0m\u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m153.6/454.7 kB\u001b[0m \u001b[31m4.3 MB/s\u001b[0m eta \u001b[36m0:00:01\u001b[0m\r\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m454.7/454.7 kB\u001b[0m \u001b[31m8.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", "\u001b[?25hRequirement already satisfied: numpy>=1.14.1 in /usr/local/lib/python3.10/dist-packages (from tf2onnx) (1.23.5)\n", "Collecting onnx>=1.4.1 (from tf2onnx)\n", " Downloading onnx-1.14.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (14.6 MB)\n", "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m14.6/14.6 MB\u001b[0m \u001b[31m101.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", "\u001b[?25hRequirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from tf2onnx) (2.31.0)\n", "Requirement already satisfied: six in /usr/local/lib/python3.10/dist-packages (from tf2onnx) (1.16.0)\n", "Requirement already satisfied: flatbuffers>=1.12 in /usr/local/lib/python3.10/dist-packages (from tf2onnx) (23.5.26)\n", "Requirement already satisfied: protobuf~=3.20.2 in /usr/local/lib/python3.10/dist-packages (from tf2onnx) (3.20.3)\n", "Requirement already satisfied: typing-extensions>=3.6.2.1 in /usr/local/lib/python3.10/dist-packages (from onnx>=1.4.1->tf2onnx) (4.5.0)\n", "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests->tf2onnx) (3.3.0)\n", "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->tf2onnx) (3.4)\n", "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests->tf2onnx) (2.0.6)\n", "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests->tf2onnx) (2023.7.22)\n", "Installing collected packages: onnx, tf2onnx\n", "Successfully installed onnx-1.14.1 tf2onnx-1.15.1\n" ] } ] }, { "cell_type": "code", "source": [ "!pip3 install onnx" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "mItVl3pOunWm", "outputId": "c97e93f3-88eb-40a4-de6a-f093da5a0a4b" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Requirement already satisfied: onnx in /usr/local/lib/python3.10/dist-packages (1.14.1)\n", "Requirement already satisfied: numpy in /usr/local/lib/python3.10/dist-packages (from onnx) (1.23.5)\n", "Requirement already satisfied: protobuf>=3.20.2 in /usr/local/lib/python3.10/dist-packages (from onnx) (3.20.3)\n", "Requirement already satisfied: typing-extensions>=3.6.2.1 in /usr/local/lib/python3.10/dist-packages (from onnx) (4.5.0)\n" ] } ] }, { "cell_type": "code", "source": [ "import torch\n", "import onnx\n", "from onnx_tf.backend import prepare\n", "\n", "# Load your PyTorch model\n", "pytorch_model = torch.load(\"/home/Prithvi_100M.pt\")\n", "# Set the model to evaluation mode\n", "pytorch_model.eval()\n", "\n", "# Create dummy input data for tracing\n", "dummy_input = torch.randn(1, 3, 224, 224) # Adjust the shape to match your model input\n", "\n", "# Export the PyTorch model to ONNX\n", "onnx_model_path = \"model.onnx\"\n", "torch.onnx.export(pytorch_model, dummy_input, onnx_model_path, verbose=True, input_names=['input'], output_names=['output'])\n", "\n" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 250 }, "id": "_ZrMfMpvsOXY", "outputId": "31ae778f-45dc-4c67-a60b-4c5dc59d0e52" }, "execution_count": null, "outputs": [ { "output_type": "error", "ename": "AttributeError", "evalue": "ignored", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mAttributeError\u001b[0m Traceback (most recent call last)", "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[1;32m 6\u001b[0m \u001b[0mpytorch_model\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtorch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mload\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"/home/Prithvi_100M.pt\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 7\u001b[0m \u001b[0;31m# Set the model to evaluation mode\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 8\u001b[0;31m \u001b[0mpytorch_model\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0meval\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 9\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 10\u001b[0m \u001b[0;31m# Create dummy input data for tracing\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;31mAttributeError\u001b[0m: 'collections.OrderedDict' object has no attribute 'eval'" ] } ] }, { "cell_type": "code", "source": [ "!pip3 install onnx-tf" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "w7bhMe8XwETk", "outputId": "120f2eba-8782-490b-fcf5-39da19287eb6" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Collecting onnx-tf\n", " Downloading onnx_tf-1.10.0-py3-none-any.whl (226 kB)\n", "\u001b[?25l \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m0.0/226.1 kB\u001b[0m \u001b[31m?\u001b[0m eta \u001b[36m-:--:--\u001b[0m\r\u001b[2K \u001b[91m━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[90m╺\u001b[0m\u001b[90m━━━━━━━━━━\u001b[0m \u001b[32m163.8/226.1 kB\u001b[0m \u001b[31m5.6 MB/s\u001b[0m eta 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onnx>=1.10.2->onnx-tf) (3.20.3)\n", "Requirement already satisfied: typing-extensions>=3.6.2.1 in /usr/local/lib/python3.10/dist-packages (from onnx>=1.10.2->onnx-tf) (4.5.0)\n", "Requirement already satisfied: packaging in /usr/local/lib/python3.10/dist-packages (from tensorflow-addons->onnx-tf) (23.2)\n", "Collecting typeguard<3.0.0,>=2.7 (from tensorflow-addons->onnx-tf)\n", " Downloading typeguard-2.13.3-py3-none-any.whl (17 kB)\n", "Installing collected packages: typeguard, tensorflow-addons, onnx-tf\n", "Successfully installed onnx-tf-1.10.0 tensorflow-addons-0.21.0 typeguard-2.13.3\n" ] } ] }, { "cell_type": "code", "source": [ "import onnx\n", "from onnx_tf.backend import prepare\n", "\n", "# Load the ONNX model\n", "onnx_model = onnx.load(onnx_model_path)\n", "\n", "# Convert the ONNX model to TensorFlow\n", "tf_rep = prepare(onnx_model)\n", "\n", "# Export the TensorFlow model to a saved model directory\n", "saved_model_dir = \"tensorflow_model\"\n", "tf_rep.export_graph(saved_model_dir)\n" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 411 }, "id": "LKoEZ9nbv-ht", "outputId": "921ad381-f5ed-4752-b31c-744947c669cb" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stderr", "text": [ "/usr/local/lib/python3.10/dist-packages/tensorflow_addons/utils/tfa_eol_msg.py:23: UserWarning: \n", "\n", "TensorFlow Addons (TFA) has ended development and introduction of new features.\n", "TFA has entered a minimal maintenance and release mode until a planned end of life in May 2024.\n", "Please modify downstream libraries to take dependencies from other repositories in our TensorFlow community (e.g. Keras, Keras-CV, and Keras-NLP). \n", "\n", "For more information see: https://github.com/tensorflow/addons/issues/2807 \n", "\n", " warnings.warn(\n" ] }, { "output_type": "error", "ename": "NameError", "evalue": "ignored", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[0;31m# Load the ONNX model\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 5\u001b[0;31m \u001b[0monnx_model\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0monnx\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mload\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0monnx_model_path\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 6\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 7\u001b[0m \u001b[0;31m# Convert the ONNX model to TensorFlow\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;31mNameError\u001b[0m: name 'onnx_model_path' is not defined" ] } ] }, { "cell_type": "code", "source": [ "import tensorflow as tf\n", "\n", "# Load the saved TensorFlow model\n", "saved_model_dir = \"tensorflow_model\"\n", "loaded_model = tf.saved_model.load(saved_model_dir)\n", "\n", "# Convert to TFLite\n", "converter = tf.lite.TFLiteConverter.from_saved_model(saved_model_dir)\n", "tflite_model = converter.convert()\n", "\n", "# Save the TFLite model to a file\n", "with open(\"model.tflite\", \"wb\") as f:\n", " f.write(tflite_model)\n" ], "metadata": { "id": "BfA_yPnKwB3R" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "!pip install rasterio\n" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "8Uptai_D8oZ-", "outputId": "3bf220cc-787e-424c-c38f-b36caffb92ef" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Collecting rasterio\n", " Downloading rasterio-1.3.8-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (21.3 MB)\n", "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m21.3/21.3 MB\u001b[0m \u001b[31m79.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", "\u001b[?25hCollecting affine (from rasterio)\n", " Downloading affine-2.4.0-py3-none-any.whl (15 kB)\n", "Requirement already satisfied: attrs in /usr/local/lib/python3.10/dist-packages (from rasterio) (23.1.0)\n", "Requirement already satisfied: certifi in /usr/local/lib/python3.10/dist-packages (from rasterio) (2023.7.22)\n", "Requirement already satisfied: click>=4.0 in /usr/local/lib/python3.10/dist-packages (from rasterio) (8.1.7)\n", "Requirement already satisfied: cligj>=0.5 in /usr/local/lib/python3.10/dist-packages (from rasterio) (0.7.2)\n", "Requirement already satisfied: numpy>=1.18 in /usr/local/lib/python3.10/dist-packages (from rasterio) (1.23.5)\n", "Collecting snuggs>=1.4.1 (from rasterio)\n", " Downloading snuggs-1.4.7-py3-none-any.whl (5.4 kB)\n", "Requirement already satisfied: click-plugins in /usr/local/lib/python3.10/dist-packages (from rasterio) (1.1.1)\n", "Requirement already satisfied: setuptools in /usr/local/lib/python3.10/dist-packages (from rasterio) (67.7.2)\n", "Requirement already satisfied: pyparsing>=2.1.6 in /usr/local/lib/python3.10/dist-packages (from snuggs>=1.4.1->rasterio) (3.1.1)\n", "Installing collected packages: snuggs, affine, rasterio\n", "Successfully installed affine-2.4.0 rasterio-1.3.8 snuggs-1.4.7\n" ] } ] }, { "cell_type": "code", "source": [ "%cd /home\n", "!sudo mkdir checkpoints" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "bPZOyqXb8oSz", "outputId": "bcd72103-2e2f-4207-c43f-e47ae57f752e" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "/home\n" ] } ] }, { "cell_type": "code", "source": [ "!gsutil cp gs://sen1floods11/v1.1/splits/flood_handlabeled/flood_train_data.csv .\n", "!gsutil cp gs://sen1floods11/v1.1/splits/flood_handlabeled/flood_test_data.csv .\n", "!gsutil cp gs://sen1floods11/v1.1/splits/flood_handlabeled/flood_valid_data.csv ." ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "1pmgiBY-8oJ_", "outputId": "641798c7-bf66-4e46-daff-efc84e7e1ba5" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Copying gs://sen1floods11/v1.1/splits/flood_handlabeled/flood_train_data.csv...\n", "/ [1 files][ 13.3 KiB/ 13.3 KiB] \n", "Operation completed over 1 objects/13.3 KiB. \n", "Copying gs://sen1floods11/v1.1/splits/flood_handlabeled/flood_test_data.csv...\n", "/ [1 files][ 4.7 KiB/ 4.7 KiB] \n", "Operation completed over 1 objects/4.7 KiB. \n", "Copying gs://sen1floods11/v1.1/splits/flood_handlabeled/flood_valid_data.csv...\n", "/ [1 files][ 4.7 KiB/ 4.7 KiB] \n", "Operation completed over 1 objects/4.7 KiB. \n" ] } ] }, { "cell_type": "code", "source": [ "!sudo mkdir files\n", "!sudo mkdir files/S1\n", "!sudo mkdir files/Labels\n", "\n", "!gsutil -m rsync -r gs://sen1floods11/v1.1/data/flood_events/HandLabeled/S1Hand files/S1\n", "!gsutil -m rsync -r gs://sen1floods11/v1.1/data/flood_events/HandLabeled/LabelHand files/Labels" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "W7MrL49489uN", "outputId": "3fb7cbdb-d542-4623-97a5-9304bbc0113a" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "\n", "WARNING: gsutil rsync uses hashes when modification time is not available at\n", "both the source and destination. Your crcmod installation isn't using the\n", "module's C extension, so checksumming will run very slowly. If this is your\n", "first rsync since updating gsutil, this rsync can take significantly longer than\n", "usual. For help installing the extension, please see \"gsutil help crcmod\".\n", "\n", "Building synchronization state...\n", "Starting synchronization...\n", "Copying gs://sen1floods11/v1.1/data/flood_events/HandLabeled/S1Hand/Bolivia_233925_S1Hand.tif...\n", "Copying gs://sen1floods11/v1.1/data/flood_events/HandLabeled/S1Hand/Bolivia_242570_S1Hand.tif...\n", "Copying gs://sen1floods11/v1.1/data/flood_events/HandLabeled/S1Hand/Bolivia_290290_S1Hand.tif...\n", "Copying gs://sen1floods11/v1.1/data/flood_events/HandLabeled/S1Hand/Bolivia_294583_S1Hand.tif...\n", "Copying gs://sen1floods11/v1.1/data/flood_events/HandLabeled/S1Hand/Bolivia_312675_S1Hand.tif...\n", "Copying gs://sen1floods11/v1.1/data/flood_events/HandLabeled/S1Hand/Bolivia_195474_S1Hand.tif...\n", "Copying gs://sen1floods11/v1.1/data/flood_events/HandLabeled/S1Hand/Bolivia_129334_S1Hand.tif...\n", "Copying gs://sen1floods11/v1.1/data/flood_events/HandLabeled/S1Hand/Bolivia_314919_S1Hand.tif...\n", "Copying 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gs://sen1floods11/v1.1/data/flood_events/HandLabeled/S1Hand/USA_955053_S1Hand.tif...\n", "Copying gs://sen1floods11/v1.1/data/flood_events/HandLabeled/S1Hand/USA_986268_S1Hand.tif...\n", "Copying gs://sen1floods11/v1.1/data/flood_events/HandLabeled/S1Hand/USA_994009_S1Hand.tif...\n", "| [446/446 files][695.7 MiB/695.7 MiB] 100% Done 15.4 MiB/s ETA 00:00:00 \n", "Operation completed over 446 objects/695.7 MiB. \n", "\n", "WARNING: gsutil rsync uses hashes when modification time is not available at\n", "both the source and destination. Your crcmod installation isn't using the\n", "module's C extension, so checksumming will run very slowly. If this is your\n", "first rsync since updating gsutil, this rsync can take significantly longer than\n", "usual. For help installing the extension, please see \"gsutil help crcmod\".\n", "\n", "Building synchronization state...\n", "Starting synchronization...\n", "Copying gs://sen1floods11/v1.1/data/flood_events/HandLabeled/LabelHand/Bolivia_23014_LabelHand.tif...\n", "Copying gs://sen1floods11/v1.1/data/flood_events/HandLabeled/LabelHand/Bolivia_129334_LabelHand.tif...\n", "Copying gs://sen1floods11/v1.1/data/flood_events/HandLabeled/LabelHand/Bolivia_294583_LabelHand.tif...\n", "Copying gs://sen1floods11/v1.1/data/flood_events/HandLabeled/LabelHand/Bolivia_242570_LabelHand.tif...\n", "Copying gs://sen1floods11/v1.1/data/flood_events/HandLabeled/LabelHand/Bolivia_290290_LabelHand.tif...\n", "Copying gs://sen1floods11/v1.1/data/flood_events/HandLabeled/LabelHand/Bolivia_314919_LabelHand.tif...\n", "Copying gs://sen1floods11/v1.1/data/flood_events/HandLabeled/LabelHand/Bolivia_233925_LabelHand.tif...\n", "Copying 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"!zip -r /data.zip ./files" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "cikXvWjK4eoU", "outputId": "d5fa7114-9842-4fc8-8621-983a5ef68872" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ " adding: files/ (stored 0%)\n", " adding: files/Labels/ (stored 0%)\n", " adding: files/Labels/USA_224165_LabelHand.tif (deflated 55%)\n", " adding: files/Labels/Spain_2472849_LabelHand.tif (deflated 41%)\n", " adding: files/Labels/Paraguay_24341_LabelHand.tif (deflated 3%)\n", " adding: files/Labels/India_79637_LabelHand.tif (deflated 8%)\n", " adding: files/Labels/Sri-Lanka_63307_LabelHand.tif (deflated 16%)\n", " adding: files/Labels/Paraguay_12870_LabelHand.tif (deflated 69%)\n", " adding: files/Labels/USA_211406_LabelHand.tif (deflated 35%)\n", " adding: files/Labels/Nigeria_598959_LabelHand.tif (deflated 2%)\n", " adding: files/Labels/Ghana_1089161_LabelHand.tif (deflated 18%)\n", " adding: 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adding: files/S1/Ghana_154838_S1Hand.tif (deflated 0%)\n", " adding: files/S1/Spain_2472849_S1Hand.tif (deflated 0%)\n", " adding: files/S1/USA_66026_S1Hand.tif (deflated 0%)\n", " adding: files/S1/Paraguay_1056717_S1Hand.tif (deflated 0%)\n", " adding: files/S1/Paraguay_271769_S1Hand.tif (deflated 0%)\n", " adding: files/S1/Paraguay_149787_S1Hand.tif (deflated 0%)\n", " adding: files/S1/India_1018327_S1Hand.tif (deflated 0%)\n", " adding: files/S1/Bolivia_129334_S1Hand.tif (deflated 0%)\n", " adding: files/S1/Spain_2594119_S1Hand.tif (deflated 0%)\n", " adding: files/S1/Sri-Lanka_748447_S1Hand.tif (deflated 0%)\n", " adding: files/S1/India_691027_S1Hand.tif (deflated 0%)\n", " adding: files/S1/Ghana_247288_S1Hand.tif (deflated 0%)\n", " adding: files/S1/Sri-Lanka_883641_S1Hand.tif (deflated 0%)\n", " adding: files/S1/India_631692_S1Hand.tif (deflated 0%)\n", " adding: files/S1/Ghana_53713_S1Hand.tif (deflated 0%)\n", " adding: files/S1/Paraguay_7894_S1Hand.tif (deflated 0%)\n", " adding: files/S1/Spain_716716_S1Hand.tif (deflated 0%)\n", " adding: files/S1/Nigeria_600295_S1Hand.tif (deflated 0%)\n", " adding: files/S1/Mekong_221789_S1Hand.tif (deflated 0%)\n", " adding: files/S1/Mekong_45934_S1Hand.tif (deflated 0%)\n", " adding: files/S1/Spain_6095801_S1Hand.tif (deflated 0%)\n", " adding: files/S1/India_773682_S1Hand.tif (deflated 0%)\n", " adding: files/S1/Spain_7558720_S1Hand.tif (deflated 0%)\n", " adding: files/S1/Spain_5816638_S1Hand.tif (deflated 0%)\n", " adding: files/S1/Ghana_359826_S1Hand.tif (deflated 0%)\n", " adding: files/S1/Somalia_32375_S1Hand.tif (deflated 0%)\n", " adding: files/S1/Pakistan_246718_S1Hand.tif (deflated 0%)\n", " adding: files/S1/Mekong_333434_S1Hand.tif (deflated 0%)\n", " adding: files/S1/Spain_2523247_S1Hand.tif (deflated 0%)\n", " adding: files/S1/India_25540_S1Hand.tif (deflated 0%)\n", " adding: files/S1/Somalia_205466_S1Hand.tif (deflated 0%)\n", " adding: files/S1/Paraguay_172476_S1Hand.tif (deflated 0%)\n", " adding: files/S1/Somalia_989553_S1Hand.tif (deflated 0%)\n" ] } ] }, { "cell_type": "code", "source": [ "LR = 5e-4\n", "EPOCHS = 100\n", "EPOCHS_PER_UPDATE = 1\n", "RUNNAME = \"Sen1Floods11\"" ], "metadata": { "id": "x4Jirr9-ptFk" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "import torch\n", "from torchvision import transforms\n", "import torchvision.transforms.functional as F\n", "import random\n", "from PIL import Image\n", "\n", "class InMemoryDataset(torch.utils.data.Dataset):\n", "\n", " def __init__(self, data_list, preprocess_func):\n", " self.data_list = data_list\n", " self.preprocess_func = preprocess_func\n", "\n", " def __getitem__(self, i):\n", " return self.preprocess_func(self.data_list[i])\n", "\n", " def __len__(self):\n", " return len(self.data_list)\n", "\n", "\n", "def processAndAugment(data):\n", " (x,y) = data\n", " im,label = x.copy(), y.copy()\n", "\n", " # convert to PIL for easier transforms\n", " im1 = Image.fromarray(im[0])\n", " im2 = Image.fromarray(im[1])\n", " label = Image.fromarray(label.squeeze())\n", "\n", " # Get params for random transforms\n", " i, j, h, w = transforms.RandomCrop.get_params(im1, (256, 256))\n", "\n", " im1 = F.crop(im1, i, j, h, w)\n", " im2 = F.crop(im2, i, j, h, w)\n", " label = F.crop(label, i, j, h, w)\n", " if random.random() > 0.5:\n", " im1 = F.hflip(im1)\n", " im2 = F.hflip(im2)\n", " label = F.hflip(label)\n", " if random.random() > 0.5:\n", " im1 = F.vflip(im1)\n", " im2 = F.vflip(im2)\n", " label = F.vflip(label)\n", "\n", " norm = transforms.Normalize([0.6851, 0.5235], [0.0820, 0.1102])\n", " im = torch.stack([transforms.ToTensor()(im1).squeeze(), transforms.ToTensor()(im2).squeeze()])\n", " im = norm(im)\n", " label = transforms.ToTensor()(label).squeeze()\n", " if torch.sum(label.gt(.003) * label.lt(.004)):\n", " label *= 255\n", " label = label.round()\n", "\n", " return im, label\n", "\n", "\n", "def processTestIm(data):\n", " (x,y) = data\n", " im,label = x.copy(), y.copy()\n", " norm = transforms.Normalize([0.6851, 0.5235], [0.0820, 0.1102])\n", "\n", " # convert to PIL for easier transforms\n", " im_c1 = Image.fromarray(im[0]).resize((512,512))\n", " im_c2 = Image.fromarray(im[1]).resize((512,512))\n", " label = Image.fromarray(label.squeeze()).resize((512,512))\n", "\n", " im_c1s = [F.crop(im_c1, 0, 0, 256, 256), F.crop(im_c1, 0, 256, 256, 256),\n", " F.crop(im_c1, 256, 0, 256, 256), F.crop(im_c1, 256, 256, 256, 256)]\n", " im_c2s = [F.crop(im_c2, 0, 0, 256, 256), F.crop(im_c2, 0, 256, 256, 256),\n", " F.crop(im_c2, 256, 0, 256, 256), F.crop(im_c2, 256, 256, 256, 256)]\n", " labels = [F.crop(label, 0, 0, 256, 256), F.crop(label, 0, 256, 256, 256),\n", " F.crop(label, 256, 0, 256, 256), F.crop(label, 256, 256, 256, 256)]\n", "\n", " ims = [torch.stack((transforms.ToTensor()(x).squeeze(),\n", " transforms.ToTensor()(y).squeeze()))\n", " for (x,y) in zip(im_c1s, im_c2s)]\n", "\n", " ims = [norm(im) for im in ims]\n", " ims = torch.stack(ims)\n", "\n", " labels = [(transforms.ToTensor()(label).squeeze()) for label in labels]\n", " labels = torch.stack(labels)\n", "\n", " if torch.sum(labels.gt(.003) * labels.lt(.004)):\n", " labels *= 255\n", " labels = labels.round()\n", "\n", " return ims, labels\n" ], "metadata": { "id": "S7TwbtFUpC56" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "from time import time\n", "import csv\n", "import os\n", "import numpy as np\n", "import rasterio\n", "\n", "def getArrFlood(fname):\n", " return rasterio.open(fname).read()\n", "\n", "def download_flood_water_data_from_list(l):\n", " i = 0\n", " tot_nan = 0\n", " tot_good = 0\n", " flood_data = []\n", " for (im_fname, mask_fname) in l:\n", " if not os.path.exists(os.path.join(\"files/\", im_fname)):\n", " continue\n", " arr_x = np.nan_to_num(getArrFlood(os.path.join(\"files/\", im_fname)))\n", " arr_y = getArrFlood(os.path.join(\"files/\", mask_fname))\n", " arr_y[arr_y == -1] = 255\n", "\n", " arr_x = np.clip(arr_x, -50, 1)\n", " arr_x = (arr_x + 50) / 51\n", "\n", " if i % 100 == 0:\n", " print(im_fname, mask_fname)\n", " i += 1\n", " flood_data.append((arr_x,arr_y))\n", "\n", " return flood_data\n", "\n", "def load_flood_train_data(input_root, label_root):\n", " fname = \"flood_train_data.csv\"\n", " training_files = []\n", " with open(fname) as f:\n", " for line in csv.reader(f):\n", " training_files.append(tuple((input_root+line[0], label_root+line[1])))\n", "\n", " return download_flood_water_data_from_list(training_files)\n", "\n", "def load_flood_valid_data(input_root, label_root):\n", " fname = \"flood_valid_data.csv\"\n", " validation_files = []\n", " with open(fname) as f:\n", " for line in csv.reader(f):\n", " validation_files.append(tuple((input_root+line[0], label_root+line[1])))\n", "\n", " return download_flood_water_data_from_list(validation_files)\n", "\n", "def load_flood_test_data(input_root, label_root):\n", " fname = \"flood_test_data.csv\"\n", " testing_files = []\n", " with open(fname) as f:\n", " for line in csv.reader(f):\n", " testing_files.append(tuple((input_root+line[0], label_root+line[1])))\n", "\n", " return download_flood_water_data_from_list(testing_files)\n" ], "metadata": { "id": "seaOk794pD2W" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "train_data = load_flood_train_data('S1/', 'Labels/')\n", "train_dataset = InMemoryDataset(train_data, processAndAugment)\n", "train_loader = torch.utils.data.DataLoader(train_dataset, batch_size=16, shuffle=True, sampler=None,\n", " batch_sampler=None, num_workers=0, collate_fn=None,\n", " pin_memory=True, drop_last=False, timeout=0,\n", " worker_init_fn=None)\n", "train_iter = iter(train_loader)\n", "\n", "valid_data = load_flood_valid_data('S1/', 'Labels/')\n", "valid_dataset = InMemoryDataset(valid_data, processTestIm)\n", "valid_loader = torch.utils.data.DataLoader(valid_dataset, batch_size=4, shuffle=True, sampler=None,\n", " batch_sampler=None, num_workers=0, collate_fn=lambda x: (torch.cat([a[0] for a in x], 0), torch.cat([a[1] for a in x], 0)),\n", " pin_memory=True, drop_last=False, timeout=0,\n", " worker_init_fn=None)\n", "valid_iter = iter(valid_loader)" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "v53D7v4ApDzf", "outputId": "94403eb2-89c4-47cd-d59c-6f3940de8b58" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "S1/Ghana_103272_S1Hand.tif Labels/Ghana_103272_LabelHand.tif\n", "S1/Pakistan_132143_S1Hand.tif Labels/Pakistan_132143_LabelHand.tif\n", "S1/Sri-Lanka_916628_S1Hand.tif Labels/Sri-Lanka_916628_LabelHand.tif\n", "S1/Ghana_5079_S1Hand.tif Labels/Ghana_5079_LabelHand.tif\n" ] } ] }, { "cell_type": "code", "source": [ "import torch\n", "import torchvision.models as models\n", "import torch.nn as nn\n", "\n", "net = models.segmentation.fcn_resnet50(pretrained=False, num_classes=2, pretrained_backbone=False)\n", "net.backbone.conv1 = nn.Conv2d(2, 64, kernel_size=7, stride=2, padding=3, bias=False)\n", "\n", "criterion = nn.CrossEntropyLoss(weight=torch.tensor([1,8]).float().cuda(), ignore_index=255)\n", "optimizer = torch.optim.AdamW(net.parameters(),lr=LR)\n", "scheduler = torch.optim.lr_scheduler.CosineAnnealingWarmRestarts(optimizer, len(train_loader) * 10, T_mult=2, eta_min=0, last_epoch=-1)\n", "\n", "def convertBNtoGN(module, num_groups=16):\n", " if isinstance(module, torch.nn.modules.batchnorm.BatchNorm2d):\n", " return nn.GroupNorm(num_groups, module.num_features,\n", " eps=module.eps, affine=module.affine)\n", " if module.affine:\n", " mod.weight.data = module.weight.data.clone().detach()\n", " mod.bias.data = module.bias.data.clone().detach()\n", "\n", " for name, child in module.named_children():\n", " module.add_module(name, convertBNtoGN(child, num_groups=num_groups))\n", "\n", " return module\n", "\n", "net = convertBNtoGN(net)" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "kG2TQ78lpJKL", "outputId": "70e11f51-d25b-4f40-872c-d92c48e1357a" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stderr", "text": [ "/usr/local/lib/python3.10/dist-packages/torchvision/models/_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead.\n", " warnings.warn(\n", "/usr/local/lib/python3.10/dist-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing `weights=None`.\n", " warnings.warn(msg)\n", "/usr/local/lib/python3.10/dist-packages/torchvision/models/_utils.py:208: UserWarning: The parameter 'pretrained_backbone' is deprecated since 0.13 and may be removed in the future, please use 'weights_backbone' instead.\n", " warnings.warn(\n", "/usr/local/lib/python3.10/dist-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights_backbone' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing `weights_backbone=None`.\n", " warnings.warn(msg)\n" ] } ] }, { "cell_type": "code", "source": [ "def computeIOU(output, target):\n", " output = torch.argmax(output, dim=1).flatten()\n", " target = target.flatten()\n", "\n", " no_ignore = target.ne(255).cuda()\n", " output = output.masked_select(no_ignore)\n", " target = target.masked_select(no_ignore)\n", " intersection = torch.sum(output * target)\n", " union = torch.sum(target) + torch.sum(output) - intersection\n", " iou = (intersection + .0000001) / (union + .0000001)\n", "\n", " if iou != iou:\n", " print(\"failed, replacing with 0\")\n", " iou = torch.tensor(0).float()\n", "\n", " return iou\n", "\n", "def computeAccuracy(output, target):\n", " output = torch.argmax(output, dim=1).flatten()\n", " target = target.flatten()\n", "\n", " no_ignore = target.ne(255).cuda()\n", " output = output.masked_select(no_ignore)\n", " target = target.masked_select(no_ignore)\n", " correct = torch.sum(output.eq(target))\n", "\n", " return correct.float() / len(target)\n", "\n", "def truePositives(output, target):\n", " output = torch.argmax(output, dim=1).flatten()\n", " target = target.flatten()\n", " no_ignore = target.ne(255).cuda()\n", " output = output.masked_select(no_ignore)\n", " target = target.masked_select(no_ignore)\n", " correct = torch.sum(output * target)\n", "\n", " return correct\n", "\n", "def trueNegatives(output, target):\n", " output = torch.argmax(output, dim=1).flatten()\n", " target = target.flatten()\n", " no_ignore = target.ne(255).cuda()\n", " output = output.masked_select(no_ignore)\n", " target = target.masked_select(no_ignore)\n", " output = (output == 0)\n", " target = (target == 0)\n", " correct = torch.sum(output * target)\n", "\n", " return correct\n", "\n", "def falsePositives(output, target):\n", " output = torch.argmax(output, dim=1).flatten()\n", " target = target.flatten()\n", " no_ignore = target.ne(255).cuda()\n", " output = output.masked_select(no_ignore)\n", " target = target.masked_select(no_ignore)\n", " output = (output == 1)\n", " target = (target == 0)\n", " correct = torch.sum(output * target)\n", "\n", " return correct\n", "\n", "def falseNegatives(output, target):\n", " output = torch.argmax(output, dim=1).flatten()\n", " target = target.flatten()\n", " no_ignore = target.ne(255).cuda()\n", " output = output.masked_select(no_ignore)\n", " target = target.masked_select(no_ignore)\n", " output = (output == 0)\n", " target = (target == 1)\n", " correct = torch.sum(output * target)\n", "\n", " return correct" ], "metadata": { "id": "Io4p0xTspJEb" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [], "metadata": { "id": "pe6Y5yKWvblW" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "valid_losses = []\n", "valid_accuracies = []\n", "valid_ious = []\n", "\n", "def validation_loop(validation_data_loader, net):\n", " global running_loss\n", " global running_iou\n", " global running_count\n", " global running_accuracy\n", " global max_valid_iou\n", "\n", " global training_losses\n", " global training_accuracies\n", " global training_ious\n", " global valid_losses\n", " global valid_accuracies\n", " global valid_ious\n", "\n", " net = net.eval()\n", " net = net.cuda()\n", " count = 0\n", " iou = 0\n", " loss = 0\n", " accuracy = 0\n", " with torch.no_grad():\n", " for (images, labels) in validation_data_loader:\n", " net = net.cuda()\n", " outputs = net(images.cuda())\n", " valid_loss = criterion(outputs[\"out\"], labels.long().cuda())\n", " valid_iou = computeIOU(outputs[\"out\"], labels.cuda())\n", " valid_accuracy = computeAccuracy(outputs[\"out\"], labels.cuda())\n", " iou += valid_iou\n", " loss += valid_loss\n", " accuracy += valid_accuracy\n", " count += 1\n", "\n", " iou = iou / count\n", " print(f\"init acc: {valid_accuracy}\")\n", " print(f\"init count: {count}\")\n", " accuracy = accuracy / count\n", "\n", "\n", " if iou > max_valid_iou:\n", " max_valid_iou = iou\n", " save_path = os.path.join(\"checkpoints\", \"{}_{}_{}.cp\".format(RUNNAME, i, iou.item()))\n", " torch.save(net.state_dict(), save_path)\n", " print(\"model saved at\", save_path)\n", "\n", " loss = loss / count\n", " print(\"Training Loss:\", running_loss / running_count)\n", " print(\"Training IOU:\", running_iou / running_count)\n", " print(\"Training Accuracy:\", running_accuracy / running_count)\n", " print(\"Validation Loss:\", loss)\n", " print(\"Validation IOU:\", iou)\n", " print(\"Validation Accuracy:\", accuracy)\n", "\n", "\n", " training_losses.append(running_loss / running_count)\n", " training_accuracies.append(running_accuracy / running_count)\n", " training_ious.append(running_iou / running_count)\n", " valid_losses.append(loss)\n", " valid_accuracies.append(accuracy)\n", " valid_ious.append(iou)\n" ], "metadata": { "id": "M8n-GnQgpJB4" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [], "metadata": { "id": "angaCVj3pDra" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "def test_loop(test_data_loader, net):\n", " net = net.eval()\n", " net = net.cuda()\n", " count = 0\n", " iou = 0\n", " loss = 0\n", " accuracy = 0\n", " with torch.no_grad():\n", " for (images, labels) in tqdm(test_data_loader):\n", " net = net.cuda()\n", " outputs = net(images.cuda())\n", " valid_loss = criterion(outputs[\"out\"], labels.long().cuda())\n", " valid_iou = computeIOU(outputs[\"out\"], labels.cuda())\n", " iou += valid_iou\n", " accuracy += computeAccuracy(outputs[\"out\"], labels.cuda())\n", " count += 1\n", "\n", " iou = iou / count\n", " print(\"Test IOU:\", iou)\n", " print(\"Test Accuracy:\", accuracy / count)" ], "metadata": { "id": "ka4ZxOnDpejK" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 250 }, "id": "UFR-IYlv1p7Q", "outputId": "3b31327c-d429-443f-e765-a9b4068711c4" }, "execution_count": null, "outputs": [ { "output_type": "error", "ename": "NameError", "evalue": "ignored", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[1;32m 8\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 9\u001b[0m \u001b[0;32mwith\u001b[0m \u001b[0mtorch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mno_grad\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 10\u001b[0;31m \u001b[0;32mfor\u001b[0m \u001b[0mimages\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mtest_data_loader\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 11\u001b[0m \u001b[0mimages\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mimages\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcuda\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mtorch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcuda\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mis_available\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32melse\u001b[0m \u001b[0mimages\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcpu\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# Move input data to GPU if available\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 12\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;31mNameError\u001b[0m: name 'test_data_loader' is not defined" ] } ] }, { "cell_type": "code", "source": [ "from tqdm.notebook import tqdm\n", "from IPython.display import clear_output\n", "\n", "running_loss = 0\n", "running_iou = 0\n", "running_count = 0\n", "running_accuracy = 0\n", "\n", "training_losses = []\n", "training_accuracies = []\n", "training_ious = []\n", "valid_losses = []\n", "valid_accuracies = []\n", "valid_ious = []\n", "\n", "\n", "def train_epoch(net, optimizer, scheduler, train_iter):\n", " for (inputs, labels) in tqdm(train_iter):\n", " train_loop(inputs.cuda(), labels.cuda(), net.cuda(), optimizer, scheduler)\n", "\n", "\n", "def train_validation_loop(net, optimizer, scheduler, train_loader,\n", " valid_loader, num_epochs, cur_epoch):\n", " global running_loss\n", " global running_iou\n", " global running_count\n", " global running_accuracy\n", " net = net.train()\n", " running_loss = 0\n", " running_iou = 0\n", " running_count = 0\n", " running_accuracy = 0\n", "\n", " for i in tqdm(range(num_epochs)):\n", " train_iter = iter(train_loader)\n", " train_epoch(net, optimizer, scheduler, train_iter)\n", " clear_output()\n", "\n", " print(\"Current Epoch:\", cur_epoch)\n", " validation_loop(iter(valid_loader), net)" ], "metadata": { "id": "zSYvzCRJphkH" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")" ], "metadata": { "id": "DK44DPMzrn3G" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "!nvidia-smi" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "S7vTa8sou7Ft", "outputId": "827ed9cb-7991-4aa5-e2fc-aff226208f20" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Sun Oct 8 05:36:41 2023 \n", "+-----------------------------------------------------------------------------+\n", "| NVIDIA-SMI 525.105.17 Driver Version: 525.105.17 CUDA Version: 12.0 |\n", "|-------------------------------+----------------------+----------------------+\n", "| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |\n", "| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |\n", "| | | MIG M. |\n", "|===============================+======================+======================|\n", "| 0 Tesla T4 Off | 00000000:00:04.0 Off | 0 |\n", "| N/A 48C P0 26W / 70W | 14613MiB / 15360MiB | 0% Default |\n", "| | | N/A |\n", "+-------------------------------+----------------------+----------------------+\n", " \n", "+-----------------------------------------------------------------------------+\n", "| Processes: |\n", "| GPU GI CI PID Type Process name GPU Memory |\n", "| ID ID Usage |\n", "|=============================================================================|\n", "+-----------------------------------------------------------------------------+\n" ] } ] }, { "cell_type": "code", "source": [ "training_losses = []\n", "training_accuracies = []\n", "training_ious = []\n", "\n", "def train_loop(inputs, labels, net, optimizer, scheduler):\n", " global running_loss\n", " global running_iou\n", " global running_count\n", " global running_accuracy\n", "\n", " # zero the parameter gradients\n", " optimizer.zero_grad()\n", " net = net.cuda()\n", "\n", " # forward + backward + optimize\n", " outputs = net(inputs.cuda())\n", " loss = criterion(outputs[\"out\"], labels.long().cuda())\n", " loss.backward()\n", " optimizer.step()\n", " scheduler.step()\n", "\n", " running_loss += loss\n", " running_iou += computeIOU(outputs[\"out\"], labels.cuda())\n", " running_accuracy += computeAccuracy(outputs[\"out\"], labels.cuda())\n", " running_count += 1" ], "metadata": { "id": "KPaw5RGKwWBZ" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "import os\n", "from IPython.display import display\n", "import matplotlib.pyplot as plt\n", "from torch import Tensor\n", "\n", "max_valid_iou = 0\n", "start = 0\n", "\n", "epochs = []\n", "training_losses = []\n", "training_accuracies = []\n", "training_ious = []\n", "valid_losses = []\n", "valid_accuracies = []\n", "valid_ious = []\n", "\n", "for i in range(start, 1000):\n", " train_validation_loop(net, optimizer, scheduler, train_loader, valid_loader, 10, i)\n", " epochs.append(i)\n", " x = epochs\n", "\n", " training_losses_np = np.array([t.cpu().item() for t in training_losses])\n", " training_accuracies_np = np.array([t.cpu().item() for t in training_accuracies])\n", " training_ious_np = np.array([t.cpu().item() for t in training_ious])\n", " valid_losses_np = np.array([t.cpu().item() for t in valid_losses])\n", " valid_accuracies_np = np.array([t.cpu().item() for t in valid_accuracies])\n", " valid_ious_np = np.array([t.cpu().item() for t in valid_ious])\n", " plt.plot(x, training_losses, label='training losses')\n", " plt.plot(x, training_accuracies, 'tab:orange', label='training accuracy')\n", " plt.plot(x, training_ious, 'tab:purple', label='training iou')\n", " plt.plot(x, valid_losses, label='valid losses')\n", " plt.plot(x, valid_accuracies, 'tab:red',label='valid accuracy')\n", " plt.plot(x, valid_ious, 'tab:green',label='valid iou')\n", " plt.legend(loc=\"upper left\")\n", "\n", " display(plt.show())\n", "\n", " print(\"max valid iou:\", max_valid_iou)" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 554, "referenced_widgets": [ "af462120bb6448abae4ea16ecd240282", "5f7a58ee16b94a2e930eb1455b2dabf0", "7ab352c458f846f79f5ba068b100b548", "eab04cc1cb6946db8db4ebabbe9656bd", "99aa39cdfb2643cdb52fcf9c85e5f079", "ff6da393c7474be2a704da5185b749bb", "62f49e0479b34f77b46b2c4b45decd90", "8dd117f468684b2097107fdedd8a3831", "f72b0858231642eebfed230a22a4fe62", "ccfeb11c092a4a6db374be869f6fc330", "aff1301695144ea7b1e6de787194e263", "21c6f7e718da4f9c9cbedfda876e8a94", "1fcf3fd2c38044208ee88d0020d6f618", "d1fd033c008c4d8e971c8d862b3c2679", "a132f57af85047fdb8e10ac415fea3b6", "350db220ffab43a3bff8daf3ea5c335c", "d58d73cb5fc045aab13ca03c3121a130", "59f53083835e4489be513690eb614910", "4396d4254f20481d9b5eebf45eb0976e", "b9bd60aaee484a1c9b9f171b18a88ea2", "2efcd9ef8ea44ab9ae1e268c6060a27a", "519ff2a5e8024cfb8a0b11953e541066", "8ec2023b4a914f1dbd8c89b02a3b9180", "086765d5a42243d68713aca99b1d45ad", "d8b7d3046de34343aede523a14f80f52", "54001e5c48ee47cb9d30c6c172916e79", "43410fe013a343e2b7893db97fa97dfb", "1e857302f11847b7bac74f12d91355d3", "c8f81c43fec84a659bbd611852a7b654", "e0d97789365e4008a48925b7230051ed", "f88316cebea5498d824fa7cd0e613d43", "fdd58ce657c84ebd94c5bd9f07a36d98", "46617be420bf4122ab7741cabb9c02b9", "43ea8ca512d84383afce6a90c860076a", "02daf138842b40aba6e7328c443a8bc0", "5e37409ef33c49f291e55084d6ee39b0", "a5db80ac14a64bceac9ab83e33f11dea", "b10980dcd6fc41f084bbc040676122c8", "8f5a5c179d864a4ebbc9c92b228272f2", "9e58a9700f4a416888109ae8bf88f314", "d0b91aa9f81e4abeb137383f7cae12a7", "087190f2602a485fb129623e39496597", "d05e211233494a899c94b03238a3f186", "3e099679aedc4d11a4409daacbd1c722", "e2da8fd64a06401d96d333549af4b397", "82c1f70a3b3c47e882a2cf93a7ae18a0", "1d6f9e2c30cd47268d070d38d9cee9b9", "70dd6b78ad9b4f669500666e7525bb93", "cb7960a616504afba3d85b45a9f3a532", "61fdcd2c9da4488ba65f62e403a3810b", "a0d0185dcb174c069c88481fcad2bc94", "831f9b54823a421ba7bebe3350f7a8c6", "09f1a39dce9c4497b7cea4348f812270", "520f68b78f0e4b438003bea7f2d260ce", "6c83774f27284372beb31be100eb31a0", "8147bb25a8594adab8bf7d97ed57a0b8", "4b0b882d22c84c509bba9bf9116db82a", "f2a9d4b05a624d06bbec19a8c93bb934", "60bb5fdc9e5c480b946a1e18577c0062", "5bd9815d3d06489297e1b1333af3f593", "8138d22858c1458ea7c87a8e041c4eb7", "f282b62d06714af9a0fbb7d8f8def82f", "30e490cffb4449fd8932ff43d928f492", "ddbe1f3f77324eb6bb637ba539794941", "e29d7a1efcb74ef08a564a1f2f748834", "db142381b6a04da9a75977c2151d314f", "b9db0da2d5ab455f9496d1d282db1f3f", "8881316de0974a30908b7782100f7eae", "f2158f0867144580a45fe2fd7f6561a6", "b38c6537121f484d916607bad872594f", "748dee67f8a24f51871adaedfcf9ce62", "6cd74cab94d74dbd84422effe90e154c", "49fe9589ba434df89bea907ca865bc96", "1e8112f40a114a98b0cae07963cc5e9e", "f7c28a7038e64c05a4f03e17e45f482f", "d572bbf38b5d46f798bf85d3c2dcadd3", "8bd98acc00344e00b2a40d4457f18642", "b7620fb5746248c6b2cdd1aec43f59b2", "9374433d01244775abada20ac3958908", "3c69e1c0c1e44027ab8d7fefddf90a7f", "6c7069c1c7b745f1ae0bd39831791485", "cb816c5ae41348acba5b871db5089067", "cdd38e1429d344bc872ae20d6fd0ed54", "527758361ea64af998a5147d44aa4961", "27253357c9a94b328090cfffe478a103", "2916dd6da90e4b9b8505b20cf44c96e2", "3c72af0588b443278c031716d37b359f", "b9e03dd09e4942db808ec6f92b2b41e5", "710c94ded8ad42e49e4d90b25fedfec8", "fae5c8474acb432b86f20897c032d685", "e216cdb559d54e6bae992e4f42152439", "7fa123fd5ab942a69ddbba6620cc4947", "9c95b9ff6bb647529bc892820fe6e685", "bf7ac56e580d49c587ceb09afe9a10c3", "7b913ba025414a5ba5317fb8a033d404", "80003e00f2be48d3b87541b42fe76af6", "efd3c7f48b6f4c6f81e405eab02ba3b4", "ddb705233d9f40c8ba88d47ea1796592", "3cd2eab583774ed98a7b74c5eeb8f59f", "30fee15e800c464f82c8ebc25fbc156b", "abbcaf3b416140828de65e7c3c6fbc0a", "b76d22163a0c49029212363011026dac", "7441c191e41f41a7b7136420128cf8a2", "d7426b25b0f14ece94cae8f22098b524", "9234fa022c6248378df03778c9bc72aa", "baa8db02925e4d78a6a955c7973456d5", "19b63c17328b49bfb54b4769d3412fc0", "07034ebbeae34c918a0dc433394f96aa", "69b44876ef5646f99643ee0be1cdc94c", "c34664306fe34a0b927a8daac099abde", "e19c39ee43f94934bf235e14d1678657", "7c84792894a9409e96cac2c2c96bdbf8", "f506ac00e33d41468e6eeb9898b44bbb", "d8c8cfb6f856424e9f91e5ea0435c735", "7de679d1a0df4995962a8cd14de6f016", "819d6a99e520466eb0749076c0d2e8f8", "fc23c714bb7a479287dad863766ef82e", "6f879e683ec3490093f879da51eeeec6", "d23e3c5472854e488f34bff0116f237a", "b760de646e054a198f315e3f80b5c5d2", "0962f7596aa145aeb7963b860d31fa08" ] }, "id": "4m0mbhpKpjtX", "outputId": "83584696-affe-4bd4-a0c7-c8beffc2e252" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Current Epoch: 0\n", "init acc: 0.8956934809684753\n", "init count: 23\n", "model saved at checkpoints/Sen1Floods11_0_0.37147924304008484.cp\n", "Training Loss: tensor(0.3158, device='cuda:0', grad_fn=)\n", "Training IOU: tensor(0.4031, device='cuda:0')\n", "Training Accuracy: tensor(0.8984, device='cuda:0')\n", "Validation Loss: tensor(0.2967, device='cuda:0')\n", "Validation IOU: tensor(0.3715, device='cuda:0')\n", "Validation Accuracy: tensor(0.8761, device='cuda:0')\n" ] }, { "output_type": "error", "ename": "TypeError", "evalue": "ignored", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)", "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[1;32m 20\u001b[0m \u001b[0mx\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mepochs\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 21\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 22\u001b[0;31m \u001b[0mtraining_losses_np\u001b[0m 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the GPU if available\n", "\n", " iou = 0\n", " accuracy = 0\n", " count = 0\n", "\n", " with torch.no_grad():\n", " for (images, labels) in tqdm(test_data_loader):\n", " images = images.cuda() # Move input data to the GPU\n", " outputs = net(images) # Forward pass through the network\n", "\n", " # Assuming that outputs[\"out\"] contains your model's predictions\n", "\n", " valid_iou = computeIOU(outputs[\"out\"], labels.cuda()) # Calculate IOU\n", " valid_accuracy = computeAccuracy(outputs[\"out\"], labels.cuda()) # Calculate Accuracy\n", "\n", " iou += valid_iou\n", " accuracy += valid_accuracy\n", " count += 1\n", "\n", " iou = iou / count # Calculate the average IOU\n", " accuracy = accuracy / count # Calculate the average accuracy\n", "\n", " print(\"Inference IOU:\", iou)\n", " print(\"Inference Accuracy:\", accuracy)\n", "\n", "# Example usage:\n", "inference(valid_loader, net)\n" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 85, 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satisfied: cffi>=1.12 in /usr/local/lib/python3.10/dist-packages (from cryptography>=2.6.0->aliyun-python-sdk-core>=2.13.12->oss2~=2.17.0->openxlab->opendatalab->openmim) (1.16.0)\n", "Requirement already satisfied: pycparser in /usr/local/lib/python3.10/dist-packages (from cffi>=1.12->cryptography>=2.6.0->aliyun-python-sdk-core>=2.13.12->oss2~=2.17.0->openxlab->opendatalab->openmim) (2.21)\n", "Building wheels for collected packages: oss2, aliyun-python-sdk-core, crcmod\n", " Building wheel for oss2 (setup.py) ... \u001b[?25l\u001b[?25hdone\n", " Created wheel for oss2: filename=oss2-2.17.0-py3-none-any.whl size=112371 sha256=7fad888ea097e033d25dbc4632c50955109c613ea3e057f40e4ffc13440da2b4\n", " Stored in directory: /root/.cache/pip/wheels/87/04/7b/7e61b8157fdf211c5131375240d0d86ca82e2a88ead9672c88\n", " Building wheel for aliyun-python-sdk-core (setup.py) ... \u001b[?25l\u001b[?25hdone\n", " Created wheel for aliyun-python-sdk-core: filename=aliyun_python_sdk_core-2.14.0-py3-none-any.whl size=535290 sha256=bc2cef9fa577387767ded8870d62fbaf1bd40589c65a582ba053db4fc688cfe1\n", " Stored in directory: /root/.cache/pip/wheels/16/3c/68/b7eab618d9f1d5e7d386296f1e07e2cf36aaa1eb5161885038\n", " Building wheel for crcmod (setup.py) ... \u001b[?25l\u001b[?25hdone\n", " Created wheel for crcmod: filename=crcmod-1.7-cp310-cp310-linux_x86_64.whl size=31405 sha256=039523084a1dd81cbd630c9478f402bec7f8192d72245b79f3e05a01928a1985\n", " Stored in directory: /root/.cache/pip/wheels/85/4c/07/72215c529bd59d67e3dac29711d7aba1b692f543c808ba9e86\n", "Successfully built oss2 aliyun-python-sdk-core crcmod\n", "Installing collected packages: crcmod, urllib3, tqdm, setuptools, pycryptodome, ordered-set, jmespath, colorama, rich, requests, model-index, aliyun-python-sdk-core, aliyun-python-sdk-kms, oss2, openxlab, opendatalab, openmim\n", " Attempting uninstall: urllib3\n", " Found existing installation: urllib3 2.0.6\n", " Uninstalling urllib3-2.0.6:\n", " Successfully uninstalled urllib3-2.0.6\n", " Attempting uninstall: tqdm\n", " Found existing installation: tqdm 4.66.1\n", " Uninstalling tqdm-4.66.1:\n", " Successfully uninstalled tqdm-4.66.1\n", " Attempting uninstall: setuptools\n", " Found existing installation: setuptools 67.7.2\n", " Uninstalling setuptools-67.7.2:\n", " Successfully uninstalled setuptools-67.7.2\n", " Attempting uninstall: rich\n", " Found existing installation: rich 13.6.0\n", " Uninstalling rich-13.6.0:\n", " Successfully uninstalled rich-13.6.0\n", " Attempting uninstall: requests\n", " Found existing installation: requests 2.31.0\n", " Uninstalling requests-2.31.0:\n", " Successfully uninstalled requests-2.31.0\n", "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n", "ipython 7.34.0 requires jedi>=0.16, which is not installed.\n", "cvxpy 1.3.2 requires setuptools>65.5.1, but you have setuptools 60.2.0 which is incompatible.\n", "google-colab 1.0.0 requires requests==2.31.0, but you have requests 2.28.2 which is incompatible.\n", "yfinance 0.2.30 requires requests>=2.31, but you have requests 2.28.2 which is incompatible.\u001b[0m\u001b[31m\n", "\u001b[0mSuccessfully installed aliyun-python-sdk-core-2.14.0 aliyun-python-sdk-kms-2.16.2 colorama-0.4.6 crcmod-1.7 jmespath-0.10.0 model-index-0.1.11 opendatalab-0.0.10 openmim-0.3.9 openxlab-0.0.26 ordered-set-4.1.0 oss2-2.17.0 pycryptodome-3.19.0 requests-2.28.2 rich-13.4.2 setuptools-60.2.0 tqdm-4.65.2 urllib3-1.26.17\n" ] }, { "output_type": "display_data", "data": { "application/vnd.colab-display-data+json": { "pip_warning": { "packages": [ "_distutils_hack", "pkg_resources", "requests", "setuptools", "tqdm", "urllib3" ] } } }, "metadata": {} }, { "output_type": "stream", "name": "stdout", "text": [ "Looking in links: https://download.openmmlab.com/mmcv/dist/cu118/torch2.0.0/index.html\n", "Collecting mmcv-full==1.6.0\n", " Downloading mmcv-full-1.6.0.tar.gz (554 kB)\n", "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m554.9/554.9 kB\u001b[0m \u001b[31m9.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", "\u001b[?25h Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n", "Collecting addict (from mmcv-full==1.6.0)\n", " Downloading addict-2.4.0-py3-none-any.whl (3.8 kB)\n", "Requirement already satisfied: numpy in /usr/local/lib/python3.10/dist-packages (from mmcv-full==1.6.0) (1.23.5)\n", "Requirement already satisfied: packaging in /usr/local/lib/python3.10/dist-packages (from mmcv-full==1.6.0) (23.2)\n", "Requirement already satisfied: Pillow in /usr/local/lib/python3.10/dist-packages (from mmcv-full==1.6.0) (9.4.0)\n", "Requirement already satisfied: pyyaml in /usr/local/lib/python3.10/dist-packages (from mmcv-full==1.6.0) (6.0.1)\n", "Collecting yapf (from mmcv-full==1.6.0)\n", " Downloading yapf-0.40.2-py3-none-any.whl (254 kB)\n", "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m254.7/254.7 kB\u001b[0m \u001b[31m24.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", "\u001b[?25hRequirement already satisfied: importlib-metadata>=6.6.0 in /usr/local/lib/python3.10/dist-packages (from yapf->mmcv-full==1.6.0) (6.8.0)\n", "Requirement already satisfied: platformdirs>=3.5.1 in /usr/local/lib/python3.10/dist-packages (from yapf->mmcv-full==1.6.0) (3.11.0)\n", "Requirement already satisfied: tomli>=2.0.1 in /usr/local/lib/python3.10/dist-packages (from yapf->mmcv-full==1.6.0) (2.0.1)\n", "Requirement already satisfied: zipp>=0.5 in /usr/local/lib/python3.10/dist-packages (from importlib-metadata>=6.6.0->yapf->mmcv-full==1.6.0) (3.17.0)\n", "Building wheels for collected packages: mmcv-full\n", " Building wheel for mmcv-full (setup.py) ... \u001b[?25l\u001b[?25hcanceled\n", "\u001b[31mERROR: Operation cancelled by user\u001b[0m\u001b[31m\n", "\u001b[0m\n", "Aborted!\n" ] } ] }, { "cell_type": "code", "source": [ "!rm -rf mmsegmentation\n", "!git clone https://github.com/open-mmlab/mmsegmentation.git\n", "%cd mmsegmentation\n", "!pip install -e ." ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "-vZm113ebraq", "outputId": "6c4f2342-19a3-4b4e-9abc-493d65abe8b8" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Cloning into 'mmsegmentation'...\n", "remote: Enumerating objects: 16219, done.\u001b[K\n", "remote: Counting objects: 100% (585/585), done.\u001b[K\n", "remote: Compressing objects: 100% (416/416), done.\u001b[K\n", "remote: Total 16219 (delta 234), reused 378 (delta 157), pack-reused 15634\u001b[K\n", "Receiving objects: 100% (16219/16219), 23.22 MiB | 28.08 MiB/s, done.\n", "Resolving deltas: 100% (11252/11252), done.\n", "/home/mmsegmentation\n", "Obtaining file:///home/mmsegmentation\n", " Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n", "Requirement already satisfied: matplotlib in /usr/local/lib/python3.10/dist-packages (from mmsegmentation==1.1.2) (3.7.1)\n", "Requirement already satisfied: numpy in /usr/local/lib/python3.10/dist-packages (from mmsegmentation==1.1.2) (1.23.5)\n", "Requirement already satisfied: packaging in /usr/local/lib/python3.10/dist-packages (from mmsegmentation==1.1.2) (23.2)\n", "Requirement already satisfied: prettytable in /usr/local/lib/python3.10/dist-packages (from mmsegmentation==1.1.2) (3.9.0)\n", "Requirement already satisfied: scipy in /usr/local/lib/python3.10/dist-packages (from mmsegmentation==1.1.2) (1.11.3)\n", "Requirement already satisfied: contourpy>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib->mmsegmentation==1.1.2) (1.1.1)\n", "Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.10/dist-packages (from matplotlib->mmsegmentation==1.1.2) (0.12.0)\n", "Requirement already satisfied: fonttools>=4.22.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib->mmsegmentation==1.1.2) (4.43.0)\n", "Requirement already satisfied: kiwisolver>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib->mmsegmentation==1.1.2) (1.4.5)\n", "Requirement already satisfied: pillow>=6.2.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib->mmsegmentation==1.1.2) (9.4.0)\n", "Requirement already satisfied: pyparsing>=2.3.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib->mmsegmentation==1.1.2) (3.1.1)\n", "Requirement already satisfied: python-dateutil>=2.7 in /usr/local/lib/python3.10/dist-packages (from matplotlib->mmsegmentation==1.1.2) (2.8.2)\n", "Requirement already satisfied: wcwidth in /usr/local/lib/python3.10/dist-packages (from prettytable->mmsegmentation==1.1.2) (0.2.8)\n", "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil>=2.7->matplotlib->mmsegmentation==1.1.2) (1.16.0)\n", "Installing collected packages: mmsegmentation\n", " Running setup.py develop for mmsegmentation\n", "Successfully installed mmsegmentation-1.1.2\n" ] } ] }, { "cell_type": "code", "source": [ "# Check Pytorch installation\n", "import torch, torchvision\n", "print(torch.__version__, torch.cuda.is_available())\n", "\n", "# Check MMSegmentation installation\n" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "zGzjgghZbrYw", "outputId": "277a4e7e-891a-4369-a329-5c680e4265c2" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "2.0.1+cu118 True\n" ] } ] }, { "cell_type": "code", "source": [ "!nvcc --version" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "WmPKPoc1fMvE", "outputId": "7b81bd6a-1e29-434a-fbc9-63de215f29a8" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "nvcc: NVIDIA (R) Cuda compiler driver\n", "Copyright (c) 2005-2022 NVIDIA Corporation\n", "Built on Wed_Sep_21_10:33:58_PDT_2022\n", "Cuda compilation tools, release 11.8, V11.8.89\n", "Build cuda_11.8.r11.8/compiler.31833905_0\n" ] } ] }, { "cell_type": "code", "source": [ "!mim install mmcv-full==2.0.0 -f https://download.openmmlab.com/mmcv/dist/cu115/torch2.0.1/index.html" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "FrEYWxo7e0KF", "outputId": "aca2e4c4-af83-4206-b8f9-fb88d251ed20" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Looking in links: https://download.openmmlab.com/mmcv/dist/cu115/torch2.0.1/index.html, https://download.openmmlab.com/mmcv/dist/cu118/torch2.0.0/index.html\n", "\u001b[31mERROR: Could not find a version that satisfies the requirement mmcv-full==2.0.0 (from versions: 1.0rc0, 1.0rc2, 1.0.0, 1.0.1, 1.0.2, 1.0.3, 1.0.4, 1.0.5, 1.1.0, 1.1.1, 1.1.2, 1.1.3, 1.1.4, 1.1.5, 1.1.6, 1.2.0, 1.2.1, 1.2.2, 1.2.3, 1.2.4, 1.2.5, 1.2.6, 1.2.7, 1.3.0, 1.3.1, 1.3.3, 1.3.4, 1.3.5, 1.3.6, 1.3.7, 1.3.8, 1.3.9, 1.3.10, 1.3.11, 1.3.12, 1.3.13, 1.3.14, 1.3.15, 1.3.16, 1.3.17, 1.3.18, 1.4.0, 1.4.1, 1.4.2, 1.4.3, 1.4.4, 1.4.5, 1.4.6, 1.4.7, 1.4.8, 1.5.0, 1.5.1, 1.5.2, 1.5.3, 1.6.0, 1.6.1, 1.6.2, 1.7.0, 1.7.1)\u001b[0m\u001b[31m\n", "\u001b[0m\u001b[31mERROR: No matching distribution found for mmcv-full==2.0.0\u001b[0m\u001b[31m\n", "\u001b[0m" ] } ] }, { "cell_type": "code", "source": [ "%cd" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "Z776_NYMfamc", "outputId": "02b61bba-4abf-4145-f0f2-da2dbb55fce6" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "/root\n" ] } ] }, { "cell_type": "code", "source": [ "!pip3 install mmcv==2.0.0rc4" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "1PR-B6Tdsleo", "outputId": "db769c20-c499-4b98-c321-0845f8644dc5" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Collecting mmcv==2.0.0rc4\n", " Downloading mmcv-2.0.0rc4.tar.gz (436 kB)\n", "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m436.4/436.4 kB\u001b[0m \u001b[31m7.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", "\u001b[?25h Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n", "Requirement already satisfied: addict in /usr/local/lib/python3.10/dist-packages (from mmcv==2.0.0rc4) (2.4.0)\n", "Requirement already satisfied: mmengine>=0.2.0 in /usr/local/lib/python3.10/dist-packages (from mmcv==2.0.0rc4) (0.8.5)\n", "Requirement already satisfied: numpy in /usr/local/lib/python3.10/dist-packages (from mmcv==2.0.0rc4) (1.23.5)\n", "Requirement already satisfied: packaging in /usr/local/lib/python3.10/dist-packages (from mmcv==2.0.0rc4) (23.2)\n", "Requirement already satisfied: Pillow in /usr/local/lib/python3.10/dist-packages (from mmcv==2.0.0rc4) (9.4.0)\n", "Requirement already satisfied: pyyaml in /usr/local/lib/python3.10/dist-packages (from mmcv==2.0.0rc4) (6.0.1)\n", "Requirement already satisfied: yapf in /usr/local/lib/python3.10/dist-packages (from mmcv==2.0.0rc4) (0.40.2)\n", "Requirement already satisfied: matplotlib in /usr/local/lib/python3.10/dist-packages (from mmengine>=0.2.0->mmcv==2.0.0rc4) (3.7.1)\n", "Requirement already satisfied: rich in /usr/local/lib/python3.10/dist-packages (from mmengine>=0.2.0->mmcv==2.0.0rc4) (13.4.2)\n", "Requirement already satisfied: termcolor in /usr/local/lib/python3.10/dist-packages (from mmengine>=0.2.0->mmcv==2.0.0rc4) (2.3.0)\n", "Requirement already satisfied: opencv-python>=3 in /usr/local/lib/python3.10/dist-packages (from mmengine>=0.2.0->mmcv==2.0.0rc4) (4.8.0.76)\n", "Requirement already satisfied: importlib-metadata>=6.6.0 in /usr/local/lib/python3.10/dist-packages (from yapf->mmcv==2.0.0rc4) (6.8.0)\n", "Requirement already satisfied: platformdirs>=3.5.1 in /usr/local/lib/python3.10/dist-packages (from yapf->mmcv==2.0.0rc4) (3.11.0)\n", "Requirement already satisfied: tomli>=2.0.1 in /usr/local/lib/python3.10/dist-packages (from yapf->mmcv==2.0.0rc4) (2.0.1)\n", "Requirement already satisfied: zipp>=0.5 in /usr/local/lib/python3.10/dist-packages (from importlib-metadata>=6.6.0->yapf->mmcv==2.0.0rc4) (3.17.0)\n", "Requirement already satisfied: contourpy>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib->mmengine>=0.2.0->mmcv==2.0.0rc4) (1.1.1)\n", "Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.10/dist-packages (from matplotlib->mmengine>=0.2.0->mmcv==2.0.0rc4) (0.12.0)\n", "Requirement already satisfied: fonttools>=4.22.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib->mmengine>=0.2.0->mmcv==2.0.0rc4) (4.43.0)\n", "Requirement already satisfied: kiwisolver>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib->mmengine>=0.2.0->mmcv==2.0.0rc4) (1.4.5)\n", "Requirement already satisfied: pyparsing>=2.3.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib->mmengine>=0.2.0->mmcv==2.0.0rc4) (3.1.1)\n", "Requirement already satisfied: python-dateutil>=2.7 in /usr/local/lib/python3.10/dist-packages (from matplotlib->mmengine>=0.2.0->mmcv==2.0.0rc4) (2.8.2)\n", "Requirement already satisfied: markdown-it-py>=2.2.0 in /usr/local/lib/python3.10/dist-packages (from rich->mmengine>=0.2.0->mmcv==2.0.0rc4) (3.0.0)\n", "Requirement already satisfied: pygments<3.0.0,>=2.13.0 in /usr/local/lib/python3.10/dist-packages (from rich->mmengine>=0.2.0->mmcv==2.0.0rc4) (2.16.1)\n", "Requirement already satisfied: mdurl~=0.1 in /usr/local/lib/python3.10/dist-packages (from markdown-it-py>=2.2.0->rich->mmengine>=0.2.0->mmcv==2.0.0rc4) (0.1.2)\n", "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil>=2.7->matplotlib->mmengine>=0.2.0->mmcv==2.0.0rc4) (1.16.0)\n", "Building wheels for collected packages: mmcv\n", " Building wheel for mmcv (setup.py) ... \u001b[?25l\u001b[?25hdone\n", " Created wheel for mmcv: filename=mmcv-2.0.0rc4-cp310-cp310-linux_x86_64.whl size=30970455 sha256=46610ca0fc23ac365cece7df09c1edce2e6274b832f15cf0e250056fa2efdd9d\n", " Stored in directory: /root/.cache/pip/wheels/1a/14/d1/793dd16d71f91daf81152095a93d43618e60dee1762c678940\n", "Successfully built mmcv\n", "Installing collected packages: mmcv\n", "Successfully installed mmcv-2.0.0rc4\n" ] } ] }, { "cell_type": "code", "source": [ "!mkdir geospatial_fm" ], "metadata": { "id": "dQHR2S948QCL" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "%cd" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "U6I2itrY8Yk0", "outputId": "f2103a1b-8f7a-4710-e1b0-cc73d9da11f2" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "/root\n" ] } ] }, { "cell_type": "code", "source": [], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "zRUtpIP_8gmW", "outputId": "d3b702f4-60f1-4a01-c12e-570ef09a6830" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "\u001b[0m\u001b[01;36mbin\u001b[0m@ \u001b[01;34mmedia\u001b[0m/\n", "\u001b[01;34mboot\u001b[0m/ \u001b[01;34mmnt\u001b[0m/\n", "\u001b[01;34mcontent\u001b[0m/ NGC-DL-CONTAINER-LICENSE\n", "cuda-keyring_1.0-1_all.deb \u001b[01;34mopt\u001b[0m/\n", "\u001b[01;34mdatalab\u001b[0m/ \u001b[01;34mproc\u001b[0m/\n", "datasets.py \u001b[01;34mpython-apt\u001b[0m/\n", "\u001b[01;34mdev\u001b[0m/ \u001b[01;34mroot\u001b[0m/\n", "\u001b[01;34metc\u001b[0m/ \u001b[01;34mrun\u001b[0m/\n", "\u001b[01;34mgeospatial_fm\u001b[0m/ \u001b[01;36msbin\u001b[0m@\n", "geospatial_fm.py \u001b[01;34msrv\u001b[0m/\n", "geospatial_pipelines.py \u001b[01;34msys\u001b[0m/\n", "\u001b[01;34mhome\u001b[0m/ temporal_encoder_decoder.py\n", "__init__.py \u001b[30;42mtmp\u001b[0m/\n", "\u001b[01;36mlib\u001b[0m@ \u001b[01;34mtools\u001b[0m/\n", "\u001b[01;36mlib32\u001b[0m@ \u001b[01;34musr\u001b[0m/\n", "\u001b[01;36mlib64\u001b[0m@ \u001b[01;34mvar\u001b[0m/\n", "\u001b[01;36mlibx32\u001b[0m@\n" ] } ] }, { "cell_type": "code", "source": [], "metadata": { "id": "Bk0by-WU-YV3" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "import sys\n", "sys.path.append('/home/geospatial_fm')\n", "print(sys.path)" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "7JxauilOBSQ3", "outputId": "8314ea61-806c-43a9-f32d-037a91b54085" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "['/content', '/env/python', '/usr/lib/python310.zip', '/usr/lib/python3.10', '/usr/lib/python3.10/lib-dynload', '', '/usr/local/lib/python3.10/dist-packages', '/usr/lib/python3/dist-packages', '/usr/local/lib/python3.10/dist-packages/IPython/extensions', '/root/.ipython', '/home/geospatial_fm', '/home/geospatial_fm', '/home/', '/home/geospatial_fm', '/home/geospatial_fm']\n" ] } ] }, { "cell_type": "code", "source": [ "%%capture\n", "!export PYTHONPATH=$PYTHONPATH:/home/geospatial_fm\n" ], "metadata": { "id": "TUvAtiPCEjRm" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "sys.path.append('/home')" ], "metadata": { "id": "krK4cnXAGeBd" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "sys.path.append('/home/geospatial')\n", "\n", "!mim train mmsegmentation home/sen1floods11_config.py" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "H32vbTMCbrWW", "outputId": "24e601cb-3d7c-45a7-f208-b017f6d79b93" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Training command is /usr/bin/python3 /home/mmsegmentation/mmseg/.mim/tools/train.py home/sen1floods11_config.py --launcher none. \n", "Traceback (most recent call last):\n", " File \"/home/mmsegmentation/mmseg/.mim/tools/train.py\", line 104, in \n", " main()\n", " File \"/home/mmsegmentation/mmseg/.mim/tools/train.py\", line 93, in main\n", " runner = Runner.from_cfg(cfg)\n", " File \"/usr/local/lib/python3.10/dist-packages/mmengine/runner/runner.py\", line 444, in from_cfg\n", " cfg = copy.deepcopy(cfg)\n", " File \"/usr/lib/python3.10/copy.py\", line 153, in deepcopy\n", " y = copier(memo)\n", " File \"/usr/local/lib/python3.10/dist-packages/mmengine/config/config.py\", line 1525, in __deepcopy__\n", " super(Config, other).__setattr__(key, copy.deepcopy(value, memo))\n", " File \"/usr/lib/python3.10/copy.py\", line 153, in deepcopy\n", " y = copier(memo)\n", " File \"/usr/local/lib/python3.10/dist-packages/mmengine/config/config.py\", line 142, in __deepcopy__\n", " other[copy.deepcopy(key, memo)] = copy.deepcopy(value, memo)\n", " File \"/usr/lib/python3.10/copy.py\", line 161, in deepcopy\n", " rv = reductor(4)\n", "TypeError: cannot pickle 'module' object\n", "Traceback (most recent call last):\n", " File \"/usr/local/bin/mim\", line 8, in \n", " sys.exit(cli())\n", " File \"/usr/local/lib/python3.10/dist-packages/click/core.py\", line 1157, in __call__\n", " return self.main(*args, **kwargs)\n", " File \"/usr/local/lib/python3.10/dist-packages/click/core.py\", line 1078, in main\n", " rv = self.invoke(ctx)\n", " File \"/usr/local/lib/python3.10/dist-packages/click/core.py\", line 1688, in invoke\n", " return _process_result(sub_ctx.command.invoke(sub_ctx))\n", " File \"/usr/local/lib/python3.10/dist-packages/click/core.py\", line 1434, in invoke\n", " return ctx.invoke(self.callback, **ctx.params)\n", " File \"/usr/local/lib/python3.10/dist-packages/click/core.py\", line 783, in invoke\n", " return __callback(*args, **kwargs)\n", " File \"/usr/local/lib/python3.10/dist-packages/mim/commands/train.py\", line 100, in cli\n", " is_success, msg = train(\n", " File \"/usr/local/lib/python3.10/dist-packages/mim/commands/train.py\", line 261, in train\n", " ret = subprocess.check_call(\n", " File \"/usr/lib/python3.10/subprocess.py\", line 369, in check_call\n", " raise CalledProcessError(retcode, cmd)\n", "subprocess.CalledProcessError: Command '['/usr/bin/python3', '/home/mmsegmentation/mmseg/.mim/tools/train.py', 'home/sen1floods11_config.py', '--launcher', 'none']' returned non-zero exit status 1.\n" ] } ] }, { "cell_type": "code", "source": [ "import os\n", "from google.colab import files\n", "\n", "# Define the directory you want to download files from\n", "source_dir = '/home/files'\n", "\n", "# List all files in the source directory\n", "files_to_download = os.listdir(source_dir)\n", "\n", "# Create a zip file containing all the files\n", "zip_file_path = '/content/downloaded_files.zip'\n", "os.system(f'zip -r {zip_file_path} {source_dir}')\n", "\n", "# Download the zip file to your local PC\n", "files.download(zip_file_path)" ], "metadata": { "id": "UZAEX4eoxaAI", "colab": { "base_uri": "https://localhost:8080/", "height": 17 }, "outputId": "5a400974-85f4-4c00-a8ec-aa213cb93fab" }, "execution_count": null, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "" ], "application/javascript": [ "\n", " async function download(id, filename, size) {\n", " if (!google.colab.kernel.accessAllowed) {\n", " return;\n", " }\n", " const div = document.createElement('div');\n", " const label = document.createElement('label');\n", " label.textContent = `Downloading \"${filename}\": `;\n", " div.appendChild(label);\n", " const progress = document.createElement('progress');\n", " progress.max = size;\n", " div.appendChild(progress);\n", " document.body.appendChild(div);\n", "\n", " const buffers = [];\n", " let downloaded = 0;\n", "\n", " const channel = await google.colab.kernel.comms.open(id);\n", " // Send a message to notify the kernel that we're ready.\n", " channel.send({})\n", "\n", " for await (const message of channel.messages) {\n", " // Send a message to notify the kernel that we're ready.\n", " channel.send({})\n", " if (message.buffers) {\n", " for (const buffer of message.buffers) {\n", " buffers.push(buffer);\n", " downloaded += buffer.byteLength;\n", " progress.value = downloaded;\n", " }\n", " }\n", " }\n", " const blob = new Blob(buffers, {type: 'application/binary'});\n", " const a = document.createElement('a');\n", " a.href = window.URL.createObjectURL(blob);\n", " a.download = filename;\n", " div.appendChild(a);\n", " a.click();\n", " div.remove();\n", " }\n", " " ] }, "metadata": {} }, { "output_type": "display_data", "data": { "text/plain": [ "" ], "application/javascript": [ "download(\"download_21ab0de4-b165-4ee9-9889-2724690f65d6\", \"downloaded_files.zip\", 732038235)" ] }, "metadata": {} } ] } ] }