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{
 "nbformat": 4,
 "nbformat_minor": 0,
 "metadata": {
 "colab": {
 "provenance": [],
 "gpuType": "T4"
 },
 "kernelspec": {
 "name": "python3",
 "display_name": "Python 3"
 },
 "language_info": {
 "name": "python"
 },
 "accelerator": "GPU"
 },
 "cells": [
 {
 "cell_type": "code",
 "execution_count": 1,
 "metadata": {
 "colab": {
 "base_uri": "https://localhost:8080/"
 },
 "collapsed": true,
 "id": "qf8cNVU3M3_B",
 "outputId": "44f7d7ca-3ffe-4093-f1a4-81c41f15affb"
 },
 "outputs": [
 {
 "output_type": "stream",
 "name": "stdout",
 "text": [
 "--2025-08-05 07:52:19-- https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh\n",
 "Resolving repo.anaconda.com (repo.anaconda.com)... 104.16.32.241, 104.16.191.158, 2606:4700::6810:bf9e, ...\n",
 "Connecting to repo.anaconda.com (repo.anaconda.com)|104.16.32.241|:443... connected.\n",
 "HTTP request sent, awaiting response... 200 OK\n",
 "Length: 160039710 (153M) [application/octet-stream]\n",
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 "\n",
 "2025-08-05 07:52:20 (272 MB/s) - ‘Miniconda3-latest-Linux-x86_64.sh’ saved [160039710/160039710]\n",
 "\n",
 "PREFIX=/usr/local\n",
 "Unpacking payload ...\n",
 "entry_point.py:256: DeprecationWarning: Python 3.14 will, by default, filter extracted tar archives and reject files or modify their metadata. Use the filter argument to control this behavior.\n",
 "entry_point.py:256: DeprecationWarning: Python 3.14 will, by default, filter extracted tar archives and reject files or modify their metadata. Use the filter argument to control this behavior.\n",
 "\n",
 "Installing base environment...\n",
 "\n",
 "Preparing transaction: ...working... done\n",
 "Executing transaction: ...working... done\n",
 "entry_point.py:256: DeprecationWarning: Python 3.14 will, by default, filter extracted tar archives and reject files or modify their metadata. Use the filter argument to control this behavior.\n",
 "installation finished.\n",
 "WARNING:\n",
 " You currently have a PYTHONPATH environment variable set. This may cause\n",
 " unexpected behavior when running the Python interpreter in Miniconda3.\n",
 " For best results, please verify that your PYTHONPATH only points to\n",
 " directories of packages that are compatible with the Python interpreter\n",
 " in Miniconda3: /usr/local\n",
 "accepted Terms of Service for \u001b[4;94mhttps://repo.anaconda.com/pkgs/main\u001b[0m\n",
 "accepted Terms of Service for \u001b[4;94mhttps://repo.anaconda.com/pkgs/r\u001b[0m\n"
 ]
 }
 ],
 "source": [
 "!wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh\n",
 "!chmod +x Miniconda3-latest-Linux-x86_64.sh\n",
 "!bash ./Miniconda3-latest-Linux-x86_64.sh -b -f -p /usr/local\n",
 "\n",
 "import sys\n",
 "sys.path.append('/usr/local/lib/python3.9/site-packages')\n",
 "\n",
 "\n",
 "!conda tos accept --override-channels --channel https://repo.anaconda.com/pkgs/main\n",
 "!conda tos accept --override-channels --channel https://repo.anaconda.com/pkgs/r"
 ]
 },
 {
 "cell_type": "code",
 "source": [
 "!conda create -n nenv python=3.8 -y"
 ],
 "metadata": {
 "colab": {
 "base_uri": "https://localhost:8080/"
 },
 "collapsed": true,
 "id": "Y1MkskTkOCG2",
 "outputId": "dbb27949-d70e-4d90-8732-88482fa33a0e"
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 "execution_count": 2,
 "outputs": [
 {
 "output_type": "stream",
 "name": "stdout",
 "text": [
 "\u001b[1;32m2\u001b[0m\u001b[1;32m channel Terms of Service accepted\u001b[0m\n",
 "Channels:\n",
 " - defaults\n",
 "Platform: linux-64\n",
 "Collecting package metadata (repodata.json): - \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\bdone\n",
 "Solving environment: | \b\bdone\n",
 "\n",
 "## Package Plan ##\n",
 "\n",
 " environment location: /usr/local/envs/nenv\n",
 "\n",
 " added / updated specs:\n",
 " - python=3.8\n",
 "\n",
 "\n",
 "The following packages will be downloaded:\n",
 "\n",
 " package | build\n",
 " ---------------------------|-----------------\n",
 " ncurses-6.5 | h7934f7d_0 1.1 MB\n",
 " openssl-3.0.17 | h5eee18b_0 5.2 MB\n",
 " pip-24.2 | py38h06a4308_0 2.2 MB\n",
 " python-3.8.20 | he870216_0 23.8 MB\n",
 " setuptools-75.1.0 | py38h06a4308_0 1.7 MB\n",
 " wheel-0.44.0 | py38h06a4308_0 108 KB\n",
 " ------------------------------------------------------------\n",
 " Total: 34.1 MB\n",
 "\n",
 "The following NEW packages will be INSTALLED:\n",
 "\n",
 " _libgcc_mutex pkgs/main/linux-64::_libgcc_mutex-0.1-main \n",
 " _openmp_mutex pkgs/main/linux-64::_openmp_mutex-5.1-1_gnu \n",
 " ca-certificates pkgs/main/linux-64::ca-certificates-2025.2.25-h06a4308_0 \n",
 " ld_impl_linux-64 pkgs/main/linux-64::ld_impl_linux-64-2.40-h12ee557_0 \n",
 " libffi pkgs/main/linux-64::libffi-3.4.4-h6a678d5_1 \n",
 " libgcc-ng pkgs/main/linux-64::libgcc-ng-11.2.0-h1234567_1 \n",
 " libgomp pkgs/main/linux-64::libgomp-11.2.0-h1234567_1 \n",
 " libstdcxx-ng pkgs/main/linux-64::libstdcxx-ng-11.2.0-h1234567_1 \n",
 " libxcb pkgs/main/linux-64::libxcb-1.17.0-h9b100fa_0 \n",
 " ncurses pkgs/main/linux-64::ncurses-6.5-h7934f7d_0 \n",
 " openssl pkgs/main/linux-64::openssl-3.0.17-h5eee18b_0 \n",
 " pip pkgs/main/linux-64::pip-24.2-py38h06a4308_0 \n",
 " pthread-stubs pkgs/main/linux-64::pthread-stubs-0.3-h0ce48e5_1 \n",
 " python pkgs/main/linux-64::python-3.8.20-he870216_0 \n",
 " readline pkgs/main/linux-64::readline-8.2-h5eee18b_0 \n",
 " setuptools pkgs/main/linux-64::setuptools-75.1.0-py38h06a4308_0 \n",
 " sqlite pkgs/main/linux-64::sqlite-3.50.2-hb25bd0a_1 \n",
 " tk pkgs/main/linux-64::tk-8.6.14-h993c535_1 \n",
 " wheel pkgs/main/linux-64::wheel-0.44.0-py38h06a4308_0 \n",
 " xorg-libx11 pkgs/main/linux-64::xorg-libx11-1.8.12-h9b100fa_1 \n",
 " xorg-libxau pkgs/main/linux-64::xorg-libxau-1.0.12-h9b100fa_0 \n",
 " xorg-libxdmcp pkgs/main/linux-64::xorg-libxdmcp-1.1.5-h9b100fa_0 \n",
 " xorg-xorgproto pkgs/main/linux-64::xorg-xorgproto-2024.1-h5eee18b_1 \n",
 " xz pkgs/main/linux-64::xz-5.6.4-h5eee18b_1 \n",
 " zlib pkgs/main/linux-64::zlib-1.2.13-h5eee18b_1 \n",
 "\n",
 "\n",
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 "Downloading and Extracting Packages:\n",
 "python-3.8.20 | 23.8 MB | : 0% 0/1 [00:00<?, ?it/s]\n",
 "openssl-3.0.17 | 5.2 MB | : 0% 0/1 [00:00<?, ?it/s]\u001b[A\n",
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 "pip-24.2 | 2.2 MB | : 0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\n",
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 "setuptools-75.1.0 | 1.7 MB | : 0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n",
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 "python-3.8.20 | 23.8 MB | : 5% 0.045346856545183056/1 [00:00<00:02, 2.22s/it]\n",
 "openssl-3.0.17 | 5.2 MB | : 13% 0.134900068229486/1 [00:00<00:00, 1.35it/s]\u001b[A\n",
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 "wheel-0.44.0 | 108 KB | : 15% 0.14783134378186213/1 [00:00<00:00, 1.12s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
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 "openssl-3.0.17 | 5.2 MB | : 100% 1.0/1 [00:00<00:00, 3.76it/s] \u001b[A\n",
 "python-3.8.20 | 23.8 MB | : 100% 1.0/1 [00:00<00:00, 2.27it/s] \n",
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 "setuptools-75.1.0 | 1.7 MB | : 100% 1.0/1 [00:01<00:00, 6.80it/s]\u001b[A\u001b[A\u001b[A\n",
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 " \n",
 " \u001b[A\n",
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 " \u001b[A\u001b[A\n",
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 " \u001b[A\u001b[A\u001b[A\n",
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 " \u001b[A\u001b[A\u001b[A\u001b[A\n",
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 " \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
 "Preparing transaction: - \b\b\\ \b\bdone\n",
 "Verifying transaction: / \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\bdone\n",
 "Executing transaction: - \b\b\\ \b\b| \b\b/ \b\b- \b\bdone\n",
 "#\n",
 "# To activate this environment, use\n",
 "#\n",
 "# $ conda activate nenv\n",
 "#\n",
 "# To deactivate an active environment, use\n",
 "#\n",
 "# $ conda deactivate\n",
 "\n"
 ]
 }
 ]
 },
 {
 "cell_type": "code",
 "source": [
 "!git clone https://github.com/ACAT-SCUT/CycleNet.git\n",
 "%cd CycleNet"
 ],
 "metadata": {
 "colab": {
 "base_uri": "https://localhost:8080/"
 },
 "id": "m3Q3h_YGOFkg",
 "outputId": "802b92e7-a2e0-4221-aa3c-88b1bdee9257"
 },
 "execution_count": 3,
 "outputs": [
 {
 "output_type": "stream",
 "name": "stdout",
 "text": [
 "Cloning into 'CycleNet'...\n",
 "remote: Enumerating objects: 207, done.\u001b[K\n",
 "remote: Counting objects: 100% (72/72), done.\u001b[K\n",
 "remote: Compressing objects: 100% (30/30), done.\u001b[K\n",
 "remote: Total 207 (delta 54), reused 42 (delta 42), pack-reused 135 (from 1)\u001b[K\n",
 "Receiving objects: 100% (207/207), 2.35 MiB | 29.33 MiB/s, done.\n",
 "Resolving deltas: 100% (106/106), done.\n",
 "/content/CycleNet\n"
 ]
 }
 ]
 },
 {
 "cell_type": "code",
 "source": [
 "!gdown --id 1bNbw1y8VYp-8pkRTqbjoW-TA-G8T0EQf -O /content/CycleNet/all_dataset.zip\n",
 "!unzip /content/CycleNet/all_dataset.zip -d /content/CycleNet/dataset"
 ],
 "metadata": {
 "colab": {
 "base_uri": "https://localhost:8080/"
 },
 "collapsed": true,
 "id": "CcWSsBMSOWWV",
 "outputId": "5371bcce-c340-429b-f86d-a70eb0f3cb44"
 },
 "execution_count": 4,
 "outputs": [
 {
 "output_type": "stream",
 "name": "stdout",
 "text": [
 "/usr/local/lib/python3.11/dist-packages/gdown/__main__.py:140: FutureWarning: Option `--id` was deprecated in version 4.3.1 and will be removed in 5.0. You don't need to pass it anymore to use a file ID.\n",
 " warnings.warn(\n",
 "Downloading...\n",
 "From (original): https://drive.google.com/uc?id=1bNbw1y8VYp-8pkRTqbjoW-TA-G8T0EQf\n",
 "From (redirected): https://drive.google.com/uc?id=1bNbw1y8VYp-8pkRTqbjoW-TA-G8T0EQf&confirm=t&uuid=6925f4de-72de-472e-9122-e1f479fa8d2a\n",
 "To: /content/CycleNet/all_dataset.zip\n",
 "100% 172M/172M [00:02<00:00, 63.1MB/s]\n",
 "Archive: /content/CycleNet/all_dataset.zip\n",
 " inflating: /content/CycleNet/dataset/ETTm2.csv \n",
 " inflating: /content/CycleNet/dataset/exchange_rate.csv \n",
 " inflating: /content/CycleNet/dataset/national_illness.csv \n",
 " inflating: /content/CycleNet/dataset/PEMS03.npz \n",
 " inflating: /content/CycleNet/dataset/PEMS04.npz \n",
 " inflating: /content/CycleNet/dataset/PEMS07.npz \n",
 " inflating: /content/CycleNet/dataset/PEMS08.npz \n",
 " inflating: /content/CycleNet/dataset/solar_AL.txt \n",
 " inflating: /content/CycleNet/dataset/traffic.csv \n",
 " inflating: /content/CycleNet/dataset/weather.csv \n",
 " inflating: /content/CycleNet/dataset/electricity.csv \n",
 " inflating: /content/CycleNet/dataset/ETTh1.csv \n",
 " inflating: /content/CycleNet/dataset/ETTh2.csv \n",
 " inflating: /content/CycleNet/dataset/ETTm1.csv \n"
 ]
 }
 ]
 },
 {
 "cell_type": "code",
 "source": [
 "!source /usr/local/bin/activate nenv && pip install -r requirements.txt"
 ],
 "metadata": {
 "colab": {
 "base_uri": "https://localhost:8080/"
 },
 "collapsed": true,
 "id": "RHQfqPjJOs4e",
 "outputId": "93137cd7-b275-4b13-ce23-b9771a2f624e"
 },
 "execution_count": 5,
 "outputs": [
 {
 "output_type": "stream",
 "name": "stdout",
 "text": [
 "Collecting numpy (from -r requirements.txt (line 1))\n",
 " Downloading numpy-1.24.4-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (5.6 kB)\n",
 "Collecting matplotlib (from -r requirements.txt (line 2))\n",
 " Downloading matplotlib-3.7.5-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl.metadata (5.7 kB)\n",
 "Collecting pandas (from -r requirements.txt (line 3))\n",
 " Downloading pandas-2.0.3-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (18 kB)\n",
 "Collecting scikit-learn (from -r requirements.txt (line 4))\n",
 " Downloading scikit_learn-1.3.2-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (11 kB)\n",
 "Collecting torch (from -r requirements.txt (line 5))\n",
 " Downloading torch-2.4.1-cp38-cp38-manylinux1_x86_64.whl.metadata (26 kB)\n",
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 " Downloading contourpy-1.1.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (5.9 kB)\n",
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 ]
 }
 ]
 },
 {
 "cell_type": "code",
 "source": [
 "!source /usr/local/bin/activate nenv && bash scripts/CycleNet/MLP-Input-336/electricity.sh;"
 ],
 "metadata": {
 "colab": {
 "base_uri": "https://localhost:8080/"
 },
 "id": "Zl-xVMnOOv6N",
 "outputId": "4bd5d7aa-c44d-4279-f272-c31c1a75343b"
 },
 "execution_count": 7,
 "outputs": [
 {
 "output_type": "stream",
 "name": "stdout",
 "text": [
 "Args in experiment:\n",
 "Namespace(activation='gelu', affine=0, batch_size=64, c_out=7, channel_id=1, checkpoints='./checkpoints/', cycle=168, d_ff=2048, d_layers=1, d_model=512, data='custom', data_path='electricity.csv', dec_in=7, dec_way='pmf', decomposition=0, des='test', devices='0,1', distil=True, do_predict=False, dropout=0, e_layers=2, embed='timeF', embed_type=0, enc_in=321, factor=1, fc_dropout=0.05, features='M', freq='h', gpu=0, head_dropout=0.0, individual=0, is_training=1, itr=1, kernel_size=25, label_len=0, learning_rate=0.002, loss='mse', lradj='type3', model='CycleNet', model_id='Electricity_336_96', model_type='mlp', moving_avg=25, n_heads=8, num_workers=10, output_attention=False, padding_patch='end', patch_len=16, patience=5, pct_start=0.3, period_len=24, pred_len=96, random_seed=2024, revin=0, rnn_type='gru', root_path='./dataset/', seg_len=48, seq_len=336, stride=8, subtract_last=0, target='OT', test_flop=False, train_epochs=30, use_amp=False, use_gpu=True, use_multi_gpu=False, use_revin=1)\n",
 "Use GPU: cuda:0\n",
 ">>>>>>>start training : Electricity_336_96_CycleNet_custom_ftM_sl336_pl96_cycle168_mlp_seed2024>>>>>>>>>>>>>>>>>>>>>>>>>>\n",
 "train 17981\n",
 "val 2537\n",
 "test 5165\n",
 "\titers: 100, epoch: 1 | loss: 0.2534176\n",
 "\tspeed: 0.1178s/iter; left time: 977.8598s\n",
 "\titers: 200, epoch: 1 | loss: 0.2187174\n",
 "\tspeed: 0.0833s/iter; left time: 683.2367s\n",
 "Epoch: 1 cost time: 25.013556480407715\n",
 "Epoch: 1, Steps: 280 | Train Loss: 0.2950343 Vali Loss: 0.1701207 Test Loss: 0.1945778\n",
 "Validation loss decreased (inf --> 0.170121). Saving model ...\n",
 "Updating learning rate to 0.002\n",
 "\titers: 100, epoch: 2 | loss: 0.1501387\n",
 "\tspeed: 0.2915s/iter; left time: 2338.3453s\n",
 "\titers: 200, epoch: 2 | loss: 0.1376742\n",
 "\tspeed: 0.0801s/iter; left time: 634.7708s\n",
 "Epoch: 2 cost time: 25.036283254623413\n",
 "Traceback (most recent call last):\n",
 " File \"run.py\", line 145, in <module>\n",
 " exp.train(setting)\n",
 " File \"/content/CycleNet/exp/exp_main.py\", line 224, in train\n",
 " vali_loss = self.vali(vali_data, vali_loader, criterion)\n",
 " File \"/content/CycleNet/exp/exp_main.py\", line 68, in vali\n",
 " batch_x = batch_x.float().to(self.device)\n",
 "KeyboardInterrupt\n",
 "^C\n"
 ]
 }
 ]
 },
 {
 "cell_type": "code",
 "source": [
 "!source /usr/local/bin/activate nenv && bash scripts/CycleNet/Linear-Input-336/electricity.sh;"
 ],
 "metadata": {
 "colab": {
 "base_uri": "https://localhost:8080/"
 },
 "id": "CBfBky9NQca1",
 "outputId": "5d1b9c7a-387e-4dc8-cf47-576440e4f9e3"
 },
 "execution_count": 8,
 "outputs": [
 {
 "output_type": "stream",
 "name": "stdout",
 "text": [
 "Args in experiment:\n",
 "Namespace(activation='gelu', affine=0, batch_size=64, c_out=7, channel_id=1, checkpoints='./checkpoints/', cycle=168, d_ff=2048, d_layers=1, d_model=512, data='custom', data_path='electricity.csv', dec_in=7, dec_way='pmf', decomposition=0, des='test', devices='0,1', distil=True, do_predict=False, dropout=0, e_layers=2, embed='timeF', embed_type=0, enc_in=321, factor=1, fc_dropout=0.05, features='M', freq='h', gpu=0, head_dropout=0.0, individual=0, is_training=1, itr=1, kernel_size=25, label_len=0, learning_rate=0.005, loss='mse', lradj='type3', model='CycleNet', model_id='Electricity_336_96', model_type='linear', moving_avg=25, n_heads=8, num_workers=10, output_attention=False, padding_patch='end', patch_len=16, patience=5, pct_start=0.3, period_len=24, pred_len=96, random_seed=2024, revin=0, rnn_type='gru', root_path='./dataset/', seg_len=48, seq_len=336, stride=8, subtract_last=0, target='OT', test_flop=False, train_epochs=30, use_amp=False, use_gpu=True, use_multi_gpu=False, use_revin=1)\n",
 "Use GPU: cuda:0\n",
 ">>>>>>>start training : Electricity_336_96_CycleNet_custom_ftM_sl336_pl96_cycle168_linear_seed2024>>>>>>>>>>>>>>>>>>>>>>>>>>\n",
 "train 17981\n",
 "val 2537\n",
 "test 5165\n",
 "\titers: 100, epoch: 1 | loss: 0.2686359\n",
 "\tspeed: 0.1058s/iter; left time: 878.1525s\n",
 "\titers: 200, epoch: 1 | loss: 0.1989910\n",
 "\tspeed: 0.0778s/iter; left time: 638.3535s\n",
 "Epoch: 1 cost time: 24.25062394142151\n",
 "Traceback (most recent call last):\n",
 " File \"run.py\", line 145, in <module>\n",
 " exp.train(setting)\n",
 " File \"/content/CycleNet/exp/exp_main.py\", line 225, in train\n",
 " test_loss = self.vali(test_data, test_loader, criterion)\n",
 " File \"/content/CycleNet/exp/exp_main.py\", line 103, in vali\n",
 " batch_y = batch_y[:, -self.args.pred_len:, f_dim:].to(self.device)\n",
 "KeyboardInterrupt\n",
 "^C\n"
 ]
 }
 ]
 }
 ]
}

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