PeMSD4_PM-DMNet(R)/notebook.ipynb

{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"provenance":[],"gpuType":"T4","authorship_tag":"ABX9TyOxPhZ+Jax04GHfiXnDnfRZ"},"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/"},"id":"7h8OnVcybi50","executionInfo":{"status":"ok","timestamp":1754468128914,"user_tz":-345,"elapsed":4017,"user":{"displayName":"Santosh Upreti","userId":"01961227760879466523"}},"outputId":"80f608c8-b1a7-4e3d-9271-19b125823a10"},"outputs":[{"output_type":"stream","name":"stdout","text":["Cloning into 'PM-DMNet'...\n","remote: Enumerating objects: 262, done.\u001b[K\n","remote: Counting objects: 100% (20/20), done.\u001b[K\n","remote: Compressing objects: 100% (20/20), done.\u001b[K\n","remote: Total 262 (delta 10), reused 0 (delta 0), pack-reused 242 (from 2)\u001b[K\n","Receiving objects: 100% (262/262), 72.40 MiB | 31.20 MiB/s, done.\n","Resolving deltas: 100% (104/104), done.\n","/content/PM-DMNet\n"]}],"source":["!git clone https://github.com/wengwenchao123/PM-DMNet.git\n","%cd PM-DMNet"]},{"cell_type":"code","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","!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"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"9PuZvmHKcyUz","executionInfo":{"status":"ok","timestamp":1754468211718,"user_tz":-345,"elapsed":26424,"user":{"displayName":"Santosh Upreti","userId":"01961227760879466523"}},"outputId":"64467737-1281-435c-9f43-8402e251a1e9"},"execution_count":2,"outputs":[{"output_type":"stream","name":"stdout","text":["--2025-08-06 08:16:25--  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::6810:20f1, ...\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","Saving to: ‘Miniconda3-latest-Linux-x86_64.sh’\n","\n","Miniconda3-latest-L 100%[===================>] 152.62M   167MB/s    in 0.9s    \n","\n","2025-08-06 08:16:26 (167 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"]}]},{"cell_type":"code","source":["!conda create -n newenv python=3.6.5 -y"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"collapsed":true,"id":"o1CD_9R7dA1C","executionInfo":{"status":"ok","timestamp":1754468273418,"user_tz":-345,"elapsed":9050,"user":{"displayName":"Santosh Upreti","userId":"01961227760879466523"}},"outputId":"6835e2a7-69f9-499b-e716-0daf1cecc855"},"execution_count":3,"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/newenv\n","\n","  added / updated specs:\n","    - python=3.6.5\n","\n","\n","The following packages will be downloaded:\n","\n","    package                    |            build\n","    ---------------------------|-----------------\n","    certifi-2021.5.30          |   py36h06a4308_0         139 KB\n","    libffi-3.2.1               |    hf484d3e_1007          48 KB\n","    ncurses-6.5                |       h7934f7d_0         1.1 MB\n","    openssl-1.0.2u             |       h7b6447c_0         2.2 MB\n","    pip-21.2.2                 |   py36h06a4308_0         1.8 MB\n","    python-3.6.5               |       hc3d631a_2        25.5 MB\n","    readline-7.0               |       h7b6447c_5         324 KB\n","    setuptools-58.0.4          |   py36h06a4308_0         788 KB\n","    sqlite-3.33.0              |       h62c20be_0         1.1 MB\n","    wheel-0.37.1               |     pyhd3eb1b0_0          33 KB\n","    ------------------------------------------------------------\n","                                           Total:        33.0 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","  certifi            pkgs/main/linux-64::certifi-2021.5.30-py36h06a4308_0 \n","  libedit            pkgs/main/linux-64::libedit-3.1.20230828-h5eee18b_0 \n","  libffi             pkgs/main/linux-64::libffi-3.2.1-hf484d3e_1007 \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-1.0.2u-h7b6447c_0 \n","  pip                pkgs/main/linux-64::pip-21.2.2-py36h06a4308_0 \n","  pthread-stubs      pkgs/main/linux-64::pthread-stubs-0.3-h0ce48e5_1 \n","  python             pkgs/main/linux-64::python-3.6.5-hc3d631a_2 \n","  readline           pkgs/main/linux-64::readline-7.0-h7b6447c_5 \n","  setuptools         pkgs/main/linux-64::setuptools-58.0.4-py36h06a4308_0 \n","  sqlite             pkgs/main/linux-64::sqlite-3.33.0-h62c20be_0 \n","  tk                 pkgs/main/linux-64::tk-8.6.14-h993c535_1 \n","  wheel              pkgs/main/noarch::wheel-0.37.1-pyhd3eb1b0_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","\n","Downloading and Extracting Packages:\n","python-3.6.5         | 25.5 MB   | :   0% 0/1 [00:00<?, ?it/s]\n","openssl-1.0.2u       | 2.2 MB    | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\n","\n","pip-21.2.2           | 1.8 MB    | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\n","\n","\n","sqlite-3.33.0        | 1.1 MB    | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","\n","ncurses-6.5          | 1.1 MB    | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\n","\n","\n","\n","\n","setuptools-58.0.4    | 788 KB    | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n","\n","\n","\n","\n","\n","readline-7.0         | 324 KB    | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n","\n","\n","\n","\n","\n","\n","certifi-2021.5.30    | 139 KB    | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n","\n","\n","\n","\n","\n","\n","\n","libffi-3.2.1         | 48 KB     | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n","\n","\n","\n","\n","\n","\n","\n","\n","wheel-0.37.1         | 33 KB     | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n","\n","\n","\n","ncurses-6.5          | 1.1 MB    | :   6% 0.05760662138607143/1 [00:00<00:01,  1.81s/it]\u001b[A\u001b[A\u001b[A\u001b[A\n","\n","pip-21.2.2           | 1.8 MB    | :   3% 0.034054723679506474/1 [00:00<00:03,  3.23s/it]\u001b[A\u001b[A\n","\n","\n","\n","ncurses-6.5          | 1.1 MB    | : 100% 1.0/1 [00:00<00:00,  1.81s/it]                \u001b[A\u001b[A\u001b[A\u001b[A\n","\n","pip-21.2.2           | 1.8 MB    | : 100% 1.0/1 [00:00<00:00,  3.23s/it]                 \u001b[A\u001b[A\n","\n","\n","\n","\n","setuptools-58.0.4    | 788 KB    | :   2% 0.020302530505221236/1 [00:00<00:09,  9.42s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n","\n","\n","\n","\n","setuptools-58.0.4    | 788 KB    | : 100% 1.0/1 [00:00<00:00,  9.42s/it]                 \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n","\n","\n","\n","\n","\n","readline-7.0         | 324 KB    | :   5% 0.04936828244539327/1 [00:00<00:04,  4.46s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n","\n","\n","\n","\n","\n","readline-7.0         | 324 KB    | : 100% 1.0/1 [00:00<00:00,  4.46s/it]                \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n","\n","\n","\n","\n","\n","\n","certifi-2021.5.30    | 139 KB    | :  11% 0.11497947296396364/1 [00:00<00:01,  2.10s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n","\n","\n","sqlite-3.33.0        | 1.1 MB    | :   1% 0.014005980581063546/1 [00:00<00:17, 17.60s/it]\u001b[A\u001b[A\u001b[A\n","\n","\n","\n","\n","\n","\n","certifi-2021.5.30    | 139 KB    | : 100% 1.0/1 [00:00<00:00,  2.10s/it]                \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n","\n","\n","\n","\n","\n","\n","\n","\n","wheel-0.37.1         | 33 KB     | :  49% 0.491583905907768/1 [00:00<00:00,  1.78it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n","\n","\n","\n","\n","\n","\n","\n","\n","wheel-0.37.1         | 33 KB     | : 100% 1.0/1 [00:00<00:00,  1.78it/s]              \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n","\n","\n","sqlite-3.33.0        | 1.1 MB    | : 100% 1.0/1 [00:00<00:00, 17.60s/it]                 \u001b[A\u001b[A\u001b[A\n","\n","\n","\n","\n","\n","\n","\n","python-3.6.5         | 25.5 MB   | :   0% 0.0006120161359488656/1 [00:00<12:14, 734.81s/it]\n","\n","\n","\n","\n","\n","\n","\n","python-3.6.5         | 25.5 MB   | :   1% 0.00979225817518185/1 [00:00<00:42, 43.20s/it]   \n","python-3.6.5         | 25.5 MB   | :   4% 0.04406516178831832/1 [00:00<00:09,  9.54s/it]\n","python-3.6.5         | 25.5 MB   | :  16% 0.16096024375455165/1 [00:00<00:02,  2.57s/it]\n","python-3.6.5         | 25.5 MB   | :  38% 0.38312210110398986/1 [00:00<00:00,  1.12s/it]\n","openssl-1.0.2u       | 2.2 MB    | : 100% 1.0/1 [00:00<00:00,  1.06s/it]             \u001b[A\n","\n","pip-21.2.2           | 1.8 MB    | : 100% 1.0/1 [00:00<00:00,  1.12it/s]\u001b[A\u001b[A\n","\n","python-3.6.5         | 25.5 MB   | :  87% 0.8727350098630823/1 [00:01<00:00,  1.67it/s]\n","\n","\n","\n","\n","setuptools-58.0.4    | 788 KB    | : 100% 1.0/1 [00:01<00:00,  1.18s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n","\n","\n","\n","\n","setuptools-58.0.4    | 788 KB    | : 100% 1.0/1 [00:01<00:00,  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\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n","\n","\n","\n","\n","\n","\n","\n","\n","                                                                        \u001b[A\u001b[A\u001b[A\u001b[A\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\bdone\n","Executing transaction: / \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\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\bdone\n","#\n","# To activate this environment, use\n","#\n","#     $ conda activate newenv\n","#\n","# To deactivate an active environment, use\n","#\n","#     $ conda deactivate\n","\n"]}]},{"cell_type":"code","source":["!source /usr/local/bin/activate newenv && pip install torch==1.9.0+cu111 torchvision==0.10.0+cu111 -f https://download.pytorch.org/whl/torch_stable.html\n"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"1C66Rm3tdJpi","executionInfo":{"status":"ok","timestamp":1754468597561,"user_tz":-345,"elapsed":233285,"user":{"displayName":"Santosh Upreti","userId":"01961227760879466523"}},"outputId":"aab1e395-0283-4849-fc07-73a4a4f55d10"},"execution_count":5,"outputs":[{"output_type":"stream","name":"stdout","text":["Looking in links: https://download.pytorch.org/whl/torch_stable.html\n","Collecting torch==1.9.0+cu111\n","  Downloading https://download.pytorch.org/whl/cu111/torch-1.9.0%2Bcu111-cp36-cp36m-linux_x86_64.whl (2041.3 MB)\n","\u001b[K     |████████████████████████████████| 2041.3 MB 2.5 kB/s \n","\u001b[?25hCollecting torchvision==0.10.0+cu111\n","  Downloading https://download.pytorch.org/whl/cu111/torchvision-0.10.0%2Bcu111-cp36-cp36m-linux_x86_64.whl (23.2 MB)\n","\u001b[K     |████████████████████████████████| 23.2 MB 1.2 MB/s \n","\u001b[?25hCollecting 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torchvision\n","Successfully installed dataclasses-0.8 numpy-1.19.5 pillow-8.4.0 torch-1.9.0+cu111 torchvision-0.10.0+cu111 typing-extensions-4.1.1\n","\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\n"]}]},{"cell_type":"code","source":["!source /usr/local/bin/activate newenv && pip install numpy==1.16.3 configparser"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"WiGkJ-Pbdlsj","executionInfo":{"status":"ok","timestamp":1754468670217,"user_tz":-345,"elapsed":7068,"user":{"displayName":"Santosh Upreti","userId":"01961227760879466523"}},"outputId":"6785b481-a386-4f77-efa7-16ecdf5614f9"},"execution_count":6,"outputs":[{"output_type":"stream","name":"stdout","text":["Collecting numpy==1.16.3\n","  Downloading numpy-1.16.3-cp36-cp36m-manylinux1_x86_64.whl (17.3 MB)\n","\u001b[K     |████████████████████████████████| 17.3 MB 473 kB/s \n","\u001b[?25hCollecting configparser\n","  Downloading configparser-5.2.0-py3-none-any.whl (19 kB)\n","Installing collected packages: numpy, configparser\n","  Attempting uninstall: numpy\n","    Found existing installation: numpy 1.19.5\n","    Uninstalling numpy-1.19.5:\n","      Successfully uninstalled numpy-1.19.5\n","Successfully installed configparser-5.2.0 numpy-1.16.3\n","\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\n"]}]},{"cell_type":"code","source":["!gdown 1Q8boyeVNmZTz_HASN_57qd9wX1JZeGem"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"f70C1VOxd3xj","executionInfo":{"status":"ok","timestamp":1754468686703,"user_tz":-345,"elapsed":4509,"user":{"displayName":"Santosh Upreti","userId":"01961227760879466523"}},"outputId":"9030fe5b-a213-4b80-ebce-3767c61940c2"},"execution_count":7,"outputs":[{"output_type":"stream","name":"stdout","text":["Downloading...\n","From (original): https://drive.google.com/uc?id=1Q8boyeVNmZTz_HASN_57qd9wX1JZeGem\n","From (redirected): https://drive.google.com/uc?id=1Q8boyeVNmZTz_HASN_57qd9wX1JZeGem&confirm=t&uuid=1ecd2a8c-ed96-4e3a-9e02-8d59cab16e46\n","To: /content/PM-DMNet/Data.zip\n","100% 143M/143M [00:01<00:00, 75.4MB/s]\n"]}]},{"cell_type":"code","source":["!unzip Data.zip"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"collapsed":true,"id":"RoGVUsIJd-UR","executionInfo":{"status":"ok","timestamp":1754468705555,"user_tz":-345,"elapsed":2515,"user":{"displayName":"Santosh Upreti","userId":"01961227760879466523"}},"outputId":"e9f73cac-9910-4e84-e7f8-ee52e5b0eec9"},"execution_count":8,"outputs":[{"output_type":"stream","name":"stdout","text":["Archive:  Data.zip\n","   creating: data/NYC-Bike14/\n","  inflating: data/NYC-Bike14/NYC-Bike14.npz  \n","  inflating: data/NYC-Bike14/adj_mx.npz  \n","   creating: data/NYC-Bike15/\n","  inflating: data/NYC-Bike15/NYC-Bike15.npz  \n","  inflating: data/NYC-Bike15/adj_mx.npz  \n","   creating: data/NYC-Bike16/\n","  inflating: data/NYC-Bike16/NYC-Bike16.h5  \n","  inflating: data/NYC-Bike16/all_graph.h5  \n","   creating: data/NYC-Taxi15/\n","  inflating: data/NYC-Taxi15/NYC-Taxi15.npz  \n","  inflating: data/NYC-Taxi15/adj_mx.npz  \n","   creating: data/NYC-Taxi16/\n","  inflating: data/NYC-Taxi16/NYC-Taxi16.h5  \n","  inflating: data/NYC-Taxi16/all_graph.h5  \n","   creating: data/PEMS07/\n","  inflating: data/PEMS07/PEMS07.npz  \n","   creating: data/PEMS07(L)/\n","  inflating: data/PEMS07(L)/PEMS07L.npz  \n","  inflating: data/PEMS07(L)/PeMSD7L.csv  \n","   creating: data/PEMS07(M)/\n","  inflating: data/PEMS07(M)/V_228.csv  \n","   creating: data/PEMS08/\n","  inflating: data/PEMS08/PEMS08.csv  \n","  inflating: data/PEMS08/PEMS08.npz  \n","   creating: data/PeMS03/\n","  inflating: data/PeMS03/PEMS03.npz  \n","   creating: data/PeMS04/\n","  inflating: data/PeMS04/PEMS04.csv  \n","  inflating: data/PeMS04/PEMS04.npz  \n"]}]},{"cell_type":"code","source":["!source /usr/local/bin/activate newenv && pip install nvidia-ml-py3 pandas h5py"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"ZV7Rjfo-f02P","executionInfo":{"status":"ok","timestamp":1754469005067,"user_tz":-345,"elapsed":2317,"user":{"displayName":"Santosh Upreti","userId":"01961227760879466523"}},"outputId":"320b3b00-965b-45b7-866e-3202d35f4d66"},"execution_count":14,"outputs":[{"output_type":"stream","name":"stdout","text":["Requirement already satisfied: nvidia-ml-py3 in /usr/local/envs/newenv/lib/python3.6/site-packages (7.352.0)\n","Requirement already satisfied: pandas in /usr/local/envs/newenv/lib/python3.6/site-packages (1.1.5)\n","Collecting h5py\n","  Downloading h5py-3.1.0-cp36-cp36m-manylinux1_x86_64.whl (4.0 MB)\n","\u001b[K     |████████████████████████████████| 4.0 MB 5.6 MB/s \n","\u001b[?25hRequirement already satisfied: numpy>=1.15.4 in /usr/local/envs/newenv/lib/python3.6/site-packages (from pandas) (1.16.3)\n","Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/envs/newenv/lib/python3.6/site-packages (from pandas) (2.9.0.post0)\n","Requirement already satisfied: pytz>=2017.2 in /usr/local/envs/newenv/lib/python3.6/site-packages (from pandas) (2025.2)\n","Collecting cached-property\n","  Downloading cached_property-1.5.2-py2.py3-none-any.whl (7.6 kB)\n","Requirement already satisfied: six>=1.5 in /usr/local/envs/newenv/lib/python3.6/site-packages (from python-dateutil>=2.7.3->pandas) (1.17.0)\n","Installing collected packages: cached-property, h5py\n","Successfully installed cached-property-1.5.2 h5py-3.1.0\n","\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\n"]}]},{"cell_type":"code","source":["!source /usr/local/bin/activate newenv && python run.py --dataset PEMSD4 --type R --mode train"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"MfM3fnODfIqr","executionInfo":{"status":"ok","timestamp":1754469683310,"user_tz":-345,"elapsed":217707,"user":{"displayName":"Santosh Upreti","userId":"01961227760879466523"}},"outputId":"fe617b50-fa44-442b-9b73-d3bd8a250212"},"execution_count":19,"outputs":[{"output_type":"stream","name":"stdout","text":["/content\n","Namespace(batch_size=64, cheb_k=2, column_wise=False, cuda=True, dataset='PEMSD4', debug=False, default_graph=True, device='cuda:0', early_stop=True, early_stop_patience=30, embed_dim=10, epochs=500, grad_norm=False, horizon=12, input_dim=1, lag=12, log_dir='./', log_step=10000, loss_func='mae', lr_decay=True, lr_decay_rate=0.3, lr_decay_step='80,100,120', lr_init=0.003, mae_thresh=None, mape_thresh=0.0, max_grad_norm=5, mode='train', model='PM_DMNet', normalizer='std', num_layers=1, num_nodes=307, output_dim=1, plot=False, real_value=True, rnn_units=64, seed=10, steps_per_day=288, steps_per_week=7, teacher_decay_step=1500, teacher_forcing=True, test_ratio=0.2, time_dim=20, tod=False, type='R', use_day=True, use_week=True, val_ratio=0.2, weight_decay=0.0)\n","*****************Model Parameter*****************\n","node_embeddings torch.Size([307, 10]) True\n","T_i_D_emb torch.Size([288, 20]) True\n","D_i_W_emb torch.Size([7, 20]) True\n","encoder.PM_cells.0.gate.weights_pool torch.Size([10, 2, 65, 128]) True\n","encoder.PM_cells.0.gate.weights torch.Size([2, 65, 128]) True\n","encoder.PM_cells.0.gate.bias_pool torch.Size([10, 128]) True\n","encoder.PM_cells.0.gate.bias torch.Size([128]) True\n","encoder.PM_cells.0.gate.node_embeddings torch.Size([10, 20]) True\n","encoder.PM_cells.0.gate.fc1.fc1.weight torch.Size([16, 65]) True\n","encoder.PM_cells.0.gate.fc1.fc1.bias torch.Size([16]) True\n","encoder.PM_cells.0.gate.fc1.fc2.weight torch.Size([2, 16]) True\n","encoder.PM_cells.0.gate.fc1.fc2.bias torch.Size([2]) True\n","encoder.PM_cells.0.gate.fc1.fc3.weight torch.Size([20, 2]) True\n","encoder.PM_cells.0.gate.fc1.fc3.bias torch.Size([20]) True\n","encoder.PM_cells.0.gate.fc2.fc1.weight torch.Size([2, 20]) True\n","encoder.PM_cells.0.gate.fc2.fc1.bias torch.Size([2]) True\n","encoder.PM_cells.0.gate.fc2.fc2.weight torch.Size([16, 2]) True\n","encoder.PM_cells.0.gate.fc2.fc2.bias torch.Size([16]) True\n","encoder.PM_cells.0.gate.fc2.fc3.weight torch.Size([65, 16]) True\n","encoder.PM_cells.0.gate.fc2.fc3.bias torch.Size([65]) True\n","encoder.PM_cells.0.update.weights_pool torch.Size([10, 2, 65, 64]) True\n","encoder.PM_cells.0.update.weights torch.Size([2, 65, 64]) True\n","encoder.PM_cells.0.update.bias_pool torch.Size([10, 64]) True\n","encoder.PM_cells.0.update.bias torch.Size([64]) True\n","encoder.PM_cells.0.update.node_embeddings torch.Size([10, 20]) True\n","encoder.PM_cells.0.update.fc1.fc1.weight torch.Size([16, 65]) True\n","encoder.PM_cells.0.update.fc1.fc1.bias torch.Size([16]) True\n","encoder.PM_cells.0.update.fc1.fc2.weight torch.Size([2, 16]) True\n","encoder.PM_cells.0.update.fc1.fc2.bias torch.Size([2]) True\n","encoder.PM_cells.0.update.fc1.fc3.weight torch.Size([20, 2]) True\n","encoder.PM_cells.0.update.fc1.fc3.bias torch.Size([20]) True\n","encoder.PM_cells.0.update.fc2.fc1.weight torch.Size([2, 20]) True\n","encoder.PM_cells.0.update.fc2.fc1.bias torch.Size([2]) True\n","encoder.PM_cells.0.update.fc2.fc2.weight torch.Size([16, 2]) True\n","encoder.PM_cells.0.update.fc2.fc2.bias torch.Size([16]) True\n","encoder.PM_cells.0.update.fc2.fc3.weight torch.Size([65, 16]) True\n","encoder.PM_cells.0.update.fc2.fc3.bias torch.Size([65]) True\n","proj.0.weight torch.Size([1, 64]) True\n","proj.0.bias torch.Size([1]) True\n","end_conv1.weight torch.Size([12, 1, 1, 64]) True\n","end_conv1.bias torch.Size([12]) True\n","decoder.decoder.PM_cells.0.gate.weights_pool torch.Size([10, 2, 65, 128]) True\n","decoder.decoder.PM_cells.0.gate.weights torch.Size([2, 65, 128]) True\n","decoder.decoder.PM_cells.0.gate.bias_pool torch.Size([10, 128]) True\n","decoder.decoder.PM_cells.0.gate.bias torch.Size([128]) True\n","decoder.decoder.PM_cells.0.gate.node_embeddings torch.Size([10, 20]) True\n","decoder.decoder.PM_cells.0.gate.fc1.fc1.weight torch.Size([16, 65]) True\n","decoder.decoder.PM_cells.0.gate.fc1.fc1.bias torch.Size([16]) True\n","decoder.decoder.PM_cells.0.gate.fc1.fc2.weight torch.Size([2, 16]) True\n","decoder.decoder.PM_cells.0.gate.fc1.fc2.bias torch.Size([2]) True\n","decoder.decoder.PM_cells.0.gate.fc1.fc3.weight torch.Size([20, 2]) True\n","decoder.decoder.PM_cells.0.gate.fc1.fc3.bias torch.Size([20]) True\n","decoder.decoder.PM_cells.0.gate.fc2.fc1.weight torch.Size([2, 20]) True\n","decoder.decoder.PM_cells.0.gate.fc2.fc1.bias torch.Size([2]) True\n","decoder.decoder.PM_cells.0.gate.fc2.fc2.weight torch.Size([16, 2]) True\n","decoder.decoder.PM_cells.0.gate.fc2.fc2.bias torch.Size([16]) True\n","decoder.decoder.PM_cells.0.gate.fc2.fc3.weight torch.Size([65, 16]) True\n","decoder.decoder.PM_cells.0.gate.fc2.fc3.bias torch.Size([65]) True\n","decoder.decoder.PM_cells.0.update.weights_pool torch.Size([10, 2, 65, 64]) True\n","decoder.decoder.PM_cells.0.update.weights torch.Size([2, 65, 64]) True\n","decoder.decoder.PM_cells.0.update.bias_pool torch.Size([10, 64]) True\n","decoder.decoder.PM_cells.0.update.bias torch.Size([64]) True\n","decoder.decoder.PM_cells.0.update.node_embeddings torch.Size([10, 20]) True\n","decoder.decoder.PM_cells.0.update.fc1.fc1.weight torch.Size([16, 65]) True\n","decoder.decoder.PM_cells.0.update.fc1.fc1.bias torch.Size([16]) True\n","decoder.decoder.PM_cells.0.update.fc1.fc2.weight torch.Size([2, 16]) True\n","decoder.decoder.PM_cells.0.update.fc1.fc2.bias torch.Size([2]) True\n","decoder.decoder.PM_cells.0.update.fc1.fc3.weight torch.Size([20, 2]) True\n","decoder.decoder.PM_cells.0.update.fc1.fc3.bias torch.Size([20]) True\n","decoder.decoder.PM_cells.0.update.fc2.fc1.weight torch.Size([2, 20]) True\n","decoder.decoder.PM_cells.0.update.fc2.fc1.bias torch.Size([2]) True\n","decoder.decoder.PM_cells.0.update.fc2.fc2.weight torch.Size([16, 2]) True\n","decoder.decoder.PM_cells.0.update.fc2.fc2.bias torch.Size([16]) True\n","decoder.decoder.PM_cells.0.update.fc2.fc3.weight torch.Size([65, 16]) True\n","decoder.decoder.PM_cells.0.update.fc2.fc3.bias torch.Size([65]) True\n","decoder.proj.0.weight torch.Size([1, 64]) True\n","decoder.proj.0.bias torch.Size([1]) True\n","Total params num: 573404\n","*****************Finish Parameter****************\n","Load PEMSD4 Dataset shaped:  (16992, 307, 1) 919.0 0.0 211.7007794815878 180.0\n","Normalize the dataset by Standard Normalization\n","Train:  (10182, 12, 307, 3) (10182, 12, 307, 3)\n","Val:  (3394, 12, 307, 3) (3394, 12, 307, 3)\n","Test:  (3393, 12, 307, 3) (3393, 12, 307, 3)\n","Applying learning rate decay.\n","Creat Log File in:  /content/PM-DMNet/experiments/PEMSD4/R/20250806083803/run.log\n","2025-08-06 08:38: Namespace(batch_size=64, cheb_k=2, column_wise=False, cuda=True, dataset='PEMSD4', debug=False, default_graph=True, device='cuda:0', early_stop=True, early_stop_patience=30, embed_dim=10, epochs=500, grad_norm=False, horizon=12, input_dim=1, lag=12, log_dir='/content/PM-DMNet/experiments/PEMSD4/R/20250806083803', log_step=10000, loss_func='mae', lr_decay=True, lr_decay_rate=0.3, lr_decay_step='80,100,120', lr_init=0.003, mae_thresh=None, mape_thresh=0.0, max_grad_norm=5, mode='train', model='PM_DMNet', normalizer='std', num_layers=1, num_nodes=307, output_dim=1, plot=False, real_value=True, rnn_units=64, seed=10, steps_per_day=288, steps_per_week=7, teacher_decay_step=1500, teacher_forcing=True, test_ratio=0.2, time_dim=20, tod=False, type='R', use_day=True, use_week=True, val_ratio=0.2, weight_decay=0.0)\n","2025-08-06 08:38: Experiment log path in: /content/PM-DMNet/experiments/PEMSD4/R/20250806083803\n","2025-08-06 08:38: ********Train Epoch 1: averaged Loss: 38.028598, GPU cost: 2.64 GB, train time: 29.17 s\n","2025-08-06 08:38: ***********Val Epoch 1: average Loss: 27.263447, train time: 3.30 s\n","2025-08-06 08:38: **********test Epoch 1: average Loss: 26.053058, train time: 3.33 s\n","2025-08-06 08:38: *********************************Current best model saved!\n","2025-08-06 08:39: ********Train Epoch 2: averaged Loss: 17.746848, GPU cost: 2.64 GB, train time: 29.59 s\n","2025-08-06 08:39: ***********Val Epoch 2: average Loss: 24.127087, train time: 3.32 s\n","2025-08-06 08:39: **********test Epoch 2: average Loss: 22.859991, train time: 3.42 s\n","2025-08-06 08:39: *********************************Current best model saved!\n","2025-08-06 08:39: ********Train Epoch 3: averaged Loss: 17.504388, GPU cost: 2.64 GB, train time: 29.82 s\n","2025-08-06 08:39: ***********Val Epoch 3: average Loss: 24.125681, train time: 3.37 s\n","2025-08-06 08:39: **********test Epoch 3: average Loss: 22.868657, train time: 3.41 s\n","2025-08-06 08:39: *********************************Current best model saved!\n","2025-08-06 08:40: ********Train Epoch 4: averaged Loss: 17.402669, GPU cost: 2.64 GB, train time: 30.06 s\n","2025-08-06 08:40: ***********Val Epoch 4: average Loss: 23.430854, train time: 3.47 s\n","2025-08-06 08:40: **********test Epoch 4: average Loss: 22.228232, train time: 3.44 s\n","2025-08-06 08:40: *********************************Current best model saved!\n","2025-08-06 08:40: ********Train Epoch 5: averaged Loss: 17.461098, GPU cost: 2.64 GB, train time: 30.20 s\n","2025-08-06 08:41: ***********Val Epoch 5: average Loss: 23.193937, train time: 3.48 s\n","2025-08-06 08:41: **********test Epoch 5: average Loss: 22.020786, train time: 3.44 s\n","2025-08-06 08:41: *********************************Current best model saved!\n","Traceback (most recent call last):\n","  File \"run.py\", line 160, in <module>\n","    trainer.train()\n","  File \"/content/PM-DMNet/model/BasicTrainer.py\", line 148, in train\n","    train_epoch_loss = self.train_epoch(epoch)\n","  File \"/content/PM-DMNet/model/BasicTrainer.py\", line 106, in train_epoch\n","    loss.backward()\n","  File \"/usr/local/envs/newenv/lib/python3.6/site-packages/torch/_tensor.py\", line 255, in backward\n","    torch.autograd.backward(self, gradient, retain_graph, create_graph, inputs=inputs)\n","  File \"/usr/local/envs/newenv/lib/python3.6/site-packages/torch/autograd/__init__.py\", line 149, in backward\n","    allow_unreachable=True, accumulate_grad=True)  # allow_unreachable flag\n","KeyboardInterrupt\n"]}]}]}