VPP_LGBM_GPU_0.4506.ipynb

{
 "cells": [
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   "cell_type": "markdown",
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     "start_time": "2021-10-25T19:15:14.557070",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Re-compile LGBM with GPU support"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "985a802d",
   "metadata": {
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     "exception": false,
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     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "rm: cannot remove '/opt/conda/lib/python3.6/site-packages/lightgbm': No such file or directory\r\n",
      "Cloning into 'LightGBM'...\r\n",
      "remote: Enumerating objects: 23671, done.\u001b[K\r\n",
      "remote: Counting objects: 100% (1347/1347), done.\u001b[K\r\n",
      "remote: Compressing objects: 100% (731/731), done.\u001b[K\r\n",
      "remote: Total 23671 (delta 851), reused 979 (delta 584), pack-reused 22324\u001b[K\r\n",
      "Receiving objects: 100% (23671/23671), 18.14 MiB | 22.41 MiB/s, done.\r\n",
      "Resolving deltas: 100% (17244/17244), done.\r\n",
      "Submodule 'include/boost/compute' (https://github.com/boostorg/compute) registered for path 'external_libs/compute'\r\n",
      "Submodule 'eigen' (https://gitlab.com/libeigen/eigen.git) registered for path 'external_libs/eigen'\r\n",
      "Submodule 'external_libs/fast_double_parser' (https://github.com/lemire/fast_double_parser.git) registered for path 'external_libs/fast_double_parser'\r\n",
      "Submodule 'external_libs/fmt' (https://github.com/fmtlib/fmt.git) registered for path 'external_libs/fmt'\r\n",
      "Cloning into '/kaggle/working/LightGBM/external_libs/compute'...\r\n",
      "remote: Enumerating objects: 21733, done.        \r\n",
      "remote: Counting objects: 100% (5/5), done.        \r\n",
      "remote: Compressing objects: 100% (5/5), done.        \r\n",
      "remote: Total 21733 (delta 1), reused 2 (delta 0), pack-reused 21728        \r\n",
      "Receiving objects: 100% (21733/21733), 8.51 MiB | 16.23 MiB/s, done.\r\n",
      "Resolving deltas: 100% (17567/17567), done.\r\n",
      "Cloning into '/kaggle/working/LightGBM/external_libs/eigen'...\r\n",
      "remote: Enumerating objects: 112747, done.        \r\n",
      "remote: Counting objects: 100% (112747/112747), done.        \r\n",
      "remote: Compressing objects: 100% (20611/20611), done.        \r\n",
      "remote: Total 112747 (delta 93052), reused 111516 (delta 91829), pack-reused 0        \r\n",
      "Receiving objects: 100% (112747/112747), 98.41 MiB | 27.36 MiB/s, done.\r\n",
      "Resolving deltas: 100% (93052/93052), done.\r\n",
      "Cloning into '/kaggle/working/LightGBM/external_libs/fast_double_parser'...\r\n",
      "remote: Enumerating objects: 692, done.        \r\n",
      "remote: Counting objects: 100% (192/192), done.        \r\n",
      "remote: Compressing objects: 100% (124/124), done.        \r\n",
      "remote: Total 692 (delta 95), reused 99 (delta 41), pack-reused 500        \r\n",
      "Receiving objects: 100% (692/692), 802.86 KiB | 3.26 MiB/s, done.\r\n",
      "Resolving deltas: 100% (349/349), done.\r\n",
      "Cloning into '/kaggle/working/LightGBM/external_libs/fmt'...\r\n",
      "remote: Enumerating objects: 27771, done.        \r\n",
      "remote: Counting objects: 100% (511/511), done.        \r\n",
      "remote: Compressing objects: 100% (212/212), done.        \r\n",
      "remote: Total 27771 (delta 300), reused 377 (delta 224), pack-reused 27260        \r\n",
      "Receiving objects: 100% (27771/27771), 13.61 MiB | 19.38 MiB/s, done.\r\n",
      "Resolving deltas: 100% (18734/18734), done.\r\n",
      "Submodule path 'external_libs/compute': checked out '36c89134d4013b2e5e45bc55656a18bd6141995a'\r\n",
      "Submodule path 'external_libs/eigen': checked out '8ba1b0f41a7950dc3e1d4ed75859e36c73311235'\r\n",
      "Submodule path 'external_libs/fast_double_parser': checked out 'ace60646c02dc54c57f19d644e49a61e7e7758ec'\r\n",
      "Submodule 'benchmark/dependencies/abseil-cpp' (https://github.com/abseil/abseil-cpp.git) registered for path 'external_libs/fast_double_parser/benchmarks/dependencies/abseil-cpp'\r\n",
      "Submodule 'benchmark/dependencies/double-conversion' (https://github.com/google/double-conversion.git) registered for path 'external_libs/fast_double_parser/benchmarks/dependencies/double-conversion'\r\n",
      "Cloning into '/kaggle/working/LightGBM/external_libs/fast_double_parser/benchmarks/dependencies/abseil-cpp'...\r\n",
      "remote: Enumerating objects: 15486, done.        \r\n",
      "remote: Counting objects: 100% (1421/1421), done.        \r\n",
      "remote: Compressing objects: 100% (779/779), done.        \r\n",
      "remote: Total 15486 (delta 944), reused 1001 (delta 638), pack-reused 14065        \r\n",
      "Receiving objects: 100% (15486/15486), 10.49 MiB | 15.43 MiB/s, done.\r\n",
      "Resolving deltas: 100% (11685/11685), done.\r\n",
      "Cloning into '/kaggle/working/LightGBM/external_libs/fast_double_parser/benchmarks/dependencies/double-conversion'...\r\n",
      "remote: Enumerating objects: 1239, done.        \r\n",
      "remote: Counting objects: 100% (83/83), done.        \r\n",
      "remote: Compressing objects: 100% (65/65), done.        \r\n",
      "remote: Total 1239 (delta 48), reused 36 (delta 18), pack-reused 1156        \r\n",
      "Receiving objects: 100% (1239/1239), 7.09 MiB | 13.18 MiB/s, done.\r\n",
      "Resolving deltas: 100% (820/820), done.\r\n",
      "Submodule path 'external_libs/fast_double_parser/benchmarks/dependencies/abseil-cpp': checked out 'd936052d32a5b7ca08b0199a6724724aea432309'\r\n",
      "Submodule path 'external_libs/fast_double_parser/benchmarks/dependencies/double-conversion': checked out 'f4cb2384efa55dee0e6652f8674b05763441ab09'\r\n",
      "Submodule path 'external_libs/fmt': checked out 'cc09f1a6798c085c325569ef466bcdcffdc266d4'\r\n"
     ]
    }
   ],
   "source": [
    "!rm -r /opt/conda/lib/python3.6/site-packages/lightgbm\n",
    "!git clone --recursive https://github.com/Microsoft/LightGBM"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "768468b0",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-10-25T19:15:39.154915Z",
     "iopub.status.busy": "2021-10-25T19:15:39.154127Z",
     "iopub.status.idle": "2021-10-25T19:15:41.480924Z",
     "shell.execute_reply": "2021-10-25T19:15:41.479988Z",
     "shell.execute_reply.started": "2021-10-24T15:26:55.225981Z"
    },
    "papermill": {
     "duration": 2.412353,
     "end_time": "2021-10-25T19:15:41.481070",
     "exception": false,
     "start_time": "2021-10-25T19:15:39.068717",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "!apt-get install -y -qq libboost-all-dev"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "c22b54d0",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-10-25T19:15:41.647076Z",
     "iopub.status.busy": "2021-10-25T19:15:41.646494Z",
     "iopub.status.idle": "2021-10-25T19:20:25.966095Z",
     "shell.execute_reply": "2021-10-25T19:20:25.965031Z"
    },
    "papermill": {
     "duration": 284.40515,
     "end_time": "2021-10-25T19:20:25.966277",
     "exception": false,
     "start_time": "2021-10-25T19:15:41.561127",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-- The C compiler identification is GNU 7.5.0\n",
      "-- The CXX compiler identification is GNU 7.5.0\n",
      "-- Check for working C compiler: /usr/bin/cc\n",
      "-- Check for working C compiler: /usr/bin/cc -- works\n",
      "-- Detecting C compiler ABI info\n",
      "-- Detecting C compiler ABI info - done\n",
      "-- Detecting C compile features\n",
      "-- Detecting C compile features - done\n",
      "-- Check for working CXX compiler: /usr/bin/c++\n",
      "-- Check for working CXX compiler: /usr/bin/c++ -- works\n",
      "-- Detecting CXX compiler ABI info\n",
      "-- Detecting CXX compiler ABI info - done\n",
      "-- Detecting CXX compile features\n",
      "-- Detecting CXX compile features - done\n",
      "-- Found OpenMP_C: -fopenmp (found version \"4.5\") \n",
      "-- Found OpenMP_CXX: -fopenmp (found version \"4.5\") \n",
      "-- Found OpenMP: TRUE (found version \"4.5\")  \n",
      "-- Looking for CL_VERSION_2_2\n",
      "-- Looking for CL_VERSION_2_2 - not found\n",
      "-- Looking for CL_VERSION_2_1\n",
      "-- Looking for CL_VERSION_2_1 - not found\n",
      "-- Looking for CL_VERSION_2_0\n",
      "-- Looking for CL_VERSION_2_0 - not found\n",
      "-- Looking for CL_VERSION_1_2\n",
      "-- Looking for CL_VERSION_1_2 - found\n",
      "-- Found OpenCL: /usr/local/cuda/lib64/libOpenCL.so (found version \"1.2\") \n",
      "-- OpenCL include directory: /usr/local/cuda/include\n",
      "-- Boost version: 1.65.1\n",
      "-- Found the following Boost libraries:\n",
      "--   filesystem\n",
      "--   system\n",
      "-- Performing Test MM_PREFETCH\n",
      "-- Performing Test MM_PREFETCH - Success\n",
      "-- Using _mm_prefetch\n",
      "-- Performing Test MM_MALLOC\n",
      "-- Performing Test MM_MALLOC - Success\n",
      "-- Using _mm_malloc\n",
      "-- Configuring done\n",
      "-- Generating done\n",
      "-- Build files have been written to: /kaggle/working/LightGBM/build\n",
      "Scanning dependencies of target lightgbm\n",
      "Scanning dependencies of target _lightgbm\n",
      "[  2%] Building CXX object CMakeFiles/lightgbm.dir/src/main.cpp.o\n",
      "[  2%] Building CXX object CMakeFiles/_lightgbm.dir/src/boosting/boosting.cpp.o\n",
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      "[  5%] Building CXX object CMakeFiles/_lightgbm.dir/src/boosting/gbdt.cpp.o\n",
      "[  7%] Building CXX object CMakeFiles/lightgbm.dir/src/boosting/boosting.cpp.o\n",
      "[  8%] Building CXX object CMakeFiles/_lightgbm.dir/src/boosting/gbdt_model_text.cpp.o\n",
      "[ 10%] Building CXX object CMakeFiles/lightgbm.dir/src/boosting/gbdt.cpp.o\n",
      "[ 11%] Building CXX object CMakeFiles/_lightgbm.dir/src/boosting/gbdt_prediction.cpp.o\n",
      "[ 13%] Building CXX object CMakeFiles/lightgbm.dir/src/boosting/gbdt_model_text.cpp.o\n",
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      "[ 18%] Building CXX object CMakeFiles/lightgbm.dir/src/boosting/prediction_early_stop.cpp.o\n",
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      "[ 73%] Building CXX object CMakeFiles/lightgbm.dir/src/network/linkers_socket.cpp.o\n",
      "[ 75%] Building CXX object CMakeFiles/lightgbm.dir/src/network/network.cpp.o\n",
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      "[ 82%] Building CXX object CMakeFiles/_lightgbm.dir/src/treelearner/gpu_tree_learner.cpp.o\n",
      "[ 84%] Building CXX object CMakeFiles/lightgbm.dir/src/treelearner/gpu_tree_learner.cpp.o\n",
      "[ 85%] Building CXX object CMakeFiles/_lightgbm.dir/src/treelearner/linear_tree_learner.cpp.o\n",
      "[ 86%] Building CXX object CMakeFiles/lightgbm.dir/src/treelearner/linear_tree_learner.cpp.o\n",
      "[ 88%] Building CXX object CMakeFiles/_lightgbm.dir/src/treelearner/serial_tree_learner.cpp.o\n",
      "[ 89%] Building CXX object CMakeFiles/lightgbm.dir/src/treelearner/serial_tree_learner.cpp.o\n",
      "[ 91%] Building CXX object CMakeFiles/_lightgbm.dir/src/treelearner/tree_learner.cpp.o\n",
      "[ 92%] Building CXX object CMakeFiles/lightgbm.dir/src/treelearner/tree_learner.cpp.o\n",
      "[ 94%] Building CXX object CMakeFiles/_lightgbm.dir/src/treelearner/voting_parallel_tree_learner.cpp.o\n",
      "[ 95%] Building CXX object CMakeFiles/lightgbm.dir/src/treelearner/voting_parallel_tree_learner.cpp.o\n",
      "[ 97%] Building CXX object CMakeFiles/_lightgbm.dir/src/c_api.cpp.o\n",
      "[ 98%] Linking CXX executable ../lightgbm\n",
      "[ 98%] Built target lightgbm\n",
      "[100%] Linking CXX shared library ../lib_lightgbm.so\n",
      "[100%] Built target _lightgbm\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "rm: cannot remove 'build': No such file or directory\n",
      "cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n",
      "/usr/bin/cmake: /opt/conda/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)\n"
     ]
    }
   ],
   "source": [
    "%%bash\n",
    "cd LightGBM\n",
    "rm -r build\n",
    "mkdir build\n",
    "cd build\n",
    "cmake -DUSE_GPU=1 -DOpenCL_LIBRARY=/usr/local/cuda/lib64/libOpenCL.so -DOpenCL_INCLUDE_DIR=/usr/local/cuda/include/ ..\n",
    "make -j$(nproc)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "7fa18600",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-10-25T19:20:26.257643Z",
     "iopub.status.busy": "2021-10-25T19:20:26.256654Z",
     "iopub.status.idle": "2021-10-25T19:20:27.784238Z",
     "shell.execute_reply": "2021-10-25T19:20:27.783485Z"
    },
    "papermill": {
     "duration": 1.680479,
     "end_time": "2021-10-25T19:20:27.784386",
     "exception": false,
     "start_time": "2021-10-25T19:20:26.103907",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "running install\r\n",
      "running build\r\n",
      "running build_py\r\n",
      "creating build\r\n",
      "creating build/lib\r\n",
      "creating build/lib/lightgbm\r\n",
      "copying lightgbm/engine.py -> build/lib/lightgbm\r\n",
      "copying lightgbm/basic.py -> build/lib/lightgbm\r\n",
      "copying lightgbm/__init__.py -> build/lib/lightgbm\r\n",
      "copying lightgbm/compat.py -> build/lib/lightgbm\r\n",
      "copying lightgbm/libpath.py -> build/lib/lightgbm\r\n",
      "copying lightgbm/plotting.py -> build/lib/lightgbm\r\n",
      "copying lightgbm/callback.py -> build/lib/lightgbm\r\n",
      "copying lightgbm/sklearn.py -> build/lib/lightgbm\r\n",
      "copying lightgbm/dask.py -> build/lib/lightgbm\r\n",
      "running egg_info\r\n",
      "creating lightgbm.egg-info\r\n",
      "writing lightgbm.egg-info/PKG-INFO\r\n",
      "writing dependency_links to lightgbm.egg-info/dependency_links.txt\r\n",
      "writing requirements to lightgbm.egg-info/requires.txt\r\n",
      "writing top-level names to lightgbm.egg-info/top_level.txt\r\n",
      "writing manifest file 'lightgbm.egg-info/SOURCES.txt'\r\n",
      "reading manifest template 'MANIFEST.in'\r\n",
      "no previously-included directories found matching 'build'\r\n",
      "warning: no files found matching 'LICENSE'\r\n",
      "warning: no files found matching '*.txt'\r\n",
      "warning: no files found matching '*.so' under directory 'lightgbm'\r\n",
      "warning: no files found matching 'compile/CMakeLists.txt'\r\n",
      "warning: no files found matching 'compile/cmake/IntegratedOpenCL.cmake'\r\n",
      "warning: no files found matching '*.so' under directory 'compile'\r\n",
      "warning: no files found matching '*.dll' under directory 'compile/Release'\r\n",
      "warning: no files found matching 'compile/external_libs/compute/CMakeLists.txt'\r\n",
      "warning: no files found matching '*' under directory 'compile/external_libs/compute/cmake'\r\n",
      "warning: no files found matching '*' under directory 'compile/external_libs/compute/include'\r\n",
      "warning: no files found matching '*' under directory 'compile/external_libs/compute/meta'\r\n",
      "warning: no files found matching 'compile/external_libs/eigen/CMakeLists.txt'\r\n",
      "warning: no files found matching 'compile/external_libs/eigen/Eigen/Cholesky'\r\n",
      "warning: no files found matching 'compile/external_libs/eigen/Eigen/Core'\r\n",
      "warning: no files found matching 'compile/external_libs/eigen/Eigen/Dense'\r\n",
      "warning: no files found matching 'compile/external_libs/eigen/Eigen/Eigenvalues'\r\n",
      "warning: no files found matching 'compile/external_libs/eigen/Eigen/Geometry'\r\n",
      "warning: no files found matching 'compile/external_libs/eigen/Eigen/Householder'\r\n",
      "warning: no files found matching 'compile/external_libs/eigen/Eigen/Jacobi'\r\n",
      "warning: no files found matching 'compile/external_libs/eigen/Eigen/LU'\r\n",
      "warning: no files found matching 'compile/external_libs/eigen/Eigen/QR'\r\n",
      "warning: no files found matching 'compile/external_libs/eigen/Eigen/SVD'\r\n",
      "warning: no files found matching '*' under directory 'compile/external_libs/eigen/Eigen/src/Cholesky'\r\n",
      "warning: no files found matching '*' under directory 'compile/external_libs/eigen/Eigen/src/Core'\r\n",
      "warning: no files found matching '*' under directory 'compile/external_libs/eigen/Eigen/src/Eigenvalues'\r\n",
      "warning: no files found matching '*' under directory 'compile/external_libs/eigen/Eigen/src/Geometry'\r\n",
      "warning: no files found matching '*' under directory 'compile/external_libs/eigen/Eigen/src/Householder'\r\n",
      "warning: no files found matching '*' under directory 'compile/external_libs/eigen/Eigen/src/Jacobi'\r\n",
      "warning: no files found matching '*' under directory 'compile/external_libs/eigen/Eigen/src/LU'\r\n",
      "warning: no files found matching '*' under directory 'compile/external_libs/eigen/Eigen/src/misc'\r\n",
      "warning: no files found matching '*' under directory 'compile/external_libs/eigen/Eigen/src/plugins'\r\n",
      "warning: no files found matching '*' under directory 'compile/external_libs/eigen/Eigen/src/QR'\r\n",
      "warning: no files found matching '*' under directory 'compile/external_libs/eigen/Eigen/src/SVD'\r\n",
      "warning: no files found matching 'compile/external_libs/fast_double_parser/CMakeLists.txt'\r\n",
      "warning: no files found matching 'compile/external_libs/fast_double_parser/LICENSE'\r\n",
      "warning: no files found matching 'compile/external_libs/fast_double_parser/LICENSE.BSL'\r\n",
      "warning: no files found matching '*' under directory 'compile/external_libs/fast_double_parser/include'\r\n",
      "warning: no files found matching 'compile/external_libs/fmt/CMakeLists.txt'\r\n",
      "warning: no files found matching 'compile/external_libs/fmt/LICENSE.rst'\r\n",
      "warning: no files found matching '*' under directory 'compile/external_libs/fmt/include'\r\n",
      "warning: no files found matching '*' under directory 'compile/include'\r\n",
      "warning: no files found matching '*' under directory 'compile/src'\r\n",
      "warning: no files found matching 'LightGBM.sln' under directory 'compile/windows'\r\n",
      "warning: no files found matching 'LightGBM.vcxproj' under directory 'compile/windows'\r\n",
      "warning: no files found matching '*.dll' under directory 'compile/windows/x64/DLL'\r\n",
      "warning: no previously-included files matching '*.py[co]' found anywhere in distribution\r\n",
      "warning: no previously-included files found matching 'compile/external_libs/compute/.git'\r\n",
      "writing manifest file 'lightgbm.egg-info/SOURCES.txt'\r\n",
      "copying lightgbm/VERSION.txt -> build/lib/lightgbm\r\n",
      "running install_lib\r\n",
      "copying build/lib/lightgbm/VERSION.txt -> /opt/conda/lib/python3.7/site-packages/lightgbm\r\n",
      "copying build/lib/lightgbm/engine.py -> /opt/conda/lib/python3.7/site-packages/lightgbm\r\n",
      "copying build/lib/lightgbm/basic.py -> /opt/conda/lib/python3.7/site-packages/lightgbm\r\n",
      "copying build/lib/lightgbm/__init__.py -> /opt/conda/lib/python3.7/site-packages/lightgbm\r\n",
      "copying build/lib/lightgbm/compat.py -> /opt/conda/lib/python3.7/site-packages/lightgbm\r\n",
      "copying build/lib/lightgbm/libpath.py -> /opt/conda/lib/python3.7/site-packages/lightgbm\r\n",
      "copying build/lib/lightgbm/plotting.py -> /opt/conda/lib/python3.7/site-packages/lightgbm\r\n",
      "copying build/lib/lightgbm/callback.py -> /opt/conda/lib/python3.7/site-packages/lightgbm\r\n",
      "copying build/lib/lightgbm/sklearn.py -> /opt/conda/lib/python3.7/site-packages/lightgbm\r\n",
      "copying build/lib/lightgbm/dask.py -> /opt/conda/lib/python3.7/site-packages/lightgbm\r\n",
      "copying /kaggle/working/LightGBM/lib_lightgbm.so -> /opt/conda/lib/python3.7/site-packages/lightgbm\r\n",
      "byte-compiling /opt/conda/lib/python3.7/site-packages/lightgbm/engine.py to engine.cpython-37.pyc\r\n",
      "byte-compiling /opt/conda/lib/python3.7/site-packages/lightgbm/basic.py to basic.cpython-37.pyc\r\n",
      "byte-compiling /opt/conda/lib/python3.7/site-packages/lightgbm/__init__.py to __init__.cpython-37.pyc\r\n",
      "byte-compiling /opt/conda/lib/python3.7/site-packages/lightgbm/compat.py to compat.cpython-37.pyc\r\n",
      "byte-compiling /opt/conda/lib/python3.7/site-packages/lightgbm/libpath.py to libpath.cpython-37.pyc\r\n",
      "byte-compiling /opt/conda/lib/python3.7/site-packages/lightgbm/plotting.py to plotting.cpython-37.pyc\r\n",
      "byte-compiling /opt/conda/lib/python3.7/site-packages/lightgbm/callback.py to callback.cpython-37.pyc\r\n",
      "byte-compiling /opt/conda/lib/python3.7/site-packages/lightgbm/sklearn.py to sklearn.cpython-37.pyc\r\n",
      "byte-compiling /opt/conda/lib/python3.7/site-packages/lightgbm/dask.py to dask.cpython-37.pyc\r\n",
      "running install_egg_info\r\n",
      "Copying lightgbm.egg-info to /opt/conda/lib/python3.7/site-packages/lightgbm-3.3.0.99-py3.7.egg-info\r\n",
      "running install_scripts\r\n"
     ]
    }
   ],
   "source": [
    "!cd LightGBM/python-package/;python3 setup.py install --precompile"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "9411f6c5",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-10-25T19:20:27.968347Z",
     "iopub.status.busy": "2021-10-25T19:20:27.967505Z",
     "iopub.status.idle": "2021-10-25T19:20:29.441157Z",
     "shell.execute_reply": "2021-10-25T19:20:29.440347Z"
    },
    "papermill": {
     "duration": 1.566555,
     "end_time": "2021-10-25T19:20:29.441286",
     "exception": false,
     "start_time": "2021-10-25T19:20:27.874731",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "!mkdir -p /etc/OpenCL/vendors && echo \"libnvidia-opencl.so.1\" > /etc/OpenCL/vendors/nvidia.icd\n",
    "!rm -r LightGBM"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "53135020",
   "metadata": {
    "papermill": {
     "duration": 0.082766,
     "end_time": "2021-10-25T19:20:29.607105",
     "exception": false,
     "start_time": "2021-10-25T19:20:29.524339",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Loading dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "ffecbb4b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-10-25T19:20:29.787516Z",
     "iopub.status.busy": "2021-10-25T19:20:29.786708Z",
     "iopub.status.idle": "2021-10-25T19:20:32.920311Z",
     "shell.execute_reply": "2021-10-25T19:20:32.919810Z",
     "shell.execute_reply.started": "2021-10-25T19:00:39.239418Z"
    },
    "papermill": {
     "duration": 3.230272,
     "end_time": "2021-10-25T19:20:32.920456",
     "exception": false,
     "start_time": "2021-10-25T19:20:29.690184",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
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     },
     "metadata": {},
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   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "import seaborn as sns\n",
    "import os\n",
    "import numpy as np\n",
    "import time\n",
    "import lightgbm as lgb\n",
    "\n",
    "from sklearn.model_selection import GroupKFold \n",
    "from sklearn.model_selection import  KFold\n",
    "from sklearn import metrics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "c85b1934",
   "metadata": {
    "execution": {
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       "      <td>18.383041</td>\n",
       "      <td>0</td>\n",
       "      <td>5.907794</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>20</td>\n",
       "      <td>50</td>\n",
       "      <td>0.067514</td>\n",
       "      <td>22.509278</td>\n",
       "      <td>0</td>\n",
       "      <td>7.876254</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>20</td>\n",
       "      <td>50</td>\n",
       "      <td>0.101542</td>\n",
       "      <td>22.808822</td>\n",
       "      <td>0</td>\n",
       "      <td>11.742872</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>20</td>\n",
       "      <td>50</td>\n",
       "      <td>0.135756</td>\n",
       "      <td>25.355850</td>\n",
       "      <td>0</td>\n",
       "      <td>12.234987</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   id  breath_id   R   C  time_step       u_in  u_out   pressure\n",
       "0   1          1  20  50   0.000000   0.083334      0   5.837492\n",
       "1   2          1  20  50   0.033652  18.383041      0   5.907794\n",
       "2   3          1  20  50   0.067514  22.509278      0   7.876254\n",
       "3   4          1  20  50   0.101542  22.808822      0  11.742872\n",
       "4   5          1  20  50   0.135756  25.355850      0  12.234987"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train = pd.read_csv(\"../input/ventilator-pressure-prediction/train.csv\")\n",
    "test = pd.read_csv(\"../input/ventilator-pressure-prediction/test.csv\")\n",
    "submission = pd.read_csv(\"../input/ventilator-pressure-prediction/sample_submission.csv\")\n",
    "train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "781bf4ac",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-10-25T19:20:45.813951Z",
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     "shell.execute_reply": "2021-10-25T19:20:45.856312Z",
     "shell.execute_reply.started": "2021-10-25T19:08:11.59345Z"
    },
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     "status": "completed"
    },
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   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>pressure_preds</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   id pressure_preds\n",
       "0   1               \n",
       "1   2               \n",
       "2   3               \n",
       "3   4               \n",
       "4   5               "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_preds = pd.DataFrame(train, columns=['id'])\n",
    "train_preds['pressure_preds'] = \"\"\n",
    "train_preds.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "4e5772fe",
   "metadata": {
    "execution": {
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     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "def add_features(df):\n",
    "    df['area'] = df['time_step'] * df['u_in']\n",
    "    df['area'] = df.groupby('breath_id')['area'].cumsum()\n",
    "    df['cross']= df['u_in']*df['u_out']\n",
    "    df['cross2']= df['time_step']*df['u_out']\n",
    "    \n",
    "    df['u_in_cumsum'] = df.groupby(['breath_id'])['u_in'].cumsum()\n",
    "    df['time_step_cumsum'] = df.groupby(['breath_id'])['time_step'].cumsum()\n",
    "    \n",
    "    df['u_in_1st_derivative'] = (df['u_in'].diff().fillna(0) / df['time_step'].diff().fillna(0)).fillna(0)\n",
    "    df['expand_mean_1sr_der'] = df.groupby('breath_id')['u_in_1st_derivative'].expanding(2).mean().reset_index(level=0,drop=True)\n",
    "    df['u_in_1st_der_mean10'] = df.groupby('breath_id')['u_in_1st_derivative'].rolling(window=10, min_periods=1).mean().reset_index(level=0,drop=True)\n",
    "    df['u_in_lag4'] = df.groupby('breath_id')['u_in'].shift(4).fillna(0).reset_index(level=0,drop=True)\n",
    "    df['u_in_lag-4'] = df.groupby('breath_id')['u_in'].shift(-4).fillna(0).reset_index(level=0,drop=True)\n",
    "    \n",
    "    df['time_diff'] = df['time_step']-df['time_step'].shift(1)\n",
    "    df['power'] = df['time_diff']*df['u_in']\n",
    "    df['power_cumsum'] = df.groupby(['breath_id'])['power'].cumsum()\n",
    "    \n",
    "    df['u_in_lag1'] = df.groupby('breath_id')['u_in'].shift(1)\n",
    "    df['u_in_lag2'] = df.groupby('breath_id')['u_in'].shift(2)\n",
    "    df['u_in_lag3'] = df.groupby('breath_id')['u_in'].shift(3)\n",
    "    \n",
    "    df['breath_id__u_in__max'] = df.groupby(['breath_id'])['u_in'].transform('max')\n",
    "    df['breath_id__u_in__min'] = df.groupby(['breath_id'])['u_in'].transform('min')\n",
    "                                                     \n",
    "    df['R'] = df['R'].astype(str)\n",
    "    df['C'] = df['C'].astype(str)\n",
    "    df['RC'] = df['R']+df['C']\n",
    "    df = pd.get_dummies(df)\n",
    "    \n",
    "    df['last_value_u_in'] = df.groupby('breath_id')['u_in'].transform('last')\n",
    "    df['u_in_lag_back1'] = df.groupby('breath_id')['u_in'].shift(-1)\n",
    "    df['u_in_lag_back2'] = df.groupby('breath_id')['u_in'].shift(-2)\n",
    "    df['u_in_lag_back3'] = df.groupby('breath_id')['u_in'].shift(-3)\n",
    "    df['u_in_diff1'] = df['u_in'] - df['u_in_lag1']\n",
    "    df['u_in_diff2'] = df['u_in'] - df['u_in_lag2']\n",
    "    \n",
    "    df['breath_id__u_in__diffmax'] = df.groupby(['breath_id'])['u_in'].transform('max') - df['u_in']\n",
    "    df['breath_id__u_in__diffmean'] = df.groupby(['breath_id'])['u_in'].transform('mean') - df['u_in']\n",
    "\n",
    "    df['ewm_u_in_mean'] = df.groupby('breath_id')['u_in'].ewm(halflife=10).mean().reset_index(level=0,drop=True)\n",
    "    df['ewm_u_in_std'] = df.groupby('breath_id')['u_in'].ewm(halflife=10).std().reset_index(level=0,drop=True)\n",
    "    df['ewm_u_in_corr'] = df.groupby('breath_id')['u_in'].ewm(halflife=10).corr().reset_index(level=0,drop=True)\n",
    "    \n",
    "    df['delta_u_in'] = abs(df.groupby(df['breath_id'])['u_in'].diff().fillna(0)).reset_index(level=0,drop=True)\n",
    "    df['delta_u_in_exp'] = df.groupby(df['breath_id'])['delta_u_in'].rolling(window=10, min_periods=1).mean().reset_index(level=0,drop=True)\n",
    "    df['delta_rolling_10_mean'] = df.groupby('breath_id')['delta_u_in'].rolling(window=10, min_periods=1).mean().reset_index(level=0,drop=True)\n",
    "    df['delta_rolling_10_max'] = df.groupby('breath_id')['delta_u_in'].rolling(window=10, min_periods=1).max().reset_index(level=0,drop=True)\n",
    "   \n",
    "    df['work']=((df['u_in'] + df['u_in'].shift(1).fillna(0))/2 * df['time_step'].diff().fillna(0)).clip(0,)\n",
    "    df['work_roll_10']=df.groupby(df['breath_id'])['work'].rolling(window=10, min_periods=1).sum().reset_index(level=0,drop=True)\n",
    "    df['work_roll_15']=df.groupby(df['breath_id'])['work'].rolling(window=15, min_periods=1).sum().reset_index(level=0,drop=True)\n",
    "      \n",
    "    df['u_in_rol_q0.1'] = df.groupby(df['breath_id'])['u_in'].rolling(window=10, min_periods=1).quantile(0.1).reset_index(level=0,drop=True)\n",
    "    df['u_in_rol_q0.25'] = df.groupby(df['breath_id'])['u_in'].rolling(window=10, min_periods=1).quantile(0.25).reset_index(level=0,drop=True)\n",
    "    df['u_in_rol_q0.5'] = df.groupby(df['breath_id'])['u_in'].rolling(window=10, min_periods=1).quantile(0.5).reset_index(level=0,drop=True)\n",
    "    df['u_in_rol_q0.75'] = df.groupby(df['breath_id'])['u_in'].rolling(window=10, min_periods=1).quantile(0.75).reset_index(level=0,drop=True)\n",
    "    df['u_in_rol_q0.9'] = df.groupby(df['breath_id'])['u_in'].rolling(window=10, min_periods=1).quantile(0.9).reset_index(level=0,drop=True)     \n",
    "    \n",
    "    df = df.fillna(0)\n",
    "    return df\n",
    "\n",
    "train = add_features(train)\n",
    "test = add_features(test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "cfe865eb",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-10-25T19:28:56.282819Z",
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     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "train = train[train['u_out'] < 1].reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "31a4d67c",
   "metadata": {
    "execution": {
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     "status": "completed"
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mon Oct 25 19:28:58 2021       \r\n",
      "+-----------------------------------------------------------------------------+\r\n",
      "| NVIDIA-SMI 450.119.04   Driver Version: 450.119.04   CUDA Version: 11.0     |\r\n",
      "|-------------------------------+----------------------+----------------------+\r\n",
      "| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |\r\n",
      "| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |\r\n",
      "|                               |                      |               MIG M. |\r\n",
      "|===============================+======================+======================|\r\n",
      "|   0  Tesla P100-PCIE...  Off  | 00000000:00:04.0 Off |                    0 |\r\n",
      "| N/A   37C    P0    27W / 250W |      0MiB / 16280MiB |      0%      Default |\r\n",
      "|                               |                      |                  N/A |\r\n",
      "+-------------------------------+----------------------+----------------------+\r\n",
      "                                                                               \r\n",
      "+-----------------------------------------------------------------------------+\r\n",
      "| Processes:                                                                  |\r\n",
      "|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |\r\n",
      "|        ID   ID                                                   Usage      |\r\n",
      "|=============================================================================|\r\n",
      "|  No running processes found                                                 |\r\n",
      "+-----------------------------------------------------------------------------+\r\n"
     ]
    }
   ],
   "source": [
    "!nvidia-smi"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "028b2a76",
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fold 0 started at Mon Oct 25 19:28:59 2021\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.7/site-packages/lightgbm/sklearn.py:726: UserWarning: 'early_stopping_rounds' argument is deprecated and will be removed in a future release of LightGBM. Pass 'early_stopping()' callback via 'callbacks' argument instead.\n",
      "  _log_warning(\"'early_stopping_rounds' argument is deprecated and will be removed in a future release of LightGBM. \"\n",
      "/opt/conda/lib/python3.7/site-packages/lightgbm/sklearn.py:736: UserWarning: 'verbose' argument is deprecated and will be removed in a future release of LightGBM. Pass 'log_evaluation()' callback via 'callbacks' argument instead.\n",
      "  _log_warning(\"'verbose' argument is deprecated and will be removed in a future release of LightGBM. \"\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[LightGBM] [Warning] min_data_in_leaf is set=30, min_child_samples=20 will be ignored. Current value: min_data_in_leaf=30\n",
      "[100]\ttraining's l2: 0.448807\tvalid_1's l2: 0.890518\n",
      "[200]\ttraining's l2: 0.297141\tvalid_1's l2: 0.834181\n",
      "[300]\ttraining's l2: 0.220501\tvalid_1's l2: 0.810058\n",
      "[400]\ttraining's l2: 0.169082\tvalid_1's l2: 0.791713\n",
      "[500]\ttraining's l2: 0.135122\tvalid_1's l2: 0.782432\n",
      "[600]\ttraining's l2: 0.109881\tvalid_1's l2: 0.777276\n",
      "[700]\ttraining's l2: 0.0914083\tvalid_1's l2: 0.772122\n",
      "[800]\ttraining's l2: 0.0772555\tvalid_1's l2: 0.768338\n",
      "[900]\ttraining's l2: 0.0658602\tvalid_1's l2: 0.765304\n",
      "[1000]\ttraining's l2: 0.0565063\tvalid_1's l2: 0.762754\n",
      "[1100]\ttraining's l2: 0.0488769\tvalid_1's l2: 0.761159\n",
      "[1200]\ttraining's l2: 0.0428541\tvalid_1's l2: 0.759764\n",
      "[1300]\ttraining's l2: 0.0375125\tvalid_1's l2: 0.758666\n",
      "[1400]\ttraining's l2: 0.0330198\tvalid_1's l2: 0.757922\n",
      "Fold 1 started at Mon Oct 25 19:35:52 2021\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.7/site-packages/lightgbm/sklearn.py:726: UserWarning: 'early_stopping_rounds' argument is deprecated and will be removed in a future release of LightGBM. Pass 'early_stopping()' callback via 'callbacks' argument instead.\n",
      "  _log_warning(\"'early_stopping_rounds' argument is deprecated and will be removed in a future release of LightGBM. \"\n",
      "/opt/conda/lib/python3.7/site-packages/lightgbm/sklearn.py:736: UserWarning: 'verbose' argument is deprecated and will be removed in a future release of LightGBM. Pass 'log_evaluation()' callback via 'callbacks' argument instead.\n",
      "  _log_warning(\"'verbose' argument is deprecated and will be removed in a future release of LightGBM. \"\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[LightGBM] [Warning] min_data_in_leaf is set=30, min_child_samples=20 will be ignored. Current value: min_data_in_leaf=30\n",
      "[100]\ttraining's l2: 0.446879\tvalid_1's l2: 0.862382\n",
      "[200]\ttraining's l2: 0.298434\tvalid_1's l2: 0.805658\n",
      "[300]\ttraining's l2: 0.220002\tvalid_1's l2: 0.779603\n",
      "[400]\ttraining's l2: 0.171068\tvalid_1's l2: 0.766908\n",
      "[500]\ttraining's l2: 0.137278\tvalid_1's l2: 0.757681\n",
      "[600]\ttraining's l2: 0.112158\tvalid_1's l2: 0.751021\n",
      "[700]\ttraining's l2: 0.0930351\tvalid_1's l2: 0.745731\n",
      "[800]\ttraining's l2: 0.0783848\tvalid_1's l2: 0.741847\n",
      "[900]\ttraining's l2: 0.0669215\tvalid_1's l2: 0.738424\n",
      "[1000]\ttraining's l2: 0.0571318\tvalid_1's l2: 0.736116\n",
      "[1100]\ttraining's l2: 0.0495732\tvalid_1's l2: 0.734538\n",
      "[1200]\ttraining's l2: 0.0429613\tvalid_1's l2: 0.732733\n",
      "[1300]\ttraining's l2: 0.0375401\tvalid_1's l2: 0.731315\n",
      "[1400]\ttraining's l2: 0.0329784\tvalid_1's l2: 0.730434\n",
      "[1500]\ttraining's l2: 0.0290533\tvalid_1's l2: 0.729584\n",
      "[1600]\ttraining's l2: 0.0255991\tvalid_1's l2: 0.728644\n",
      "[1700]\ttraining's l2: 0.0226085\tvalid_1's l2: 0.727836\n",
      "[1800]\ttraining's l2: 0.0202761\tvalid_1's l2: 0.72709\n",
      "[1900]\ttraining's l2: 0.0180419\tvalid_1's l2: 0.726528\n",
      "[2000]\ttraining's l2: 0.0161094\tvalid_1's l2: 0.726042\n",
      "[2100]\ttraining's l2: 0.0144493\tvalid_1's l2: 0.725605\n",
      "[2200]\ttraining's l2: 0.0130336\tvalid_1's l2: 0.725149\n",
      "[2300]\ttraining's l2: 0.0117464\tvalid_1's l2: 0.724735\n",
      "[2400]\ttraining's l2: 0.0106799\tvalid_1's l2: 0.724434\n",
      "[2500]\ttraining's l2: 0.00973196\tvalid_1's l2: 0.724113\n",
      "[2600]\ttraining's l2: 0.00877691\tvalid_1's l2: 0.72384\n",
      "[2700]\ttraining's l2: 0.00795433\tvalid_1's l2: 0.723572\n",
      "[2800]\ttraining's l2: 0.00719748\tvalid_1's l2: 0.723278\n",
      "[2900]\ttraining's l2: 0.00655364\tvalid_1's l2: 0.723075\n",
      "[3000]\ttraining's l2: 0.0059363\tvalid_1's l2: 0.722802\n",
      "[3100]\ttraining's l2: 0.00541102\tvalid_1's l2: 0.72271\n",
      "[3200]\ttraining's l2: 0.00490304\tvalid_1's l2: 0.722446\n",
      "[3300]\ttraining's l2: 0.00447457\tvalid_1's l2: 0.722316\n",
      "[3400]\ttraining's l2: 0.00409853\tvalid_1's l2: 0.722217\n",
      "Fold 2 started at Mon Oct 25 19:51:00 2021\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.7/site-packages/lightgbm/sklearn.py:726: UserWarning: 'early_stopping_rounds' argument is deprecated and will be removed in a future release of LightGBM. Pass 'early_stopping()' callback via 'callbacks' argument instead.\n",
      "  _log_warning(\"'early_stopping_rounds' argument is deprecated and will be removed in a future release of LightGBM. \"\n",
      "/opt/conda/lib/python3.7/site-packages/lightgbm/sklearn.py:736: UserWarning: 'verbose' argument is deprecated and will be removed in a future release of LightGBM. Pass 'log_evaluation()' callback via 'callbacks' argument instead.\n",
      "  _log_warning(\"'verbose' argument is deprecated and will be removed in a future release of LightGBM. \"\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[LightGBM] [Warning] min_data_in_leaf is set=30, min_child_samples=20 will be ignored. Current value: min_data_in_leaf=30\n",
      "[100]\ttraining's l2: 0.443007\tvalid_1's l2: 0.912536\n",
      "[200]\ttraining's l2: 0.295205\tvalid_1's l2: 0.857273\n",
      "[300]\ttraining's l2: 0.2151\tvalid_1's l2: 0.829078\n",
      "[400]\ttraining's l2: 0.168068\tvalid_1's l2: 0.815299\n",
      "[500]\ttraining's l2: 0.135086\tvalid_1's l2: 0.806179\n",
      "[600]\ttraining's l2: 0.109818\tvalid_1's l2: 0.799185\n",
      "[700]\ttraining's l2: 0.0907417\tvalid_1's l2: 0.794085\n",
      "[800]\ttraining's l2: 0.0773845\tvalid_1's l2: 0.790572\n",
      "[900]\ttraining's l2: 0.0661046\tvalid_1's l2: 0.787932\n",
      "[1000]\ttraining's l2: 0.0570929\tvalid_1's l2: 0.786192\n",
      "[1100]\ttraining's l2: 0.0490493\tvalid_1's l2: 0.78492\n",
      "[1200]\ttraining's l2: 0.0428317\tvalid_1's l2: 0.783572\n",
      "[1300]\ttraining's l2: 0.0376196\tvalid_1's l2: 0.782406\n",
      "[1400]\ttraining's l2: 0.0328584\tvalid_1's l2: 0.781442\n",
      "[1500]\ttraining's l2: 0.0287291\tvalid_1's l2: 0.780555\n",
      "[1600]\ttraining's l2: 0.0253175\tvalid_1's l2: 0.779658\n",
      "[1700]\ttraining's l2: 0.0225728\tvalid_1's l2: 0.779089\n",
      "[1800]\ttraining's l2: 0.0201767\tvalid_1's l2: 0.778767\n",
      "[1900]\ttraining's l2: 0.0178837\tvalid_1's l2: 0.778015\n",
      "[2000]\ttraining's l2: 0.0158849\tvalid_1's l2: 0.777688\n",
      "[2100]\ttraining's l2: 0.0142714\tvalid_1's l2: 0.77731\n",
      "[2200]\ttraining's l2: 0.0128114\tvalid_1's l2: 0.776986\n",
      "[2300]\ttraining's l2: 0.0114977\tvalid_1's l2: 0.776604\n",
      "[2400]\ttraining's l2: 0.0103578\tvalid_1's l2: 0.776304\n",
      "[2500]\ttraining's l2: 0.00934978\tvalid_1's l2: 0.776093\n",
      "[2600]\ttraining's l2: 0.00849516\tvalid_1's l2: 0.775887\n",
      "[2700]\ttraining's l2: 0.0076665\tvalid_1's l2: 0.775648\n",
      "[2800]\ttraining's l2: 0.00698877\tvalid_1's l2: 0.775463\n",
      "[2900]\ttraining's l2: 0.00633432\tvalid_1's l2: 0.775276\n",
      "[3000]\ttraining's l2: 0.00575073\tvalid_1's l2: 0.77516\n",
      "[3100]\ttraining's l2: 0.00525138\tvalid_1's l2: 0.775039\n",
      "[3200]\ttraining's l2: 0.00478214\tvalid_1's l2: 0.774866\n",
      "Fold 3 started at Mon Oct 25 20:05:19 2021\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.7/site-packages/lightgbm/sklearn.py:726: UserWarning: 'early_stopping_rounds' argument is deprecated and will be removed in a future release of LightGBM. Pass 'early_stopping()' callback via 'callbacks' argument instead.\n",
      "  _log_warning(\"'early_stopping_rounds' argument is deprecated and will be removed in a future release of LightGBM. \"\n",
      "/opt/conda/lib/python3.7/site-packages/lightgbm/sklearn.py:736: UserWarning: 'verbose' argument is deprecated and will be removed in a future release of LightGBM. Pass 'log_evaluation()' callback via 'callbacks' argument instead.\n",
      "  _log_warning(\"'verbose' argument is deprecated and will be removed in a future release of LightGBM. \"\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[LightGBM] [Warning] min_data_in_leaf is set=30, min_child_samples=20 will be ignored. Current value: min_data_in_leaf=30\n",
      "[100]\ttraining's l2: 0.448141\tvalid_1's l2: 0.840021\n",
      "[200]\ttraining's l2: 0.294764\tvalid_1's l2: 0.779376\n",
      "[300]\ttraining's l2: 0.221541\tvalid_1's l2: 0.754467\n",
      "[400]\ttraining's l2: 0.170576\tvalid_1's l2: 0.74312\n",
      "[500]\ttraining's l2: 0.137058\tvalid_1's l2: 0.733197\n",
      "[600]\ttraining's l2: 0.111857\tvalid_1's l2: 0.726538\n",
      "[700]\ttraining's l2: 0.0936519\tvalid_1's l2: 0.722382\n",
      "[800]\ttraining's l2: 0.0782799\tvalid_1's l2: 0.718076\n",
      "[900]\ttraining's l2: 0.0663528\tvalid_1's l2: 0.715012\n",
      "[1000]\ttraining's l2: 0.0568272\tvalid_1's l2: 0.712369\n",
      "[1100]\ttraining's l2: 0.0491651\tvalid_1's l2: 0.710455\n",
      "[1200]\ttraining's l2: 0.0427595\tvalid_1's l2: 0.709106\n",
      "[1300]\ttraining's l2: 0.0375085\tvalid_1's l2: 0.707781\n",
      "[1400]\ttraining's l2: 0.032778\tvalid_1's l2: 0.706769\n",
      "[1500]\ttraining's l2: 0.0289327\tvalid_1's l2: 0.705723\n",
      "[1600]\ttraining's l2: 0.0254183\tvalid_1's l2: 0.705101\n",
      "[1700]\ttraining's l2: 0.0226362\tvalid_1's l2: 0.704381\n",
      "[1800]\ttraining's l2: 0.0202542\tvalid_1's l2: 0.703751\n",
      "[1900]\ttraining's l2: 0.0181355\tvalid_1's l2: 0.703215\n",
      "[2000]\ttraining's l2: 0.0161992\tvalid_1's l2: 0.702714\n",
      "[2100]\ttraining's l2: 0.0144838\tvalid_1's l2: 0.702288\n",
      "[2200]\ttraining's l2: 0.0129836\tvalid_1's l2: 0.701991\n",
      "[2300]\ttraining's l2: 0.0116676\tvalid_1's l2: 0.701647\n",
      "[2400]\ttraining's l2: 0.0105216\tvalid_1's l2: 0.701371\n",
      "[2500]\ttraining's l2: 0.00953561\tvalid_1's l2: 0.701167\n",
      "[2600]\ttraining's l2: 0.00864024\tvalid_1's l2: 0.700868\n",
      "[2700]\ttraining's l2: 0.00779474\tvalid_1's l2: 0.700685\n",
      "[2800]\ttraining's l2: 0.00710296\tvalid_1's l2: 0.700416\n",
      "[2900]\ttraining's l2: 0.0064323\tvalid_1's l2: 0.700171\n",
      "Fold 4 started at Mon Oct 25 20:18:21 2021\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.7/site-packages/lightgbm/sklearn.py:726: UserWarning: 'early_stopping_rounds' argument is deprecated and will be removed in a future release of LightGBM. Pass 'early_stopping()' callback via 'callbacks' argument instead.\n",
      "  _log_warning(\"'early_stopping_rounds' argument is deprecated and will be removed in a future release of LightGBM. \"\n",
      "/opt/conda/lib/python3.7/site-packages/lightgbm/sklearn.py:736: UserWarning: 'verbose' argument is deprecated and will be removed in a future release of LightGBM. Pass 'log_evaluation()' callback via 'callbacks' argument instead.\n",
      "  _log_warning(\"'verbose' argument is deprecated and will be removed in a future release of LightGBM. \"\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[LightGBM] [Warning] min_data_in_leaf is set=30, min_child_samples=20 will be ignored. Current value: min_data_in_leaf=30\n",
      "[100]\ttraining's l2: 0.454276\tvalid_1's l2: 0.907656\n",
      "[200]\ttraining's l2: 0.299849\tvalid_1's l2: 0.847397\n",
      "[300]\ttraining's l2: 0.221371\tvalid_1's l2: 0.821542\n",
      "[400]\ttraining's l2: 0.172192\tvalid_1's l2: 0.806821\n",
      "[500]\ttraining's l2: 0.137519\tvalid_1's l2: 0.796346\n",
      "[600]\ttraining's l2: 0.112921\tvalid_1's l2: 0.790495\n",
      "[700]\ttraining's l2: 0.093165\tvalid_1's l2: 0.785847\n",
      "[800]\ttraining's l2: 0.0777626\tvalid_1's l2: 0.781957\n",
      "[900]\ttraining's l2: 0.0660792\tvalid_1's l2: 0.779212\n",
      "[1000]\ttraining's l2: 0.0566507\tvalid_1's l2: 0.776506\n",
      "[1100]\ttraining's l2: 0.0491616\tvalid_1's l2: 0.774733\n",
      "[1200]\ttraining's l2: 0.0425553\tvalid_1's l2: 0.773417\n",
      "[1300]\ttraining's l2: 0.0371039\tvalid_1's l2: 0.772255\n",
      "[1400]\ttraining's l2: 0.0328029\tvalid_1's l2: 0.771488\n",
      "[1500]\ttraining's l2: 0.0290449\tvalid_1's l2: 0.770474\n",
      "[1600]\ttraining's l2: 0.0256669\tvalid_1's l2: 0.769735\n",
      "[1700]\ttraining's l2: 0.0228232\tvalid_1's l2: 0.769193\n",
      "[1800]\ttraining's l2: 0.0202392\tvalid_1's l2: 0.76846\n",
      "[1900]\ttraining's l2: 0.0179776\tvalid_1's l2: 0.767993\n",
      "[2000]\ttraining's l2: 0.0160138\tvalid_1's l2: 0.767443\n",
      "[2100]\ttraining's l2: 0.0142896\tvalid_1's l2: 0.766819\n",
      "[2200]\ttraining's l2: 0.0129017\tvalid_1's l2: 0.76635\n",
      "CV mean score: 0.5137, std: 0.0050.\n"
     ]
    }
   ],
   "source": [
    "scores = []\n",
    "feature_importance = pd.DataFrame()\n",
    "models = []\n",
    "columns = [col for col in train.columns if col not in ['id', 'breath_id', 'pressure','u_out']]\n",
    "columns = ['time_step', 'u_in', 'area', 'u_in_cumsum', 'time_step_cumsum', \n",
    "           'u_in_1st_derivative', 'expand_mean_1sr_der', 'u_in_1st_der_mean10',\n",
    "           'u_in_lag4', 'u_in_lag-4', 'time_diff', 'power_cumsum', 'u_in_lag2',\n",
    "           'u_in_lag3', 'breath_id__u_in__max', 'C_50', 'RC_2020', 'RC_2050', \n",
    "           'RC_5010', 'RC_510', 'RC_520', 'RC_550', 'last_value_u_in', 'u_in_lag_back1', \n",
    "           'u_in_lag_back2', 'u_in_lag_back3', 'u_in_diff1', 'u_in_diff2', \n",
    "           'breath_id__u_in__diffmean', 'ewm_u_in_mean', 'ewm_u_in_std', 'ewm_u_in_corr', \n",
    "           'delta_u_in', 'delta_rolling_10_mean', 'delta_rolling_10_max', 'work',\n",
    "           'work_roll_10', 'work_roll_15', 'u_in_rol_q0.1', 'u_in_rol_q0.25', \n",
    "           'u_in_rol_q0.5', 'u_in_rol_q0.75', 'u_in_rol_q0.9', 'R_5', 'RC_5050', \n",
    "           'breath_id__u_in__diffmax']\n",
    "X = train[columns]\n",
    "y = train['pressure']\n",
    "params = {'objective': 'regression',\n",
    "          'learning_rate': 0.2, #0.35,\n",
    "          \"boosting_type\": \"gbdt\",\n",
    "          'min_data_in_leaf':30,\n",
    "          'max_bin': 119, #600,\n",
    "#           'max_bin': 700, #600,\n",
    "          'num_leaves':1200,\n",
    "          \"metric\": 'mse', #'mae',\n",
    "          'n_jobs': -1,\n",
    "          'device': 'gpu',\n",
    "          'gpu_platform_id': 0,\n",
    "          'gpu_device_id': 0\n",
    "         }\n",
    "folds = GroupKFold(n_splits=5)\n",
    "for fold_n, (train_index, valid_index) in enumerate(folds.split(train, y, groups=train['breath_id'])):\n",
    "    print(f'Fold {fold_n} started at {time.ctime()}')\n",
    "    X_train, X_valid = X[columns].iloc[train_index], X[columns].iloc[valid_index]\n",
    "    y_train, y_valid = y.iloc[train_index], y.iloc[valid_index]\n",
    "    model = lgb.LGBMRegressor(**params, n_estimators=6000)\n",
    "    model.fit(X_train, y_train, \n",
    "            eval_set=[(X_train, y_train), (X_valid, y_valid)],\n",
    "            verbose=100, early_stopping_rounds=25)\n",
    "    score = metrics.mean_absolute_error(y_valid, model.predict(X_valid))\n",
    "    \n",
    "    models.append(model)\n",
    "    scores.append(score)\n",
    "\n",
    "    #fold_importance = pd.DataFrame()\n",
    "    #fold_importance[\"feature\"] = columns\n",
    "    #fold_importance[\"importance\"] = model.feature_importances_\n",
    "    #fold_importance[\"fold\"] = fold_n + 1\n",
    "    #feature_importance = pd.concat([feature_importance, fold_importance], axis=0)\n",
    "    \n",
    "print('CV mean score: {0:.4f}, std: {1:.4f}.'.format(np.mean(scores), np.std(scores)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "1b0873a1",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-10-25T20:28:23.762035Z",
     "iopub.status.busy": "2021-10-25T20:28:23.760615Z",
     "iopub.status.idle": "2021-10-25T20:44:31.678672Z",
     "shell.execute_reply": "2021-10-25T20:44:31.679349Z"
    },
    "papermill": {
     "duration": 968.469948,
     "end_time": "2021-10-25T20:44:31.679661",
     "exception": true,
     "start_time": "2021-10-25T20:28:23.209713",
     "status": "failed"
    },
    "tags": []
   },
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "operands could not be broadcast together with shapes (6036000,) (2290968,) ",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32m/tmp/ipykernel_26/3040226262.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      2\u001b[0m     \u001b[0msubmission\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'pressure'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m+=\u001b[0m \u001b[0mmodel\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpredict\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtest\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mcolumns\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[1;32m      3\u001b[0m \u001b[0;31m#     model.save_model(f'./LGBM_model_{num+1}.txt')\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 4\u001b[0;31m     \u001b[0mtrain_preds\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'pressure_preds'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m+=\u001b[0m \u001b[0mmodel\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpredict\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtrain\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mcolumns\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      5\u001b[0m \u001b[0msubmission\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'pressure'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m/=\u001b[0m \u001b[0;36m5\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      6\u001b[0m \u001b[0msubmission\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mto_csv\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'submission.csv'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mindex\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/pandas/core/generic.py\u001b[0m in \u001b[0;36m__iadd__\u001b[0;34m(self, other)\u001b[0m\n\u001b[1;32m  11329\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m  11330\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m__iadd__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mother\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> 11331\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_inplace_method\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mother\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtype\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__add__\u001b[0m\u001b[0;34m)\u001b[0m  \u001b[0;31m# type: ignore[operator]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m  11332\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m  11333\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m__isub__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mother\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/opt/conda/lib/python3.7/site-packages/pandas/core/generic.py\u001b[0m in \u001b[0;36m_inplace_method\u001b[0;34m(self, other, op)\u001b[0m\n\u001b[1;32m  11307\u001b[0m         \u001b[0mWrap\u001b[0m \u001b[0marithmetic\u001b[0m \u001b[0mmethod\u001b[0m \u001b[0mto\u001b[0m \u001b[0moperate\u001b[0m \u001b[0minplace\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m  11308\u001b[0m         \"\"\"\n\u001b[0;32m> 11309\u001b[0;31m         \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mop\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mother\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  11310\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m  11311\u001b[0m         if (\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/pandas/core/ops/common.py\u001b[0m in \u001b[0;36mnew_method\u001b[0;34m(self, other)\u001b[0m\n\u001b[1;32m     63\u001b[0m         \u001b[0mother\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mitem_from_zerodim\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mother\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     64\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 65\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mmethod\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mother\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     66\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     67\u001b[0m     \u001b[0;32mreturn\u001b[0m \u001b[0mnew_method\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/pandas/core/arraylike.py\u001b[0m in \u001b[0;36m__add__\u001b[0;34m(self, other)\u001b[0m\n\u001b[1;32m     87\u001b[0m     \u001b[0;34m@\u001b[0m\u001b[0munpack_zerodim_and_defer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"__add__\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     88\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m__add__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mother\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---> 89\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_arith_method\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mother\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0moperator\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0madd\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     90\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     91\u001b[0m     \u001b[0;34m@\u001b[0m\u001b[0munpack_zerodim_and_defer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"__radd__\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/pandas/core/series.py\u001b[0m in \u001b[0;36m_arith_method\u001b[0;34m(self, other, op)\u001b[0m\n\u001b[1;32m   4996\u001b[0m         \u001b[0mlvalues\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mextract_array\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mextract_numpy\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   4997\u001b[0m         \u001b[0mrvalues\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mextract_array\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mother\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mextract_numpy\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 4998\u001b[0;31m         \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mops\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marithmetic_op\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlvalues\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrvalues\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mop\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   4999\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   5000\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_construct_result\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mresult\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mres_name\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/pandas/core/ops/array_ops.py\u001b[0m in \u001b[0;36marithmetic_op\u001b[0;34m(left, right, op)\u001b[0m\n\u001b[1;32m    187\u001b[0m     \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    188\u001b[0m         \u001b[0;32mwith\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0merrstate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mall\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"ignore\"\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--> 189\u001b[0;31m             \u001b[0mres_values\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_na_arithmetic_op\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlvalues\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrvalues\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mop\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    190\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    191\u001b[0m     \u001b[0;32mreturn\u001b[0m \u001b[0mres_values\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/pandas/core/ops/array_ops.py\u001b[0m in \u001b[0;36m_na_arithmetic_op\u001b[0;34m(left, right, op, is_cmp)\u001b[0m\n\u001b[1;32m    140\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    141\u001b[0m     \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 142\u001b[0;31m         \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mexpressions\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mevaluate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mop\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mleft\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mright\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    143\u001b[0m     \u001b[0;32mexcept\u001b[0m \u001b[0mTypeError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    144\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mis_cmp\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/pandas/core/computation/expressions.py\u001b[0m in \u001b[0;36mevaluate\u001b[0;34m(op, a, b, use_numexpr)\u001b[0m\n\u001b[1;32m    233\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0muse_numexpr\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    234\u001b[0m             \u001b[0;31m# error: \"None\" not callable\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 235\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0m_evaluate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mop\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mop_str\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0ma\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mb\u001b[0m\u001b[0;34m)\u001b[0m  \u001b[0;31m# type: ignore[misc]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    236\u001b[0m     \u001b[0;32mreturn\u001b[0m \u001b[0m_evaluate_standard\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mop\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mop_str\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0ma\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mb\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    237\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/pandas/core/computation/expressions.py\u001b[0m in \u001b[0;36m_evaluate_standard\u001b[0;34m(op, op_str, a, b)\u001b[0m\n\u001b[1;32m     67\u001b[0m         \u001b[0m_store_test_result\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     68\u001b[0m     \u001b[0;32mwith\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0merrstate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mall\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"ignore\"\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---> 69\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mop\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ma\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mb\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     70\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     71\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mValueError\u001b[0m: operands could not be broadcast together with shapes (6036000,) (2290968,) "
     ]
    }
   ],
   "source": [
    "for num, model in enumerate(models):\n",
    "    submission['pressure'] += model.predict(test[columns])\n",
    "#     model.save_model(f'./LGBM_model_{num+1}.txt')\n",
    "    train_preds['pressure_preds'] += model.predict(train[columns])\n",
    "submission['pressure'] /= 5\n",
    "submission.to_csv('submission.csv', index=False)\n",
    "train_preds['pressure_preds'] /= 5 \n",
    "train_preds.to_csv('train_preds.csv',index=False)\n",
    "\n",
    "\n",
    "# # ENSEMBLE FOLDS WITH MEDIAN\n",
    "# #取中位数\n",
    "# submission[\"pressure\"] = np.median(np.vstack(test_preds),axis=0)\n",
    "# submission.to_csv('submission_median.csv', index=False)\n",
    "\n",
    "\n",
    "# # ENSEMBLE FOLDS WITH MEDIAN AND ROUND PREDICTIONS\n",
    "# submission[\"pressure\"] =\\\n",
    "#     np.round( (submission.pressure - pressure_min)/pressure_step ) * pressure_step + pressure_min\n",
    "# submission.pressure = np.clip(submission.pressure, pressure_min, pressure_max)\n",
    "# submission.to_csv('submission_median_round.csv', index=False)"
   ]
  }
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