samHawp.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "authorship_tag": "ABX9TyOnWNuznPyx5kr/Uu5Snxv0",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/kujiwa/testIncolab/blob/main/samHawp.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "samHawp"
      ],
      "metadata": {
        "id": "rvo1KndIwvED"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!git clone https://github.com/kujiwa/testIncolab.git"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "KEEMVIgEwzOY",
        "outputId": "ffa7fe68-8c26-4343-a35c-f064d4884c22"
      },
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Cloning into 'testIncolab'...\n",
            "remote: Enumerating objects: 108, done.\u001b[K\n",
            "remote: Counting objects: 100% (8/8), done.\u001b[K\n",
            "remote: Compressing objects: 100% (8/8), done.\u001b[K\n",
            "remote: Total 108 (delta 3), reused 0 (delta 0), pack-reused 100\u001b[K\n",
            "Receiving objects: 100% (108/108), 55.34 KiB | 4.61 MiB/s, done.\n",
            "Resolving deltas: 100% (37/37), done.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!apt install ninja-build"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "r9n9qCGBUo_d",
        "outputId": "41d8a5d3-904f-4d57-ceac-eb0d57d3c171"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Reading package lists... Done\n",
            "Building dependency tree... Done\n",
            "Reading state information... Done\n",
            "The following NEW packages will be installed:\n",
            "  ninja-build\n",
            "0 upgraded, 1 newly installed, 0 to remove and 18 not upgraded.\n",
            "Need to get 111 kB of archives.\n",
            "After this operation, 358 kB of additional disk space will be used.\n",
            "Get:1 http://archive.ubuntu.com/ubuntu jammy/universe amd64 ninja-build amd64 1.10.1-1 [111 kB]\n",
            "Fetched 111 kB in 0s (1,329 kB/s)\n",
            "Selecting previously unselected package ninja-build.\n",
            "(Reading database ... 120876 files and directories currently installed.)\n",
            "Preparing to unpack .../ninja-build_1.10.1-1_amd64.deb ...\n",
            "Unpacking ninja-build (1.10.1-1) ...\n",
            "Setting up ninja-build (1.10.1-1) ...\n",
            "Processing triggers for man-db (2.10.2-1) ...\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import sys\n",
        "sys.path.append('./testIncolab/amp_extensions/afm')\n",
        "import torch\n",
        "import numpy as np\n",
        "from torch.utils.data.dataloader import default_collate\n",
        "from csrc import _C\n",
        "\n",
        "height=16\n",
        "width =16\n",
        "import torch\n",
        "\n",
        "device='cuda'\n",
        "lines = torch.Tensor([[0, 0, 1, 1], [1, 4, 2, 3], [4, 4, 8, 7],[9,7,8,3]]).to(device)\n",
        "print(lines)\n",
        "print(_C)\n",
        "lmap, labels, _ = _C.encodels(lines,height,width,height,width,lines.size(0))\n",
        "#print(lmap)\n",
        "#print(labels)\n",
        "print(lmap.size())#(6,height,width)\n",
        "print(labels.size())#(lines_num,height,width)\n",
        "print(labels)\n",
        "#查看特定像素点(13,13)的label\n",
        "# y_index=13\n",
        "# z_index=13\n",
        "print(labels[:,4,4])#(f,f,t,f)\n",
        "print(labels[:,1,1])#(t,f,f,f)\n",
        "print(labels[:,4,5])#(f,f,t,f)\n",
        "print(labels[:,8,8])#(f,f,f,f)\n",
        "print(labels[:,10,9])#(f,f,f,f)\n",
        "print(labels[:,15,5])#(f,f,f,f)\n",
        "\n",
        "\n",
        "dismap = torch.sqrt(lmap[0]**2+lmap[1]**2)[None]\n",
        "print(dismap.size())\n",
        "print(dismap)\n",
        "print(dismap[0,4,4])\n",
        "print(dismap[0,1,1])\n",
        "print(dismap[0,4,5])\n",
        "print(dismap[0,8,8])\n",
        "print(dismap[0,10,9])\n",
        "print(dismap[0,15,5])\n",
        "#距离像素点1之外的都是false？\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "BV8qDtjsWkVB",
        "outputId": "cb53316b-dac8-45b0-b184-bc056be47252"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "tensor([[0., 0., 1., 1.],\n",
            "        [1., 4., 2., 3.],\n",
            "        [4., 4., 8., 7.],\n",
            "        [9., 7., 8., 3.]], device='cuda:0')\n",
            "<module '_C' from '/root/.cache/torch_extensions/py310_cu118/_C/_C.so'>\n",
            "torch.Size([6, 16, 16])\n",
            "torch.Size([4, 16, 16])\n",
            "tensor([[[ True,  True,  True,  ..., False, False, False],\n",
            "         [ True,  True, False,  ..., False, False, False],\n",
            "         [ True, False, False,  ..., False, False, False],\n",
            "         ...,\n",
            "         [False, False, False,  ..., False, False, False],\n",
            "         [False, False, False,  ..., False, False, False],\n",
            "         [False, False, False,  ..., False, False, False]],\n",
            "\n",
            "        [[False, False, False,  ..., False, False, False],\n",
            "         [False, False, False,  ..., False, False, False],\n",
            "         [False, False, False,  ..., False, False, False],\n",
            "         ...,\n",
            "         [False, False, False,  ..., False, False, False],\n",
            "         [False, False, False,  ..., False, False, False],\n",
            "         [False, False, False,  ..., False, False, False]],\n",
            "\n",
            "        [[False, False, False,  ..., False, False, False],\n",
            "         [False, False, False,  ..., False, False, False],\n",
            "         [False, False, False,  ..., False, False, False],\n",
            "         ...,\n",
            "         [False, False,  True,  ..., False, False, False],\n",
            "         [False,  True,  True,  ..., False, False, False],\n",
            "         [False,  True,  True,  ..., False, False, False]],\n",
            "\n",
            "        [[False, False, False,  ..., False, False, False],\n",
            "         [False, False, False,  ..., False, False, False],\n",
            "         [False, False, False,  ...,  True,  True,  True],\n",
            "         ...,\n",
            "         [False, False, False,  ..., False, False, False],\n",
            "         [False, False, False,  ..., False, False, False],\n",
            "         [False, False, False,  ..., False, False, False]]], device='cuda:0')\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "tensor([ True, False, False, False], device='cuda:0')\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "torch.Size([1, 16, 16])\n",
            "tensor([[[0.0000e+00, 7.0711e-01, 1.4142e+00, 2.2361e+00, 3.1623e+00,\n",
            "          4.1231e+00, 3.6056e+00, 3.1623e+00, 3.0000e+00, 3.1623e+00,\n",
            "          3.6056e+00, 4.2426e+00, 5.0000e+00, 5.8310e+00, 6.7082e+00,\n",
            "          7.6158e+00],\n",
            "         [7.0711e-01, 6.7435e-07, 1.0000e+00, 2.0000e+00, 2.8284e+00,\n",
            "          3.1623e+00, 2.8284e+00, 2.2361e+00, 2.0000e+00, 2.2361e+00,\n",
            "          2.8284e+00, 3.6056e+00, 4.4721e+00, 5.3852e+00, 6.3246e+00,\n",
            "          7.2801e+00],\n",
            "         [1.4142e+00, 1.0000e+00, 1.0000e+00, 1.4142e+00, 2.0000e+00,\n",
            "          2.2361e+00, 2.2361e+00, 1.4142e+00, 1.0000e+00, 1.4142e+00,\n",
            "          2.2361e+00, 3.1623e+00, 4.1231e+00, 5.0932e+00, 6.0634e+00,\n",
            "          7.0335e+00],\n",
            "         [1.4142e+00, 7.0711e-01, 6.7435e-07, 1.0000e+00, 1.0000e+00,\n",
            "          1.4000e+00, 2.0000e+00, 1.0000e+00, 2.3842e-07, 9.7014e-01,\n",
            "          1.9403e+00, 2.9104e+00, 3.8806e+00, 4.8507e+00, 5.8209e+00,\n",
            "          6.7910e+00],\n",
            "         [1.0000e+00, 0.0000e+00, 7.0711e-01, 1.0000e+00, 0.0000e+00,\n",
            "          6.0000e-01, 1.2000e+00, 1.2127e+00, 2.4254e-01, 7.2761e-01,\n",
            "          1.6977e+00, 2.6679e+00, 3.6380e+00, 4.6082e+00, 5.5783e+00,\n",
            "          6.5485e+00],\n",
            "         [1.4142e+00, 1.0000e+00, 1.4142e+00, 1.4142e+00, 8.0000e-01,\n",
            "          2.0000e-01, 4.0000e-01, 1.0000e+00, 4.8507e-01, 4.8507e-01,\n",
            "          1.4552e+00, 2.4254e+00, 3.3955e+00, 4.3656e+00, 5.3358e+00,\n",
            "          6.3059e+00],\n",
            "         [2.2361e+00, 2.0000e+00, 2.2361e+00, 2.2000e+00, 1.6000e+00,\n",
            "          1.0000e+00, 4.0000e-01, 2.0000e-01, 7.2761e-01, 2.4254e-01,\n",
            "          1.2127e+00, 2.1828e+00, 3.1530e+00, 4.1231e+00, 5.0990e+00,\n",
            "          6.0828e+00],\n",
            "         [3.1623e+00, 3.0000e+00, 3.1623e+00, 3.0000e+00, 2.4000e+00,\n",
            "          1.8000e+00, 1.2000e+00, 6.0000e-01, 0.0000e+00, 0.0000e+00,\n",
            "          1.0000e+00, 2.0000e+00, 3.0000e+00, 4.0000e+00, 5.0000e+00,\n",
            "          6.0000e+00],\n",
            "         [4.1231e+00, 4.0000e+00, 4.1231e+00, 3.8000e+00, 3.2000e+00,\n",
            "          2.6000e+00, 2.0000e+00, 1.4000e+00, 1.0000e+00, 1.0000e+00,\n",
            "          1.4142e+00, 2.2361e+00, 3.1623e+00, 4.1231e+00, 5.0990e+00,\n",
            "          6.0828e+00],\n",
            "         [5.0990e+00, 5.0000e+00, 5.0990e+00, 4.6000e+00, 4.0000e+00,\n",
            "          3.4000e+00, 2.8000e+00, 2.2361e+00, 2.0000e+00, 2.0000e+00,\n",
            "          2.2361e+00, 2.8284e+00, 3.6056e+00, 4.4721e+00, 5.3852e+00,\n",
            "          6.3246e+00],\n",
            "         [6.0828e+00, 6.0000e+00, 6.0000e+00, 5.4000e+00, 4.8000e+00,\n",
            "          4.2000e+00, 3.6056e+00, 3.1623e+00, 3.0000e+00, 3.0000e+00,\n",
            "          3.1623e+00, 3.6056e+00, 4.2426e+00, 5.0000e+00, 5.8310e+00,\n",
            "          6.7082e+00],\n",
            "         [7.0711e+00, 7.0000e+00, 6.8000e+00, 6.2000e+00, 5.6000e+00,\n",
            "          5.0000e+00, 4.4721e+00, 4.1231e+00, 4.0000e+00, 4.0000e+00,\n",
            "          4.1231e+00, 4.4721e+00, 5.0000e+00, 5.6569e+00, 6.4031e+00,\n",
            "          7.2111e+00],\n",
            "         [8.0623e+00, 8.0000e+00, 7.6000e+00, 7.0000e+00, 6.4000e+00,\n",
            "          5.8310e+00, 5.3852e+00, 5.0990e+00, 5.0000e+00, 5.0000e+00,\n",
            "          5.0990e+00, 5.3852e+00, 5.8310e+00, 6.4031e+00, 7.0711e+00,\n",
            "          7.8102e+00],\n",
            "         [9.0554e+00, 9.0000e+00, 8.4000e+00, 7.8000e+00, 7.2111e+00,\n",
            "          6.7082e+00, 6.3246e+00, 6.0828e+00, 6.0000e+00, 6.0000e+00,\n",
            "          6.0828e+00, 6.3246e+00, 6.7082e+00, 7.2111e+00, 7.8102e+00,\n",
            "          8.4853e+00],\n",
            "         [1.0050e+01, 9.8000e+00, 9.2000e+00, 8.6023e+00, 8.0623e+00,\n",
            "          7.6158e+00, 7.2801e+00, 7.0711e+00, 7.0000e+00, 7.0000e+00,\n",
            "          7.0711e+00, 7.2801e+00, 7.6158e+00, 8.0623e+00, 8.6023e+00,\n",
            "          9.2195e+00],\n",
            "         [1.1045e+01, 1.0600e+01, 1.0000e+01, 9.4340e+00, 8.9443e+00,\n",
            "          8.5440e+00, 8.2462e+00, 8.0623e+00, 8.0000e+00, 8.0000e+00,\n",
            "          8.0623e+00, 8.2462e+00, 8.5440e+00, 8.9443e+00, 9.4340e+00,\n",
            "          1.0000e+01]]], device='cuda:0')\n",
            "tensor(0., device='cuda:0')\n",
            "tensor(6.7435e-07, device='cuda:0')\n",
            "tensor(0.6000, device='cuda:0')\n",
            "tensor(1., device='cuda:0')\n",
            "tensor(3., device='cuda:0')\n",
            "tensor(8.5440, device='cuda:0')\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import torch\n",
        "\n",
        "if torch.cuda.is_available():\n",
        "    print(\"CUDA is available!\")\n",
        "else:\n",
        "    print(\"CUDA is not available.\")\n",
        "\n",
        "print(torch.version.cuda)"
      ],
      "metadata": {
        "id": "R2Dc-SQOqdSQ",
        "outputId": "b79c024d-dd2e-4b66-b31f-d95d5b107a62",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "CUDA is available!\n",
            "11.8\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#把linesegment.cu里的1都改成3 看看t和f\n",
        "#最后三个点的t和f不同，且距离计算也不同\n",
        "#1好像是为了判断投影点在不在线上 而不是点到线段距离之类的\n",
        "\n",
        "#如果有一个点投影在线上，但是距线很远，会不会是true\n",
        "#测试方法 找到距离中所有>1的，看看是不是全部为ffff\n",
        "#把linesegment.cu里的1都改成3 看看t和f\n",
        "#最后三个点的t和f不同，且距离计算也不同\n",
        "#1好像是为了判断投影点在不在线上\n",
        "import sys\n",
        "sys.path.append('./testIncolab/amp_extensions/afm')\n",
        "import torch\n",
        "import numpy as np\n",
        "from torch.utils.data.dataloader import default_collate\n",
        "from csrc import _C\n",
        "\n",
        "height=16\n",
        "width =16\n",
        "import torch\n",
        "\n",
        "device='cuda'\n",
        "lines = torch.Tensor([[0, 0, 1, 1], [1, 4, 2, 3], [4, 4, 8, 7],[9,7,8,3]]).to(device)\n",
        "print(lines)\n",
        "print(_C)\n",
        "lmap, labels, _ = _C.encodels(lines,height,width,height,width,lines.size(0))\n",
        "#print(lmap)\n",
        "#print(labels)\n",
        "print(lmap.size())#(6,height,width)\n",
        "print(labels.size())#(lines_num,height,width)\n",
        "print(labels)\n",
        "#查看特定像素点(13,13)的label\n",
        "# y_index=13\n",
        "# z_index=13\n",
        "print(labels[:,4,4])#(f,f,t,f)\n",
        "print(labels[:,1,1])#(t,f,f,f)\n",
        "print(labels[:,4,5])#(f,f,t,f)\n",
        "print(labels[:,8,8])#(f,f,f,f)\n",
        "print(labels[:,10,9])#(f,f,f,f)\n",
        "print(labels[:,15,5])#(f,f,f,f)\n",
        "\n",
        "\n",
        "dismap = torch.sqrt(lmap[0]**2+lmap[1]**2)[None]\n",
        "print(dismap.size())\n",
        "print(dismap)\n",
        "print(dismap[0,4,4])\n",
        "print(dismap[0,1,1])\n",
        "print(dismap[0,4,5])\n",
        "print(dismap[0,8,8])\n",
        "print(dismap[0,10,9])\n",
        "print(dismap[0,15,5])\n",
        "#距离像素点1之外的都是false\n",
        "for i in range(dismap.size(1)):\n",
        "    for j in range(dismap.size(2)):\n",
        "        if dismap[0, i, j] > 1:\n",
        "            print(\"dis:\",dismap[0, i, j])\n",
        "            print(\"i\",i,\"j\",j)\n",
        "            print(labels[:,i,j])\n",
        "            # do something\n",
        "#dismap 是距离 label是标签 如果全为f 说明无法投影到任何一条线段上（写得tql😭\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "V5wKvTH-Zndt",
        "outputId": "ef77469e-e28d-4d05-cebf-79824b5c904d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "tensor([[0., 0., 1., 1.],\n",
            "        [1., 4., 2., 3.],\n",
            "        [4., 4., 8., 7.],\n",
            "        [9., 7., 8., 3.]], device='cuda:0')\n",
            "<module '_C' from '/root/.cache/torch_extensions/py310_cu118/_C/_C.so'>\n",
            "torch.Size([6, 16, 16])\n",
            "torch.Size([4, 16, 16])\n",
            "tensor([[[ True,  True,  True,  ..., False, False, False],\n",
            "         [ True,  True, False,  ..., False, False, False],\n",
            "         [ True, False, False,  ..., False, False, False],\n",
            "         ...,\n",
            "         [False, False, False,  ..., False, False, False],\n",
            "         [False, False, False,  ..., False, False, False],\n",
            "         [False, False, False,  ..., False, False, False]],\n",
            "\n",
            "        [[False, False, False,  ..., False, False, False],\n",
            "         [False, False, False,  ..., False, False, False],\n",
            "         [False, False, False,  ..., False, False, False],\n",
            "         ...,\n",
            "         [False, False, False,  ..., False, False, False],\n",
            "         [False, False, False,  ..., False, False, False],\n",
            "         [False, False, False,  ..., False, False, False]],\n",
            "\n",
            "        [[False, False, False,  ..., False, False, False],\n",
            "         [False, False, False,  ..., False, False, False],\n",
            "         [False, False, False,  ..., False, False, False],\n",
            "         ...,\n",
            "         [False, False,  True,  ..., False, False, False],\n",
            "         [False,  True,  True,  ..., False, False, False],\n",
            "         [False,  True,  True,  ..., False, False, False]],\n",
            "\n",
            "        [[False, False, False,  ..., False, False, False],\n",
            "         [False, False, False,  ..., False, False, False],\n",
            "         [False, False, False,  ...,  True,  True,  True],\n",
            "         ...,\n",
            "         [False, False, False,  ..., False, False, False],\n",
            "         [False, False, False,  ..., False, False, False],\n",
            "         [False, False, False,  ..., False, False, False]]], device='cuda:0')\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "tensor([ True, False, False, False], device='cuda:0')\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "torch.Size([1, 16, 16])\n",
            "tensor([[[0.0000e+00, 7.0711e-01, 1.4142e+00, 2.2361e+00, 3.1623e+00,\n",
            "          4.1231e+00, 3.6056e+00, 3.1623e+00, 3.0000e+00, 3.1623e+00,\n",
            "          3.6056e+00, 4.2426e+00, 5.0000e+00, 5.8310e+00, 6.7082e+00,\n",
            "          7.6158e+00],\n",
            "         [7.0711e-01, 6.7435e-07, 1.0000e+00, 2.0000e+00, 2.8284e+00,\n",
            "          3.1623e+00, 2.8284e+00, 2.2361e+00, 2.0000e+00, 2.2361e+00,\n",
            "          2.8284e+00, 3.6056e+00, 4.4721e+00, 5.3852e+00, 6.3246e+00,\n",
            "          7.2801e+00],\n",
            "         [1.4142e+00, 1.0000e+00, 1.0000e+00, 1.4142e+00, 2.0000e+00,\n",
            "          2.2361e+00, 2.2361e+00, 1.4142e+00, 1.0000e+00, 1.4142e+00,\n",
            "          2.2361e+00, 3.1623e+00, 4.1231e+00, 5.0932e+00, 6.0634e+00,\n",
            "          7.0335e+00],\n",
            "         [1.4142e+00, 7.0711e-01, 6.7435e-07, 1.0000e+00, 1.0000e+00,\n",
            "          1.4000e+00, 2.0000e+00, 1.0000e+00, 2.3842e-07, 9.7014e-01,\n",
            "          1.9403e+00, 2.9104e+00, 3.8806e+00, 4.8507e+00, 5.8209e+00,\n",
            "          6.7910e+00],\n",
            "         [1.0000e+00, 0.0000e+00, 7.0711e-01, 1.0000e+00, 0.0000e+00,\n",
            "          6.0000e-01, 1.2000e+00, 1.2127e+00, 2.4254e-01, 7.2761e-01,\n",
            "          1.6977e+00, 2.6679e+00, 3.6380e+00, 4.6082e+00, 5.5783e+00,\n",
            "          6.5485e+00],\n",
            "         [1.4142e+00, 1.0000e+00, 1.4142e+00, 1.4142e+00, 8.0000e-01,\n",
            "          2.0000e-01, 4.0000e-01, 1.0000e+00, 4.8507e-01, 4.8507e-01,\n",
            "          1.4552e+00, 2.4254e+00, 3.3955e+00, 4.3656e+00, 5.3358e+00,\n",
            "          6.3059e+00],\n",
            "         [2.2361e+00, 2.0000e+00, 2.2361e+00, 2.2000e+00, 1.6000e+00,\n",
            "          1.0000e+00, 4.0000e-01, 2.0000e-01, 7.2761e-01, 2.4254e-01,\n",
            "          1.2127e+00, 2.1828e+00, 3.1530e+00, 4.1231e+00, 5.0990e+00,\n",
            "          6.0828e+00],\n",
            "         [3.1623e+00, 3.0000e+00, 3.1623e+00, 3.0000e+00, 2.4000e+00,\n",
            "          1.8000e+00, 1.2000e+00, 6.0000e-01, 0.0000e+00, 0.0000e+00,\n",
            "          1.0000e+00, 2.0000e+00, 3.0000e+00, 4.0000e+00, 5.0000e+00,\n",
            "          6.0000e+00],\n",
            "         [4.1231e+00, 4.0000e+00, 4.1231e+00, 3.8000e+00, 3.2000e+00,\n",
            "          2.6000e+00, 2.0000e+00, 1.4000e+00, 1.0000e+00, 1.0000e+00,\n",
            "          1.4142e+00, 2.2361e+00, 3.1623e+00, 4.1231e+00, 5.0990e+00,\n",
            "          6.0828e+00],\n",
            "         [5.0990e+00, 5.0000e+00, 5.0990e+00, 4.6000e+00, 4.0000e+00,\n",
            "          3.4000e+00, 2.8000e+00, 2.2361e+00, 2.0000e+00, 2.0000e+00,\n",
            "          2.2361e+00, 2.8284e+00, 3.6056e+00, 4.4721e+00, 5.3852e+00,\n",
            "          6.3246e+00],\n",
            "         [6.0828e+00, 6.0000e+00, 6.0000e+00, 5.4000e+00, 4.8000e+00,\n",
            "          4.2000e+00, 3.6056e+00, 3.1623e+00, 3.0000e+00, 3.0000e+00,\n",
            "          3.1623e+00, 3.6056e+00, 4.2426e+00, 5.0000e+00, 5.8310e+00,\n",
            "          6.7082e+00],\n",
            "         [7.0711e+00, 7.0000e+00, 6.8000e+00, 6.2000e+00, 5.6000e+00,\n",
            "          5.0000e+00, 4.4721e+00, 4.1231e+00, 4.0000e+00, 4.0000e+00,\n",
            "          4.1231e+00, 4.4721e+00, 5.0000e+00, 5.6569e+00, 6.4031e+00,\n",
            "          7.2111e+00],\n",
            "         [8.0623e+00, 8.0000e+00, 7.6000e+00, 7.0000e+00, 6.4000e+00,\n",
            "          5.8310e+00, 5.3852e+00, 5.0990e+00, 5.0000e+00, 5.0000e+00,\n",
            "          5.0990e+00, 5.3852e+00, 5.8310e+00, 6.4031e+00, 7.0711e+00,\n",
            "          7.8102e+00],\n",
            "         [9.0554e+00, 9.0000e+00, 8.4000e+00, 7.8000e+00, 7.2111e+00,\n",
            "          6.7082e+00, 6.3246e+00, 6.0828e+00, 6.0000e+00, 6.0000e+00,\n",
            "          6.0828e+00, 6.3246e+00, 6.7082e+00, 7.2111e+00, 7.8102e+00,\n",
            "          8.4853e+00],\n",
            "         [1.0050e+01, 9.8000e+00, 9.2000e+00, 8.6023e+00, 8.0623e+00,\n",
            "          7.6158e+00, 7.2801e+00, 7.0711e+00, 7.0000e+00, 7.0000e+00,\n",
            "          7.0711e+00, 7.2801e+00, 7.6158e+00, 8.0623e+00, 8.6023e+00,\n",
            "          9.2195e+00],\n",
            "         [1.1045e+01, 1.0600e+01, 1.0000e+01, 9.4340e+00, 8.9443e+00,\n",
            "          8.5440e+00, 8.2462e+00, 8.0623e+00, 8.0000e+00, 8.0000e+00,\n",
            "          8.0623e+00, 8.2462e+00, 8.5440e+00, 8.9443e+00, 9.4340e+00,\n",
            "          1.0000e+01]]], device='cuda:0')\n",
            "tensor(0., device='cuda:0')\n",
            "tensor(6.7435e-07, device='cuda:0')\n",
            "tensor(0.6000, device='cuda:0')\n",
            "tensor(1., device='cuda:0')\n",
            "tensor(3., device='cuda:0')\n",
            "tensor(8.5440, device='cuda:0')\n",
            "dis: tensor(1.4142, device='cuda:0')\n",
            "i 0 j 2\n",
            "tensor([ True, False, False, False], device='cuda:0')\n",
            "dis: tensor(2.2361, device='cuda:0')\n",
            "i 0 j 3\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(3.1623, device='cuda:0')\n",
            "i 0 j 4\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(4.1231, device='cuda:0')\n",
            "i 0 j 5\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(3.6056, device='cuda:0')\n",
            "i 0 j 6\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(3.1623, device='cuda:0')\n",
            "i 0 j 7\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(3., device='cuda:0')\n",
            "i 0 j 8\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(3.1623, device='cuda:0')\n",
            "i 0 j 9\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(3.6056, device='cuda:0')\n",
            "i 0 j 10\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(4.2426, device='cuda:0')\n",
            "i 0 j 11\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(5., device='cuda:0')\n",
            "i 0 j 12\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(5.8310, device='cuda:0')\n",
            "i 0 j 13\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(6.7082, device='cuda:0')\n",
            "i 0 j 14\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(7.6158, device='cuda:0')\n",
            "i 0 j 15\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(2., device='cuda:0')\n",
            "i 1 j 3\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(2.8284, device='cuda:0')\n",
            "i 1 j 4\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(3.1623, device='cuda:0')\n",
            "i 1 j 5\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(2.8284, device='cuda:0')\n",
            "i 1 j 6\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(2.2361, device='cuda:0')\n",
            "i 1 j 7\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(2., device='cuda:0')\n",
            "i 1 j 8\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(2.2361, device='cuda:0')\n",
            "i 1 j 9\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(2.8284, device='cuda:0')\n",
            "i 1 j 10\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(3.6056, device='cuda:0')\n",
            "i 1 j 11\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(4.4721, device='cuda:0')\n",
            "i 1 j 12\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(5.3852, device='cuda:0')\n",
            "i 1 j 13\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(6.3246, device='cuda:0')\n",
            "i 1 j 14\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(7.2801, device='cuda:0')\n",
            "i 1 j 15\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(1.4142, device='cuda:0')\n",
            "i 2 j 0\n",
            "tensor([ True, False, False, False], device='cuda:0')\n",
            "dis: tensor(1.4142, device='cuda:0')\n",
            "i 2 j 3\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(2., device='cuda:0')\n",
            "i 2 j 4\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(2.2361, device='cuda:0')\n",
            "i 2 j 5\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(2.2361, device='cuda:0')\n",
            "i 2 j 6\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(1.4142, device='cuda:0')\n",
            "i 2 j 7\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(1.4142, device='cuda:0')\n",
            "i 2 j 9\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(2.2361, device='cuda:0')\n",
            "i 2 j 10\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(3.1623, device='cuda:0')\n",
            "i 2 j 11\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(4.1231, device='cuda:0')\n",
            "i 2 j 12\n",
            "tensor([False, False, False,  True], device='cuda:0')\n",
            "dis: tensor(5.0932, device='cuda:0')\n",
            "i 2 j 13\n",
            "tensor([False, False, False,  True], device='cuda:0')\n",
            "dis: tensor(6.0634, device='cuda:0')\n",
            "i 2 j 14\n",
            "tensor([False, False, False,  True], device='cuda:0')\n",
            "dis: tensor(7.0335, device='cuda:0')\n",
            "i 2 j 15\n",
            "tensor([False, False, False,  True], device='cuda:0')\n",
            "dis: tensor(1.4142, device='cuda:0')\n",
            "i 3 j 0\n",
            "tensor([False,  True, False, False], device='cuda:0')\n",
            "dis: tensor(1.4000, device='cuda:0')\n",
            "i 3 j 5\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(2.0000, device='cuda:0')\n",
            "i 3 j 6\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(1.9403, device='cuda:0')\n",
            "i 3 j 10\n",
            "tensor([False, False, False,  True], device='cuda:0')\n",
            "dis: tensor(2.9104, device='cuda:0')\n",
            "i 3 j 11\n",
            "tensor([False, False, False,  True], device='cuda:0')\n",
            "dis: tensor(3.8806, device='cuda:0')\n",
            "i 3 j 12\n",
            "tensor([False, False, False,  True], device='cuda:0')\n",
            "dis: tensor(4.8507, device='cuda:0')\n",
            "i 3 j 13\n",
            "tensor([False, False, False,  True], device='cuda:0')\n",
            "dis: tensor(5.8209, device='cuda:0')\n",
            "i 3 j 14\n",
            "tensor([False, False, False,  True], device='cuda:0')\n",
            "dis: tensor(6.7910, device='cuda:0')\n",
            "i 3 j 15\n",
            "tensor([False, False, False,  True], device='cuda:0')\n",
            "dis: tensor(1.2000, device='cuda:0')\n",
            "i 4 j 6\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(1.2127, device='cuda:0')\n",
            "i 4 j 7\n",
            "tensor([False, False, False,  True], device='cuda:0')\n",
            "dis: tensor(1.6977, device='cuda:0')\n",
            "i 4 j 10\n",
            "tensor([False, False, False,  True], device='cuda:0')\n",
            "dis: tensor(2.6679, device='cuda:0')\n",
            "i 4 j 11\n",
            "tensor([False, False, False,  True], device='cuda:0')\n",
            "dis: tensor(3.6380, device='cuda:0')\n",
            "i 4 j 12\n",
            "tensor([False, False, False,  True], device='cuda:0')\n",
            "dis: tensor(4.6082, device='cuda:0')\n",
            "i 4 j 13\n",
            "tensor([False, False, False,  True], device='cuda:0')\n",
            "dis: tensor(5.5783, device='cuda:0')\n",
            "i 4 j 14\n",
            "tensor([False, False, False,  True], device='cuda:0')\n",
            "dis: tensor(6.5485, device='cuda:0')\n",
            "i 4 j 15\n",
            "tensor([False, False, False,  True], device='cuda:0')\n",
            "dis: tensor(1.4142, device='cuda:0')\n",
            "i 5 j 0\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(1.4142, device='cuda:0')\n",
            "i 5 j 2\n",
            "tensor([False,  True, False, False], device='cuda:0')\n",
            "dis: tensor(1.4142, device='cuda:0')\n",
            "i 5 j 3\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(1.4552, device='cuda:0')\n",
            "i 5 j 10\n",
            "tensor([False, False, False,  True], device='cuda:0')\n",
            "dis: tensor(2.4254, device='cuda:0')\n",
            "i 5 j 11\n",
            "tensor([False, False, False,  True], device='cuda:0')\n",
            "dis: tensor(3.3955, device='cuda:0')\n",
            "i 5 j 12\n",
            "tensor([False, False, False,  True], device='cuda:0')\n",
            "dis: tensor(4.3656, device='cuda:0')\n",
            "i 5 j 13\n",
            "tensor([False, False, False,  True], device='cuda:0')\n",
            "dis: tensor(5.3358, device='cuda:0')\n",
            "i 5 j 14\n",
            "tensor([False, False, False,  True], device='cuda:0')\n",
            "dis: tensor(6.3059, device='cuda:0')\n",
            "i 5 j 15\n",
            "tensor([False, False, False,  True], device='cuda:0')\n",
            "dis: tensor(2.2361, device='cuda:0')\n",
            "i 6 j 0\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(2., device='cuda:0')\n",
            "i 6 j 1\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(2.2361, device='cuda:0')\n",
            "i 6 j 2\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(2.2000, device='cuda:0')\n",
            "i 6 j 3\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(1.6000, device='cuda:0')\n",
            "i 6 j 4\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(1.0000, device='cuda:0')\n",
            "i 6 j 5\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(1.2127, device='cuda:0')\n",
            "i 6 j 10\n",
            "tensor([False, False, False,  True], device='cuda:0')\n",
            "dis: tensor(2.1828, device='cuda:0')\n",
            "i 6 j 11\n",
            "tensor([False, False, False,  True], device='cuda:0')\n",
            "dis: tensor(3.1530, device='cuda:0')\n",
            "i 6 j 12\n",
            "tensor([False, False, False,  True], device='cuda:0')\n",
            "dis: tensor(4.1231, device='cuda:0')\n",
            "i 6 j 13\n",
            "tensor([False, False, False,  True], device='cuda:0')\n",
            "dis: tensor(5.0990, device='cuda:0')\n",
            "i 6 j 14\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(6.0828, device='cuda:0')\n",
            "i 6 j 15\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(3.1623, device='cuda:0')\n",
            "i 7 j 0\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(3., device='cuda:0')\n",
            "i 7 j 1\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(3.1623, device='cuda:0')\n",
            "i 7 j 2\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(3.0000, device='cuda:0')\n",
            "i 7 j 3\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(2.4000, device='cuda:0')\n",
            "i 7 j 4\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(1.8000, device='cuda:0')\n",
            "i 7 j 5\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(1.2000, device='cuda:0')\n",
            "i 7 j 6\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(2., device='cuda:0')\n",
            "i 7 j 11\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(3., device='cuda:0')\n",
            "i 7 j 12\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(4., device='cuda:0')\n",
            "i 7 j 13\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(5., device='cuda:0')\n",
            "i 7 j 14\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(6., device='cuda:0')\n",
            "i 7 j 15\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(4.1231, device='cuda:0')\n",
            "i 8 j 0\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(4., device='cuda:0')\n",
            "i 8 j 1\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(4.1231, device='cuda:0')\n",
            "i 8 j 2\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(3.8000, device='cuda:0')\n",
            "i 8 j 3\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(3.2000, device='cuda:0')\n",
            "i 8 j 4\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(2.6000, device='cuda:0')\n",
            "i 8 j 5\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(2.0000, device='cuda:0')\n",
            "i 8 j 6\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(1.4000, device='cuda:0')\n",
            "i 8 j 7\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(1.4142, device='cuda:0')\n",
            "i 8 j 10\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(2.2361, device='cuda:0')\n",
            "i 8 j 11\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(3.1623, device='cuda:0')\n",
            "i 8 j 12\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(4.1231, device='cuda:0')\n",
            "i 8 j 13\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(5.0990, device='cuda:0')\n",
            "i 8 j 14\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(6.0828, device='cuda:0')\n",
            "i 8 j 15\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(5.0990, device='cuda:0')\n",
            "i 9 j 0\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(5., device='cuda:0')\n",
            "i 9 j 1\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(5.0990, device='cuda:0')\n",
            "i 9 j 2\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(4.6000, device='cuda:0')\n",
            "i 9 j 3\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(4., device='cuda:0')\n",
            "i 9 j 4\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(3.4000, device='cuda:0')\n",
            "i 9 j 5\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(2.8000, device='cuda:0')\n",
            "i 9 j 6\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(2.2361, device='cuda:0')\n",
            "i 9 j 7\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(2., device='cuda:0')\n",
            "i 9 j 8\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(2., device='cuda:0')\n",
            "i 9 j 9\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(2.2361, device='cuda:0')\n",
            "i 9 j 10\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(2.8284, device='cuda:0')\n",
            "i 9 j 11\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(3.6056, device='cuda:0')\n",
            "i 9 j 12\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(4.4721, device='cuda:0')\n",
            "i 9 j 13\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(5.3852, device='cuda:0')\n",
            "i 9 j 14\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(6.3246, device='cuda:0')\n",
            "i 9 j 15\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(6.0828, device='cuda:0')\n",
            "i 10 j 0\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(6., device='cuda:0')\n",
            "i 10 j 1\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(6., device='cuda:0')\n",
            "i 10 j 2\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(5.4000, device='cuda:0')\n",
            "i 10 j 3\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(4.8000, device='cuda:0')\n",
            "i 10 j 4\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(4.2000, device='cuda:0')\n",
            "i 10 j 5\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(3.6056, device='cuda:0')\n",
            "i 10 j 6\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(3.1623, device='cuda:0')\n",
            "i 10 j 7\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(3., device='cuda:0')\n",
            "i 10 j 8\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(3., device='cuda:0')\n",
            "i 10 j 9\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(3.1623, device='cuda:0')\n",
            "i 10 j 10\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(3.6056, device='cuda:0')\n",
            "i 10 j 11\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(4.2426, device='cuda:0')\n",
            "i 10 j 12\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(5., device='cuda:0')\n",
            "i 10 j 13\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(5.8310, device='cuda:0')\n",
            "i 10 j 14\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(6.7082, device='cuda:0')\n",
            "i 10 j 15\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(7.0711, device='cuda:0')\n",
            "i 11 j 0\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(7., device='cuda:0')\n",
            "i 11 j 1\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(6.8000, device='cuda:0')\n",
            "i 11 j 2\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(6.2000, device='cuda:0')\n",
            "i 11 j 3\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(5.6000, device='cuda:0')\n",
            "i 11 j 4\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(5., device='cuda:0')\n",
            "i 11 j 5\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(4.4721, device='cuda:0')\n",
            "i 11 j 6\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(4.1231, device='cuda:0')\n",
            "i 11 j 7\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(4., device='cuda:0')\n",
            "i 11 j 8\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(4., device='cuda:0')\n",
            "i 11 j 9\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(4.1231, device='cuda:0')\n",
            "i 11 j 10\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(4.4721, device='cuda:0')\n",
            "i 11 j 11\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(5., device='cuda:0')\n",
            "i 11 j 12\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(5.6569, device='cuda:0')\n",
            "i 11 j 13\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(6.4031, device='cuda:0')\n",
            "i 11 j 14\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(7.2111, device='cuda:0')\n",
            "i 11 j 15\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(8.0623, device='cuda:0')\n",
            "i 12 j 0\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(8., device='cuda:0')\n",
            "i 12 j 1\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(7.6000, device='cuda:0')\n",
            "i 12 j 2\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(7., device='cuda:0')\n",
            "i 12 j 3\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(6.4000, device='cuda:0')\n",
            "i 12 j 4\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(5.8310, device='cuda:0')\n",
            "i 12 j 5\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(5.3852, device='cuda:0')\n",
            "i 12 j 6\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(5.0990, device='cuda:0')\n",
            "i 12 j 7\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(5., device='cuda:0')\n",
            "i 12 j 8\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(5., device='cuda:0')\n",
            "i 12 j 9\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(5.0990, device='cuda:0')\n",
            "i 12 j 10\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(5.3852, device='cuda:0')\n",
            "i 12 j 11\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(5.8310, device='cuda:0')\n",
            "i 12 j 12\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(6.4031, device='cuda:0')\n",
            "i 12 j 13\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(7.0711, device='cuda:0')\n",
            "i 12 j 14\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(7.8102, device='cuda:0')\n",
            "i 12 j 15\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(9.0554, device='cuda:0')\n",
            "i 13 j 0\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(9., device='cuda:0')\n",
            "i 13 j 1\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(8.4000, device='cuda:0')\n",
            "i 13 j 2\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(7.8000, device='cuda:0')\n",
            "i 13 j 3\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(7.2111, device='cuda:0')\n",
            "i 13 j 4\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(6.7082, device='cuda:0')\n",
            "i 13 j 5\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(6.3246, device='cuda:0')\n",
            "i 13 j 6\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(6.0828, device='cuda:0')\n",
            "i 13 j 7\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(6., device='cuda:0')\n",
            "i 13 j 8\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(6., device='cuda:0')\n",
            "i 13 j 9\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(6.0828, device='cuda:0')\n",
            "i 13 j 10\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(6.3246, device='cuda:0')\n",
            "i 13 j 11\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(6.7082, device='cuda:0')\n",
            "i 13 j 12\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(7.2111, device='cuda:0')\n",
            "i 13 j 13\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(7.8102, device='cuda:0')\n",
            "i 13 j 14\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(8.4853, device='cuda:0')\n",
            "i 13 j 15\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(10.0499, device='cuda:0')\n",
            "i 14 j 0\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(9.8000, device='cuda:0')\n",
            "i 14 j 1\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(9.2000, device='cuda:0')\n",
            "i 14 j 2\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(8.6023, device='cuda:0')\n",
            "i 14 j 3\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(8.0623, device='cuda:0')\n",
            "i 14 j 4\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(7.6158, device='cuda:0')\n",
            "i 14 j 5\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(7.2801, device='cuda:0')\n",
            "i 14 j 6\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(7.0711, device='cuda:0')\n",
            "i 14 j 7\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(7., device='cuda:0')\n",
            "i 14 j 8\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(7., device='cuda:0')\n",
            "i 14 j 9\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(7.0711, device='cuda:0')\n",
            "i 14 j 10\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(7.2801, device='cuda:0')\n",
            "i 14 j 11\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(7.6158, device='cuda:0')\n",
            "i 14 j 12\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(8.0623, device='cuda:0')\n",
            "i 14 j 13\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(8.6023, device='cuda:0')\n",
            "i 14 j 14\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(9.2195, device='cuda:0')\n",
            "i 14 j 15\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(11.0454, device='cuda:0')\n",
            "i 15 j 0\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(10.6000, device='cuda:0')\n",
            "i 15 j 1\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(10., device='cuda:0')\n",
            "i 15 j 2\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(9.4340, device='cuda:0')\n",
            "i 15 j 3\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(8.9443, device='cuda:0')\n",
            "i 15 j 4\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(8.5440, device='cuda:0')\n",
            "i 15 j 5\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(8.2462, device='cuda:0')\n",
            "i 15 j 6\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(8.0623, device='cuda:0')\n",
            "i 15 j 7\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(8., device='cuda:0')\n",
            "i 15 j 8\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(8., device='cuda:0')\n",
            "i 15 j 9\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(8.0623, device='cuda:0')\n",
            "i 15 j 10\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(8.2462, device='cuda:0')\n",
            "i 15 j 11\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(8.5440, device='cuda:0')\n",
            "i 15 j 12\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(8.9443, device='cuda:0')\n",
            "i 15 j 13\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(9.4340, device='cuda:0')\n",
            "i 15 j 14\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(10., device='cuda:0')\n",
            "i 15 j 15\n",
            "tensor([False, False, False, False], device='cuda:0')\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "dismap 是距离 label是标签 如果全为f 说明无法投影到任何一条线段上"
      ],
      "metadata": {
        "id": "aXqhRdT4upTN"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#.so报错的时候先跑一下\n",
        "!python /content/testIncolab/amp_extensions/afm/yjh_sizeTest.py"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_QNg_gO0xOhl",
        "outputId": "580c4b75-a0ef-412f-818c-82138dffda2c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "tensor([[0., 0., 1., 1.],\n",
            "        [1., 4., 2., 3.],\n",
            "        [4., 4., 8., 7.]], device='cuda:0')\n",
            "<module '_C' from '/root/.cache/torch_extensions/py310_cu118/_C/_C.so'>\n",
            "tensor([[[ 0.0000e+00, -5.0000e-01, -1.0000e+00,  ..., -5.1600e+00,\n",
            "          -6.0000e+00, -7.0000e+00],\n",
            "         [ 5.0000e-01, -4.7684e-07, -1.0000e+00,  ..., -5.0000e+00,\n",
            "          -6.0000e+00, -7.0000e+00],\n",
            "         [ 1.0000e+00,  0.0000e+00,  0.0000e+00,  ..., -5.0000e+00,\n",
            "          -6.0000e+00, -7.0000e+00],\n",
            "         ...,\n",
            "         [ 1.0000e+00,  0.0000e+00,  5.0400e+00,  ..., -5.0000e+00,\n",
            "          -6.0000e+00, -7.0000e+00],\n",
            "         [ 1.0000e+00,  5.8800e+00,  5.5200e+00,  ..., -5.0000e+00,\n",
            "          -6.0000e+00, -7.0000e+00],\n",
            "         [ 1.0000e+00,  6.3600e+00,  6.0000e+00,  ..., -5.0000e+00,\n",
            "          -6.0000e+00, -7.0000e+00]],\n",
            "\n",
            "        [[ 0.0000e+00,  5.0000e-01,  1.0000e+00,  ...,  6.8800e+00,\n",
            "           7.0000e+00,  7.0000e+00],\n",
            "         [-5.0000e-01, -4.7684e-07,  0.0000e+00,  ...,  6.0000e+00,\n",
            "           6.0000e+00,  6.0000e+00],\n",
            "         [-1.0000e+00, -1.0000e+00,  1.0000e+00,  ...,  5.0000e+00,\n",
            "           5.0000e+00,  5.0000e+00],\n",
            "         ...,\n",
            "         [-9.0000e+00, -9.0000e+00, -6.7200e+00,  ..., -6.0000e+00,\n",
            "          -6.0000e+00, -6.0000e+00],\n",
            "         [-1.0000e+01, -7.8400e+00, -7.3600e+00,  ..., -7.0000e+00,\n",
            "          -7.0000e+00, -7.0000e+00],\n",
            "         [-1.1000e+01, -8.4800e+00, -8.0000e+00,  ..., -8.0000e+00,\n",
            "          -8.0000e+00, -8.0000e+00]],\n",
            "\n",
            "        [[ 0.0000e+00,  0.0000e+00, -1.0000e+00,  ..., -5.0000e+00,\n",
            "          -6.0000e+00, -7.0000e+00],\n",
            "         [ 1.0000e+00,  0.0000e+00, -1.0000e+00,  ..., -5.0000e+00,\n",
            "          -6.0000e+00, -7.0000e+00],\n",
            "         [ 1.0000e+00,  0.0000e+00,  0.0000e+00,  ..., -5.0000e+00,\n",
            "          -6.0000e+00, -7.0000e+00],\n",
            "         ...,\n",
            "         [ 1.0000e+00,  0.0000e+00,  6.0000e+00,  ..., -5.0000e+00,\n",
            "          -6.0000e+00, -7.0000e+00],\n",
            "         [ 1.0000e+00,  7.0000e+00,  6.0000e+00,  ..., -5.0000e+00,\n",
            "          -6.0000e+00, -7.0000e+00],\n",
            "         [ 1.0000e+00,  7.0000e+00,  6.0000e+00,  ..., -5.0000e+00,\n",
            "          -6.0000e+00, -7.0000e+00]],\n",
            "\n",
            "        [[ 0.0000e+00,  1.0000e+00,  1.0000e+00,  ...,  7.0000e+00,\n",
            "           7.0000e+00,  7.0000e+00],\n",
            "         [ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  6.0000e+00,\n",
            "           6.0000e+00,  6.0000e+00],\n",
            "         [-1.0000e+00, -1.0000e+00,  1.0000e+00,  ...,  5.0000e+00,\n",
            "           5.0000e+00,  5.0000e+00],\n",
            "         ...,\n",
            "         [-9.0000e+00, -9.0000e+00, -6.0000e+00,  ..., -6.0000e+00,\n",
            "          -6.0000e+00, -6.0000e+00],\n",
            "         [-1.0000e+01, -7.0000e+00, -7.0000e+00,  ..., -7.0000e+00,\n",
            "          -7.0000e+00, -7.0000e+00],\n",
            "         [-1.1000e+01, -8.0000e+00, -8.0000e+00,  ..., -8.0000e+00,\n",
            "          -8.0000e+00, -8.0000e+00]],\n",
            "\n",
            "        [[ 1.0000e+00, -1.0000e+00, -2.0000e+00,  ..., -9.0000e+00,\n",
            "          -1.0000e+01, -1.1000e+01],\n",
            "         [ 0.0000e+00, -1.0000e+00, -2.0000e+00,  ..., -9.0000e+00,\n",
            "          -1.0000e+01, -1.1000e+01],\n",
            "         [ 0.0000e+00, -1.0000e+00, -1.0000e+00,  ..., -9.0000e+00,\n",
            "          -1.0000e+01, -1.1000e+01],\n",
            "         ...,\n",
            "         [ 2.0000e+00,  1.0000e+00,  2.0000e+00,  ..., -9.0000e+00,\n",
            "          -1.0000e+01, -1.1000e+01],\n",
            "         [ 2.0000e+00,  3.0000e+00,  2.0000e+00,  ..., -9.0000e+00,\n",
            "          -1.0000e+01, -1.1000e+01],\n",
            "         [ 2.0000e+00,  3.0000e+00,  2.0000e+00,  ..., -9.0000e+00,\n",
            "          -1.0000e+01, -1.1000e+01]],\n",
            "\n",
            "        [[ 1.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  4.0000e+00,\n",
            "           4.0000e+00,  4.0000e+00],\n",
            "         [-1.0000e+00, -1.0000e+00, -1.0000e+00,  ...,  3.0000e+00,\n",
            "           3.0000e+00,  3.0000e+00],\n",
            "         [-2.0000e+00, -2.0000e+00,  2.0000e+00,  ...,  2.0000e+00,\n",
            "           2.0000e+00,  2.0000e+00],\n",
            "         ...,\n",
            "         [-1.0000e+01, -1.0000e+01, -9.0000e+00,  ..., -9.0000e+00,\n",
            "          -9.0000e+00, -9.0000e+00],\n",
            "         [-1.1000e+01, -1.0000e+01, -1.0000e+01,  ..., -1.0000e+01,\n",
            "          -1.0000e+01, -1.0000e+01],\n",
            "         [-1.2000e+01, -1.1000e+01, -1.1000e+01,  ..., -1.1000e+01,\n",
            "          -1.1000e+01, -1.1000e+01]]], device='cuda:0')\n",
            "tensor([[[ True,  True,  True, False, False, False, False, False, False, False,\n",
            "          False, False, False, False, False, False],\n",
            "         [ True,  True, False, False, False, False, False, False, False, False,\n",
            "          False, False, False, False, False, False],\n",
            "         [ True, False, False, False, False, False, False, False, False, False,\n",
            "          False, False, False, False, False, False],\n",
            "         [False, False, False, False, False, False, False, False, False, False,\n",
            "          False, False, False, False, False, False],\n",
            "         [False, False, False, False, False, False, False, False, False, False,\n",
            "          False, False, False, False, False, False],\n",
            "         [False, False, False, False, False, False, False, False, False, False,\n",
            "          False, False, False, False, False, False],\n",
            "         [False, False, False, False, False, False, False, False, False, False,\n",
            "          False, False, False, False, False, False],\n",
            "         [False, False, False, False, False, False, False, False, False, False,\n",
            "          False, False, False, False, False, False],\n",
            "         [False, False, False, False, False, False, False, False, False, False,\n",
            "          False, False, False, False, False, False],\n",
            "         [False, False, False, False, False, False, False, False, False, False,\n",
            "          False, False, False, False, False, False],\n",
            "         [False, False, False, False, False, False, False, False, False, False,\n",
            "          False, False, False, False, False, False],\n",
            "         [False, False, False, False, False, False, False, False, False, False,\n",
            "          False, False, False, False, False, False],\n",
            "         [False, False, False, False, False, False, False, False, False, False,\n",
            "          False, False, False, False, False, False],\n",
            "         [False, False, False, False, False, False, False, False, False, False,\n",
            "          False, False, False, False, False, False],\n",
            "         [False, False, False, False, False, False, False, False, False, False,\n",
            "          False, False, False, False, False, False],\n",
            "         [False, False, False, False, False, False, False, False, False, False,\n",
            "          False, False, False, False, False, False]],\n",
            "\n",
            "        [[False, False, False, False, False, False, False, False, False, False,\n",
            "          False, False, False, False, False, False],\n",
            "         [False, False, False, False, False, False, False, False, False, False,\n",
            "          False, False, False, False, False, False],\n",
            "         [False, False, False, False, False, False, False, False, False, False,\n",
            "          False, False, False, False, False, False],\n",
            "         [ True,  True,  True, False, False, False, False, False, False, False,\n",
            "          False, False, False, False, False, False],\n",
            "         [False,  True,  True, False, False, False, False, False, False, False,\n",
            "          False, False, False, False, False, False],\n",
            "         [False, False,  True, False, False, False, False, False, False, False,\n",
            "          False, False, False, False, False, False],\n",
            "         [False, False, False, False, False, False, False, False, False, False,\n",
            "          False, False, False, False, False, False],\n",
            "         [False, False, False, False, False, False, False, False, False, False,\n",
            "          False, False, False, False, False, False],\n",
            "         [False, False, False, False, False, False, False, False, False, False,\n",
            "          False, False, False, False, False, False],\n",
            "         [False, False, False, False, False, False, False, False, False, False,\n",
            "          False, False, False, False, False, False],\n",
            "         [False, False, False, False, False, False, False, False, False, False,\n",
            "          False, False, False, False, False, False],\n",
            "         [False, False, False, False, False, False, False, False, False, False,\n",
            "          False, False, False, False, False, False],\n",
            "         [False, False, False, False, False, False, False, False, False, False,\n",
            "          False, False, False, False, False, False],\n",
            "         [False, False, False, False, False, False, False, False, False, False,\n",
            "          False, False, False, False, False, False],\n",
            "         [False, False, False, False, False, False, False, False, False, False,\n",
            "          False, False, False, False, False, False],\n",
            "         [False, False, False, False, False, False, False, False, False, False,\n",
            "          False, False, False, False, False, False]],\n",
            "\n",
            "        [[False, False, False, False, False, False, False,  True,  True,  True,\n",
            "           True,  True,  True,  True, False, False],\n",
            "         [False, False, False, False, False, False, False,  True,  True,  True,\n",
            "           True,  True,  True, False, False, False],\n",
            "         [False, False, False, False, False, False,  True,  True,  True,  True,\n",
            "           True,  True, False, False, False, False],\n",
            "         [False, False, False, False, False,  True,  True,  True,  True,  True,\n",
            "           True,  True, False, False, False, False],\n",
            "         [False, False, False, False,  True,  True,  True,  True,  True,  True,\n",
            "           True, False, False, False, False, False],\n",
            "         [False, False, False, False,  True,  True,  True,  True,  True,  True,\n",
            "          False, False, False, False, False, False],\n",
            "         [False, False, False,  True,  True,  True,  True,  True,  True, False,\n",
            "          False, False, False, False, False, False],\n",
            "         [False, False, False,  True,  True,  True,  True,  True,  True, False,\n",
            "          False, False, False, False, False, False],\n",
            "         [False, False, False,  True,  True,  True,  True,  True, False, False,\n",
            "          False, False, False, False, False, False],\n",
            "         [False, False, False,  True,  True,  True,  True, False, False, False,\n",
            "          False, False, False, False, False, False],\n",
            "         [False, False,  True,  True,  True,  True, False, False, False, False,\n",
            "          False, False, False, False, False, False],\n",
            "         [False, False,  True,  True,  True,  True, False, False, False, False,\n",
            "          False, False, False, False, False, False],\n",
            "         [False, False,  True,  True,  True, False, False, False, False, False,\n",
            "          False, False, False, False, False, False],\n",
            "         [False, False,  True,  True, False, False, False, False, False, False,\n",
            "          False, False, False, False, False, False],\n",
            "         [False,  True,  True, False, False, False, False, False, False, False,\n",
            "          False, False, False, False, False, False],\n",
            "         [False,  True,  True, False, False, False, False, False, False, False,\n",
            "          False, False, False, False, False, False]]], device='cuda:0')\n",
            "torch.Size([6, 16, 16])\n",
            "torch.Size([3, 16, 16])\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#测试改进程序 linesegment-hawp中tmap的值为分配线段标号（从0开始）\n",
        "import sys\n",
        "sys.path.append('./testIncolab/amp_extensions/afm')\n",
        "import torch\n",
        "import numpy as np\n",
        "from torch.utils.data.dataloader import default_collate\n",
        "from csrc import _C\n",
        "\n",
        "height=16\n",
        "width =16\n",
        "import torch\n",
        "\n",
        "device='cuda'\n",
        "lines = torch.Tensor([[0, 0, 1, 1], [1, 4, 2, 3], [4, 4, 8, 7],[9,7,8,3]]).to(device)\n",
        "print(lines)\n",
        "print(_C)\n",
        "lmap, labels, tmap = _C.encodels(lines,height,width,height,width,lines.size(0))\n",
        "#print(lmap)\n",
        "#print(labels)\n",
        "print(lmap.size())#(6,height,width)\n",
        "print(labels.size())#(lines_num,height,width)\n",
        "print(tmap.size())#(lines_num,height,width)\n",
        "print(labels)\n",
        "#查看特定像素点(13,13)的label\n",
        "# y_index=13\n",
        "# z_index=13\n",
        "print(labels[:,4,4])#(f,f,t,f)\n",
        "print(tmap[0,4,4])#(f,f,t,f)\n",
        "print(labels[:,1,1])#(t,f,f,f)\n",
        "print(labels[:,4,5])#(f,f,t,f)\n",
        "print(tmap[0,4,5])\n",
        "print(labels[:,8,8])#(f,f,f,f)\n",
        "print(labels[:,10,9])#(f,f,f,f)\n",
        "print(tmap[0,10,9])#(f,f,f,f)\n",
        "print(labels[:,15,5])#(f,f,f,f)\n",
        "\n",
        "\n",
        "dismap = torch.sqrt(lmap[0]**2+lmap[1]**2)[None]\n",
        "print(dismap.size())\n",
        "print(dismap)\n",
        "print(dismap[0,4,4])\n",
        "print(dismap[0,1,1])\n",
        "print(dismap[0,4,5])\n",
        "print(dismap[0,8,8])\n",
        "print(dismap[0,10,9])\n",
        "print(dismap[0,15,5])\n",
        "#距离像素点1之外的都是false\n",
        "for i in range(dismap.size(1)):\n",
        "    for j in range(dismap.size(2)):\n",
        "        if dismap[0, i, j] > 1:\n",
        "            print(\"dis:\",dismap[0, i, j])\n",
        "            print(\"i\",i,\"j\",j)\n",
        "            print(labels[:,i,j])\n",
        "            # do something\n",
        "#dismap 是距离 label是标签 如果全为f 说明无法投影到任何一条线段上（写得tql😭\n"
      ],
      "metadata": {
        "id": "8xNVJsRcVYU7",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "91622668-5207-4e6d-a761-e4fcf0fa7eef"
      },
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "tensor([[0., 0., 1., 1.],\n",
            "        [1., 4., 2., 3.],\n",
            "        [4., 4., 8., 7.],\n",
            "        [9., 7., 8., 3.]], device='cuda:0')\n",
            "<module '_C' from '/root/.cache/torch_extensions/py310_cu118/_C/_C.so'>\n",
            "torch.Size([6, 16, 16])\n",
            "torch.Size([4, 16, 16])\n",
            "torch.Size([1, 16, 16])\n",
            "tensor([[[ True,  True,  True,  ..., False, False, False],\n",
            "         [ True,  True, False,  ..., False, False, False],\n",
            "         [ True, False, False,  ..., False, False, False],\n",
            "         ...,\n",
            "         [False, False, False,  ..., False, False, False],\n",
            "         [False, False, False,  ..., False, False, False],\n",
            "         [False, False, False,  ..., False, False, False]],\n",
            "\n",
            "        [[False, False, False,  ..., False, False, False],\n",
            "         [False, False, False,  ..., False, False, False],\n",
            "         [False, False, False,  ..., False, False, False],\n",
            "         ...,\n",
            "         [False, False, False,  ..., False, False, False],\n",
            "         [False, False, False,  ..., False, False, False],\n",
            "         [False, False, False,  ..., False, False, False]],\n",
            "\n",
            "        [[False, False, False,  ..., False, False, False],\n",
            "         [False, False, False,  ..., False, False, False],\n",
            "         [False, False, False,  ..., False, False, False],\n",
            "         ...,\n",
            "         [False, False,  True,  ..., False, False, False],\n",
            "         [False,  True,  True,  ..., False, False, False],\n",
            "         [False,  True,  True,  ..., False, False, False]],\n",
            "\n",
            "        [[False, False, False,  ..., False, False, False],\n",
            "         [False, False, False,  ..., False, False, False],\n",
            "         [False, False, False,  ...,  True,  True,  True],\n",
            "         ...,\n",
            "         [False, False, False,  ..., False, False, False],\n",
            "         [False, False, False,  ..., False, False, False],\n",
            "         [False, False, False,  ..., False, False, False]]], device='cuda:0')\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "tensor(2., device='cuda:0')\n",
            "tensor([ True, False, False, False], device='cuda:0')\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "tensor(2., device='cuda:0')\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "tensor(-1., device='cuda:0')\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "torch.Size([1, 16, 16])\n",
            "tensor([[[0.0000e+00, 7.0711e-01, 1.4142e+00, 2.2361e+00, 3.1623e+00,\n",
            "          4.1231e+00, 3.6056e+00, 3.1623e+00, 3.0000e+00, 3.1623e+00,\n",
            "          3.6056e+00, 4.2426e+00, 5.0000e+00, 5.8310e+00, 6.7082e+00,\n",
            "          7.6158e+00],\n",
            "         [7.0711e-01, 6.7435e-07, 1.0000e+00, 2.0000e+00, 2.8284e+00,\n",
            "          3.1623e+00, 2.8284e+00, 2.2361e+00, 2.0000e+00, 2.2361e+00,\n",
            "          2.8284e+00, 3.6056e+00, 4.4721e+00, 5.3852e+00, 6.3246e+00,\n",
            "          7.2801e+00],\n",
            "         [1.4142e+00, 1.0000e+00, 1.0000e+00, 1.4142e+00, 2.0000e+00,\n",
            "          2.2361e+00, 2.2361e+00, 1.4142e+00, 1.0000e+00, 1.4142e+00,\n",
            "          2.2361e+00, 3.1623e+00, 4.1231e+00, 5.0932e+00, 6.0634e+00,\n",
            "          7.0335e+00],\n",
            "         [1.4142e+00, 7.0711e-01, 6.7435e-07, 1.0000e+00, 1.0000e+00,\n",
            "          1.4000e+00, 2.0000e+00, 1.0000e+00, 2.3842e-07, 9.7014e-01,\n",
            "          1.9403e+00, 2.9104e+00, 3.8806e+00, 4.8507e+00, 5.8209e+00,\n",
            "          6.7910e+00],\n",
            "         [1.0000e+00, 0.0000e+00, 7.0711e-01, 1.0000e+00, 0.0000e+00,\n",
            "          6.0000e-01, 1.2000e+00, 1.2127e+00, 2.4254e-01, 7.2761e-01,\n",
            "          1.6977e+00, 2.6679e+00, 3.6380e+00, 4.6082e+00, 5.5783e+00,\n",
            "          6.5485e+00],\n",
            "         [1.4142e+00, 1.0000e+00, 1.4142e+00, 1.4142e+00, 8.0000e-01,\n",
            "          2.0000e-01, 4.0000e-01, 1.0000e+00, 4.8507e-01, 4.8507e-01,\n",
            "          1.4552e+00, 2.4254e+00, 3.3955e+00, 4.3656e+00, 5.3358e+00,\n",
            "          6.3059e+00],\n",
            "         [2.2361e+00, 2.0000e+00, 2.2361e+00, 2.2000e+00, 1.6000e+00,\n",
            "          1.0000e+00, 4.0000e-01, 2.0000e-01, 7.2761e-01, 2.4254e-01,\n",
            "          1.2127e+00, 2.1828e+00, 3.1530e+00, 4.1231e+00, 5.0990e+00,\n",
            "          6.0828e+00],\n",
            "         [3.1623e+00, 3.0000e+00, 3.1623e+00, 3.0000e+00, 2.4000e+00,\n",
            "          1.8000e+00, 1.2000e+00, 6.0000e-01, 0.0000e+00, 0.0000e+00,\n",
            "          1.0000e+00, 2.0000e+00, 3.0000e+00, 4.0000e+00, 5.0000e+00,\n",
            "          6.0000e+00],\n",
            "         [4.1231e+00, 4.0000e+00, 4.1231e+00, 3.8000e+00, 3.2000e+00,\n",
            "          2.6000e+00, 2.0000e+00, 1.4000e+00, 1.0000e+00, 1.0000e+00,\n",
            "          1.4142e+00, 2.2361e+00, 3.1623e+00, 4.1231e+00, 5.0990e+00,\n",
            "          6.0828e+00],\n",
            "         [5.0990e+00, 5.0000e+00, 5.0990e+00, 4.6000e+00, 4.0000e+00,\n",
            "          3.4000e+00, 2.8000e+00, 2.2361e+00, 2.0000e+00, 2.0000e+00,\n",
            "          2.2361e+00, 2.8284e+00, 3.6056e+00, 4.4721e+00, 5.3852e+00,\n",
            "          6.3246e+00],\n",
            "         [6.0828e+00, 6.0000e+00, 6.0000e+00, 5.4000e+00, 4.8000e+00,\n",
            "          4.2000e+00, 3.6056e+00, 3.1623e+00, 3.0000e+00, 3.0000e+00,\n",
            "          3.1623e+00, 3.6056e+00, 4.2426e+00, 5.0000e+00, 5.8310e+00,\n",
            "          6.7082e+00],\n",
            "         [7.0711e+00, 7.0000e+00, 6.8000e+00, 6.2000e+00, 5.6000e+00,\n",
            "          5.0000e+00, 4.4721e+00, 4.1231e+00, 4.0000e+00, 4.0000e+00,\n",
            "          4.1231e+00, 4.4721e+00, 5.0000e+00, 5.6569e+00, 6.4031e+00,\n",
            "          7.2111e+00],\n",
            "         [8.0623e+00, 8.0000e+00, 7.6000e+00, 7.0000e+00, 6.4000e+00,\n",
            "          5.8310e+00, 5.3852e+00, 5.0990e+00, 5.0000e+00, 5.0000e+00,\n",
            "          5.0990e+00, 5.3852e+00, 5.8310e+00, 6.4031e+00, 7.0711e+00,\n",
            "          7.8102e+00],\n",
            "         [9.0554e+00, 9.0000e+00, 8.4000e+00, 7.8000e+00, 7.2111e+00,\n",
            "          6.7082e+00, 6.3246e+00, 6.0828e+00, 6.0000e+00, 6.0000e+00,\n",
            "          6.0828e+00, 6.3246e+00, 6.7082e+00, 7.2111e+00, 7.8102e+00,\n",
            "          8.4853e+00],\n",
            "         [1.0050e+01, 9.8000e+00, 9.2000e+00, 8.6023e+00, 8.0623e+00,\n",
            "          7.6158e+00, 7.2801e+00, 7.0711e+00, 7.0000e+00, 7.0000e+00,\n",
            "          7.0711e+00, 7.2801e+00, 7.6158e+00, 8.0623e+00, 8.6023e+00,\n",
            "          9.2195e+00],\n",
            "         [1.1045e+01, 1.0600e+01, 1.0000e+01, 9.4340e+00, 8.9443e+00,\n",
            "          8.5440e+00, 8.2462e+00, 8.0623e+00, 8.0000e+00, 8.0000e+00,\n",
            "          8.0623e+00, 8.2462e+00, 8.5440e+00, 8.9443e+00, 9.4340e+00,\n",
            "          1.0000e+01]]], device='cuda:0')\n",
            "tensor(0., device='cuda:0')\n",
            "tensor(6.7435e-07, device='cuda:0')\n",
            "tensor(0.6000, device='cuda:0')\n",
            "tensor(1., device='cuda:0')\n",
            "tensor(3., device='cuda:0')\n",
            "tensor(8.5440, device='cuda:0')\n",
            "dis: tensor(1.4142, device='cuda:0')\n",
            "i 0 j 2\n",
            "tensor([ True, False, False, False], device='cuda:0')\n",
            "dis: tensor(2.2361, device='cuda:0')\n",
            "i 0 j 3\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(3.1623, device='cuda:0')\n",
            "i 0 j 4\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(4.1231, device='cuda:0')\n",
            "i 0 j 5\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(3.6056, device='cuda:0')\n",
            "i 0 j 6\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(3.1623, device='cuda:0')\n",
            "i 0 j 7\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(3., device='cuda:0')\n",
            "i 0 j 8\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(3.1623, device='cuda:0')\n",
            "i 0 j 9\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(3.6056, device='cuda:0')\n",
            "i 0 j 10\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(4.2426, device='cuda:0')\n",
            "i 0 j 11\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(5., device='cuda:0')\n",
            "i 0 j 12\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(5.8310, device='cuda:0')\n",
            "i 0 j 13\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(6.7082, device='cuda:0')\n",
            "i 0 j 14\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(7.6158, device='cuda:0')\n",
            "i 0 j 15\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(2., device='cuda:0')\n",
            "i 1 j 3\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(2.8284, device='cuda:0')\n",
            "i 1 j 4\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(3.1623, device='cuda:0')\n",
            "i 1 j 5\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(2.8284, device='cuda:0')\n",
            "i 1 j 6\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(2.2361, device='cuda:0')\n",
            "i 1 j 7\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(2., device='cuda:0')\n",
            "i 1 j 8\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(2.2361, device='cuda:0')\n",
            "i 1 j 9\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(2.8284, device='cuda:0')\n",
            "i 1 j 10\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(3.6056, device='cuda:0')\n",
            "i 1 j 11\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(4.4721, device='cuda:0')\n",
            "i 1 j 12\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(5.3852, device='cuda:0')\n",
            "i 1 j 13\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(6.3246, device='cuda:0')\n",
            "i 1 j 14\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(7.2801, device='cuda:0')\n",
            "i 1 j 15\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(1.4142, device='cuda:0')\n",
            "i 2 j 0\n",
            "tensor([ True, False, False, False], device='cuda:0')\n",
            "dis: tensor(1.4142, device='cuda:0')\n",
            "i 2 j 3\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(2., device='cuda:0')\n",
            "i 2 j 4\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(2.2361, device='cuda:0')\n",
            "i 2 j 5\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(2.2361, device='cuda:0')\n",
            "i 2 j 6\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(1.4142, device='cuda:0')\n",
            "i 2 j 7\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(1.4142, device='cuda:0')\n",
            "i 2 j 9\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(2.2361, device='cuda:0')\n",
            "i 2 j 10\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(3.1623, device='cuda:0')\n",
            "i 2 j 11\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(4.1231, device='cuda:0')\n",
            "i 2 j 12\n",
            "tensor([False, False, False,  True], device='cuda:0')\n",
            "dis: tensor(5.0932, device='cuda:0')\n",
            "i 2 j 13\n",
            "tensor([False, False, False,  True], device='cuda:0')\n",
            "dis: tensor(6.0634, device='cuda:0')\n",
            "i 2 j 14\n",
            "tensor([False, False, False,  True], device='cuda:0')\n",
            "dis: tensor(7.0335, device='cuda:0')\n",
            "i 2 j 15\n",
            "tensor([False, False, False,  True], device='cuda:0')\n",
            "dis: tensor(1.4142, device='cuda:0')\n",
            "i 3 j 0\n",
            "tensor([False,  True, False, False], device='cuda:0')\n",
            "dis: tensor(1.4000, device='cuda:0')\n",
            "i 3 j 5\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(2.0000, device='cuda:0')\n",
            "i 3 j 6\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(1.9403, device='cuda:0')\n",
            "i 3 j 10\n",
            "tensor([False, False, False,  True], device='cuda:0')\n",
            "dis: tensor(2.9104, device='cuda:0')\n",
            "i 3 j 11\n",
            "tensor([False, False, False,  True], device='cuda:0')\n",
            "dis: tensor(3.8806, device='cuda:0')\n",
            "i 3 j 12\n",
            "tensor([False, False, False,  True], device='cuda:0')\n",
            "dis: tensor(4.8507, device='cuda:0')\n",
            "i 3 j 13\n",
            "tensor([False, False, False,  True], device='cuda:0')\n",
            "dis: tensor(5.8209, device='cuda:0')\n",
            "i 3 j 14\n",
            "tensor([False, False, False,  True], device='cuda:0')\n",
            "dis: tensor(6.7910, device='cuda:0')\n",
            "i 3 j 15\n",
            "tensor([False, False, False,  True], device='cuda:0')\n",
            "dis: tensor(1.2000, device='cuda:0')\n",
            "i 4 j 6\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(1.2127, device='cuda:0')\n",
            "i 4 j 7\n",
            "tensor([False, False, False,  True], device='cuda:0')\n",
            "dis: tensor(1.6977, device='cuda:0')\n",
            "i 4 j 10\n",
            "tensor([False, False, False,  True], device='cuda:0')\n",
            "dis: tensor(2.6679, device='cuda:0')\n",
            "i 4 j 11\n",
            "tensor([False, False, False,  True], device='cuda:0')\n",
            "dis: tensor(3.6380, device='cuda:0')\n",
            "i 4 j 12\n",
            "tensor([False, False, False,  True], device='cuda:0')\n",
            "dis: tensor(4.6082, device='cuda:0')\n",
            "i 4 j 13\n",
            "tensor([False, False, False,  True], device='cuda:0')\n",
            "dis: tensor(5.5783, device='cuda:0')\n",
            "i 4 j 14\n",
            "tensor([False, False, False,  True], device='cuda:0')\n",
            "dis: tensor(6.5485, device='cuda:0')\n",
            "i 4 j 15\n",
            "tensor([False, False, False,  True], device='cuda:0')\n",
            "dis: tensor(1.4142, device='cuda:0')\n",
            "i 5 j 0\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(1.4142, device='cuda:0')\n",
            "i 5 j 2\n",
            "tensor([False,  True, False, False], device='cuda:0')\n",
            "dis: tensor(1.4142, device='cuda:0')\n",
            "i 5 j 3\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(1.4552, device='cuda:0')\n",
            "i 5 j 10\n",
            "tensor([False, False, False,  True], device='cuda:0')\n",
            "dis: tensor(2.4254, device='cuda:0')\n",
            "i 5 j 11\n",
            "tensor([False, False, False,  True], device='cuda:0')\n",
            "dis: tensor(3.3955, device='cuda:0')\n",
            "i 5 j 12\n",
            "tensor([False, False, False,  True], device='cuda:0')\n",
            "dis: tensor(4.3656, device='cuda:0')\n",
            "i 5 j 13\n",
            "tensor([False, False, False,  True], device='cuda:0')\n",
            "dis: tensor(5.3358, device='cuda:0')\n",
            "i 5 j 14\n",
            "tensor([False, False, False,  True], device='cuda:0')\n",
            "dis: tensor(6.3059, device='cuda:0')\n",
            "i 5 j 15\n",
            "tensor([False, False, False,  True], device='cuda:0')\n",
            "dis: tensor(2.2361, device='cuda:0')\n",
            "i 6 j 0\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(2., device='cuda:0')\n",
            "i 6 j 1\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(2.2361, device='cuda:0')\n",
            "i 6 j 2\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(2.2000, device='cuda:0')\n",
            "i 6 j 3\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(1.6000, device='cuda:0')\n",
            "i 6 j 4\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(1.0000, device='cuda:0')\n",
            "i 6 j 5\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(1.2127, device='cuda:0')\n",
            "i 6 j 10\n",
            "tensor([False, False, False,  True], device='cuda:0')\n",
            "dis: tensor(2.1828, device='cuda:0')\n",
            "i 6 j 11\n",
            "tensor([False, False, False,  True], device='cuda:0')\n",
            "dis: tensor(3.1530, device='cuda:0')\n",
            "i 6 j 12\n",
            "tensor([False, False, False,  True], device='cuda:0')\n",
            "dis: tensor(4.1231, device='cuda:0')\n",
            "i 6 j 13\n",
            "tensor([False, False, False,  True], device='cuda:0')\n",
            "dis: tensor(5.0990, device='cuda:0')\n",
            "i 6 j 14\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(6.0828, device='cuda:0')\n",
            "i 6 j 15\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(3.1623, device='cuda:0')\n",
            "i 7 j 0\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(3., device='cuda:0')\n",
            "i 7 j 1\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(3.1623, device='cuda:0')\n",
            "i 7 j 2\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(3.0000, device='cuda:0')\n",
            "i 7 j 3\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(2.4000, device='cuda:0')\n",
            "i 7 j 4\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(1.8000, device='cuda:0')\n",
            "i 7 j 5\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(1.2000, device='cuda:0')\n",
            "i 7 j 6\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(2., device='cuda:0')\n",
            "i 7 j 11\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(3., device='cuda:0')\n",
            "i 7 j 12\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(4., device='cuda:0')\n",
            "i 7 j 13\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(5., device='cuda:0')\n",
            "i 7 j 14\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(6., device='cuda:0')\n",
            "i 7 j 15\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(4.1231, device='cuda:0')\n",
            "i 8 j 0\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(4., device='cuda:0')\n",
            "i 8 j 1\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(4.1231, device='cuda:0')\n",
            "i 8 j 2\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(3.8000, device='cuda:0')\n",
            "i 8 j 3\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(3.2000, device='cuda:0')\n",
            "i 8 j 4\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(2.6000, device='cuda:0')\n",
            "i 8 j 5\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(2.0000, device='cuda:0')\n",
            "i 8 j 6\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(1.4000, device='cuda:0')\n",
            "i 8 j 7\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(1.4142, device='cuda:0')\n",
            "i 8 j 10\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(2.2361, device='cuda:0')\n",
            "i 8 j 11\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(3.1623, device='cuda:0')\n",
            "i 8 j 12\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(4.1231, device='cuda:0')\n",
            "i 8 j 13\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(5.0990, device='cuda:0')\n",
            "i 8 j 14\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(6.0828, device='cuda:0')\n",
            "i 8 j 15\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(5.0990, device='cuda:0')\n",
            "i 9 j 0\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(5., device='cuda:0')\n",
            "i 9 j 1\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(5.0990, device='cuda:0')\n",
            "i 9 j 2\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(4.6000, device='cuda:0')\n",
            "i 9 j 3\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(4., device='cuda:0')\n",
            "i 9 j 4\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(3.4000, device='cuda:0')\n",
            "i 9 j 5\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(2.8000, device='cuda:0')\n",
            "i 9 j 6\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(2.2361, device='cuda:0')\n",
            "i 9 j 7\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(2., device='cuda:0')\n",
            "i 9 j 8\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(2., device='cuda:0')\n",
            "i 9 j 9\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(2.2361, device='cuda:0')\n",
            "i 9 j 10\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(2.8284, device='cuda:0')\n",
            "i 9 j 11\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(3.6056, device='cuda:0')\n",
            "i 9 j 12\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(4.4721, device='cuda:0')\n",
            "i 9 j 13\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(5.3852, device='cuda:0')\n",
            "i 9 j 14\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(6.3246, device='cuda:0')\n",
            "i 9 j 15\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(6.0828, device='cuda:0')\n",
            "i 10 j 0\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(6., device='cuda:0')\n",
            "i 10 j 1\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(6., device='cuda:0')\n",
            "i 10 j 2\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(5.4000, device='cuda:0')\n",
            "i 10 j 3\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(4.8000, device='cuda:0')\n",
            "i 10 j 4\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(4.2000, device='cuda:0')\n",
            "i 10 j 5\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(3.6056, device='cuda:0')\n",
            "i 10 j 6\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(3.1623, device='cuda:0')\n",
            "i 10 j 7\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(3., device='cuda:0')\n",
            "i 10 j 8\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(3., device='cuda:0')\n",
            "i 10 j 9\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(3.1623, device='cuda:0')\n",
            "i 10 j 10\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(3.6056, device='cuda:0')\n",
            "i 10 j 11\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(4.2426, device='cuda:0')\n",
            "i 10 j 12\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(5., device='cuda:0')\n",
            "i 10 j 13\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(5.8310, device='cuda:0')\n",
            "i 10 j 14\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(6.7082, device='cuda:0')\n",
            "i 10 j 15\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(7.0711, device='cuda:0')\n",
            "i 11 j 0\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(7., device='cuda:0')\n",
            "i 11 j 1\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(6.8000, device='cuda:0')\n",
            "i 11 j 2\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(6.2000, device='cuda:0')\n",
            "i 11 j 3\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(5.6000, device='cuda:0')\n",
            "i 11 j 4\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(5., device='cuda:0')\n",
            "i 11 j 5\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(4.4721, device='cuda:0')\n",
            "i 11 j 6\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(4.1231, device='cuda:0')\n",
            "i 11 j 7\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(4., device='cuda:0')\n",
            "i 11 j 8\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(4., device='cuda:0')\n",
            "i 11 j 9\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(4.1231, device='cuda:0')\n",
            "i 11 j 10\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(4.4721, device='cuda:0')\n",
            "i 11 j 11\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(5., device='cuda:0')\n",
            "i 11 j 12\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(5.6569, device='cuda:0')\n",
            "i 11 j 13\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(6.4031, device='cuda:0')\n",
            "i 11 j 14\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(7.2111, device='cuda:0')\n",
            "i 11 j 15\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(8.0623, device='cuda:0')\n",
            "i 12 j 0\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(8., device='cuda:0')\n",
            "i 12 j 1\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(7.6000, device='cuda:0')\n",
            "i 12 j 2\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(7., device='cuda:0')\n",
            "i 12 j 3\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(6.4000, device='cuda:0')\n",
            "i 12 j 4\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(5.8310, device='cuda:0')\n",
            "i 12 j 5\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(5.3852, device='cuda:0')\n",
            "i 12 j 6\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(5.0990, device='cuda:0')\n",
            "i 12 j 7\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(5., device='cuda:0')\n",
            "i 12 j 8\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(5., device='cuda:0')\n",
            "i 12 j 9\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(5.0990, device='cuda:0')\n",
            "i 12 j 10\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(5.3852, device='cuda:0')\n",
            "i 12 j 11\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(5.8310, device='cuda:0')\n",
            "i 12 j 12\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(6.4031, device='cuda:0')\n",
            "i 12 j 13\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(7.0711, device='cuda:0')\n",
            "i 12 j 14\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(7.8102, device='cuda:0')\n",
            "i 12 j 15\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(9.0554, device='cuda:0')\n",
            "i 13 j 0\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(9., device='cuda:0')\n",
            "i 13 j 1\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(8.4000, device='cuda:0')\n",
            "i 13 j 2\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(7.8000, device='cuda:0')\n",
            "i 13 j 3\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(7.2111, device='cuda:0')\n",
            "i 13 j 4\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(6.7082, device='cuda:0')\n",
            "i 13 j 5\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(6.3246, device='cuda:0')\n",
            "i 13 j 6\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(6.0828, device='cuda:0')\n",
            "i 13 j 7\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(6., device='cuda:0')\n",
            "i 13 j 8\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(6., device='cuda:0')\n",
            "i 13 j 9\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(6.0828, device='cuda:0')\n",
            "i 13 j 10\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(6.3246, device='cuda:0')\n",
            "i 13 j 11\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(6.7082, device='cuda:0')\n",
            "i 13 j 12\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(7.2111, device='cuda:0')\n",
            "i 13 j 13\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(7.8102, device='cuda:0')\n",
            "i 13 j 14\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(8.4853, device='cuda:0')\n",
            "i 13 j 15\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(10.0499, device='cuda:0')\n",
            "i 14 j 0\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(9.8000, device='cuda:0')\n",
            "i 14 j 1\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(9.2000, device='cuda:0')\n",
            "i 14 j 2\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(8.6023, device='cuda:0')\n",
            "i 14 j 3\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(8.0623, device='cuda:0')\n",
            "i 14 j 4\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(7.6158, device='cuda:0')\n",
            "i 14 j 5\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(7.2801, device='cuda:0')\n",
            "i 14 j 6\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(7.0711, device='cuda:0')\n",
            "i 14 j 7\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(7., device='cuda:0')\n",
            "i 14 j 8\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(7., device='cuda:0')\n",
            "i 14 j 9\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(7.0711, device='cuda:0')\n",
            "i 14 j 10\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(7.2801, device='cuda:0')\n",
            "i 14 j 11\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(7.6158, device='cuda:0')\n",
            "i 14 j 12\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(8.0623, device='cuda:0')\n",
            "i 14 j 13\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(8.6023, device='cuda:0')\n",
            "i 14 j 14\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(9.2195, device='cuda:0')\n",
            "i 14 j 15\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(11.0454, device='cuda:0')\n",
            "i 15 j 0\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(10.6000, device='cuda:0')\n",
            "i 15 j 1\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(10., device='cuda:0')\n",
            "i 15 j 2\n",
            "tensor([False, False,  True, False], device='cuda:0')\n",
            "dis: tensor(9.4340, device='cuda:0')\n",
            "i 15 j 3\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(8.9443, device='cuda:0')\n",
            "i 15 j 4\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(8.5440, device='cuda:0')\n",
            "i 15 j 5\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(8.2462, device='cuda:0')\n",
            "i 15 j 6\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(8.0623, device='cuda:0')\n",
            "i 15 j 7\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(8., device='cuda:0')\n",
            "i 15 j 8\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(8., device='cuda:0')\n",
            "i 15 j 9\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(8.0623, device='cuda:0')\n",
            "i 15 j 10\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(8.2462, device='cuda:0')\n",
            "i 15 j 11\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(8.5440, device='cuda:0')\n",
            "i 15 j 12\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(8.9443, device='cuda:0')\n",
            "i 15 j 13\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(9.4340, device='cuda:0')\n",
            "i 15 j 14\n",
            "tensor([False, False, False, False], device='cuda:0')\n",
            "dis: tensor(10., device='cuda:0')\n",
            "i 15 j 15\n",
            "tensor([False, False, False, False], device='cuda:0')\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "hawp环境配置\n",
        "1.记得下载ckpt文件hawpv3-imagenet-03a84.pth"
      ],
      "metadata": {
        "id": "p8ZjNpQarJEW"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "eTrashsPqnJP",
        "outputId": "425e5e29-56da-4eb2-ee1a-24051b4a61ec"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Cloning into 'hawp'...\n",
            "remote: Enumerating objects: 982, done.\u001b[K\n",
            "remote: Counting objects: 100% (705/705), done.\u001b[K\n",
            "remote: Compressing objects: 100% (465/465), done.\u001b[K\n",
            "remote: Total 982 (delta 293), reused 591 (delta 227), pack-reused 277\u001b[K\n",
            "Receiving objects: 100% (982/982), 6.80 MiB | 18.28 MiB/s, done.\n",
            "Resolving deltas: 100% (393/393), done.\n"
          ]
        }
      ],
      "source": [
        "!git clone https://github.com/cherubicXN/hawp.git"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!apt install ninja-build"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Ly4ncF5DrQYT",
        "outputId": "3870e091-af2d-4b1d-c32c-3226d860fb0d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Reading package lists... Done\n",
            "Building dependency tree... Done\n",
            "Reading state information... Done\n",
            "The following NEW packages will be installed:\n",
            "  ninja-build\n",
            "0 upgraded, 1 newly installed, 0 to remove and 18 not upgraded.\n",
            "Need to get 111 kB of archives.\n",
            "After this operation, 358 kB of additional disk space will be used.\n",
            "Get:1 http://archive.ubuntu.com/ubuntu jammy/universe amd64 ninja-build amd64 1.10.1-1 [111 kB]\n",
            "Fetched 111 kB in 0s (1,336 kB/s)\n",
            "Selecting previously unselected package ninja-build.\n",
            "(Reading database ... 120875 files and directories currently installed.)\n",
            "Preparing to unpack .../ninja-build_1.10.1-1_amd64.deb ...\n",
            "Unpacking ninja-build (1.10.1-1) ...\n",
            "Setting up ninja-build (1.10.1-1) ...\n",
            "Processing triggers for man-db (2.10.2-1) ...\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!cd hawp;pip install -e .;pip install -r requirement.;python -c \"import torch; print(torch.cuda.is_available())\""
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hkQkIzs6rg0e",
        "outputId": "d82dce76-f2ca-49d5-8373-edf27a7c4d82"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Obtaining file:///content/hawp\n",
            "  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "Requirement already satisfied: torch in /usr/local/lib/python3.10/dist-packages (from hawp==1.0) (2.0.1+cu118)\n",
            "Requirement already satisfied: torchvision in /usr/local/lib/python3.10/dist-packages (from hawp==1.0) (0.15.2+cu118)\n",
            "Requirement already satisfied: opencv-python in /usr/local/lib/python3.10/dist-packages (from hawp==1.0) (4.8.0.76)\n",
            "Requirement already satisfied: cython in /usr/local/lib/python3.10/dist-packages (from hawp==1.0) (3.0.3)\n",
            "Requirement already satisfied: matplotlib in /usr/local/lib/python3.10/dist-packages (from hawp==1.0) (3.7.1)\n",
            "Collecting yacs (from hawp==1.0)\n",
            "  Downloading yacs-0.1.8-py3-none-any.whl (14 kB)\n",
            "Requirement already satisfied: scikit-image in /usr/local/lib/python3.10/dist-packages (from hawp==1.0) (0.19.3)\n",
            "Requirement already satisfied: tqdm in /usr/local/lib/python3.10/dist-packages (from hawp==1.0) (4.66.1)\n",
            "Collecting python-json-logger (from hawp==1.0)\n",
            "  Downloading python_json_logger-2.0.7-py3-none-any.whl (8.1 kB)\n",
            "Requirement already satisfied: h5py in /usr/local/lib/python3.10/dist-packages (from hawp==1.0) (3.9.0)\n",
            "Requirement already satisfied: shapely in /usr/local/lib/python3.10/dist-packages (from hawp==1.0) (2.0.1)\n",
            "Requirement already satisfied: seaborn in /usr/local/lib/python3.10/dist-packages (from hawp==1.0) (0.12.2)\n",
            "Requirement already satisfied: easydict in /usr/local/lib/python3.10/dist-packages (from hawp==1.0) (1.10)\n",
            "Requirement already satisfied: numpy>=1.17.3 in /usr/local/lib/python3.10/dist-packages (from h5py->hawp==1.0) (1.23.5)\n",
            "Requirement already satisfied: contourpy>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib->hawp==1.0) (1.1.1)\n",
            "Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.10/dist-packages (from matplotlib->hawp==1.0) (0.12.1)\n",
            "Requirement already satisfied: fonttools>=4.22.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib->hawp==1.0) (4.43.1)\n",
            "Requirement already satisfied: kiwisolver>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib->hawp==1.0) (1.4.5)\n",
            "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib->hawp==1.0) (23.2)\n",
            "Requirement already satisfied: pillow>=6.2.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib->hawp==1.0) (9.4.0)\n",
            "Requirement already satisfied: pyparsing>=2.3.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib->hawp==1.0) (3.1.1)\n",
            "Requirement already satisfied: python-dateutil>=2.7 in /usr/local/lib/python3.10/dist-packages (from matplotlib->hawp==1.0) (2.8.2)\n",
            "Requirement already satisfied: scipy>=1.4.1 in /usr/local/lib/python3.10/dist-packages (from scikit-image->hawp==1.0) (1.11.3)\n",
            "Requirement already satisfied: networkx>=2.2 in /usr/local/lib/python3.10/dist-packages (from scikit-image->hawp==1.0) (3.1)\n",
            "Requirement already satisfied: imageio>=2.4.1 in /usr/local/lib/python3.10/dist-packages (from scikit-image->hawp==1.0) (2.31.5)\n",
            "Requirement already satisfied: tifffile>=2019.7.26 in /usr/local/lib/python3.10/dist-packages (from scikit-image->hawp==1.0) (2023.9.26)\n",
            "Requirement already satisfied: PyWavelets>=1.1.1 in /usr/local/lib/python3.10/dist-packages (from scikit-image->hawp==1.0) (1.4.1)\n",
            "Requirement already satisfied: pandas>=0.25 in /usr/local/lib/python3.10/dist-packages (from seaborn->hawp==1.0) (1.5.3)\n",
            "Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from torch->hawp==1.0) (3.12.4)\n",
            "Requirement already satisfied: typing-extensions in /usr/local/lib/python3.10/dist-packages (from torch->hawp==1.0) (4.5.0)\n",
            "Requirement already satisfied: sympy in /usr/local/lib/python3.10/dist-packages (from torch->hawp==1.0) (1.12)\n",
            "Requirement already satisfied: jinja2 in /usr/local/lib/python3.10/dist-packages (from torch->hawp==1.0) (3.1.2)\n",
            "Requirement already satisfied: triton==2.0.0 in /usr/local/lib/python3.10/dist-packages (from torch->hawp==1.0) (2.0.0)\n",
            "Requirement already satisfied: cmake in /usr/local/lib/python3.10/dist-packages (from triton==2.0.0->torch->hawp==1.0) (3.27.6)\n",
            "Requirement already satisfied: lit in /usr/local/lib/python3.10/dist-packages (from triton==2.0.0->torch->hawp==1.0) (17.0.2)\n",
            "Requirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from torchvision->hawp==1.0) (2.31.0)\n",
            "Requirement already satisfied: PyYAML in /usr/local/lib/python3.10/dist-packages (from yacs->hawp==1.0) (6.0.1)\n",
            "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.10/dist-packages (from pandas>=0.25->seaborn->hawp==1.0) (2023.3.post1)\n",
            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil>=2.7->matplotlib->hawp==1.0) (1.16.0)\n",
            "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2->torch->hawp==1.0) (2.1.3)\n",
            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests->torchvision->hawp==1.0) (3.3.0)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->torchvision->hawp==1.0) (3.4)\n",
            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests->torchvision->hawp==1.0) (2.0.6)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests->torchvision->hawp==1.0) (2023.7.22)\n",
            "Requirement already satisfied: mpmath>=0.19 in /usr/local/lib/python3.10/dist-packages (from sympy->torch->hawp==1.0) (1.3.0)\n",
            "Installing collected packages: yacs, python-json-logger, hawp\n",
            "  Running setup.py develop for hawp\n",
            "Successfully installed hawp-1.0 python-json-logger-2.0.7 yacs-0.1.8\n",
            "Requirement already satisfied: opencv-python in /usr/local/lib/python3.10/dist-packages (from -r requirement.txt (line 1)) (4.8.0.76)\n",
            "Requirement already satisfied: cython in /usr/local/lib/python3.10/dist-packages (from -r requirement.txt (line 2)) (3.0.3)\n",
            "Requirement already satisfied: matplotlib in /usr/local/lib/python3.10/dist-packages (from -r requirement.txt (line 3)) (3.7.1)\n",
            "Requirement already satisfied: yacs in /usr/local/lib/python3.10/dist-packages (from -r requirement.txt (line 4)) (0.1.8)\n",
            "Requirement already satisfied: scikit-image in /usr/local/lib/python3.10/dist-packages (from -r requirement.txt (line 5)) (0.19.3)\n",
            "Requirement already satisfied: tqdm in /usr/local/lib/python3.10/dist-packages (from -r requirement.txt (line 6)) (4.66.1)\n",
            "Requirement already satisfied: python-json-logger in /usr/local/lib/python3.10/dist-packages (from -r requirement.txt (line 7)) (2.0.7)\n",
            "Requirement already satisfied: h5py in /usr/local/lib/python3.10/dist-packages (from -r requirement.txt (line 8)) (3.9.0)\n",
            "Requirement already satisfied: shapely in /usr/local/lib/python3.10/dist-packages (from -r requirement.txt (line 9)) (2.0.1)\n",
            "Collecting pycolmap (from -r requirement.txt (line 10))\n",
            "  Downloading pycolmap-0.4.0-cp310-cp310-manylinux2014_x86_64.whl (14.4 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m14.4/14.4 MB\u001b[0m \u001b[31m66.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: seaborn in /usr/local/lib/python3.10/dist-packages (from -r requirement.txt (line 11)) (0.12.2)\n",
            "Collecting kornia (from -r requirement.txt (line 12))\n",
            "  Downloading kornia-0.7.0-py2.py3-none-any.whl (705 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m705.7/705.7 kB\u001b[0m \u001b[31m53.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: easydict in /usr/local/lib/python3.10/dist-packages (from -r requirement.txt (line 13)) (1.10)\n",
            "Requirement already satisfied: numpy>=1.21.2 in /usr/local/lib/python3.10/dist-packages (from opencv-python->-r requirement.txt (line 1)) (1.23.5)\n",
            "Requirement already satisfied: contourpy>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib->-r requirement.txt (line 3)) (1.1.1)\n",
            "Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.10/dist-packages (from matplotlib->-r requirement.txt (line 3)) (0.12.1)\n",
            "Requirement already satisfied: fonttools>=4.22.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib->-r requirement.txt (line 3)) (4.43.1)\n",
            "Requirement already satisfied: kiwisolver>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib->-r requirement.txt (line 3)) (1.4.5)\n",
            "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib->-r requirement.txt (line 3)) (23.2)\n",
            "Requirement already satisfied: pillow>=6.2.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib->-r requirement.txt (line 3)) (9.4.0)\n",
            "Requirement already satisfied: pyparsing>=2.3.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib->-r requirement.txt (line 3)) (3.1.1)\n",
            "Requirement already satisfied: python-dateutil>=2.7 in /usr/local/lib/python3.10/dist-packages (from matplotlib->-r requirement.txt (line 3)) (2.8.2)\n",
            "Requirement already satisfied: PyYAML in /usr/local/lib/python3.10/dist-packages (from yacs->-r requirement.txt (line 4)) (6.0.1)\n",
            "Requirement already satisfied: scipy>=1.4.1 in /usr/local/lib/python3.10/dist-packages (from scikit-image->-r requirement.txt (line 5)) (1.11.3)\n",
            "Requirement already satisfied: networkx>=2.2 in /usr/local/lib/python3.10/dist-packages (from scikit-image->-r requirement.txt (line 5)) (3.1)\n",
            "Requirement already satisfied: imageio>=2.4.1 in /usr/local/lib/python3.10/dist-packages (from scikit-image->-r requirement.txt (line 5)) (2.31.5)\n",
            "Requirement already satisfied: tifffile>=2019.7.26 in /usr/local/lib/python3.10/dist-packages (from scikit-image->-r requirement.txt (line 5)) (2023.9.26)\n",
            "Requirement already satisfied: PyWavelets>=1.1.1 in /usr/local/lib/python3.10/dist-packages (from scikit-image->-r requirement.txt (line 5)) (1.4.1)\n",
            "Requirement already satisfied: pandas>=0.25 in /usr/local/lib/python3.10/dist-packages (from seaborn->-r requirement.txt (line 11)) (1.5.3)\n",
            "Requirement already satisfied: torch>=1.9.1 in /usr/local/lib/python3.10/dist-packages (from kornia->-r requirement.txt (line 12)) (2.0.1+cu118)\n",
            "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.10/dist-packages (from pandas>=0.25->seaborn->-r requirement.txt (line 11)) (2023.3.post1)\n",
            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil>=2.7->matplotlib->-r requirement.txt (line 3)) (1.16.0)\n",
            "Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from torch>=1.9.1->kornia->-r requirement.txt (line 12)) (3.12.4)\n",
            "Requirement already satisfied: typing-extensions in /usr/local/lib/python3.10/dist-packages (from torch>=1.9.1->kornia->-r requirement.txt (line 12)) (4.5.0)\n",
            "Requirement already satisfied: sympy in /usr/local/lib/python3.10/dist-packages (from torch>=1.9.1->kornia->-r requirement.txt (line 12)) (1.12)\n",
            "Requirement already satisfied: jinja2 in /usr/local/lib/python3.10/dist-packages (from torch>=1.9.1->kornia->-r requirement.txt (line 12)) (3.1.2)\n",
            "Requirement already satisfied: triton==2.0.0 in /usr/local/lib/python3.10/dist-packages (from torch>=1.9.1->kornia->-r requirement.txt (line 12)) (2.0.0)\n",
            "Requirement already satisfied: cmake in /usr/local/lib/python3.10/dist-packages (from triton==2.0.0->torch>=1.9.1->kornia->-r requirement.txt (line 12)) (3.27.6)\n",
            "Requirement already satisfied: lit in /usr/local/lib/python3.10/dist-packages (from triton==2.0.0->torch>=1.9.1->kornia->-r requirement.txt (line 12)) (17.0.2)\n",
            "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2->torch>=1.9.1->kornia->-r requirement.txt (line 12)) (2.1.3)\n",
            "Requirement already satisfied: mpmath>=0.19 in /usr/local/lib/python3.10/dist-packages (from sympy->torch>=1.9.1->kornia->-r requirement.txt (line 12)) (1.3.0)\n",
            "Installing collected packages: pycolmap, kornia\n",
            "Successfully installed kornia-0.7.0 pycolmap-0.4.0\n",
            "True\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!python -m hawp.ssl.predict --ckpt hawpv3-imagenet-03a84.pth --threshold 0.05 --img 33044.jpg --device='cuda'"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "L9bKuYbasvty",
        "outputId": "bc874fff-5c43-4bd9-be7d-5377972a15d0"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "  0% 0/1 [00:00<?, ?it/s]Figure(1400x2097.82)\n",
            "100% 1/1 [00:06<00:00,  6.81s/it]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "sam环境配置\n",
        "https://github.com/facebookresearch/segment-anything#model-checkpoints"
      ],
      "metadata": {
        "id": "j6iEX2j6tt0X"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install git+https://github.com/facebookresearch/segment-anything.git"
      ],
      "metadata": {
        "id": "m_XPJwBKsvub"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install opencv-python pycocotools matplotlib onnxruntime onnx"
      ],
      "metadata": {
        "id": "D4eh7pDAsvxT"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "sam&&hawp"
      ],
      "metadata": {
        "id": "WXLPOfVNt8EF"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "备忘录\n",
        "1.偶尔报错 xx.so no such file 先用python .py运行，再运行ipynb里的代码，不知道原理，但是问题能解决"
      ],
      "metadata": {
        "id": "kDK2i4Y4s8fv"
      }
    }
  ]
}