{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
"name": "pointnet.ipynb",
"provenance": [],
"collapsed_sections": []
},
"kernelspec": {
"name": "python3",
"display_name": "Python 3"
},
"accelerator": "GPU"
},
"cells": [
{
"cell_type": "code",
"metadata": {
"id": "yL-v2aZ-va31"
},
"source": [
"# Define some helper functions for downloading pretrained model\r\n",
"# taken from this StackOverflow answer: https://stackoverflow.com/a/39225039\r\n",
"import requests\r\n",
"\r\n",
"def download_file_from_google_drive(id, destination):\r\n",
" URL = \"https://docs.google.com/uc?export=download\"\r\n",
"\r\n",
" session = requests.Session()\r\n",
"\r\n",
" response = session.get(URL, params = { 'id' : id }, stream = True)\r\n",
" token = get_confirm_token(response)\r\n",
"\r\n",
" if token:\r\n",
" params = { 'id' : id, 'confirm' : token }\r\n",
" response = session.get(URL, params = params, stream = True)\r\n",
"\r\n",
" save_response_content(response, destination) \r\n",
"\r\n",
"def get_confirm_token(response):\r\n",
" for key, value in response.cookies.items():\r\n",
" if key.startswith('download_warning'):\r\n",
" return value\r\n",
"\r\n",
" return None\r\n",
"\r\n",
"def save_response_content(response, destination):\r\n",
" CHUNK_SIZE = 32768\r\n",
"\r\n",
" with open(destination, \"wb\") as f:\r\n",
" for chunk in response.iter_content(CHUNK_SIZE):\r\n",
" if chunk: # filter out keep-alive new chunks\r\n",
" f.write(chunk)"
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "3x14XnVyvqQT",
"outputId": "8c498939-12d8-4e52-e4d9-23c375492ae3"
},
"source": [
"# download and unzip...\r\n",
"def download_all():\r\n",
" file_id = '1DAmlftwj9UEOI1S2J1YycnUtM392Sk6d'\r\n",
" destination = './data/ModelNet40_PLY.zip'\r\n",
" download_file_from_google_drive(file_id, destination)\r\n",
"\r\n",
" file_id = '1KlhouSbf7j3lpKWUb5l6Y0K74MNf0Fen'\r\n",
" destination = './data/ModelNet10_PLY.zip'\r\n",
" download_file_from_google_drive(file_id, destination)\r\n",
"\r\n",
"# Launch at starting session\r\n",
"download_all()\r\n",
"!unzip ./data/ModelNet40_PLY.zip -d ./data/\r\n",
"!unzip ./data/ModelNet10_PLY.zip -d ./data/"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"text": [
"\u001b[1;30;43mLe flux de sortie a été tronqué et ne contient que les 5000 dernières lignes.\u001b[0m\n",
" inflating: ./data/ModelNet40_PLY/xbox/train/xbox_0035.ply \n",
" inflating: ./data/ModelNet40_PLY/xbox/train/xbox_0036.ply \n",
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"Archive: ./data/ModelNet10_PLY.zip\n",
" creating: ./data/ModelNet10_PLY/\n",
" creating: ./data/ModelNet10_PLY/bathtub/\n",
" creating: ./data/ModelNet10_PLY/bathtub/test/\n",
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"name": "stdout"
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "dd6JSnzV0ixv"
},
"source": [
"#\r\n",
"#\r\n",
"# 0===========================================================0\r\n",
"# | TP6 PointNet for point cloud classification |\r\n",
"# 0===========================================================0\r\n",
"#\r\n",
"#\r\n",
"# ------------------------------------------------------------------------------------------\r\n",
"#\r\n",
"# Jean-Emmanuel DESCHAUD - 12/01/2021\r\n",
"#\r\n",
"\r\n",
"import numpy as np\r\n",
"import random\r\n",
"import math\r\n",
"import os\r\n",
"import time\r\n",
"import torch\r\n",
"import scipy.spatial.distance\r\n",
"from torch.utils.data import Dataset, DataLoader\r\n",
"from torchvision import transforms, utils\r\n",
"import torch.nn as nn\r\n",
"import torch.nn.functional as F\r\n",
"\r\n",
"# Import functions to read and write ply files\r\n",
"from ply import write_ply, read_ply"
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "HGJEdzEPEzJK"
},
"source": [
"def rand_rotation_matrix(deflection=1.0, randnums=None):\r\n",
" \"\"\"\r\n",
" Creates a random rotation matrix.\r\n",
" \r\n",
" deflection: the magnitude of the rotation. For 0, no rotation; for 1, competely random\r\n",
" rotation. Small deflection => small perturbation.\r\n",
" randnums: 3 random numbers in the range [0, 1]. If `None`, they will be auto-generated.\r\n",
" \"\"\"\r\n",
" # from http://www.realtimerendering.com/resources/GraphicsGems/gemsiii/rand_rotation.c\r\n",
" \r\n",
" if randnums is None:\r\n",
" randnums = np.random.uniform(size=(3,))\r\n",
" \r\n",
" theta, phi, z = randnums\r\n",
" \r\n",
" theta = theta * 2.0*deflection*np.pi # Rotation about the pole (Z).\r\n",
" phi = phi * 2.0*np.pi # For direction of pole deflection.\r\n",
" z = z * 2.0*deflection # For magnitude of pole deflection.\r\n",
" \r\n",
" # Compute a vector V used for distributing points over the sphere\r\n",
" # via the reflection I - V Transpose(V). This formulation of V\r\n",
" # will guarantee that if x[1] and x[2] are uniformly distributed,\r\n",
" # the reflected points will be uniform on the sphere. Note that V\r\n",
" # has length sqrt(2) to eliminate the 2 in the Householder matrix.\r\n",
" \r\n",
" r = np.sqrt(z)\r\n",
" Vx, Vy, Vz = V = (\r\n",
" np.sin(phi) * r,\r\n",
" np.cos(phi) * r,\r\n",
" np.sqrt(2.0 - z)\r\n",
" )\r\n",
" \r\n",
" st = np.sin(theta)\r\n",
" ct = np.cos(theta)\r\n",
" \r\n",
" R = np.array(((ct, st, 0), (-st, ct, 0), (0, 0, 1)))\r\n",
" \r\n",
" # Construct the rotation matrix ( V Transpose(V) - I ) R.\r\n",
" \r\n",
" M = (np.outer(V, V) - np.eye(3)).dot(R)\r\n",
" return M"
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "P3vAXXGxvX6a"
},
"source": [
"class RandomRotation_z(object):\r\n",
" def __call__(self, pointcloud):\r\n",
" theta = random.random() * 2. * math.pi\r\n",
" rot_matrix = np.array([[ math.cos(theta), -math.sin(theta), 0],\r\n",
" [ math.sin(theta), math.cos(theta), 0],\r\n",
" [0, 0, 1]])\r\n",
" rot_pointcloud = rot_matrix.dot(pointcloud.T).T\r\n",
" return rot_pointcloud\r\n",
"\r\n",
"class RandomScaling(object):\r\n",
" def __call__(self, pointcloud):\r\n",
" scale = 0.5 + 10 * random.random()\r\n",
" scale_matrix = scale * np.eye(3)\r\n",
" scaled_pointcloud = scale_matrix.dot(pointcloud.T).T\r\n",
" return scaled_pointcloud\r\n",
"\r\n",
"class RandomRotation(object):\r\n",
" def __init__(self, deflection):\r\n",
" self.deflection = deflection\r\n",
"\r\n",
" def __call__(self, pointcloud):\r\n",
" rot_matrix = rand_rotation_matrix(deflection=self.deflection)\r\n",
" rot_pointcloud = rot_matrix.dot(pointcloud.T).T\r\n",
" return rot_pointcloud\r\n",
"\r\n",
"class RandomRotation_z(object):\r\n",
" def __call__(self, pointcloud):\r\n",
" theta = random.random() * 2. * math.pi\r\n",
" rot_matrix = np.array([[ math.cos(theta), -math.sin(theta), 0],\r\n",
" [ math.sin(theta), math.cos(theta), 0],\r\n",
" [0, 0, 1]])\r\n",
" rot_pointcloud = rot_matrix.dot(pointcloud.T).T\r\n",
" return rot_pointcloud\r\n",
"\r\n",
"class RandomNoise(object):\r\n",
" def __call__(self, pointcloud):\r\n",
" noise = np.random.normal(0, 0.02, (pointcloud.shape))\r\n",
" noisy_pointcloud = pointcloud + noise\r\n",
" return noisy_pointcloud\r\n",
"\r\n",
"class ShufflePoints(object):\r\n",
" def __call__(self, pointcloud):\r\n",
" np.random.shuffle(pointcloud)\r\n",
" return pointcloud\r\n",
"\r\n",
"class ToTensor(object):\r\n",
" def __call__(self, pointcloud):\r\n",
" return torch.from_numpy(pointcloud)\r\n",
"\r\n",
"\r\n",
"def default_transforms():\r\n",
" # return transforms.Compose([RandomRotation(),RandomNoise(),ShufflePoints(),ToTensor()])\r\n",
" return transforms.Compose([RandomRotation_z(),RandomNoise(),ShufflePoints(),ToTensor()])\r\n",
"\r\n",
"\r\n",
"class PointCloudData(Dataset):\r\n",
" def __init__(self, root_dir, folder=\"train\", transform=default_transforms()):\r\n",
" self.root_dir = root_dir\r\n",
" folders = [dir for dir in sorted(os.listdir(root_dir)) if os.path.isdir(root_dir+\"/\"+dir)]\r\n",
" self.classes = {folder: i for i, folder in enumerate(folders)}\r\n",
" self.transforms = transform\r\n",
" self.files = []\r\n",
" for category in self.classes.keys():\r\n",
" new_dir = root_dir+\"/\"+category+\"/\"+folder\r\n",
" for file in os.listdir(new_dir):\r\n",
" if file.endswith('.ply'):\r\n",
" sample = {}\r\n",
" sample['ply_path'] = new_dir+\"/\"+file\r\n",
" sample['category'] = category\r\n",
" self.files.append(sample)\r\n",
"\r\n",
" def __len__(self):\r\n",
" return len(self.files)\r\n",
"\r\n",
" def __getitem__(self, idx):\r\n",
" ply_path = self.files[idx]['ply_path']\r\n",
" category = self.files[idx]['category']\r\n",
" data = read_ply(ply_path)\r\n",
" pointcloud = self.transforms(np.vstack((data['x'], data['y'], data['z'])).T)\r\n",
" return {'pointcloud': pointcloud, 'category': self.classes[category]}\r\n",
"\r\n",
"\r\n",
"\r\n",
"class PointMLP(nn.Module):\r\n",
" def __init__(self, classes = 40):\r\n",
" super().__init__()\r\n",
" self.flatten = nn.Flatten()\r\n",
"\r\n",
" self.fc1 = nn.Linear(3072, 512)\r\n",
" self.fc2 = nn.Linear(512, 256)\r\n",
" self.fc3 = nn.Linear(256, classes)\r\n",
"\r\n",
" self.dropout = nn.Dropout(0.3)\r\n",
" self.bn1 = nn.BatchNorm1d(512)\r\n",
" self.bn2 = nn.BatchNorm1d(256)\r\n",
"\r\n",
" self.logsoftmax = nn.LogSoftmax(dim=1)\r\n",
"\r\n",
" def forward(self, input):\r\n",
" x = self.flatten(input)\r\n",
" x = F.relu(self.bn1(self.fc1(x)))\r\n",
" x = F.relu(self.bn2(self.dropout(self.fc2(x))))\r\n",
" x = self.fc3(x)\r\n",
" return self.logsoftmax(x)\r\n",
"\r\n",
"\r\n",
"class PointNetBasic(nn.Module):\r\n",
" def __init__(self, classes = 40):\r\n",
" super().__init__()\r\n",
" self.flatten = nn.Flatten()\r\n",
"\r\n",
" self.conv1 = torch.nn.Conv1d(3, 64, 1)\r\n",
" self.conv2 = torch.nn.Conv1d(64, 64, 1)\r\n",
" self.conv3 = torch.nn.Conv1d(64, 64, 1)\r\n",
" self.conv4 = torch.nn.Conv1d(64, 128, 1)\r\n",
" self.conv5 = torch.nn.Conv1d(128, 1024, 1)\r\n",
"\r\n",
" self.maxpool = nn.MaxPool1d(1024)\r\n",
"\r\n",
" self.fc1 = nn.Linear(1024, 512)\r\n",
" self.fc2 = nn.Linear(512, 256)\r\n",
" self.fc3 = nn.Linear(256, classes)\r\n",
"\r\n",
" self.dropout = nn.Dropout(0.3)\r\n",
" self.bn1 = nn.BatchNorm1d(64)\r\n",
" self.bn2 = nn.BatchNorm1d(64)\r\n",
" self.bn3 = nn.BatchNorm1d(64)\r\n",
" self.bn4 = nn.BatchNorm1d(128)\r\n",
" self.bn5 = nn.BatchNorm1d(1024)\r\n",
" self.bn6 = nn.BatchNorm1d(512)\r\n",
" self.bn7 = nn.BatchNorm1d(256)\r\n",
"\r\n",
" self.logsoftmax = nn.LogSoftmax(dim=1)\r\n",
"\r\n",
" def forward(self, input):\r\n",
"\r\n",
" x = F.relu(self.bn1(self.conv1(input)))\r\n",
" x = F.relu(self.bn2(self.conv2(x)))\r\n",
"\r\n",
" x = F.relu(self.bn3(self.conv3(x)))\r\n",
" x = F.relu(self.bn4(self.conv4(x)))\r\n",
" x = F.relu(self.bn5(self.conv5(x)))\r\n",
"\r\n",
" x = self.maxpool(x)\r\n",
" x = x.view(-1, 1024)\r\n",
"\r\n",
" x = F.relu(self.bn6(self.fc1(x)))\r\n",
" x = F.relu(self.bn7(self.dropout(self.fc2(x))))\r\n",
" x = self.fc3(x)\r\n",
"\r\n",
" return self.logsoftmax(x)\r\n",
" \r\n",
" \r\n",
" \r\n",
"class Tnet(nn.Module):\r\n",
" def __init__(self, k=3):\r\n",
" super().__init__()\r\n",
" self.conv1 = torch.nn.Conv1d(k, 64, 1)\r\n",
" self.conv2 = torch.nn.Conv1d(64, 128, 1)\r\n",
" self.conv3 = torch.nn.Conv1d(128, 1024, 1)\r\n",
"\r\n",
" self.maxpool = nn.MaxPool1d(1024)\r\n",
"\r\n",
" self.fc1 = nn.Linear(1024, 512)\r\n",
" self.fc2 = nn.Linear(512, 256)\r\n",
" self.fc3 = nn.Linear(256, k*k)\r\n",
" \r\n",
" self.bn1 = nn.BatchNorm1d(64)\r\n",
" self.bn2 = nn.BatchNorm1d(128)\r\n",
" self.bn3 = nn.BatchNorm1d(1024)\r\n",
" self.bn4 = nn.BatchNorm1d(512)\r\n",
" self.bn5 = nn.BatchNorm1d(256)\r\n",
"\r\n",
" self.k = k\r\n",
"\r\n",
" def forward(self, input):\r\n",
" x = F.relu(self.bn1(self.conv1(input)))\r\n",
" x = F.relu(self.bn2(self.conv2(x)))\r\n",
" x = F.relu(self.bn3(self.conv3(x)))\r\n",
"\r\n",
" x = self.maxpool(x)\r\n",
" x = x.view(-1, 1024)\r\n",
"\r\n",
" x = F.relu(self.bn4(self.fc1(x)))\r\n",
" x = F.relu(self.bn5(self.fc2(x)))\r\n",
" x = self.fc3(x)\r\n",
"\r\n",
" id3x3 = torch.eye(self.k, requires_grad=True).flatten().repeat(x.shape[0], 1)\r\n",
" if x.is_cuda:\r\n",
" id3x3 = id3x3.cuda()\r\n",
" x = x + id3x3\r\n",
" x = x.view(-1, self.k, self.k)\r\n",
"\r\n",
" return x\r\n",
"\r\n",
"\r\n",
"class PointNetFull(nn.Module):\r\n",
" def __init__(self, classes = 40):\r\n",
" super().__init__()\r\n",
"\r\n",
" self.tnet = Tnet(k=3)\r\n",
"\r\n",
" self.flatten = nn.Flatten()\r\n",
"\r\n",
" self.conv1 = torch.nn.Conv1d(3, 64, 1)\r\n",
" self.conv2 = torch.nn.Conv1d(64, 64, 1)\r\n",
" self.conv3 = torch.nn.Conv1d(64, 64, 1)\r\n",
" self.conv4 = torch.nn.Conv1d(64, 128, 1)\r\n",
" self.conv5 = torch.nn.Conv1d(128, 1024, 1)\r\n",
"\r\n",
" self.maxpool = nn.MaxPool1d(1024)\r\n",
"\r\n",
" self.fc1 = nn.Linear(1024, 512)\r\n",
" self.fc2 = nn.Linear(512, 256)\r\n",
" self.fc3 = nn.Linear(256, classes)\r\n",
"\r\n",
" self.dropout = nn.Dropout(0.3)\r\n",
" self.bn1 = nn.BatchNorm1d(64)\r\n",
" self.bn2 = nn.BatchNorm1d(64)\r\n",
" self.bn3 = nn.BatchNorm1d(64)\r\n",
" self.bn4 = nn.BatchNorm1d(128)\r\n",
" self.bn5 = nn.BatchNorm1d(1024)\r\n",
" self.bn6 = nn.BatchNorm1d(512)\r\n",
" self.bn7 = nn.BatchNorm1d(256)\r\n",
"\r\n",
" self.logsoftmax = nn.LogSoftmax(dim=1)\r\n",
"\r\n",
" def forward(self, input):\r\n",
"\r\n",
" tmat = self.tnet(input)\r\n",
" x = torch.matmul(tmat, input)\r\n",
"\r\n",
" x = F.relu(self.bn1(self.conv1(input)))\r\n",
" x = F.relu(self.bn2(self.conv2(x)))\r\n",
"\r\n",
" x = F.relu(self.bn3(self.conv3(x)))\r\n",
" x = F.relu(self.bn4(self.conv4(x)))\r\n",
" x = F.relu(self.bn5(self.conv5(x)))\r\n",
"\r\n",
" x = self.maxpool(x)\r\n",
" x = x.view(-1, 1024)\r\n",
"\r\n",
" x = F.relu(self.bn6(self.fc1(x)))\r\n",
" x = F.relu(self.bn7(self.dropout(self.fc2(x))))\r\n",
" x = self.fc3(x)\r\n",
"\r\n",
" return self.logsoftmax(x), tmat\r\n",
"\r\n",
"\r\n",
"def basic_loss(outputs, labels):\r\n",
" criterion = torch.nn.NLLLoss()\r\n",
" bs=outputs.size(0)\r\n",
" return criterion(outputs, labels)\r\n",
"\r\n",
"def pointnet_full_loss(outputs, labels, m3x3, alpha = 0.001):\r\n",
" criterion = torch.nn.NLLLoss()\r\n",
" bs=outputs.size(0)\r\n",
" id3x3 = torch.eye(3, requires_grad=True).repeat(bs,1,1)\r\n",
" if outputs.is_cuda:\r\n",
" id3x3=id3x3.cuda()\r\n",
" diff3x3 = id3x3-torch.bmm(m3x3,m3x3.transpose(1,2))\r\n",
" return criterion(outputs, labels) + alpha * (torch.norm(diff3x3)) / float(bs)\r\n",
"\r\n",
"\r\n",
"def train(model, device, train_loader, test_loader=None, epochs=250):\r\n",
" optimizer = torch.optim.Adam(model.parameters(), lr=0.001)\r\n",
" scheduler = torch.optim.lr_scheduler.StepLR(optimizer, step_size=20, gamma=0.5)\r\n",
" val_accs = []\r\n",
" loss=0\r\n",
" for epoch in range(epochs): \r\n",
" model.train()\r\n",
" for i, data in enumerate(train_loader, 0):\r\n",
" inputs, labels = data['pointcloud'].to(device).float(), data['category'].to(device)\r\n",
" optimizer.zero_grad()\r\n",
" outputs = model(inputs.transpose(1,2))\r\n",
" # outputs, m3x3 = model(inputs.transpose(1,2))\r\n",
" loss = basic_loss(outputs, labels)\r\n",
" # loss = pointnet_full_loss(outputs, labels, m3x3)\r\n",
" loss.backward()\r\n",
" optimizer.step()\r\n",
"\r\n",
" model.eval()\r\n",
" correct = total = 0\r\n",
" if test_loader:\r\n",
" with torch.no_grad():\r\n",
" for data in test_loader:\r\n",
" inputs, labels = data['pointcloud'].to(device).float(), data['category'].to(device)\r\n",
" outputs = model(inputs.transpose(1,2))\r\n",
" # outputs, __ = model(inputs.transpose(1,2))\r\n",
" _, predicted = torch.max(outputs.data, 1)\r\n",
" total += labels.size(0)\r\n",
" correct += (predicted == labels).sum().item()\r\n",
" val_acc = 100. * correct / total\r\n",
" val_accs.append(val_acc)\r\n",
" print('Epoch: %d, Loss: %.3f, Test accuracy: %.1f %%' %(epoch+1, loss, val_acc))\r\n",
"\r\n",
" scheduler.step()\r\n",
" return val_accs"
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "ERxlixmVyHf5",
"outputId": "841a6f20-1611-45e0-993f-5ce9797c7989"
},
"source": [
"t0 = time.time()\r\n",
" \r\n",
"train_ds = PointCloudData(\"./data/ModelNet40_PLY\")\r\n",
"test_ds = PointCloudData(\"./data/ModelNet40_PLY\", folder='test')\r\n",
"\r\n",
"inv_classes = {i: cat for cat, i in train_ds.classes.items()}\r\n",
"print(\"Classes: \", inv_classes)\r\n",
"print('Train dataset size: ', len(train_ds))\r\n",
"print('Test dataset size: ', len(test_ds))\r\n",
"print('Number of classes: ', len(train_ds.classes))\r\n",
"print('Sample pointcloud shape: ', train_ds[0]['pointcloud'].size())\r\n",
"\r\n",
"train_loader = DataLoader(dataset=train_ds, batch_size=32, shuffle=True)\r\n",
"test_loader = DataLoader(dataset=test_ds, batch_size=32)\r\n",
"\r\n",
"# model = PointMLP()\r\n",
"model = PointNetBasic()\r\n",
"# model = PointNetFull()\r\n",
"\r\n",
"model_parameters = filter(lambda p: p.requires_grad, model.parameters())\r\n",
"print(\"Number of parameters in the Neural Networks: \", sum([np.prod(p.size()) for p in model_parameters]))\r\n",
"\r\n",
"device = torch.device(\"cuda:0\" if torch.cuda.is_available() else \"cpu\") \r\n",
"print(\"Device: \", device)\r\n",
"model.to(device);\r\n",
"\r\n",
"valaccs_1 = train(model, device, train_loader, test_loader, epochs = 50)\r\n",
"\r\n",
"print(\"Total time for training : \", time.time()-t0)"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"text": [
"Classes: {0: 'airplane', 1: 'bathtub', 2: 'bed', 3: 'bench', 4: 'bookshelf', 5: 'bottle', 6: 'bowl', 7: 'car', 8: 'chair', 9: 'cone', 10: 'cup', 11: 'curtain', 12: 'desk', 13: 'door', 14: 'dresser', 15: 'flower_pot', 16: 'glass_box', 17: 'guitar', 18: 'keyboard', 19: 'lamp', 20: 'laptop', 21: 'mantel', 22: 'monitor', 23: 'night_stand', 24: 'person', 25: 'piano', 26: 'plant', 27: 'radio', 28: 'range_hood', 29: 'sink', 30: 'sofa', 31: 'stairs', 32: 'stool', 33: 'table', 34: 'tent', 35: 'toilet', 36: 'tv_stand', 37: 'vase', 38: 'wardrobe', 39: 'xbox'}\n",
"Train dataset size: 9843\n",
"Test dataset size: 2468\n",
"Number of classes: 40\n",
"Sample pointcloud shape: torch.Size([1024, 3])\n",
"Number of parameters in the Neural Networks: 819624\n",
"Device: cuda:0\n",
"Epoch: 1, Loss: 1.110, Test accuracy: 56.0 %\n",
"Epoch: 2, Loss: 1.203, Test accuracy: 72.5 %\n",
"Epoch: 3, Loss: 0.816, Test accuracy: 72.6 %\n",
"Epoch: 4, Loss: 0.896, Test accuracy: 72.3 %\n",
"Epoch: 5, Loss: 0.804, Test accuracy: 68.8 %\n",
"Epoch: 6, Loss: 0.971, Test accuracy: 66.7 %\n",
"Epoch: 7, Loss: 0.879, Test accuracy: 61.7 %\n",
"Epoch: 8, Loss: 0.554, Test accuracy: 74.8 %\n",
"Epoch: 9, Loss: 0.322, Test accuracy: 76.3 %\n",
"Epoch: 10, Loss: 0.355, Test accuracy: 78.9 %\n",
"Epoch: 11, Loss: 0.795, Test accuracy: 76.6 %\n",
"Epoch: 12, Loss: 0.540, Test accuracy: 77.5 %\n",
"Epoch: 13, Loss: 0.598, Test accuracy: 78.6 %\n",
"Epoch: 14, Loss: 0.759, Test accuracy: 77.4 %\n",
"Epoch: 15, Loss: 0.423, Test accuracy: 80.6 %\n",
"Epoch: 16, Loss: 1.356, Test accuracy: 78.1 %\n",
"Epoch: 17, Loss: 0.104, Test accuracy: 79.4 %\n",
"Epoch: 18, Loss: 0.510, Test accuracy: 81.2 %\n",
"Epoch: 19, Loss: 0.731, Test accuracy: 78.3 %\n",
"Epoch: 20, Loss: 0.401, Test accuracy: 81.8 %\n",
"Epoch: 21, Loss: 0.489, Test accuracy: 83.3 %\n",
"Epoch: 22, Loss: 0.428, Test accuracy: 82.8 %\n",
"Epoch: 23, Loss: 0.877, Test accuracy: 82.5 %\n",
"Epoch: 24, Loss: 0.549, Test accuracy: 84.0 %\n",
"Epoch: 25, Loss: 0.368, Test accuracy: 82.8 %\n",
"Epoch: 26, Loss: 0.297, Test accuracy: 84.6 %\n",
"Epoch: 27, Loss: 0.526, Test accuracy: 83.7 %\n",
"Epoch: 28, Loss: 0.628, Test accuracy: 84.4 %\n",
"Epoch: 29, Loss: 0.195, Test accuracy: 83.7 %\n",
"Epoch: 30, Loss: 0.450, Test accuracy: 83.1 %\n",
"Epoch: 31, Loss: 0.209, Test accuracy: 83.4 %\n",
"Epoch: 32, Loss: 0.264, Test accuracy: 83.0 %\n",
"Epoch: 33, Loss: 1.278, Test accuracy: 83.5 %\n",
"Epoch: 34, Loss: 0.475, Test accuracy: 84.1 %\n",
"Epoch: 35, Loss: 0.299, Test accuracy: 84.4 %\n",
"Epoch: 36, Loss: 0.384, Test accuracy: 84.2 %\n",
"Epoch: 37, Loss: 0.173, Test accuracy: 85.2 %\n",
"Epoch: 38, Loss: 0.181, Test accuracy: 84.7 %\n",
"Epoch: 39, Loss: 0.490, Test accuracy: 84.0 %\n",
"Epoch: 40, Loss: 0.187, Test accuracy: 85.1 %\n",
"Epoch: 41, Loss: 0.131, Test accuracy: 84.8 %\n",
"Epoch: 42, Loss: 0.248, Test accuracy: 85.6 %\n",
"Epoch: 43, Loss: 0.050, Test accuracy: 85.7 %\n",
"Epoch: 44, Loss: 0.453, Test accuracy: 85.5 %\n",
"Epoch: 45, Loss: 0.353, Test accuracy: 85.0 %\n",
"Epoch: 46, Loss: 0.123, Test accuracy: 84.8 %\n",
"Epoch: 47, Loss: 0.123, Test accuracy: 85.2 %\n",
"Epoch: 48, Loss: 0.454, Test accuracy: 84.6 %\n",
"Epoch: 49, Loss: 0.422, Test accuracy: 84.6 %\n",
"Epoch: 50, Loss: 0.370, Test accuracy: 85.0 %\n",
"Total time for training : 1030.853891134262\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "UC2P9_m7GgTC",
"outputId": "9ae8868e-9aa5-4802-ae2a-f615fd1dc176"
},
"source": [
"t0 = time.time()\r\n",
" \r\n",
"def default_transforms():\r\n",
" return transforms.Compose([RandomScaling(),RandomNoise(),ShufflePoints(),ToTensor()])\r\n",
" # return transforms.Compose([RandomRotation_z(),RandomNoise(),ShufflePoints(),ToTensor()])\r\n",
" \r\n",
"train_ds = PointCloudData(\"./data/ModelNet40_PLY\", transform=default_transforms())\r\n",
"test_ds = PointCloudData(\"./data/ModelNet40_PLY\", transform=default_transforms(), folder='test')\r\n",
"\r\n",
"inv_classes = {i: cat for cat, i in train_ds.classes.items()}\r\n",
"print(\"Classes: \", inv_classes)\r\n",
"print('Train dataset size: ', len(train_ds))\r\n",
"print('Test dataset size: ', len(test_ds))\r\n",
"print('Number of classes: ', len(train_ds.classes))\r\n",
"print('Sample pointcloud shape: ', train_ds[0]['pointcloud'].size())\r\n",
"\r\n",
"train_loader = DataLoader(dataset=train_ds, batch_size=32, shuffle=True)\r\n",
"test_loader = DataLoader(dataset=test_ds, batch_size=32)\r\n",
"\r\n",
"def train(model, device, train_loader, test_loader=None, epochs=250):\r\n",
" optimizer = torch.optim.Adam(model.parameters(), lr=0.001)\r\n",
" scheduler = torch.optim.lr_scheduler.StepLR(optimizer, step_size=20, gamma=0.5)\r\n",
" val_accs = []\r\n",
" loss=0\r\n",
" for epoch in range(epochs): \r\n",
" model.train()\r\n",
" for i, data in enumerate(train_loader, 0):\r\n",
" inputs, labels = data['pointcloud'].to(device).float(), data['category'].to(device)\r\n",
" optimizer.zero_grad()\r\n",
" outputs = model(inputs.transpose(1,2))\r\n",
" # outputs, m3x3 = model(inputs.transpose(1,2))\r\n",
" loss = basic_loss(outputs, labels)\r\n",
" # loss = pointnet_full_loss(outputs, labels, m3x3)\r\n",
" loss.backward()\r\n",
" optimizer.step()\r\n",
"\r\n",
" model.eval()\r\n",
" correct = total = 0\r\n",
" if test_loader:\r\n",
" with torch.no_grad():\r\n",
" for data in test_loader:\r\n",
" inputs, labels = data['pointcloud'].to(device).float(), data['category'].to(device)\r\n",
" outputs = model(inputs.transpose(1,2))\r\n",
" # outputs, __ = model(inputs.transpose(1,2))\r\n",
" _, predicted = torch.max(outputs.data, 1)\r\n",
" total += labels.size(0)\r\n",
" correct += (predicted == labels).sum().item()\r\n",
" val_acc = 100. * correct / total\r\n",
" val_accs.append(val_acc)\r\n",
" print('Epoch: %d, Loss: %.3f, Test accuracy: %.1f %%' %(epoch+1, loss, val_acc))\r\n",
"\r\n",
" scheduler.step()\r\n",
" return val_accs\r\n",
"\r\n",
"model = PointNetBasic()\r\n",
"\r\n",
"model_parameters = filter(lambda p: p.requires_grad, model.parameters())\r\n",
"print(\"Number of parameters in the Neural Networks: \", sum([np.prod(p.size()) for p in model_parameters]))\r\n",
"\r\n",
"device = torch.device(\"cuda:0\" if torch.cuda.is_available() else \"cpu\") \r\n",
"print(\"Device: \", device)\r\n",
"model.to(device);\r\n",
"\r\n",
"valaccs_2 = train(model, device, train_loader, test_loader, epochs = 100)\r\n",
"\r\n",
"print(\"Total time for training : \", time.time()-t0)"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"text": [
"Classes: {0: 'airplane', 1: 'bathtub', 2: 'bed', 3: 'bench', 4: 'bookshelf', 5: 'bottle', 6: 'bowl', 7: 'car', 8: 'chair', 9: 'cone', 10: 'cup', 11: 'curtain', 12: 'desk', 13: 'door', 14: 'dresser', 15: 'flower_pot', 16: 'glass_box', 17: 'guitar', 18: 'keyboard', 19: 'lamp', 20: 'laptop', 21: 'mantel', 22: 'monitor', 23: 'night_stand', 24: 'person', 25: 'piano', 26: 'plant', 27: 'radio', 28: 'range_hood', 29: 'sink', 30: 'sofa', 31: 'stairs', 32: 'stool', 33: 'table', 34: 'tent', 35: 'toilet', 36: 'tv_stand', 37: 'vase', 38: 'wardrobe', 39: 'xbox'}\n",
"Train dataset size: 9843\n",
"Test dataset size: 2468\n",
"Number of classes: 40\n",
"Sample pointcloud shape: torch.Size([1024, 3])\n",
"Number of parameters in the Neural Networks: 819624\n",
"Device: cuda:0\n",
"Epoch: 1, Loss: 1.820, Test accuracy: 58.6 %\n",
"Epoch: 2, Loss: 0.594, Test accuracy: 58.2 %\n",
"Epoch: 3, Loss: 0.784, Test accuracy: 71.6 %\n",
"Epoch: 4, Loss: 0.711, Test accuracy: 66.7 %\n",
"Epoch: 5, Loss: 0.778, Test accuracy: 68.1 %\n",
"Epoch: 6, Loss: 0.656, Test accuracy: 66.3 %\n",
"Epoch: 7, Loss: 0.956, Test accuracy: 66.7 %\n",
"Epoch: 8, Loss: 0.717, Test accuracy: 77.2 %\n",
"Epoch: 9, Loss: 0.616, Test accuracy: 49.1 %\n",
"Epoch: 10, Loss: 0.784, Test accuracy: 72.6 %\n",
"Epoch: 11, Loss: 0.968, Test accuracy: 75.2 %\n",
"Epoch: 12, Loss: 0.809, Test accuracy: 75.0 %\n",
"Epoch: 13, Loss: 0.958, Test accuracy: 78.2 %\n",
"Epoch: 14, Loss: 0.727, Test accuracy: 73.1 %\n",
"Epoch: 15, Loss: 1.037, Test accuracy: 69.9 %\n",
"Epoch: 16, Loss: 0.989, Test accuracy: 76.3 %\n",
"Epoch: 17, Loss: 0.248, Test accuracy: 78.0 %\n",
"Epoch: 18, Loss: 0.557, Test accuracy: 72.0 %\n",
"Epoch: 19, Loss: 0.548, Test accuracy: 76.4 %\n",
"Epoch: 20, Loss: 0.802, Test accuracy: 76.5 %\n",
"Epoch: 21, Loss: 0.360, Test accuracy: 80.9 %\n",
"Epoch: 22, Loss: 0.260, Test accuracy: 80.8 %\n",
"Epoch: 23, Loss: 0.297, Test accuracy: 84.2 %\n",
"Epoch: 24, Loss: 0.164, Test accuracy: 83.2 %\n",
"Epoch: 25, Loss: 0.376, Test accuracy: 81.3 %\n",
"Epoch: 26, Loss: 0.448, Test accuracy: 82.3 %\n",
"Epoch: 27, Loss: 0.701, Test accuracy: 83.0 %\n",
"Epoch: 28, Loss: 0.423, Test accuracy: 82.3 %\n",
"Epoch: 29, Loss: 0.543, Test accuracy: 82.5 %\n",
"Epoch: 30, Loss: 0.524, Test accuracy: 82.0 %\n",
"Epoch: 31, Loss: 0.294, Test accuracy: 83.2 %\n",
"Epoch: 32, Loss: 0.441, Test accuracy: 82.8 %\n",
"Epoch: 33, Loss: 0.695, Test accuracy: 83.7 %\n",
"Epoch: 34, Loss: 0.766, Test accuracy: 82.9 %\n",
"Epoch: 35, Loss: 0.518, Test accuracy: 79.8 %\n",
"Epoch: 36, Loss: 0.187, Test accuracy: 82.2 %\n",
"Epoch: 37, Loss: 0.335, Test accuracy: 83.6 %\n",
"Epoch: 38, Loss: 0.387, Test accuracy: 81.9 %\n",
"Epoch: 39, Loss: 0.352, Test accuracy: 82.5 %\n",
"Epoch: 40, Loss: 0.533, Test accuracy: 82.5 %\n",
"Epoch: 41, Loss: 0.463, Test accuracy: 85.9 %\n",
"Epoch: 42, Loss: 0.609, Test accuracy: 86.2 %\n",
"Epoch: 43, Loss: 0.496, Test accuracy: 85.4 %\n",
"Epoch: 44, Loss: 0.070, Test accuracy: 84.9 %\n",
"Epoch: 45, Loss: 0.496, Test accuracy: 85.2 %\n",
"Epoch: 46, Loss: 0.054, Test accuracy: 86.1 %\n",
"Epoch: 47, Loss: 0.300, Test accuracy: 85.3 %\n",
"Epoch: 48, Loss: 0.102, Test accuracy: 85.7 %\n",
"Epoch: 49, Loss: 0.271, Test accuracy: 85.6 %\n",
"Epoch: 50, Loss: 0.373, Test accuracy: 84.2 %\n",
"Epoch: 51, Loss: 0.155, Test accuracy: 84.2 %\n",
"Epoch: 52, Loss: 0.322, Test accuracy: 84.6 %\n",
"Epoch: 53, Loss: 0.166, Test accuracy: 84.0 %\n",
"Epoch: 54, Loss: 0.237, Test accuracy: 84.7 %\n",
"Epoch: 55, Loss: 0.139, Test accuracy: 84.6 %\n",
"Epoch: 56, Loss: 0.086, Test accuracy: 84.2 %\n",
"Epoch: 57, Loss: 0.222, Test accuracy: 83.5 %\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"collapsed": true,
"id": "JHCJWyXuRki6",
"outputId": "989534f3-08d5-4de1-9199-fe6523bc2f88"
},
"source": [
"t0 = time.time()\r\n",
" \r\n",
"def default_transforms():\r\n",
" return transforms.Compose([RandomRotation(0.3),RandomNoise(),ShufflePoints(),ToTensor()])\r\n",
" # return transforms.Compose([RandomRotation_z(),RandomNoise(),ShufflePoints(),ToTensor()])\r\n",
" \r\n",
"train_ds = PointCloudData(\"./data/ModelNet40_PLY\", transform=default_transforms())\r\n",
"test_ds = PointCloudData(\"./data/ModelNet40_PLY\", transform=default_transforms(), folder='test')\r\n",
"\r\n",
"inv_classes = {i: cat for cat, i in train_ds.classes.items()}\r\n",
"print(\"Classes: \", inv_classes)\r\n",
"print('Train dataset size: ', len(train_ds))\r\n",
"print('Test dataset size: ', len(test_ds))\r\n",
"print('Number of classes: ', len(train_ds.classes))\r\n",
"print('Sample pointcloud shape: ', train_ds[0]['pointcloud'].size())\r\n",
"\r\n",
"train_loader = DataLoader(dataset=train_ds, batch_size=32, shuffle=True)\r\n",
"test_loader = DataLoader(dataset=test_ds, batch_size=32)\r\n",
"\r\n",
"def train(model, device, train_loader, test_loader=None, epochs=250):\r\n",
" optimizer = torch.optim.Adam(model.parameters(), lr=0.001)\r\n",
" scheduler = torch.optim.lr_scheduler.StepLR(optimizer, step_size=20, gamma=0.5)\r\n",
" val_accs = []\r\n",
" loss=0\r\n",
" for epoch in range(epochs): \r\n",
" model.train()\r\n",
" for i, data in enumerate(train_loader, 0):\r\n",
" inputs, labels = data['pointcloud'].to(device).float(), data['category'].to(device)\r\n",
" optimizer.zero_grad()\r\n",
" # outputs = model(inputs.transpose(1,2))\r\n",
" outputs, m3x3 = model(inputs.transpose(1,2))\r\n",
" # loss = basic_loss(outputs, labels)\r\n",
" loss = pointnet_full_loss(outputs, labels, m3x3)\r\n",
" loss.backward()\r\n",
" optimizer.step()\r\n",
"\r\n",
" model.eval()\r\n",
" correct = total = 0\r\n",
" if test_loader:\r\n",
" with torch.no_grad():\r\n",
" for data in test_loader:\r\n",
" inputs, labels = data['pointcloud'].to(device).float(), data['category'].to(device)\r\n",
" # outputs = model(inputs.transpose(1,2))\r\n",
" outputs, __ = model(inputs.transpose(1,2))\r\n",
" _, predicted = torch.max(outputs.data, 1)\r\n",
" total += labels.size(0)\r\n",
" correct += (predicted == labels).sum().item()\r\n",
" val_acc = 100. * correct / total\r\n",
" val_accs.append(val_acc)\r\n",
" print('Epoch: %d, Loss: %.3f, Test accuracy: %.1f %%' %(epoch+1, loss, val_acc))\r\n",
"\r\n",
" scheduler.step()\r\n",
" return val_accs\r\n",
"\r\n",
"model = PointNetFull()\r\n",
"\r\n",
"model_parameters = filter(lambda p: p.requires_grad, model.parameters())\r\n",
"print(\"Number of parameters in the Neural Networks: \", sum([np.prod(p.size()) for p in model_parameters]))\r\n",
"\r\n",
"device = torch.device(\"cuda:0\" if torch.cuda.is_available() else \"cpu\") \r\n",
"print(\"Device: \", device)\r\n",
"model.to(device);\r\n",
"\r\n",
"valaccs_3 = train(model, device, train_loader, test_loader, epochs = 100)\r\n",
"\r\n",
"print(\"Total time for training : \", time.time()-t0)"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"text": [
"Classes: {0: 'airplane', 1: 'bathtub', 2: 'bed', 3: 'bench', 4: 'bookshelf', 5: 'bottle', 6: 'bowl', 7: 'car', 8: 'chair', 9: 'cone', 10: 'cup', 11: 'curtain', 12: 'desk', 13: 'door', 14: 'dresser', 15: 'flower_pot', 16: 'glass_box', 17: 'guitar', 18: 'keyboard', 19: 'lamp', 20: 'laptop', 21: 'mantel', 22: 'monitor', 23: 'night_stand', 24: 'person', 25: 'piano', 26: 'plant', 27: 'radio', 28: 'range_hood', 29: 'sink', 30: 'sofa', 31: 'stairs', 32: 'stool', 33: 'table', 34: 'tent', 35: 'toilet', 36: 'tv_stand', 37: 'vase', 38: 'wardrobe', 39: 'xbox'}\n",
"Train dataset size: 9843\n",
"Test dataset size: 2468\n",
"Number of classes: 40\n",
"Sample pointcloud shape: torch.Size([1024, 3])\n",
"Number of parameters in the Neural Networks: 1622705\n",
"Device: cuda:0\n",
"Epoch: 1, Loss: 2.342, Test accuracy: 35.4 %\n",
"Epoch: 2, Loss: 0.989, Test accuracy: 45.9 %\n",
"Epoch: 3, Loss: 1.712, Test accuracy: 51.7 %\n",
"Epoch: 4, Loss: 1.531, Test accuracy: 45.6 %\n",
"Epoch: 5, Loss: 1.047, Test accuracy: 43.2 %\n",
"Epoch: 6, Loss: 0.999, Test accuracy: 59.4 %\n",
"Epoch: 7, Loss: 1.381, Test accuracy: 59.1 %\n",
"Epoch: 8, Loss: 1.820, Test accuracy: 62.3 %\n",
"Epoch: 9, Loss: 1.392, Test accuracy: 60.2 %\n",
"Epoch: 10, Loss: 1.418, Test accuracy: 63.5 %\n",
"Epoch: 11, Loss: 1.011, Test accuracy: 66.9 %\n",
"Epoch: 12, Loss: 0.948, Test accuracy: 63.3 %\n",
"Epoch: 13, Loss: 1.153, Test accuracy: 64.5 %\n",
"Epoch: 14, Loss: 0.713, Test accuracy: 64.8 %\n",
"Epoch: 15, Loss: 1.524, Test accuracy: 68.5 %\n",
"Epoch: 16, Loss: 1.038, Test accuracy: 67.1 %\n",
"Epoch: 17, Loss: 0.644, Test accuracy: 62.8 %\n",
"Epoch: 18, Loss: 0.965, Test accuracy: 67.6 %\n",
"Epoch: 19, Loss: 0.672, Test accuracy: 66.1 %\n",
"Epoch: 20, Loss: 1.310, Test accuracy: 64.3 %\n",
"Epoch: 21, Loss: 1.304, Test accuracy: 72.8 %\n",
"Epoch: 22, Loss: 0.843, Test accuracy: 74.4 %\n",
"Epoch: 23, Loss: 0.566, Test accuracy: 75.6 %\n",
"Epoch: 24, Loss: 1.128, Test accuracy: 70.5 %\n",
"Epoch: 25, Loss: 1.057, Test accuracy: 75.6 %\n",
"Epoch: 26, Loss: 0.873, Test accuracy: 74.8 %\n",
"Epoch: 27, Loss: 0.773, Test accuracy: 75.0 %\n",
"Epoch: 28, Loss: 0.851, Test accuracy: 75.5 %\n",
"Epoch: 29, Loss: 0.343, Test accuracy: 73.9 %\n",
"Epoch: 30, Loss: 0.977, Test accuracy: 74.6 %\n",
"Epoch: 31, Loss: 0.667, Test accuracy: 77.7 %\n",
"Epoch: 32, Loss: 1.136, Test accuracy: 72.9 %\n",
"Epoch: 33, Loss: 0.508, Test accuracy: 74.5 %\n",
"Epoch: 34, Loss: 1.222, Test accuracy: 75.6 %\n",
"Epoch: 35, Loss: 0.803, Test accuracy: 76.8 %\n",
"Epoch: 36, Loss: 0.695, Test accuracy: 74.5 %\n",
"Epoch: 37, Loss: 0.580, Test accuracy: 75.5 %\n",
"Epoch: 38, Loss: 0.348, Test accuracy: 76.4 %\n",
"Epoch: 39, Loss: 0.430, Test accuracy: 75.0 %\n",
"Epoch: 40, Loss: 1.412, Test accuracy: 76.7 %\n",
"Epoch: 41, Loss: 0.550, Test accuracy: 79.1 %\n",
"Epoch: 42, Loss: 1.389, Test accuracy: 78.5 %\n",
"Epoch: 43, Loss: 0.841, Test accuracy: 78.9 %\n",
"Epoch: 44, Loss: 0.975, Test accuracy: 78.9 %\n",
"Epoch: 45, Loss: 0.668, Test accuracy: 78.9 %\n",
"Epoch: 46, Loss: 0.495, Test accuracy: 79.3 %\n",
"Epoch: 47, Loss: 1.475, Test accuracy: 79.7 %\n",
"Epoch: 48, Loss: 0.995, Test accuracy: 79.7 %\n",
"Epoch: 49, Loss: 0.405, Test accuracy: 78.4 %\n",
"Epoch: 50, Loss: 0.446, Test accuracy: 79.8 %\n",
"Epoch: 51, Loss: 0.480, Test accuracy: 78.8 %\n",
"Epoch: 52, Loss: 0.706, Test accuracy: 79.4 %\n",
"Epoch: 53, Loss: 0.538, Test accuracy: 79.6 %\n",
"Epoch: 54, Loss: 0.803, Test accuracy: 79.3 %\n",
"Epoch: 55, Loss: 0.532, Test accuracy: 78.6 %\n",
"Epoch: 56, Loss: 0.777, Test accuracy: 78.9 %\n",
"Epoch: 57, Loss: 0.647, Test accuracy: 78.1 %\n",
"Epoch: 58, Loss: 0.518, Test accuracy: 80.3 %\n",
"Epoch: 59, Loss: 0.752, Test accuracy: 78.8 %\n",
"Epoch: 60, Loss: 0.339, Test accuracy: 79.6 %\n",
"Epoch: 61, Loss: 0.603, Test accuracy: 80.1 %\n",
"Epoch: 62, Loss: 0.651, Test accuracy: 79.8 %\n",
"Epoch: 63, Loss: 0.677, Test accuracy: 80.1 %\n",
"Epoch: 64, Loss: 0.760, Test accuracy: 80.7 %\n",
"Epoch: 65, Loss: 0.333, Test accuracy: 81.6 %\n",
"Epoch: 66, Loss: 0.311, Test accuracy: 80.8 %\n",
"Epoch: 67, Loss: 0.202, Test accuracy: 80.5 %\n",
"Epoch: 68, Loss: 0.598, Test accuracy: 81.1 %\n",
"Epoch: 69, Loss: 0.231, Test accuracy: 80.8 %\n",
"Epoch: 70, Loss: 0.623, Test accuracy: 80.7 %\n",
"Epoch: 71, Loss: 1.460, Test accuracy: 80.7 %\n",
"Epoch: 72, Loss: 0.474, Test accuracy: 80.2 %\n",
"Epoch: 73, Loss: 0.636, Test accuracy: 80.3 %\n",
"Epoch: 74, Loss: 0.312, Test accuracy: 80.5 %\n",
"Epoch: 75, Loss: 0.814, Test accuracy: 81.0 %\n",
"Epoch: 76, Loss: 0.253, Test accuracy: 80.9 %\n",
"Epoch: 77, Loss: 0.599, Test accuracy: 81.4 %\n",
"Epoch: 78, Loss: 0.978, Test accuracy: 80.6 %\n",
"Epoch: 79, Loss: 0.872, Test accuracy: 80.5 %\n",
"Epoch: 80, Loss: 0.396, Test accuracy: 80.3 %\n",
"Epoch: 81, Loss: 0.769, Test accuracy: 81.5 %\n",
"Epoch: 82, Loss: 0.682, Test accuracy: 80.1 %\n",
"Epoch: 83, Loss: 0.920, Test accuracy: 81.8 %\n",
"Epoch: 84, Loss: 0.316, Test accuracy: 80.8 %\n",
"Epoch: 85, Loss: 0.414, Test accuracy: 81.1 %\n",
"Epoch: 86, Loss: 1.045, Test accuracy: 81.9 %\n",
"Epoch: 87, Loss: 1.034, Test accuracy: 81.8 %\n",
"Epoch: 88, Loss: 0.373, Test accuracy: 80.7 %\n",
"Epoch: 89, Loss: 0.523, Test accuracy: 81.2 %\n",
"Epoch: 90, Loss: 0.962, Test accuracy: 81.3 %\n",
"Epoch: 91, Loss: 0.522, Test accuracy: 81.5 %\n",
"Epoch: 92, Loss: 0.328, Test accuracy: 81.6 %\n",
"Epoch: 93, Loss: 0.246, Test accuracy: 80.7 %\n",
"Epoch: 94, Loss: 0.454, Test accuracy: 82.3 %\n",
"Epoch: 95, Loss: 0.499, Test accuracy: 80.7 %\n",
"Epoch: 96, Loss: 0.487, Test accuracy: 81.3 %\n",
"Epoch: 97, Loss: 0.770, Test accuracy: 80.9 %\n",
"Epoch: 98, Loss: 0.286, Test accuracy: 81.7 %\n",
"Epoch: 99, Loss: 0.367, Test accuracy: 81.7 %\n",
"Epoch: 100, Loss: 0.464, Test accuracy: 82.4 %\n",
"Total time for training : 3356.0661334991455\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "kN3RZqveRx5i"
},
"source": [
"import matplotlib.pyplot as plt"
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 265
},
"id": "fwG9W-JrR3wv",
"outputId": "e0876b97-a0a0-4c25-857a-03b20377a96f"
},
"source": [
"plt.plot(valaccs_2, label=\"PointNet without TNet - random Rotation\")\r\n",
"plt.plot(valaccs_3, label=\"PointNet with TNet - random Rotation\")\r\n",
"plt.legend()\r\n",
"plt.show()"
],
"execution_count": null,
"outputs": [
{
"output_type": "display_data",
"data": {
"image/png": 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v7D88cno496z1JuG9dMYcHkmFDaw//4MfU7O4w7SEcArZGvcv5nMHgYcXs+Ddf7N86Wf84Pkc0Z5lzA96kkHqfPJu/xIeTdHasUvPwMJbSV81n0Bvt2rDtUFrinj8hs5snB7HNWoqEQP/wL/GxvJcyRgUYzZ5n93HbMMc7K3iYeJXjdJ7QatFS3hfjerbBv4CMB6wAbvQuhRGoHUjDK7c9kdVVc21HUduYoraWM3lqK+2x91RgRraGWXi17y+3UTSuh9Y1HoxhrwDANjRYcOAB2d7rdq8QplnHMKhyHE8cFN/OoT54ONuYH9WCRuP5pGaUcQky1dcc/I9HLd/gO77R6DTCLhrIUVl5RTOu4lWZftwV+wQ3h3d3Z9z1BrMjbM3cEfvSF69s/IGoqkY6xeTcDuxlnUt72PIfS/B/u8gZRGoDpjwOXgHQ9JH8MPj8OcN0CqWr5JO0XrZBAbq9pLl3ZVWD68Ar/rNEyKEDOQRV7QCo4X5H/6XGQX/4G3bGKZ4rMbL05O1pk5cZ98MAVHQbyo47KRnZfNzajr+AcHc3r8rev/W3L0+kEN5VlY+Ppjw8/sGV7FWwNt9oDgDdAaYvl3rNw1QfBr7+8Mh6hr0t73j7C72r+UHmL/+OEv/MoBelcOgP9l4BM+fn+QuwzrQuWk3KYM7QPEpbRj1pO+0yZZKz8D0Hc5uaas2rMexZR59pswiMLSWNnwhziMBLq5Yh86Ucv/CHTxonMd4tw281+9Xlq7ZzP+83yDAVsCRTlPocdfMaj1Ivt+dyaNf7GJAh1AS2gbx1qojzLm7F6PjWtd+sr1LYPF90H86jHy5+nsOxwWz+5WarAz/zzoUBT66tw8xrQMYNWcDqCo/XnMQcg9C7F3Qpp/WXfDLP0LLnlof6sFPw3V/b6RvSVzNLrkXihBN7dEvdmG22hnntxdD5DCmj+iB4ubJsBVB+Oks/HT7OHB3r7bPrXGtMdscPPX1bjYezWNUz1bcGtuq7pPFjNUGeUTWMOy5hqlZ/Tzd+OT+vtz38Q7uem8LjwzvxL7MEl4YHQP9zhui3eUmuPMj+Po+rTkl5vaGfA1CNJgEuLiQqlLZObjJT5VbaubgmVJeG6jDPSkTuvwNgIeu60iIjztlZtvZeaDPc2dCJA6HytfJp3ixviM0FQWiBzboGru29GfpX67lvgU7+PdPB3HX6xgTf5Gafvcx2qCbzF3Sp1k0OQlwcaGdn8Dql+DxfdWGfzeF7Wlab5OBjh3ahk5nB/NO6Ft33+C7+rThrj5tmuTaztUywJOvp/Xn70v2EBnkddFfKgB0u0X7I0QTkwAXFzq0HIw5UJimTcHZhLYez8fbXU/LM2shIgH8rpxh8ufz9TAw5+5ev/dlCOEkq9KL6hwOSN+qPc870uDdi8otjHlnEztOFNSr/La0fIa3AV1msrYqihCi3iTARXV5h7R5QwDyDtdvH4cDDv4INgtf7jjF7lNF/JiaVedu+WVmDmeXMdancvHYLvWeoUEIgQT4VUdVVRyOWrqOpm/RHvUekH+0fgdN+hC++AOOnZ/y6VZtsrKd6YV17lbV/t27Yiv4R0KLC+ZCE0LUQgL8KvN/3+3l7ve3ctH+/+lbtZVMIvvUrwml+DT8qk1+X5D8DRmFFXRt6ce+zBLKLbaz5exW+PnvcHydc9PW4/m0dyskIGMN9Bh7afM3C3EVkwC/yuxKL2JbWgGbjubXXODkFoi6RpteNb8eAf7TX8Fhg5ixBGZvpYu/jSdu6IzdoZKaUayVUVWt3NZ34LvpYNNmXNh6vICnAtegAPT9c6N8PiGuJhLgzURjjZjNKKwA4N21NTSPFGdAcTpEDdACvKJQWwX9Yg58r60CM3QG6Z3vxYCdp9ufdC7emnyyshll+/va3CAdhmvHT15IgdHC6exshpf/pA2uCWz6roBCuBoJ8GYgo7Ccvv9axcLNJ7QNJZna5PvnUU/t0BYvuIhSk5XiCisRAZ5sPpZPyqmi6gWqep9EXQMhlRPuX+xGpqkYlj8NLXpC/4eYfyyIbDWIwfatBPm40yHMh50nC+HoKvj5GegySlustu1AWP86yUdOMV6/Bg+7UVuwQAjRYBLgzcDXSRnklpqZ+f0+Nq//BWb10Ga/O4fJYsP44RiK3hkOZbk1Hif3+G6WuT/LEt/X8PfUM++cWvj2tAKOJf8K7r7azcSqFWou1ozy6wtQlg2j36LQpPLNriyOhQzB/cQasFaQ0DaIrJOHUL++F8K7w+3ztZGdw58DYw76bfOYYliBI2oARPRujK9JiKuOBPgVzuFQ+WZnBn3bBZMQ6UvQqqdAtcOZPdXKLVmfhC9GAs2nsX8+vnIR1kqqCtvm0/abm+mqpNMifyvPxhSyYl82KaeKeHbpHu767xbMxzdTEhqvrcwSGKX1RKnpRmb6Vq3nSb9pEJHAiz/sx2p3EDXgLrCWw7HVJEb587x9LqrDoS1a4OGr7RvVD3unkQzJ+pAIJQ/dgIeb8NsTwrVJgF/htqUVkFFYwcR+USzslkQ35SRGPKk4c8hZpsxsY/VmrfnjE9sN6DJ3wpI/aesMbp0HHwyHn54mK6gPwyxv4vAKZWzFN3i66bj93U18vj2dB/uF0lWXzg/F0Vp7u04Pwe1R845wquCcXwY2C3z/KAS0geueZfXBbJbsOs1frutIZK8R2tqNB35geP4X9NMdZEfM3yC4XbXP9DYT0OPA6BsNnaXvtxCXSobSX+EWJ2fg52FgZCsTnj+8jrHdSNalGemVcYCSEhMt/D35cEMaoeZT4Abrw+6muDyahw++r91gBK1J5JZZLDzTj7zsdJR+f8J97b/5vz7381V6AM+PjqG3OQl2q3xf2Bb/PVncEtsaNaQjOcdTGPTaGnpHBXLfte24ufAz9LkH4Q9fUaJ68Pcl2+jSwo/p13UEvU4L5APLCLaZWEF/1tgG0e+cz/P5tnRm7fGgS7cZ3Dhk0G8yYZYQrkr+9VzBjGYbP+3N4pbYlnj+8hToDPjcNovevfvSwpHHAx9s4ESekfc3HOe6sBLQu3PTtYn8p/g6jiY+D8Of11ZCf3ATJE4ho8hERKAXSt+p4ObNRPsyvps+kN6tPGH7fFSdgfKweF79+SAmq53VeQEEmzO5s1cLCowW3vjiJ+xrX2V3wDB+NMXywrL95JSaeO3OWNwNlT9KXW8BSxmKbwuWRT5NcvrZG6XJJwt5ftleBncO44Z7ZjR4VkAhRHUS4Few5XuyKLfYmdLqOBxbDcP/DwIiaNkuBp2i4shP4+Y5GzBabFwbWAzB7bklPpJQX3deyR8Eg56otsr46aIKIoK8tSW/et0De77W2tI/GQNHVqKM/BdP39KbUwUVjH57Iz9m+uKm2HljeACrnxzK5103g6Ln0eIJPPT5Tr7ZmcGfBrcnrs05S4N1ukEL8Ts/olv7KI7klJFbauajjWlMWbCDVgFezJkQj76eq6YLIS5OmlCuYIuTM2gX6kPHI++BXytIuE97I6QjAP8c5MGd6+yM7RWBb84JCO2Eh0HP3X2jeHvNUdLzy4kKObuKTUZhBT0iArQX/f8CO96H+UO15cXuWgjdxzAQGNoljLWHcpmY0Af2vQd5R9C5+xKRvgwSJ/HrjePYnVHMoTOl3N47ovpFu3nBBK2HTG9rHgDXv7mO4gor13YM4aXbetY+FasQot4kwK9Qp4sq2JZWwGsDHCg718MN/zw7N3dlrTrBJ5+Vj99OZIAHvJYGnbW5tCf2a8u8tcdYtO0kf7u5GwDlFhsFRgsRgV7aMYKiIe5ubRmwu7+ANn2d535jXBzb0wq4qaMn7EPrSnhqmzbisv9DGPQ6EtoGkdA2qNbPEN8mkAAvN1oHejHn7l4M7hQqq6cL0YgkwK9QR3PKABhe8AV4+EPCvWff9PAD35aQf4yO4X5QeALsFmfNvGWAJ9e0D2Hj0TznLqcrR2BGBnmdPc6tc7QuiQaPaucO9fXg5p6Vy5P5hGmryxxdDd1Gn10EuB683Q1s+dswPA16dNJkIkSjkzbwK1R+mZlIJYfgk8u18PYMqF4gpOPZ2QKrHisDHKB3VCAHz5RiNGsjNjNqCnC94YLwvkBoZ9i3FMzFcO0jDf4c3u4GCW8hmogE+BUqv8zCA/rloOjhmgcvLBDSAQqOVRY+fnZbpV5tg7A7VHZnaL1AMoqqAtybBqn6pRA9SFsxRwhxxZAAv0KVFecwXr8WYseBfw0L6IZ0AGMuVBRpNXB3X20a2Eq922jt07squ/FlFJbjrtcR5ltHjft8VUuqXfvopXwMIUQTkjbwK5RX7n68FAvEjq+5QFXNuOCY9ie4fbX5tAO83egY7qtNKIXWBt460LPhzRlxd4N3KHS8/lI+hhCiCUkN/AqlludoT/xqqH3D2QDPP6bVwM9p/67SOyqQnemFqKpKRmEFEee2f9eXdzDEjZfFFoS4AkmAX6H05ZXzcPuE1lwgKBoUHeTs1+Y8qSHAE9oGUVhuJS3PyOmiCiIDG9j+LYS4okmAX6E8zHnY0YPXRfpaGzy0GQOP/gqqo9oNzCq9o7R9Nx/LJ7fUfGk1cCHEFUsC/Aqkqire1kLK3YJrb7oI6Xh2WtkaauAdwnzx9zTwQ2omcF4XQiFEsycBfgUqNdsIUoswewTXXvDc0K5hgI1Op9ArKohtlau/N7gLoRDiiiYBfgXKL7MQqpRg975I+3eVqgD3CtZuNtagd1QQVctpShOKEK5FAvwKlFdmJoQS8A6rvWBVu3cNzSdVerfVZgo06BRa+DWwD7gQ4opWZ4AritJFUZSUc/6UKIrymKIowYqirFQU5UjlY+0zG4l6yy81EaoUY/APr71gVXDXEuDxbQJRFG1+FINefl8L4Urq/BetquohVVXjVVWNBxKAcmApMANYpapqJ2BV5WvRCIqKi/FSLHgEtKy9oH8khHapdWEEP083urX0p12oTyNfpRDi99bQkZjDgWOqqp5UFGUMMLRy+0JgLfBM413a1auiMAsAz6A6Alyng+nb6zzevD/2RicDcYRwOQ0N8AnA/yqft1BVNavy+RmgRc27iIaylmijMA1+jfOVtg2R2rcQrqjejaKKorgDo4Gvz39PVVUVUC+y31RFUZIURUnKzc295Au9mjjKKofRX2wUphBC0LBeKDcBO1VVza58na0oSiuAysecmnZSVXW+qqqJqqomhoXV0atCAKCUV/6i85HvSwhxcQ0J8Ls523wCsAyYXPl8MvBdY13U1c6tomoeFAlwIcTF1SvAFUXxAW4Alpyz+RXgBkVRjgDXV74WjcDTUkCF3u/sGphCCFGDet3EVFXVCIScty0frVeKOJeqaov/6t0uaXeLzYG/vZAKr2Bk3KQQojYysqOx/fgEvH8d2G2XtHuB0UIIJdg8Q+ouLIS4qkmAN7bja7UZAlM+u6Td88rMhCrFOOoaRi+EuOpJgDcmUzEUHAcUWPNvsJQ3+BD5RgshSjE6PwlwIUTtJMAbU9Zu7XHwU1B2Bra+W3M5u1VbRacGBSVGgpUy3PxlXJQQonYS4I0pM0V77DcNutwMm94CY/6F5ZIXwJxekHv4grfKCs8A4FXXMHohxFVPArwxZaVoE0z5hMLw58BSBhveqKHcbq2nyvrXL3jLUqyNh/IIkBq4EKJ2EuB1KT0DVlP9ymamUBHWg0NnSiG8G/S4A3Z9hnNFhSr5R7XHvYsh72i1t2wl2kBXxaeOqWSFEFc9CfDa2K3w7jU116LPZyqGgmOsKGjF9M93atui+oO5BIozqpfNO6w1seg9LqyFGyuH0ftKgAshaicBXpsze6CiEE5sqrtsVioAm8sjySqurLGHd9Mecw9ittnJKTFBeQGU50PbAdDnftQ9XzHtrS+19wB9RZ62j0xkJYSogwR4bTKStMes3eCw1142cxcAa0sjKDPbKLfYIKyr9l7Ofj7YkMbQN9ZSkL5P2xbaGQY8ggU3rs/7jNdXHALAw5yPTXEDD/+m+ERCCBciAV6bjMrFEqxGyD1Ue9msFKy+rclxaMGbV2rRFhr2bQk5B0nLM1JusbNx6xatfEhH9pd68al1GLfpN7Jl5y5SM4rwthZidAsGWYBBCFEHCfDanNoO4d2156eTay+bmUKBf3fny9yyc1m9R7EAACAASURBVJpRcvaTXdlEcub4HlS9OwS25cONaXyuuwW9Avd5rmPGN3sIVouweNS8wrwQQpxLAvxiynKg6CTETQCPAMjcefGylTcw09w7OTfllpq1J+HdIPcQeSUVdG3pR7R6mjy3CLKNNpbtPs3gxF4onW9kottajmQVEKKUYJdh9EKIepAAv5iMHdpjm37QOr72GnjlDcw99nZ4umlfabUAt1VgKEknMTqIOK9cdlWE8eYvh7E5VKZc2w4Sp+BpKeC+kH2EKCUyD7gQol4kwC/m1HbQuUGrOIhIgOx9F+8PnqWNwNxYHklcZCA6BXKqAjxM64nS0pxGKx8D4bZMjthb8WXSKUZ2b0lUiDd0GAaBUUz3W0eYUoxfcKvf4hMKIZo5CfCLyUiClj3BzQsiemsjJ8/sqV7GYYcTG2HvElT/CHblG+jcwo9gH4+zNfCwLgB0UjJoZ8hDcdgIbKO1lf9pcDutjE4PCffhf2Yr7tjwkQAXQtSDBHhN7DatzbtNX+11RIL2eG47+Oa34T9dYMEoyNmPsddUSkw22of5EOZ3ToB7+mP2aU0XXQZtHNqAnluGDeHtP/Qioe05Nyt73aPV+EGaUIQQ9SIBXpPsvWAth8g+2mv/1uDbkiO71rHucC5kJMMvz2r9vMctgKePsbftPQB0CPMl3M+D3DKz83DFfp3orGQQbjkFQECb7twS27r6OX3DoPvos8+FEKIOEuA1qbqBWRXggK1VL3RZu3j+21TU5U+BbwuY8DnEjAUPX47nGgEurIED2R7RtFcyCSg9ou3nGVDzeftPh8C2znZzIYSojQR4TTJ2aEEbGOXclO7VlQ5KJsOLv0HJ3Ak3vAieZ0dLHsstw9NNR+sAL8L8PMgrM+NwaJNYndRH46HY8DixGkI6nX+2syJ6w2Op4C9t4EKIukmA1+TUdq32fc5oyK2maAD+5vY/DrrHQOxd1XY5nltGu1BfdDqFMF8PrHaV4gorAIfVCACU8jwIrSXAhRCiASTAz2fMg8K0as0nAN/laPNz64AnSieyP6u02vvHco10CPMBIMzPA8DZDr7X3BIHlb8MJMCFEI1EAvx8pyrnP6nqgQIUGi1sz3aQHtgXS7/ppBk68PGmNOf7JqudjMJy2of5AucEeGU7+KkyyDNUNouEdv4NPoQQ4mogAX6+jO2gM0DrXs5NW4/no6qQO/ZLPG96kTsTIvkuJdMZ0Cfzy3GoOGvg4ecFeHaJiXyfDtrBQjr+hh9GCOHKJMDPd2oHtIzVBvBU2nwsH293PbGRgQDcd200FruDt1cfweFQOZ5bBmhdCOFsDTyn1ESFxU6JyUZhcC+tf/c5N0aFEOJyGH7vC/hdZSRrNW1d5e8xu1Wb8yRhcrVim4/l0bddMG56rVz7MF/GJ7Zh4ZaTpOWX0y7EG4B2oVoN3NfDgKebjtxSMzml2vD7zG5TYPzT2qhLIYRoBFdvDTwjGT4YBrv/d3Zb9l6wVVRr/84uMXEs18i1HaqvkPPKHT158bYebE/LZ+GWk7QK8MTHQ/t9qCiKsy94donWjBIe6Fut26EQQlyuqzfAT2zQHlO/PLvtVNUAnrMBvvmYtsRZ/w4h1XZXFIV7rmnLDw8PIqFtEEO7VF/DMsxXG41ZVQNv4e/ZyB9ACHG1u3qbUNIrV8ZJWw8lWdrgmVPbwK8VBEQ6i20+mk+AlxvdW9Vce+4Y7ss3Dw64YHuYnwdpeUZnDbyFv0fjfwYhxFXt6qyBOxyQvhWiBgAq7Fuibc/YDm36kltmYfmeLF7+cT8r9p2hf/sQdLqGLXFW1YSSU2LC3aAjwMut8T+HEOKqdnXWwPMOgakIev1Rm7Qq9SvocQcUpZPW/o/c9NpqTFYH7nodMRH+3HdtdINPEe7nSWG5lYzCCsL9PFBkjUshRCO7OgP85GbtsW1/qCjUZhZM+RyAv+/wom2wD/++oycxrf3xMFxar5GqroT7s0qk/VsI0SSuziaU9K3aZFVB7bSaNwr2dW9gUQ0UBHTjswf60Tsq6JLDG7SbmABpeUZp/xZCNIl6BbiiKIGKoixWFOWgoigHFEXpryhKsKIoKxVFOVL5GNTUF3u5MgrLmbXyMI70LRB1jTZZlX8rrFED0duMHNZ3YOGfBjlrz5fj3GOE+0kNXAjR+OpbA38L+FlV1a5AHHAAmAGsUlW1E7Cq8vUVa9vxfMa8vYmvVm1FV3yq8gamJsl/OAAtYwbTMqBxwvbcAJcmFCFEU6gzwBVFCQAGAx8CqKpqUVW1CBgDLKwsthC4raku8nIt2naSiR9sI8DLjVEBJ7SNUdc4338vpwep+hhC+k1otHOG+Lo7n0sTihCiKdSnBt4OyAU+VhRll6IoHyiK4gO0UFU1q7LMGaBFTTsrijJVUZQkRVGScnNzG+eqG2Dz0TyeXbqXgZ1CWfrQtdweeooy1ZMjSltAa1ZZl25hw8BPUCITG+28HgY9gd5a10FpQhFCNIX6BLgB6A3MU1W1F2DkvOYSVVVVQK1pZ1VV56uqmqiqamJY2G+/1uP+zCK6KSeZdUd3Arzc6GTZyy61E0t2ZwOwbHcmAKPjWtd2mEtSNSuh1MCFEE2hPgGeAWSoqrqt8vVitEDPVhSlFUDlY07TXOLl8Ulfy08efyPw3e6wZCpuuQfIDerNt7tOY3eoLEvJJKFtEG2CvRv93FXt4OHSBi6EaAJ1BriqqmeAU4qidKncNBzYDywDqqbtmwx81yRXeJlsJVorjxI9CA7/DKiEx40kq9jEgs0nOHimlDHxjV/7Bq0roaebDn/Pq7O7vRCiadU3WR4GFimK4g4cB+5DC/+vFEW5HzgJ3FXL/r8bk7FEezJ6Lrj7QtFJEgPa47fuV1796SB6ncKonk2ziPCdCW3o1MJPRmEKIZpEvQJcVdUUoKY7fMMb93Ian7Wicu1Kd18wuENoJzyBUbGt+GLHKYZ2CSPEt2naqAd2CmVgp9C6CwohxCVw6ZGYZpsd1WLErhi08D7HuERtxsE7ekfWtKsQQlzxXLpxNrvYjDdm7AZvzh8Un9A2mDVPDSU6pPFvXgohxG/BpQP8dFEFPphQ3WoO6aol0IQQojly6SaUrOIKvBUTiofv730pQgjR6Fw6wDMra+AGT7/f+1KEEKLRuXaAF5vw11vRSQ1cCOGCXDvAiyoI0JvBXdq6hRCux+UD3FdnhovcxBRCiObMpQM8q8iENyapgQshXJLLBniJyUqp2Yanw6SNwhRCCBfjsgGeVWQCVAyOCqmBCyFckssGeGZRBR5Y0al2CXAhhEty3QAvrtDav0GaUIQQLsl1A7yoAn+dRXvhLr1QhBCux4UD3EQbX4f2QppQhBAuyIUDvIK2vpXLdEoTihDCBblugBdX0NpHauBCCNflkgHucKicKTbR0suubZAAF0K4IJcM8LwyM1a7SgsPm7bBTQJcCOF6XDLAM4u17oOh7pUBLjVwIYQLcs0AL6oAINCtqhuhBLgQwvW4ZIDvPV2MXqcQZLBqGyTAhRAuyCUDfOX+bPq1C8bDUQEGL9Cdv6SxEEI0fy4X4MdzyziSU8aI7i3AYpRRmEIIl+VyAb5yfzYA1zsDXJpPhBCuyeUC/Jf92cS09icyyBssZTIKUwjhslwqwHNLzexML2RE95baBmu51MCFEC6reQf4kZXw0wzny1UHslFVuKF7C22DNKEIIVxY8w7wPV/DtvfApvX3/mV/NpFBXnRr5ae9bzHKKEwhhMtq3gFelA6oUJKB0Wxj49E8RnRviaIo2vuWMqmBCyFcluH3voDLYcs/gQH43y+bWWctxGJznG0+AWlCEUK4tOYb4DYzOuMZAHbvTWWbezh92wXTJzrobBmL3MQUQriuegW4oigngFLADthUVU1UFCUY+BKIBk4Ad6mqWtg0l3mhw4cP0hltwYZXhgfxynUjqhdwOMBqlG6EQgiX1ZA28OtUVY1XVTWx8vUMYJWqqp2AVZWvfzO/btl+9kVR+oUFrOXao4zEFEK4qMu5iTkGWFj5fCFw2+VfTv2cKignI+2g9sI/AopPXVjIYtQepQlFCOGi6hvgKvCLoijJiqJMrdzWQlXVrMrnZ4AWNe2oKMpURVGSFEVJys3NvczL1Xy4MY02Si6qzgBt+tZcA7eUaY/ShCKEcFH1DfCBqqr2Bm4CHlIUZfC5b6qqqkJlg/R5VFWdr6pqoqqqiWFhYZd3tUCh0cKXO07RL8iIEhAJQdFQchoc9uoFnU0oUgMXQrimegW4qqqnKx9zgKVAXyBbUZRWAJWPOU11kef6fHs6FVY73bwKILAtBLQBhw1Kz1QvKE0oQggXV2eAK4rioyiKX9VzYASwF1gGTK4sNhn4rqku8lz7M0toF+qDl/E0BEZpf+DCdnBpQhFCuLj6dCNsASytHN1oAD5XVfVnRVF2AF8pinI/cBK4q+ku86wys40QDzvkZ5+tgQMUnYKoa84WrKqBu0kvFCGEa6ozwFVVPQ7E1bA9HxjeFBdVG6PZRltdvvYiqC0EVgX4yeoFpQlFCOHimt1cKGVmG5G6PO1FYJQW0N4hNTShVAW4NKEIIVxTswtwo8VGZNX90sC22mNAG60J5VxSAxdCuLjmF+BmOy0c2aD3AN/KrueBbS5SA1fAzes3v0YhhPgtNMMAtxFmz9ZCW1d5+QFRWg1cPacretVMhFVTywohhItpVgFuszsw2xwEWbLOdh8E7bmtAsrzz26TucCFEC6uWQW40ayNtgwwnx/gNfREkfUwhRAurlkFeJnFhjcmvKyFZ29gQvW+4FVkMQchhItrVgFuNNuIUM7pQlilqgZ+7o1MS5l0IRRCuLRmFeBlZhttlMouhEHRZ9/wDAR3vwtr4DIKUwjhwppVgBvNNiKVyilpz62BK8qFXQmlCUUI4eKaXYC3UXJx6D3B57ypaQOjzquBl0sTihDCpTWrAC8z22mpFGD3a31h/+6ANlB8zsIO0o1QCOHimlWAG802AjCCV9CFb4Z2BlMx5B/TXksTihDCxTWrAC8z2whUytB5B1/4ZueR2uOh5WC3gt0sAS6EcGnNKsDLLTYCFSM6nxoCPKgttOgJB3+UiayEEFeFZhXgRrOdIKUUxauGAAfoOgpObTs7IlMCXAjhwppVgJebTPhRUXMbOEDXm0F1wN5vtNfSC0UI4cKaVYCrFUXak4sFeMtYrTfKnsXaa6mBCyFcWLMKcCoKtceLBbiiaM0oJae11xLgQggX1qwCXG+uowYOWoBXcZMAF0K4rmYV4G7mYu2Jdy0BHjVAmxsFpAYuhHBpzSrA3a31qIHrDdD5xsodJMCFEK7L8HtfQEN42kq0J7UFOEDfqVp7uV/Lpr8oIYT4nTSrAPeylaDqFRSPgNoLRibAxK9+m4sSQojfSbNpQrHYHPippZgN/mcXMxZCiKtYs0lCo1kbRm9x8/+9L0UIIa4IzSbAy8w2AinD6hH4e1+KEEJcEZpNgBst2kyEdo86bmAKIcRVovkEeGUNXPWSGrgQQkAzCvAys51ApQylri6EQghxlWg23QiNJjMBSjl5NS3mIC5gtVrJyMjAZDL93pcihKgnT09PIiMjcXNzq1f5ZhPgljJtIit9TYs5iAtkZGTg5+dHdHQ0yvnrhwohrjiqqpKfn09GRgbt2rWr1z71bkJRFEWvKMouRVF+qHzdTlGUbYqiHFUU5UtFUdwv8brrxV6WD4Cbb0hTnsZlmEwmQkJCJLyFaCYURSEkJKRB/2tuSBv4o8CBc16/CsxSVbUjUAjc34BjNZijXKuBe/hLgNeXhLcQzUtD/83WK8AVRYkERgEfVL5WgGFA5coJLARua9CZG0itKADAzTe0KU8jhBDNRn1r4LOBvwKOytchQJGqqrbK1xlARE07KooyVVGUJEVRknJzcy/9Qk31mIlQXFH0ej3x8fH06NGDcePGUV5eftGyy5Yt45VXXqn1eCdOnODzzz93vl67di2KovD99987t91yyy2sXbu21uMsWLCAzMzM+n2I87z33nt88sknNR4nOjqavLy8SzruuYqKinj33Xcv2J6fn098fDzx8fG0bNmSiIgI52uLxYKiKDz55JPO8m+88QYzZ86s9Vxr165l8+bNl33Nl2vmzJm88cYbjX7c6OhoevbsSWxsLEOGDOHkyZO1lv/222/Zv39/ncc9v9xzzz3Hr7/+etnX21B1BriiKLcAOaqqJl/KCVRVna+qaqKqqolhYWGXcggA9KY6VuMRVxwvLy9SUlLYu3cv7u7uvPfeexctO3r0aGbMmFHr8c4PcIDIyEhefvnlBl3X5QT4tGnTmDRp0mUfpzYXC/CQkBBSUlJISUlh2rRpPP74487X7u7ueHh4sGTJkgb9EmmMALfZbHUX+h2tWbOG1NRUhg4dyksvvVRr2UsN8H/+859cf/31l32tDVWfXijXAqMVRbkZ8AT8gbeAQEVRDJW18EjgdNNdJhgslYs5eNYxE6G4wAvf72N/ZkmjHrN7a3+evzWm3uUHDRpEamoqBQUFTJkyhePHj+Pt7c38+fOJjY1lwYIFJCUl8fbbb3Pvvffi7+9PUlISZ86c4bXXXuPOO+9kxowZHDhwgPj4eCZPnkyvXr2Ii4vDarWycuVKbrjhhmrnTE5O5oknnqCsrIzQ0FAWLFjApk2bSEpKYuLEiXh5ebFlyxa8vLwAyMnJ4aabbiI5OZndu3cTHx/PyZMniYqKokOHDuzZs4fXXnsNX19foqOjLzgOwNy5c/n++++xWq18/fXXdO3a9aKfeebMmfj6+vLUU08B0KNHD3744QdmzJjBsWPHiI+P54YbbuD111+v13dsMBiYOnUqs2bNuuCXWm5uLtOmTSM9PR2A2bNnExERwXvvvYder+ezzz5j7ty5DBo0qF7nGjp0KPHx8WzcuJG7776bzp0789JLL2GxWAgJCWHRokW0aNGCmTNnkp6ezvHjx0lPT+exxx7jkUceAeDll19m4cKFhIeH06ZNGxISEgCcv6DKy8vp0KEDH330EUFBQQwdOpRevXqxYcMGjEYjn3zyCf/+97/Zs2cP48ePrzOc+/fvz5w5cwCtMjBlyhTy8vIICwvj448/JiMjg2XLlrFu3TpeeuklvvnmG1avXs38+fOxWCx07NiRTz/9lJSUlAvKvfjii9xyyy3ceeedrFq1iqeeegqbzUafPn2YN28eHh4eREdHM3ny5At+Pi5HnTVwVVX/pqpqpKqq0cAEYLWqqhOBNcCdlcUmA99d1pXUwd1aTJniCzp9U55GNAGbzcZPP/1Ez549ef755+nVqxepqan861//ctZmz5eVlcXGjRudgQbwyiuvMGjQIFJSUnj88cedZZ999tkL/vFarVYefvhhFi9eTHJyMlOmTOHZZ5/lzjvvJDExkUWLFpGSkuIMb4Dw8HBMJhMlJSVs2LCBxMRENmzYwMmTJwkPD8fb29tZ9mLHCQ0NZefOnTz44IPOJoH6fuYqr7zyCh06dCAlJaXe4V3loYceYtGiRRQXF1fb/uijj/L444+zY8cOvvnmGx544AGio6Or1eTrG95VLBYLSUlJPPnkkwwcOJCtW7eya9cuJkyYwGuvveYsd/DgQVasWMH27dt54YUXsFqtJCcn88UXX5CSksLy5cvZsWOHs/ykSZN49dVXSU1NpWfPnrzwwgvO99zd3UlKSmLatGmMGTOGd955h71797JgwQLy8/Nrvd6ff/6Z227TbtU9/PDDTJ48mdTUVCZOnMgjjzzCgAEDGD16NK+//jopKSl06NCB22+/nR07drB79266devGhx9+WGO5KiaTiXvvvZcvv/ySPXv2YLPZmDdvnvP9mn4+Lsfl9AN/BvhCUZSXgF3Ah5d9NbXwsJZg1Pnh25QncVENqSk3poqKCuLj4wGtBn7//ffTr18/vvnmGwCGDRtGfn4+JSUX/u/gtttuQ6fT0b17d7Kzs2s9z+DBgwHYuHGjc9uhQ4fYu3evs1Zut9tp1apVndc8YMAANm3axPr16/n73//Ozz//jKqq9Q6322+/HYCEhASWLFnivK76fObG4O/vz6RJk5gzZ061X06//vprtf/yl5SUUFZWdlnnGj9+vPN5RkYG48ePJysrC4vFUq0f86hRo/Dw8MDDw4Pw8HCys7PZsGEDY8eOdf5SHD16NADFxcUUFRUxZMgQACZPnsy4ceOcx6oq17NnT2JiYpx/p+3bt+fUqVOEhFzYS+26666joKAAX19fXnzxRQC2bNni/Pu55557+Otf/1rjZ9y7dy//+Mc/KCoqoqysjJEjR9b6nRw6dIh27drRuXNn5/W/8847PPbYY0DNPx+Xo0EBrqrqWmBt5fPjQN/LvoJ68rYVU2GQqWSbk6o28Evh4eHhfK6qap3lq2rhBoPBuU9MTIyzaaO+Bg8e7Kx1jxkzhldffRVFURg1alTdO59z3Xq9vs62YYPBgMPhcL5urFGzjz32GL179+a+++5zbnM4HGzduhVPT896H2fkyJFkZ2eTmJjIBx98cMH7Pj5nlyx8+OGHeeKJJxg9ejRr166tdvP03L/L+nwvtak6lk6nq3ZcnU530eOuWbOGwMBAJk6cyPPPP8+bb75Z7/Pde++9fPvtt8TFxbFgwYI6b5DX9/ov93uo0mzmQvFxlGJyk/bv5m7QoEEsWrQI0G6ghYaG4u9fv1/Mfn5+lJaW1vjeiBEjKCwsJDU1FYAuXbqQm5vrDHCr1cq+ffvqPM6gQYP47LPP6NSpEzqdjuDgYJYvX87AgQMbdD3nH7OmzxwdHc3OnTsB2LlzJ2lpaQ067sUEBwdz11138eGHZ/9TPGLECObOnet8XfWLtbZzrVixgpSUlBrD+3zFxcVERGgd0RYuXFhn+cGDB/Ptt99SUVFBaWmpsydRQEAAQUFBbNiwAYBPP/3UWRu/HAaDgdmzZ/PJJ59QUFDAgAED+OKLLwBYtGiR839Y538fpaWltGrVCqvV6vw7rKlclS5dunDixAmOHj3aqNd/Mc0mwH3VUqwS4M3ezJkzSU5OJjY2lhkzZtTrH3uV2NhY9Ho9cXFxzJo164L3n332WU6dOgVobaWLFy/mmWeeIS4ujvj4eGdvi3vvvZdp06YRHx9PRUVFtWNER0ejqqqzWWbgwIEEBgYSFHRh76fajlOfz3zHHXdQUFBATEwMb7/9tvO/3SEhIVx77bX06NGDp59+ut7fz7mefPLJar1R5syZQ1JSErGxsXTv3t3ZI+jWW29l6dKlxMfHO0PzUsycOZNx48aRkJBAaGjdYzV69+7N+PHjiYuL46abbqJPnz7O9xYuXMjTTz9NbGwsKSkpPPfcc5d8Xedq1aoVd999N++88w5z587l448/JjY2lk8//ZS33noLgAkTJvD666/Tq1cvjh07xosvvki/fv249tprq91wPL9cFU9PTz7++GPGjRtHz5490el0TJs2rVGuvyZKff572lgSExPVpKSkBu+nqipFMyNJa3kjvR9s0qZ2l3HgwAG6dev2e1+GEKKBavq3qyhKsqqqieeXbRY1cLPVRgBG7J4yF7gQQlRpFgFuLClAp6ionjKIRwghqjSLADeXVPbvlFGYQgjh1CwC3FSizaEic4ELIcRZzSLArWXaTIQS4EIIcVazCHCbsXIxBz+ZC1wIIao0iwBXKxdz8PSTucCbE5lOtroVK1Y4p3/19fWlS5cuxMfHM2nSpN/lszSmoUOHcildhGtz4sQJvLy8iI+Pp3v37kyaNAmr1VrrPrNnz6715+xi5W6++WaKioou+5p/a80jwCsXc/CU1XiaFZlOtrqRI0c6p389dyKsql8Iv/VnqWK32y9r/6ZUNanXnj17yMjI4Kuvvqq1/KUG+PLlywkMbH7dlJtFgCsVRZSoXvg2YB4HcY6fZsDHoxr3z0+1h+35Bg0axNGjRykoKOC2224jNjaWa665xjn0fcGCBUyfPh3QRjhWzQ7Xvn17Fi/WFn6aMWMGGzZsID4+3jkSMy4ujoCAAFauXHnBOZOTkxkyZAgJCQmMHDmSrKwsFi9e7JwG9vwRlDk5Oc4pTXfv3o2iKM7pVzt06EB5eblz4YGLHWfu3Ln07t2bnj17cvDgwQZ9R435Weri6+vLk08+SVxcHFu2bOGf//wnffr0oUePHkydOtU5/8zQoUN55pln6Nu3L507d3aO1qyoqGDChAl069aNsWPHVjv3//73P3r27EmPHj145plnqp3z6aefJiYmhuuvv57t27czdOhQ2rdvz7Jly2q9Xr1eT9++fTl9Wpu1etWqVfTq1YuePXsyZcoUzGYzc+bMITMzk+uuu47rrrsOgAcffJDExERiYmJ4/vnnAWosd+7/nt5880169OhBjx49mD17NqBVHrp168af/vQnYmJiGDFiRIO+76bSLALcYC6kWPXFx0Omkm2OrvbpZBuisT5LXYxGI/369WP37t0MHDiQ6dOns2PHDvbu3UtFRQU//PCDs6zNZmP79u3Mnj3bObXrvHnz8Pb25sCBA7zwwgskJ2vrvWRmZvLMM8+wevVqUlJS2LFjB99++63znMOGDWPfvn34+fnxj3/8g5UrV7J06dI6h8ubTCa2bdvGjTfeeNEpWx955BFat27NmjVrWLNmDaDNOZ6UlERqairr1q0jNTW1xnJVkpOT+fjjj9m2bRtbt27l/fffZ9euXQAcOXKEhx56iH379hEYGOicYfL3dDnTyf5mDOZiihU/2uibxe+bK89NtbctNxWZTrbh04U25mepjV6v54477nC+XrNmDa+99hrl5eXO+VluvfVWoPpnOnHiBADr1693LswQGxtLbGwsADt27GDo0KFUrb41ceJE1q9fz2233Ya7uzs33ngjoE0H6+HhgZubGz179nQe93xVC1ukpaUxatQoYmNj2b17d61Ttp7rq6++Yv78+dhsNrL+v727jY2qzuI4/v2lFka6CS3WGGQaUvfcnQAABolJREFUnI1EICTYYgqmC1ncTSjuBgrxhWKiTQQCmOgakw3GhOArugnZVRNCstF9zKa7WRfYxoRNViQIL8QWNVqLDyhq61Zo6yqUBhU8vri3k6Ew2NKZ3t4755NMOvfOtHPOnJmTzpmZ/+3tpaurKxvrlRw5coQ1a9ZkV1pcu3Ythw8fZtWqVWQymezjOfe+iFIsGvhLNz7Am2f/R/4JqpuMfDnZa1sutBC5dHd3Zxvwpk2bLltQKZVKUVYWvKI9f/48W7ZsoaOjg5qaGrZv337J0raFWgK1vLw8e9T13OVgr7YU7PAMvL+/n4aGBtra2pg9e/aobu/kyZPs3LmT9vZ2qqqqaG5uHteSvSOXxfURyii9Vz6PrlRd1GG4AijF5WTHqhC51NTUXHL8zKsZbmrV1dUMDg5m33O4mmXLlmXfUO7s7MzGWl9fz6FDh+jv7+fixYu0trYWZDnV6upqWlpa2LFjx1WXbM29P86cOUNFRQXTp0/n1KlT7N+/P/v38t1vS5cuZd++fQwNDXHu3Dn27t075iMVTaRYNPDBry8wbYrPv5OgFJeTvRaFyGW0Kisr2bBhAwsWLGDFihWXLO2az+bNmxkcHGTevHls27Yt++bvzJkzaWlpYfny5SxcuJBFixaxevXqa4prpKamJoaGhmhvb8+7ZOvGjRtpbGzM3n5tbS1z585l3bp1NDQ0ZP9W7vVy1dXV0dzcTH19PYsXL2b9+vXU1tYWJP5iiMVysrsOnuDs+QtsXTm+A4CWEl9O1rl4GstysrGYgT+8/NaoQ3DOuUknFiMU55xzl/MGnmATOR5zzo3fWJ+z3sATKpVKMTAw4E3cuZgwMwYGBkiN4RvnsZiBu7FLp9P09PTQ19cXdSjOuVFKpVKk0+lRX98beEKVl5eTyWSiDsM5V0Q+QnHOuZjyBu6cczHlDdw552JqQr+JKakP+OQaf70ayH+4k+QqxbxLMWcozbw959GZbWY3jtw5oQ18PCR1XOmrpElXinmXYs5Qmnl7zuPjIxTnnIspb+DOORdTcWrgv486gIiUYt6lmDOUZt6e8zjEZgbunHPuUnH6D9w551wOb+DOORdTsWjgkholvSfphKStUcdTDJJqJB2U1CXpHUmPhvtnSPqvpA/Cn5cf2yvmJJVJekPSi+F2RtLRsN7/kDQl6hgLTVKlpBckvSvpuKQ7k15rSY+Fj+1OSa2SUkmstaQ/SDotqTNn3xVrq8CzYf5vSRrTwX8nfQOXVAbsAlYC84H7JM2PNqqiuAA8bmbzgSXAw2GeW4EDZjYHOBBuJ82jwPGc7d8AvzOzW4H/Aw9FElVxPQP8x8zmAgsJ8k9srSXNAh4B7jCzBUAZcC/JrPWfgMYR+/LVdiUwJzxtBHaP5YYmfQMH6oETZvaRmX0D/B0ozFFSJxEz6zWz18PzZwme0LMIch0+8u+fgaZoIiwOSWngF8Bz4baAu4DhQ6MnMefpwDLgeQAz+8bMviThtSZY/fR6SdcB04BeElhrM3sF+GLE7ny1XQ38xQKvApWSZo72tuLQwGcB3TnbPeG+xJJ0C1ALHAVuMrPe8KLPgZsiCqtYngZ+DXwXbt8AfGlmF8LtJNY7A/QBfwxHR89JqiDBtTazz4CdwKcEjfsr4BjJr/WwfLUdV3+LQwMvKZJ+BPwL+JWZncm9zILPfCbmc5+SfgmcNrNjUccywa4D6oDdZlYLnGPEuCSBta4i+G8zA9wMVHD5mKEkFLK2cWjgnwE1OdvpcF/iSConaN5/M7M94e5Twy+pwp+no4qvCBqAVZI+JhiN3UUwG64MX2ZDMuvdA/SY2dFw+wWChp7kWv8cOGlmfWb2LbCHoP5Jr/WwfLUdV3+LQwNvB+aE71ZPIXjjoy3imAounP0+Dxw3s9/mXNQGPBiefxD490THVixm9oSZpc3sFoK6vmxm9wMHgXvCqyUqZwAz+xzolnRbuOtnQBcJrjXB6GSJpGnhY30450TXOke+2rYBD4SfRlkCfJUzavlhZjbpT8DdwPvAh8CTUcdTpBx/QvCy6i3gzfB0N8FM+ADwAfASMCPqWIuU/0+BF8PzPwZeA04A/wSmRh1fEfK9HegI670PqEp6rYGngHeBTuCvwNQk1hpoJZjzf0vwauuhfLUFRPApuw+Btwk+pTPq2/Kv0jvnXEzFYYTinHPuCryBO+dcTHkDd865mPIG7pxzMeUN3DnnYsobuHPOxZQ3cOeci6nvAVUrVF8vY5UxAAAAAElFTkSuQmCC\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": [],
"needs_background": "light"
}
}
]
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "zi2J7X7gSI0-",
"outputId": "b4fd73c5-aafe-423d-e90e-4a42efe64dd8"
},
"source": [
"max(valaccs_1),max(valaccs_2),max(valaccs_3)"
],
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"(16.977309562398702, 85.49432739059968, 86.10210696920583)"
]
},
"metadata": {
"tags": []
},
"execution_count": 57
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "LWsuwW2k8VuR",
"colab": {
"base_uri": "https://localhost:8080/"
},
"outputId": "08ef4ee9-484c-46fe-aea7-9a0f92d9d842"
},
"source": [
"! git clone https://github.com/NVIDIA/MinkowskiEngine"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"text": [
"Cloning into 'MinkowskiEngine'...\n",
"remote: Enumerating objects: 149, done.\u001b[K\n",
"remote: Counting objects: 100% (149/149), done.\u001b[K\n",
"remote: Compressing objects: 100% (118/118), done.\u001b[K\n",
"remote: Total 6915 (delta 78), reused 73 (delta 31), pack-reused 6766\u001b[K\n",
"Receiving objects: 100% (6915/6915), 14.62 MiB | 21.63 MiB/s, done.\n",
"Resolving deltas: 100% (5446/5446), done.\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "2LbQPTH2McPf",
"outputId": "2cb9c640-0860-4ace-b15f-735df060b39f"
},
"source": [
"%cd MinkowskiEngine/"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"text": [
"/content/MinkowskiEngine\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "uDqPx6JHMtm-",
"outputId": "5b126b9a-98fe-4fa6-e9b4-de41d0bbb79f"
},
"source": [
"!pip install -U MinkowskiEngine --install-option=\"--blas=openblas\" -v --no-deps "
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.7/dist-packages/pip/_internal/commands/install.py:283: UserWarning: Disabling all use of wheels due to the use of --build-options / --global-options / --install-options.\n",
" cmdoptions.check_install_build_global(options)\n",
"Created temporary directory: /tmp/pip-ephem-wheel-cache-iegtg94u\n",
"Created temporary directory: /tmp/pip-req-tracker-be61vixc\n",
"Created requirements tracker '/tmp/pip-req-tracker-be61vixc'\n",
"Created temporary directory: /tmp/pip-install-nrmqg_h6\n",
"1 location(s) to search for versions of MinkowskiEngine:\n",
"* https://pypi.org/simple/minkowskiengine/\n",
"Getting page https://pypi.org/simple/minkowskiengine/\n",
"Found index url https://pypi.org/simple\n",
"Looking up \"https://pypi.org/simple/minkowskiengine/\" in the cache\n",
"Request header has \"max_age\" as 0, cache bypassed\n",
"Starting new HTTPS connection (1): pypi.org:443\n",
"https://pypi.org:443 \"GET /simple/minkowskiengine/ HTTP/1.1\" 200 1580\n",
"Updating cache with response from \"https://pypi.org/simple/minkowskiengine/\"\n",
"Caching due to etag\n",
"Analyzing links from page https://pypi.org/simple/minkowskiengine/\n",
" Found link https://files.pythonhosted.org/packages/77/7f/f1a468f7ff10f2b47441c3732604032df7c66dcb0e983d408747dff4569e/MinkowskiEngine-0.3.2.tar.gz#sha256=0a63bb358df3f31151a1a286014e34e95d1287c008bb644db50c0bfad2ac06c7 (from https://pypi.org/simple/minkowskiengine/) (requires-python:>=3.6), version: 0.3.2\n",
" Found link https://files.pythonhosted.org/packages/d0/9b/951919938e9767baa15962a2662a087e8f0adf7716509ea3b4ced1c162bf/MinkowskiEngine-0.3.3.tar.gz#sha256=ce06744206fa625815caed81793669bdbb46bd8753a9bdb213de8a278434de51 (from https://pypi.org/simple/minkowskiengine/) (requires-python:>=3.6), version: 0.3.3\n",
" Found link https://files.pythonhosted.org/packages/a3/b1/6d81bdea2e652cd4fd3ff280449b9b5b24055ca43e003e2d6fddbf9834c8/MinkowskiEngine-0.4.0.tar.gz#sha256=cc8e6c3ce7d8e2ae79fd492d6fbd96b61919c415933c9f93422af434b2e164e3 (from https://pypi.org/simple/minkowskiengine/) (requires-python:>=3.6), version: 0.4.0\n",
" Found link https://files.pythonhosted.org/packages/dd/cd/0c763e1be0bebe50552bccb8196052c4d9ec4e028304857bcbed76f1efc0/MinkowskiEngine-0.4.1.tar.gz#sha256=c3018aafdeea590fc408f031447d6cd9cc9c22ded241c275944fd16b56df1b58 (from https://pypi.org/simple/minkowskiengine/) (requires-python:>=3.6), version: 0.4.1\n",
" Found link https://files.pythonhosted.org/packages/d7/7c/3892a4d9ee70869b900ba06c750943e31c85fc2a165dc483e3b79cd61b39/MinkowskiEngine-0.4.2.tar.gz#sha256=911433888976f69db3a5e58308408e7f3263e4646d8ef79cbce6218c2cae0bae (from https://pypi.org/simple/minkowskiengine/) (requires-python:>=3.6), version: 0.4.2\n",
" Found link https://files.pythonhosted.org/packages/35/86/7e3f38a84be5f1a35fef6bf2d8412e120f81f9df744324983c6218164f17/MinkowskiEngine-0.4.3.tar.gz#sha256=34744a39478dcf1a0cb600c5fa9182278c167caa44fb0abca38b0c3209560061 (from https://pypi.org/simple/minkowskiengine/) (requires-python:>=3.6), version: 0.4.3\n",
" Skipping link: unsupported archive format: .egg: https://files.pythonhosted.org/packages/9c/6b/29b051cc746440dbb63f147ec2b58199e0754b2ef8f6e3469f05b780883f/MinkowskiEngine-0.5.0b0-py3.7-linux-x86_64.egg#sha256=f7fde0af0d17ad4e39cb1b10a2ddf87c4474d47b9d93bbbb15a89c05b6f01879 (from https://pypi.org/simple/minkowskiengine/) (requires-python:>=3.6)\n",
" Skipping link: unsupported archive format: .egg: https://files.pythonhosted.org/packages/4f/84/103e1a7916d81448e4fc2f70c341111b1d605702dcbc970c056875a100e7/MinkowskiEngine-0.5.0b0-py3.8-linux-x86_64.egg#sha256=5ca6842ad64365e7f69c46afbcec1ffa3ffa401d157a7a29bb5220373793c8c4 (from https://pypi.org/simple/minkowskiengine/) (requires-python:>=3.6)\n",
" Skipping link: unsupported archive format: .egg: https://files.pythonhosted.org/packages/b9/e6/ba2548a97663d7df05ee7410c2ebb843a3c9fc3e49b5da0d2841d250b439/MinkowskiEngine-0.5.0rc0-py3.7-linux-x86_64.egg#sha256=e4199932e7a594fe016f75e69f87e47a2927e7ba528956d0f8cba8b7abbbde5a (from https://pypi.org/simple/minkowskiengine/) (requires-python:>=3.6)\n",
" Skipping link: unsupported archive format: .egg: https://files.pythonhosted.org/packages/ae/f1/96a621130c2302064ff569cf7e38d9b7e6306eb72d14f4ab71e2259bd94f/MinkowskiEngine-0.5.0rc0-py3.8-linux-x86_64.egg#sha256=465e6473cf5793e4e1e13a431c25f81f7c01b662560e61e61b2965a82eb26da7 (from https://pypi.org/simple/minkowskiengine/) (requires-python:>=3.6)\n",
" Skipping link: unsupported archive format: .egg: https://files.pythonhosted.org/packages/8e/41/3f66ced5f14afe64be00d6791d19b9e25170ed9395a89dea9f9490b1ddd7/MinkowskiEngine-0.5.0-py3.8-linux-x86_64.egg#sha256=347b5b6899a258b713db3ce161e3f3220bb060387a59e60b1cf5255bec94de07 (from https://pypi.org/simple/minkowskiengine/) (requires-python:>=3.6)\n",
" Found link https://files.pythonhosted.org/packages/fa/9b/e95d68d7dbff1f7ae8e89d6cc823c0e452f158b13cbecf3092e32a6f042f/MinkowskiEngine-0.5.0.tar.gz#sha256=7f2f4cd33cf9a5011a68808925c24767e36a19ebabe2506994d5e89ac08c4730 (from https://pypi.org/simple/minkowskiengine/) (requires-python:>=3.6), version: 0.5.0\n",
" Found link https://files.pythonhosted.org/packages/00/21/378694329d51767a94a8e76978ea490fa4ce9fec0b1f51aa044d3bff6ad3/MinkowskiEngine-0.5.1.tar.gz#sha256=a8243325d839180646b94538a99edcc374e779e70a7751fdaf2337cce70b84ca (from https://pypi.org/simple/minkowskiengine/) (requires-python:>=3.6), version: 0.5.1\n",
" Found link https://files.pythonhosted.org/packages/d1/53/8968b0e4e9552f3a7676468824c8d8b16563dbad9b858e9efef6ce2c1a08/MinkowskiEngine-0.5.2.tar.gz#sha256=c7aaa122ba624b100eb249a1d262a1949b8545ca9fc5be859b1bd3f38bf683f7 (from https://pypi.org/simple/minkowskiengine/) (requires-python:>=3.6), version: 0.5.2\n",
"Given no hashes to check 9 links for project 'MinkowskiEngine': discarding no candidates\n",
"Using version 0.5.2 (newest of versions: 0.3.2, 0.3.3, 0.4.0, 0.4.1, 0.4.2, 0.4.3, 0.5.0, 0.5.1, 0.5.2)\n",
"Collecting MinkowskiEngine\n",
" Created temporary directory: /tmp/pip-unpack-v7dhrt1o\n",
" Looking up \"https://files.pythonhosted.org/packages/d1/53/8968b0e4e9552f3a7676468824c8d8b16563dbad9b858e9efef6ce2c1a08/MinkowskiEngine-0.5.2.tar.gz\" in the cache\n",
" No cache entry available\n",
" Starting new HTTPS connection (1): files.pythonhosted.org:443\n",
" https://files.pythonhosted.org:443 \"GET /packages/d1/53/8968b0e4e9552f3a7676468824c8d8b16563dbad9b858e9efef6ce2c1a08/MinkowskiEngine-0.5.2.tar.gz HTTP/1.1\" 200 242310\n",
"\u001b[?25l Downloading https://files.pythonhosted.org/packages/d1/53/8968b0e4e9552f3a7676468824c8d8b16563dbad9b858e9efef6ce2c1a08/MinkowskiEngine-0.5.2.tar.gz (242kB)\n",
"\u001b[K |███████████████████████████████ | 235kB 8.1MB/s eta 0:00:01 Ignoring unknown cache-control directive: immutable\n",
" Updating cache with response from \"https://files.pythonhosted.org/packages/d1/53/8968b0e4e9552f3a7676468824c8d8b16563dbad9b858e9efef6ce2c1a08/MinkowskiEngine-0.5.2.tar.gz\"\n",
" Caching due to etag\n",
"\u001b[K |████████████████████████████████| 245kB 8.1MB/s \n",
"\u001b[?25h Added MinkowskiEngine from https://files.pythonhosted.org/packages/d1/53/8968b0e4e9552f3a7676468824c8d8b16563dbad9b858e9efef6ce2c1a08/MinkowskiEngine-0.5.2.tar.gz#sha256=c7aaa122ba624b100eb249a1d262a1949b8545ca9fc5be859b1bd3f38bf683f7 to build tracker '/tmp/pip-req-tracker-be61vixc'\n",
" Running setup.py (path:/tmp/pip-install-nrmqg_h6/MinkowskiEngine/setup.py) egg_info for package MinkowskiEngine\n",
" Running command python setup.py egg_info\n",
" WARNING: Skipping MinkowskiEngine as it is not installed.\n",
" --------------------------------\n",
" | CUDA compilation set |\n",
" --------------------------------\n",
"\n",
" Using BLAS=openblas\n",
" Using the default compiler\n",
" running egg_info\n",
" creating /tmp/pip-install-nrmqg_h6/MinkowskiEngine/pip-egg-info/MinkowskiEngine.egg-info\n",
" writing /tmp/pip-install-nrmqg_h6/MinkowskiEngine/pip-egg-info/MinkowskiEngine.egg-info/PKG-INFO\n",
" writing dependency_links to /tmp/pip-install-nrmqg_h6/MinkowskiEngine/pip-egg-info/MinkowskiEngine.egg-info/dependency_links.txt\n",
" writing requirements to /tmp/pip-install-nrmqg_h6/MinkowskiEngine/pip-egg-info/MinkowskiEngine.egg-info/requires.txt\n",
" writing top-level names to /tmp/pip-install-nrmqg_h6/MinkowskiEngine/pip-egg-info/MinkowskiEngine.egg-info/top_level.txt\n",
" writing manifest file '/tmp/pip-install-nrmqg_h6/MinkowskiEngine/pip-egg-info/MinkowskiEngine.egg-info/SOURCES.txt'\n",
" reading manifest file '/tmp/pip-install-nrmqg_h6/MinkowskiEngine/pip-egg-info/MinkowskiEngine.egg-info/SOURCES.txt'\n",
" reading manifest template 'MANIFEST.in'\n",
" writing manifest file '/tmp/pip-install-nrmqg_h6/MinkowskiEngine/pip-egg-info/MinkowskiEngine.egg-info/SOURCES.txt'\n",
" /usr/local/lib/python3.7/dist-packages/torch/utils/cpp_extension.py:352: UserWarning: Attempted to use ninja as the BuildExtension backend but we could not find ninja.. Falling back to using the slow distutils backend.\n",
" warnings.warn(msg.format('we could not find ninja.'))\n",
" Source in /tmp/pip-install-nrmqg_h6/MinkowskiEngine has version 0.5.2, which satisfies requirement MinkowskiEngine from https://files.pythonhosted.org/packages/d1/53/8968b0e4e9552f3a7676468824c8d8b16563dbad9b858e9efef6ce2c1a08/MinkowskiEngine-0.5.2.tar.gz#sha256=c7aaa122ba624b100eb249a1d262a1949b8545ca9fc5be859b1bd3f38bf683f7\n",
" Removed MinkowskiEngine from https://files.pythonhosted.org/packages/d1/53/8968b0e4e9552f3a7676468824c8d8b16563dbad9b858e9efef6ce2c1a08/MinkowskiEngine-0.5.2.tar.gz#sha256=c7aaa122ba624b100eb249a1d262a1949b8545ca9fc5be859b1bd3f38bf683f7 from build tracker '/tmp/pip-req-tracker-be61vixc'\n",
"Skipping wheel build for MinkowskiEngine, due to binaries being disabled for it.\n",
"Installing collected packages: MinkowskiEngine\n",
" Created temporary directory: /tmp/pip-record-oecir8zv\n",
" Running command /usr/bin/python3 -u -c 'import sys, setuptools, tokenize; sys.argv[0] = '\"'\"'/tmp/pip-install-nrmqg_h6/MinkowskiEngine/setup.py'\"'\"'; __file__='\"'\"'/tmp/pip-install-nrmqg_h6/MinkowskiEngine/setup.py'\"'\"';f=getattr(tokenize, '\"'\"'open'\"'\"', open)(__file__);code=f.read().replace('\"'\"'\\r\\n'\"'\"', '\"'\"'\\n'\"'\"');f.close();exec(compile(code, __file__, '\"'\"'exec'\"'\"'))' install --record /tmp/pip-record-oecir8zv/install-record.txt --single-version-externally-managed --compile --blas=openblas\n",
" WARNING: Skipping MinkowskiEngine as it is not installed.\n",
" --------------------------------\n",
" | CUDA compilation set |\n",
" --------------------------------\n",
"\n",
" Using BLAS=openblas\n",
" Using the default compiler\n",
" running install\n",
" running build\n",
" running build_py\n",
" creating build\n",
" creating build/lib.linux-x86_64-3.7\n",
" creating build/lib.linux-x86_64-3.7/MinkowskiEngine\n",
" copying ./MinkowskiEngine/MinkowskiConvolution.py -> build/lib.linux-x86_64-3.7/MinkowskiEngine\n",
" copying ./MinkowskiEngine/MinkowskiCommon.py -> build/lib.linux-x86_64-3.7/MinkowskiEngine\n",
" copying ./MinkowskiEngine/MinkowskiSparseTensor.py -> build/lib.linux-x86_64-3.7/MinkowskiEngine\n",
" copying ./MinkowskiEngine/MinkowskiKernelGenerator.py -> build/lib.linux-x86_64-3.7/MinkowskiEngine\n",
" copying ./MinkowskiEngine/MinkowskiOps.py -> build/lib.linux-x86_64-3.7/MinkowskiEngine\n",
" copying ./MinkowskiEngine/sparse_matrix_functions.py -> build/lib.linux-x86_64-3.7/MinkowskiEngine\n",
" copying ./MinkowskiEngine/MinkowskiFunctional.py -> build/lib.linux-x86_64-3.7/MinkowskiEngine\n",
" copying ./MinkowskiEngine/MinkowskiCoordinateManager.py -> build/lib.linux-x86_64-3.7/MinkowskiEngine\n",
" copying ./MinkowskiEngine/MinkowskiBroadcast.py -> build/lib.linux-x86_64-3.7/MinkowskiEngine\n",
" copying ./MinkowskiEngine/MinkowskiInterpolation.py -> build/lib.linux-x86_64-3.7/MinkowskiEngine\n",
" copying ./MinkowskiEngine/MinkowskiPruning.py -> build/lib.linux-x86_64-3.7/MinkowskiEngine\n",
" copying ./MinkowskiEngine/MinkowskiNonlinearity.py -> build/lib.linux-x86_64-3.7/MinkowskiEngine\n",
" copying ./MinkowskiEngine/MinkowskiPooling.py -> build/lib.linux-x86_64-3.7/MinkowskiEngine\n",
" copying ./MinkowskiEngine/MinkowskiChannelwiseConvolution.py -> build/lib.linux-x86_64-3.7/MinkowskiEngine\n",
" copying ./MinkowskiEngine/diagnostics.py -> build/lib.linux-x86_64-3.7/MinkowskiEngine\n",
" copying ./MinkowskiEngine/MinkowskiTensorField.py -> build/lib.linux-x86_64-3.7/MinkowskiEngine\n",
" copying ./MinkowskiEngine/__init__.py -> build/lib.linux-x86_64-3.7/MinkowskiEngine\n",
" copying ./MinkowskiEngine/MinkowskiNormalization.py -> build/lib.linux-x86_64-3.7/MinkowskiEngine\n",
" copying ./MinkowskiEngine/MinkowskiTensor.py -> build/lib.linux-x86_64-3.7/MinkowskiEngine\n",
" copying ./MinkowskiEngine/MinkowskiNetwork.py -> build/lib.linux-x86_64-3.7/MinkowskiEngine\n",
" copying ./MinkowskiEngine/MinkowskiUnion.py -> build/lib.linux-x86_64-3.7/MinkowskiEngine\n",
" creating build/lib.linux-x86_64-3.7/MinkowskiEngine/utils\n",
" copying ./MinkowskiEngine/utils/gradcheck.py -> build/lib.linux-x86_64-3.7/MinkowskiEngine/utils\n",
" copying ./MinkowskiEngine/utils/quantization.py -> build/lib.linux-x86_64-3.7/MinkowskiEngine/utils\n",
" copying ./MinkowskiEngine/utils/coords.py -> build/lib.linux-x86_64-3.7/MinkowskiEngine/utils\n",
" copying ./MinkowskiEngine/utils/init.py -> build/lib.linux-x86_64-3.7/MinkowskiEngine/utils\n",
" copying ./MinkowskiEngine/utils/collation.py -> build/lib.linux-x86_64-3.7/MinkowskiEngine/utils\n",
" copying ./MinkowskiEngine/utils/__init__.py -> build/lib.linux-x86_64-3.7/MinkowskiEngine/utils\n",
" creating build/lib.linux-x86_64-3.7/MinkowskiEngine/modules\n",
" copying ./MinkowskiEngine/modules/resnet_block.py -> build/lib.linux-x86_64-3.7/MinkowskiEngine/modules\n",
" copying ./MinkowskiEngine/modules/senet_block.py -> build/lib.linux-x86_64-3.7/MinkowskiEngine/modules\n",
" copying ./MinkowskiEngine/modules/__init__.py -> build/lib.linux-x86_64-3.7/MinkowskiEngine/modules\n",
" running build_ext\n",
" /usr/local/lib/python3.7/dist-packages/torch/utils/cpp_extension.py:352: UserWarning: Attempted to use ninja as the BuildExtension backend but we could not find ninja.. Falling back to using the slow distutils backend.\n",
" warnings.warn(msg.format('we could not find ninja.'))\n",
" building 'MinkowskiEngineBackend._C' extension\n",
" creating build/temp.linux-x86_64-3.7\n",
" creating build/temp.linux-x86_64-3.7/tmp\n",
" creating build/temp.linux-x86_64-3.7/tmp/pip-install-nrmqg_h6\n",
" creating build/temp.linux-x86_64-3.7/tmp/pip-install-nrmqg_h6/MinkowskiEngine\n",
" creating build/temp.linux-x86_64-3.7/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src\n",
" creating build/temp.linux-x86_64-3.7/pybind\n",
" x86_64-linux-gnu-gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O2 -Wall -g -fdebug-prefix-map=/build/python3.7-a56wZI/python3.7-3.7.10=. -fstack-protector-strong -Wformat -Werror=format-security -g -fdebug-prefix-map=/build/python3.7-a56wZI/python3.7-3.7.10=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/local/lib/python3.7/dist-packages/torch/include -I/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.7/dist-packages/torch/include/TH -I/usr/local/lib/python3.7/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src -I/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/3rdparty -I/usr/include/python3.7m -c /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/math_functions_cpu.cpp -o build/temp.linux-x86_64-3.7/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/math_functions_cpu.o -fopenmp -O3 -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_gcc\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1011\" -DTORCH_EXTENSION_NAME=_C -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++14\n",
" /usr/local/cuda/bin/nvcc -I/usr/local/lib/python3.7/dist-packages/torch/include -I/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.7/dist-packages/torch/include/TH -I/usr/local/lib/python3.7/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src -I/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/3rdparty -I/usr/include/python3.7m -c /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/math_functions_gpu.cu -o build/temp.linux-x86_64-3.7/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/math_functions_gpu.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-options '-fPIC' --expt-relaxed-constexpr --expt-extended-lambda -O3 -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_gcc\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1011\" -DTORCH_EXTENSION_NAME=_C -D_GLIBCXX_USE_CXX11_ABI=0 -gencode=arch=compute_75,code=sm_75 -std=c++14\n",
" /usr/local/cuda/bin/nvcc -I/usr/local/lib/python3.7/dist-packages/torch/include -I/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.7/dist-packages/torch/include/TH -I/usr/local/lib/python3.7/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src -I/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/3rdparty -I/usr/include/python3.7m -c /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/coordinate_map_manager.cu -o build/temp.linux-x86_64-3.7/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/coordinate_map_manager.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-options '-fPIC' --expt-relaxed-constexpr --expt-extended-lambda -O3 -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_gcc\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1011\" -DTORCH_EXTENSION_NAME=_C -D_GLIBCXX_USE_CXX11_ABI=0 -gencode=arch=compute_75,code=sm_75 -std=c++14\n",
" /usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/boxing/impl/boxing.h(100): warning: integer conversion resulted in a change of sign\n",
"\n",
" /usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/op_registration/op_whitelist.h(39): warning: integer conversion resulted in a change of sign\n",
"\n",
" /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/coordinate_map_cpu.hpp(58): warning: variable \"float_type\" was declared but never referenced\n",
" detected during:\n",
" instantiation of \"std::pair<at::Tensor, at::Tensor> minkowski::CoordinateMapCPU<coordinate_type, TemplatedAllocator>::field_map(const coordinate_field_type *, minkowski::CoordinateMapCPU<coordinate_type, TemplatedAllocator>::size_type) const [with coordinate_type=int32_t, TemplatedAllocator=std::allocator, coordinate_field_type=float]\"\n",
" /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/coordinate_map_manager.cpp(329): here\n",
" instantiation of \"std::pair<at::Tensor, at::Tensor> minkowski::CoordinateMapManager<coordinate_type, coordinate_field_type, TemplatedAllocator, CoordinateMapType>::field_to_sparse_map(const minkowski::CoordinateMapKey *, const minkowski::CoordinateMapKey *) [with coordinate_type=int32_t, coordinate_field_type=float, TemplatedAllocator=std::allocator, CoordinateMapType=minkowski::CoordinateMapCPU]\"\n",
" /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/coordinate_map_manager.cpp(1442): here\n",
"\n",
" /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/coordinate_map_manager.cpp(714): warning: returning reference to local temporary\n",
" detected during instantiation of \"const minkowski::CoordinateMapManager<coordinate_type, coordinate_field_type, TemplatedAllocator, CoordinateMapType>::kernel_map_type &minkowski::CoordinateMapManager<coordinate_type, coordinate_field_type, TemplatedAllocator, CoordinateMapType>::kernel_map(const minkowski::CoordinateMapKey *, const minkowski::CoordinateMapKey *, const minkowski::CoordinateMapManager<coordinate_type, coordinate_field_type, TemplatedAllocator, CoordinateMapType>::stride_type &, const minkowski::CoordinateMapManager<coordinate_type, coordinate_field_type, TemplatedAllocator, CoordinateMapType>::stride_type &, const minkowski::CoordinateMapManager<coordinate_type, coordinate_field_type, TemplatedAllocator, CoordinateMapType>::stride_type &, minkowski::RegionType::Type, const at::Tensor &, __nv_bool, __nv_bool) [with coordinate_type=int32_t, coordinate_field_type=float, TemplatedAllocator=std::allocator, CoordinateMapType=minkowski::CoordinateMapCPU]\"\n",
" (1442): here\n",
"\n",
" /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/coordinate_map_manager.cpp(714): warning: returning reference to local temporary\n",
" detected during instantiation of \"const minkowski::CoordinateMapManager<coordinate_type, coordinate_field_type, TemplatedAllocator, CoordinateMapType>::kernel_map_type &minkowski::CoordinateMapManager<coordinate_type, coordinate_field_type, TemplatedAllocator, CoordinateMapType>::kernel_map(const minkowski::CoordinateMapKey *, const minkowski::CoordinateMapKey *, const minkowski::CoordinateMapManager<coordinate_type, coordinate_field_type, TemplatedAllocator, CoordinateMapType>::stride_type &, const minkowski::CoordinateMapManager<coordinate_type, coordinate_field_type, TemplatedAllocator, CoordinateMapType>::stride_type &, const minkowski::CoordinateMapManager<coordinate_type, coordinate_field_type, TemplatedAllocator, CoordinateMapType>::stride_type &, minkowski::RegionType::Type, const at::Tensor &, __nv_bool, __nv_bool) [with coordinate_type=int32_t, coordinate_field_type=float, TemplatedAllocator=minkowski::detail::default_allocator, CoordinateMapType=minkowski::CoordinateMapGPU]\"\n",
" /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/coordinate_map_manager.cu(397): here\n",
"\n",
" /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/kernel_region.hpp(392): warning: calling a __host__ function from a __host__ __device__ function is not allowed\n",
" detected during:\n",
" instantiation of \"minkowski::gpu_kernel_region<coordinate_type>::gpu_kernel_region(const minkowski::cpu_kernel_region<coordinate_type> &) [with coordinate_type=int32_t]\"\n",
" /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/coordinate_map_manager.cu(201): here\n",
" instantiation of \"minkowski::gpu_kernel_map<minkowski::type_wrapper<uint32_t, int32_t, float>::index_type, TemplatedAllocator<char>> minkowski::detail::kernel_map_functor<coordinate_type, TemplatedAllocator, minkowski::CoordinateMapGPU, minkowski::gpu_kernel_map<minkowski::type_wrapper<uint32_t, int32_t, float>::index_type, TemplatedAllocator<char>>>::operator()(const minkowski::CoordinateMapGPU<coordinate_type, TemplatedAllocator> &, const minkowski::CoordinateMapGPU<coordinate_type, TemplatedAllocator> &, minkowski::CUDAKernelMapMode::Mode, minkowski::cpu_kernel_region<coordinate_type> &) [with coordinate_type=int32_t, TemplatedAllocator=minkowski::detail::default_allocator]\"\n",
" /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/coordinate_map_manager.cpp(750): here\n",
" instantiation of \"const minkowski::CoordinateMapManager<coordinate_type, coordinate_field_type, TemplatedAllocator, CoordinateMapType>::kernel_map_type &minkowski::CoordinateMapManager<coordinate_type, coordinate_field_type, TemplatedAllocator, CoordinateMapType>::kernel_map(const minkowski::CoordinateMapKey *, const minkowski::CoordinateMapKey *, const minkowski::CoordinateMapManager<coordinate_type, coordinate_field_type, TemplatedAllocator, CoordinateMapType>::stride_type &, const minkowski::CoordinateMapManager<coordinate_type, coordinate_field_type, TemplatedAllocator, CoordinateMapType>::stride_type &, const minkowski::CoordinateMapManager<coordinate_type, coordinate_field_type, TemplatedAllocator, CoordinateMapType>::stride_type &, minkowski::RegionType::Type, const at::Tensor &, __nv_bool, __nv_bool) [with coordinate_type=int32_t, coordinate_field_type=float, TemplatedAllocator=minkowski::detail::default_allocator, CoordinateMapType=minkowski::CoordinateMapGPU]\"\n",
" /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/coordinate_map_manager.cu(397): here\n",
"\n",
" /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/kernel_region.hpp(392): warning: calling a __host__ function from a __host__ __device__ function is not allowed\n",
" detected during:\n",
" instantiation of \"minkowski::gpu_kernel_region<coordinate_type>::gpu_kernel_region(const minkowski::cpu_kernel_region<coordinate_type> &) [with coordinate_type=int32_t]\"\n",
" /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/coordinate_map_manager.cu(201): here\n",
" instantiation of \"minkowski::gpu_kernel_map<minkowski::type_wrapper<uint32_t, int32_t, float>::index_type, TemplatedAllocator<char>> minkowski::detail::kernel_map_functor<coordinate_type, TemplatedAllocator, minkowski::CoordinateMapGPU, minkowski::gpu_kernel_map<minkowski::type_wrapper<uint32_t, int32_t, float>::index_type, TemplatedAllocator<char>>>::operator()(const minkowski::CoordinateMapGPU<coordinate_type, TemplatedAllocator> &, const minkowski::CoordinateMapGPU<coordinate_type, TemplatedAllocator> &, minkowski::CUDAKernelMapMode::Mode, minkowski::cpu_kernel_region<coordinate_type> &) [with coordinate_type=int32_t, TemplatedAllocator=minkowski::detail::default_allocator]\"\n",
" /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/coordinate_map_manager.cpp(750): here\n",
" instantiation of \"const minkowski::CoordinateMapManager<coordinate_type, coordinate_field_type, TemplatedAllocator, CoordinateMapType>::kernel_map_type &minkowski::CoordinateMapManager<coordinate_type, coordinate_field_type, TemplatedAllocator, CoordinateMapType>::kernel_map(const minkowski::CoordinateMapKey *, const minkowski::CoordinateMapKey *, const minkowski::CoordinateMapManager<coordinate_type, coordinate_field_type, TemplatedAllocator, CoordinateMapType>::stride_type &, const minkowski::CoordinateMapManager<coordinate_type, coordinate_field_type, TemplatedAllocator, CoordinateMapType>::stride_type &, const minkowski::CoordinateMapManager<coordinate_type, coordinate_field_type, TemplatedAllocator, CoordinateMapType>::stride_type &, minkowski::RegionType::Type, const at::Tensor &, __nv_bool, __nv_bool) [with coordinate_type=int32_t, coordinate_field_type=float, TemplatedAllocator=minkowski::detail::default_allocator, CoordinateMapType=minkowski::CoordinateMapGPU]\"\n",
" /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/coordinate_map_manager.cu(397): here\n",
"\n",
" /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/kernel_region.hpp(392): warning: calling a __host__ function from a __host__ __device__ function is not allowed\n",
" detected during:\n",
" instantiation of \"minkowski::gpu_kernel_region<coordinate_type>::gpu_kernel_region(const minkowski::cpu_kernel_region<coordinate_type> &) [with coordinate_type=int32_t]\"\n",
" /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/coordinate_map_manager.cu(201): here\n",
" instantiation of \"minkowski::gpu_kernel_map<minkowski::type_wrapper<uint32_t, int32_t, float>::index_type, TemplatedAllocator<char>> minkowski::detail::kernel_map_functor<coordinate_type, TemplatedAllocator, minkowski::CoordinateMapGPU, minkowski::gpu_kernel_map<minkowski::type_wrapper<uint32_t, int32_t, float>::index_type, TemplatedAllocator<char>>>::operator()(const minkowski::CoordinateMapGPU<coordinate_type, TemplatedAllocator> &, const minkowski::CoordinateMapGPU<coordinate_type, TemplatedAllocator> &, minkowski::CUDAKernelMapMode::Mode, minkowski::cpu_kernel_region<coordinate_type> &) [with coordinate_type=int32_t, TemplatedAllocator=minkowski::detail::default_allocator]\"\n",
" /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/coordinate_map_manager.cpp(750): here\n",
" instantiation of \"const minkowski::CoordinateMapManager<coordinate_type, coordinate_field_type, TemplatedAllocator, CoordinateMapType>::kernel_map_type &minkowski::CoordinateMapManager<coordinate_type, coordinate_field_type, TemplatedAllocator, CoordinateMapType>::kernel_map(const minkowski::CoordinateMapKey *, const minkowski::CoordinateMapKey *, const minkowski::CoordinateMapManager<coordinate_type, coordinate_field_type, TemplatedAllocator, CoordinateMapType>::stride_type &, const minkowski::CoordinateMapManager<coordinate_type, coordinate_field_type, TemplatedAllocator, CoordinateMapType>::stride_type &, const minkowski::CoordinateMapManager<coordinate_type, coordinate_field_type, TemplatedAllocator, CoordinateMapType>::stride_type &, minkowski::RegionType::Type, const at::Tensor &, __nv_bool, __nv_bool) [with coordinate_type=int32_t, coordinate_field_type=float, TemplatedAllocator=minkowski::detail::default_allocator, CoordinateMapType=minkowski::CoordinateMapGPU]\"\n",
" /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/coordinate_map_manager.cu(397): here\n",
"\n",
" /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/kernel_region.hpp(392): warning: calling a __host__ function from a __host__ __device__ function is not allowed\n",
" detected during:\n",
" instantiation of \"minkowski::gpu_kernel_region<coordinate_type>::gpu_kernel_region(const minkowski::cpu_kernel_region<coordinate_type> &) [with coordinate_type=int32_t]\"\n",
" /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/coordinate_map_manager.cu(201): here\n",
" instantiation of \"minkowski::gpu_kernel_map<minkowski::type_wrapper<uint32_t, int32_t, float>::index_type, TemplatedAllocator<char>> minkowski::detail::kernel_map_functor<coordinate_type, TemplatedAllocator, minkowski::CoordinateMapGPU, minkowski::gpu_kernel_map<minkowski::type_wrapper<uint32_t, int32_t, float>::index_type, TemplatedAllocator<char>>>::operator()(const minkowski::CoordinateMapGPU<coordinate_type, TemplatedAllocator> &, const minkowski::CoordinateMapGPU<coordinate_type, TemplatedAllocator> &, minkowski::CUDAKernelMapMode::Mode, minkowski::cpu_kernel_region<coordinate_type> &) [with coordinate_type=int32_t, TemplatedAllocator=minkowski::detail::default_allocator]\"\n",
" /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/coordinate_map_manager.cpp(750): here\n",
" instantiation of \"const minkowski::CoordinateMapManager<coordinate_type, coordinate_field_type, TemplatedAllocator, CoordinateMapType>::kernel_map_type &minkowski::CoordinateMapManager<coordinate_type, coordinate_field_type, TemplatedAllocator, CoordinateMapType>::kernel_map(const minkowski::CoordinateMapKey *, const minkowski::CoordinateMapKey *, const minkowski::CoordinateMapManager<coordinate_type, coordinate_field_type, TemplatedAllocator, CoordinateMapType>::stride_type &, const minkowski::CoordinateMapManager<coordinate_type, coordinate_field_type, TemplatedAllocator, CoordinateMapType>::stride_type &, const minkowski::CoordinateMapManager<coordinate_type, coordinate_field_type, TemplatedAllocator, CoordinateMapType>::stride_type &, minkowski::RegionType::Type, const at::Tensor &, __nv_bool, __nv_bool) [with coordinate_type=int32_t, coordinate_field_type=float, TemplatedAllocator=minkowski::detail::default_allocator, CoordinateMapType=minkowski::CoordinateMapGPU]\"\n",
" /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/coordinate_map_manager.cu(397): here\n",
"\n",
" /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/coordinate_map_manager.cpp(714): warning: returning reference to local temporary\n",
" detected during instantiation of \"const minkowski::CoordinateMapManager<coordinate_type, coordinate_field_type, TemplatedAllocator, CoordinateMapType>::kernel_map_type &minkowski::CoordinateMapManager<coordinate_type, coordinate_field_type, TemplatedAllocator, CoordinateMapType>::kernel_map(const minkowski::CoordinateMapKey *, const minkowski::CoordinateMapKey *, const minkowski::CoordinateMapManager<coordinate_type, coordinate_field_type, TemplatedAllocator, CoordinateMapType>::stride_type &, const minkowski::CoordinateMapManager<coordinate_type, coordinate_field_type, TemplatedAllocator, CoordinateMapType>::stride_type &, const minkowski::CoordinateMapManager<coordinate_type, coordinate_field_type, TemplatedAllocator, CoordinateMapType>::stride_type &, minkowski::RegionType::Type, const at::Tensor &, __nv_bool, __nv_bool) [with coordinate_type=int32_t, coordinate_field_type=float, TemplatedAllocator=minkowski::detail::c10_allocator, CoordinateMapType=minkowski::CoordinateMapGPU]\"\n",
" /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/coordinate_map_manager.cu(400): here\n",
"\n",
" /usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/boxing/impl/boxing.h(100): warning: integer conversion resulted in a change of sign\n",
"\n",
" /usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/op_registration/op_whitelist.h(39): warning: integer conversion resulted in a change of sign\n",
"\n",
" /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/coordinate_map_manager.cpp(714): warning: returning reference to local temporary\n",
" detected during instantiation of \"const minkowski::CoordinateMapManager<coordinate_type, coordinate_field_type, TemplatedAllocator, CoordinateMapType>::kernel_map_type &minkowski::CoordinateMapManager<coordinate_type, coordinate_field_type, TemplatedAllocator, CoordinateMapType>::kernel_map(const minkowski::CoordinateMapKey *, const minkowski::CoordinateMapKey *, const minkowski::CoordinateMapManager<coordinate_type, coordinate_field_type, TemplatedAllocator, CoordinateMapType>::stride_type &, const minkowski::CoordinateMapManager<coordinate_type, coordinate_field_type, TemplatedAllocator, CoordinateMapType>::stride_type &, const minkowski::CoordinateMapManager<coordinate_type, coordinate_field_type, TemplatedAllocator, CoordinateMapType>::stride_type &, minkowski::RegionType::Type, const at::Tensor &, bool, bool) [with coordinate_type=int32_t, coordinate_field_type=float, TemplatedAllocator=std::allocator, CoordinateMapType=minkowski::CoordinateMapCPU]\"\n",
" (1442): here\n",
"\n",
" /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/coordinate_map_manager.cpp(714): warning: returning reference to local temporary\n",
" detected during instantiation of \"const minkowski::CoordinateMapManager<coordinate_type, coordinate_field_type, TemplatedAllocator, CoordinateMapType>::kernel_map_type &minkowski::CoordinateMapManager<coordinate_type, coordinate_field_type, TemplatedAllocator, CoordinateMapType>::kernel_map(const minkowski::CoordinateMapKey *, const minkowski::CoordinateMapKey *, const minkowski::CoordinateMapManager<coordinate_type, coordinate_field_type, TemplatedAllocator, CoordinateMapType>::stride_type &, const minkowski::CoordinateMapManager<coordinate_type, coordinate_field_type, TemplatedAllocator, CoordinateMapType>::stride_type &, const minkowski::CoordinateMapManager<coordinate_type, coordinate_field_type, TemplatedAllocator, CoordinateMapType>::stride_type &, minkowski::RegionType::Type, const at::Tensor &, bool, bool) [with coordinate_type=int32_t, coordinate_field_type=float, TemplatedAllocator=minkowski::detail::default_allocator, CoordinateMapType=minkowski::CoordinateMapGPU]\"\n",
" /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/coordinate_map_manager.cu(397): here\n",
"\n",
" /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/coordinate_map_manager.cpp(714): warning: returning reference to local temporary\n",
" detected during instantiation of \"const minkowski::CoordinateMapManager<coordinate_type, coordinate_field_type, TemplatedAllocator, CoordinateMapType>::kernel_map_type &minkowski::CoordinateMapManager<coordinate_type, coordinate_field_type, TemplatedAllocator, CoordinateMapType>::kernel_map(const minkowski::CoordinateMapKey *, const minkowski::CoordinateMapKey *, const minkowski::CoordinateMapManager<coordinate_type, coordinate_field_type, TemplatedAllocator, CoordinateMapType>::stride_type &, const minkowski::CoordinateMapManager<coordinate_type, coordinate_field_type, TemplatedAllocator, CoordinateMapType>::stride_type &, const minkowski::CoordinateMapManager<coordinate_type, coordinate_field_type, TemplatedAllocator, CoordinateMapType>::stride_type &, minkowski::RegionType::Type, const at::Tensor &, bool, bool) [with coordinate_type=int32_t, coordinate_field_type=float, TemplatedAllocator=minkowski::detail::c10_allocator, CoordinateMapType=minkowski::CoordinateMapGPU]\"\n",
" /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/coordinate_map_manager.cu(400): here\n",
"\n",
" /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/coordinate_map_manager.cpp: In instantiation of ‘const kernel_map_type& minkowski::CoordinateMapManager<coordinate_type, coordinate_field_type, TemplatedAllocator, CoordinateMapType>::kernel_map(const minkowski::CoordinateMapKey*, const minkowski::CoordinateMapKey*, const stride_type&, const stride_type&, const stride_type&, minkowski::RegionType::Type, const at::Tensor&, bool, bool) [with coordinate_type = int; coordinate_field_type = float; TemplatedAllocator = std::allocator; CoordinateMapType = minkowski::CoordinateMapCPU; minkowski::CoordinateMapManager<coordinate_type, coordinate_field_type, TemplatedAllocator, CoordinateMapType>::kernel_map_type = minkowski::cpu_kernel_map; minkowski::CoordinateMapManager<coordinate_type, coordinate_field_type, TemplatedAllocator, CoordinateMapType>::stride_type = std::vector<unsigned int, std::allocator<unsigned int> >]’:\n",
" /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/coordinate_map_manager.cpp:1442:16: required from here\n",
" /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/coordinate_map_manager.cpp:714:111: warning: returning reference to temporary [-Wreturn-local-addr]\n",
" return detail::empty_map_functor<coordinate_type, TemplatedAllocator,\n",
" ^\n",
" /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/coordinate_map_manager.cpp: In instantiation of ‘const kernel_map_type& minkowski::CoordinateMapManager<coordinate_type, coordinate_field_type, TemplatedAllocator, CoordinateMapType>::kernel_map(const minkowski::CoordinateMapKey*, const minkowski::CoordinateMapKey*, const stride_type&, const stride_type&, const stride_type&, minkowski::RegionType::Type, const at::Tensor&, bool, bool) [with coordinate_type = int; coordinate_field_type = float; TemplatedAllocator = minkowski::detail::default_allocator; CoordinateMapType = minkowski::CoordinateMapGPU; minkowski::CoordinateMapManager<coordinate_type, coordinate_field_type, TemplatedAllocator, CoordinateMapType>::kernel_map_type = minkowski::gpu_kernel_map<unsigned int, minkowski::detail::default_allocator<char> >; minkowski::CoordinateMapManager<coordinate_type, coordinate_field_type, TemplatedAllocator, CoordinateMapType>::stride_type = std::vector<unsigned int, std::allocator<unsigned int> >]’:\n",
" /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/coordinate_map_manager.cu:397:16: required from here\n",
" /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/coordinate_map_manager.cpp:714:111: warning: returning reference to temporary [-Wreturn-local-addr]\n",
" /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/coordinate_map_manager.cpp: In instantiation of ‘const kernel_map_type& minkowski::CoordinateMapManager<coordinate_type, coordinate_field_type, TemplatedAllocator, CoordinateMapType>::kernel_map(const minkowski::CoordinateMapKey*, const minkowski::CoordinateMapKey*, const stride_type&, const stride_type&, const stride_type&, minkowski::RegionType::Type, const at::Tensor&, bool, bool) [with coordinate_type = int; coordinate_field_type = float; TemplatedAllocator = minkowski::detail::c10_allocator; CoordinateMapType = minkowski::CoordinateMapGPU; minkowski::CoordinateMapManager<coordinate_type, coordinate_field_type, TemplatedAllocator, CoordinateMapType>::kernel_map_type = minkowski::gpu_kernel_map<unsigned int, minkowski::detail::c10_allocator<char> >; minkowski::CoordinateMapManager<coordinate_type, coordinate_field_type, TemplatedAllocator, CoordinateMapType>::stride_type = std::vector<unsigned int, std::allocator<unsigned int> >]’:\n",
" /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/coordinate_map_manager.cu:400:16: required from here\n",
" /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/coordinate_map_manager.cpp:714:111: warning: returning reference to temporary [-Wreturn-local-addr]\n",
" /usr/local/cuda/bin/nvcc -I/usr/local/lib/python3.7/dist-packages/torch/include -I/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.7/dist-packages/torch/include/TH -I/usr/local/lib/python3.7/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src -I/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/3rdparty -I/usr/include/python3.7m -c /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/coordinate_map_gpu.cu -o build/temp.linux-x86_64-3.7/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/coordinate_map_gpu.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-options '-fPIC' --expt-relaxed-constexpr --expt-extended-lambda -O3 -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_gcc\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1011\" -DTORCH_EXTENSION_NAME=_C -D_GLIBCXX_USE_CXX11_ABI=0 -gencode=arch=compute_75,code=sm_75 -std=c++14\n",
" /usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/boxing/impl/boxing.h(100): warning: integer conversion resulted in a change of sign\n",
"\n",
" /usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/op_registration/op_whitelist.h(39): warning: integer conversion resulted in a change of sign\n",
"\n",
" /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/kernel_region.hpp(392): warning: calling a __host__ function from a __host__ __device__ function is not allowed\n",
" detected during:\n",
" instantiation of \"minkowski::gpu_kernel_region<coordinate_type>::gpu_kernel_region(const minkowski::cpu_kernel_region<coordinate_type> &) [with coordinate_type=int32_t]\"\n",
" /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/coordinate_map_gpu.cu(622): here\n",
" instantiation of \"minkowski::CoordinateMapGPU<coordinate_type, TemplatedAllocator>::self_type minkowski::CoordinateMapGPU<coordinate_type, TemplatedAllocator>::stride_region(minkowski::cpu_kernel_region<coordinate_type> &, const minkowski::CoordinateMapGPU<coordinate_type, TemplatedAllocator>::stride_type &) const [with coordinate_type=int32_t, TemplatedAllocator=minkowski::detail::default_allocator]\"\n",
" /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/coordinate_map_gpu.cu(2461): here\n",
"\n",
" /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/kernel_region.hpp(392): warning: calling a __host__ function from a __host__ __device__ function is not allowed\n",
" detected during:\n",
" instantiation of \"minkowski::gpu_kernel_region<coordinate_type>::gpu_kernel_region(const minkowski::cpu_kernel_region<coordinate_type> &) [with coordinate_type=int32_t]\"\n",
" /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/coordinate_map_gpu.cu(622): here\n",
" instantiation of \"minkowski::CoordinateMapGPU<coordinate_type, TemplatedAllocator>::self_type minkowski::CoordinateMapGPU<coordinate_type, TemplatedAllocator>::stride_region(minkowski::cpu_kernel_region<coordinate_type> &, const minkowski::CoordinateMapGPU<coordinate_type, TemplatedAllocator>::stride_type &) const [with coordinate_type=int32_t, TemplatedAllocator=minkowski::detail::default_allocator]\"\n",
" /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/coordinate_map_gpu.cu(2461): here\n",
"\n",
" /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/kernel_region.hpp(392): warning: calling a __host__ function from a __host__ __device__ function is not allowed\n",
" detected during:\n",
" instantiation of \"minkowski::gpu_kernel_region<coordinate_type>::gpu_kernel_region(const minkowski::cpu_kernel_region<coordinate_type> &) [with coordinate_type=int32_t]\"\n",
" /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/coordinate_map_gpu.cu(622): here\n",
" instantiation of \"minkowski::CoordinateMapGPU<coordinate_type, TemplatedAllocator>::self_type minkowski::CoordinateMapGPU<coordinate_type, TemplatedAllocator>::stride_region(minkowski::cpu_kernel_region<coordinate_type> &, const minkowski::CoordinateMapGPU<coordinate_type, TemplatedAllocator>::stride_type &) const [with coordinate_type=int32_t, TemplatedAllocator=minkowski::detail::default_allocator]\"\n",
" /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/coordinate_map_gpu.cu(2461): here\n",
"\n",
" /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/kernel_region.hpp(392): warning: calling a __host__ function from a __host__ __device__ function is not allowed\n",
" detected during:\n",
" instantiation of \"minkowski::gpu_kernel_region<coordinate_type>::gpu_kernel_region(const minkowski::cpu_kernel_region<coordinate_type> &) [with coordinate_type=int32_t]\"\n",
" /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/coordinate_map_gpu.cu(622): here\n",
" instantiation of \"minkowski::CoordinateMapGPU<coordinate_type, TemplatedAllocator>::self_type minkowski::CoordinateMapGPU<coordinate_type, TemplatedAllocator>::stride_region(minkowski::cpu_kernel_region<coordinate_type> &, const minkowski::CoordinateMapGPU<coordinate_type, TemplatedAllocator>::stride_type &) const [with coordinate_type=int32_t, TemplatedAllocator=minkowski::detail::default_allocator]\"\n",
" /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/coordinate_map_gpu.cu(2461): here\n",
"\n",
" /usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/boxing/impl/boxing.h(100): warning: integer conversion resulted in a change of sign\n",
"\n",
" /usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/op_registration/op_whitelist.h(39): warning: integer conversion resulted in a change of sign\n",
"\n",
" /usr/local/cuda/bin/nvcc -I/usr/local/lib/python3.7/dist-packages/torch/include -I/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.7/dist-packages/torch/include/TH -I/usr/local/lib/python3.7/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src -I/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/3rdparty -I/usr/include/python3.7m -c /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/convolution_kernel.cu -o build/temp.linux-x86_64-3.7/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/convolution_kernel.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-options '-fPIC' --expt-relaxed-constexpr --expt-extended-lambda -O3 -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_gcc\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1011\" -DTORCH_EXTENSION_NAME=_C -D_GLIBCXX_USE_CXX11_ABI=0 -gencode=arch=compute_75,code=sm_75 -std=c++14\n",
" /usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/boxing/impl/boxing.h(100): warning: integer conversion resulted in a change of sign\n",
"\n",
" /usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/op_registration/op_whitelist.h(39): warning: integer conversion resulted in a change of sign\n",
"\n",
" /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/convolution_kernel.cu(334): warning: integer conversion resulted in a change of sign\n",
"\n",
" /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/convolution_kernel.cu(571): warning: integer conversion resulted in a change of sign\n",
"\n",
" /usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/boxing/impl/boxing.h(100): warning: integer conversion resulted in a change of sign\n",
"\n",
" /usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/op_registration/op_whitelist.h(39): warning: integer conversion resulted in a change of sign\n",
"\n",
" /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/convolution_kernel.cu(334): warning: integer conversion resulted in a change of sign\n",
"\n",
" /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/convolution_kernel.cu(571): warning: integer conversion resulted in a change of sign\n",
"\n",
" /usr/local/cuda/bin/nvcc -I/usr/local/lib/python3.7/dist-packages/torch/include -I/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.7/dist-packages/torch/include/TH -I/usr/local/lib/python3.7/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src -I/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/3rdparty -I/usr/include/python3.7m -c /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/convolution_gpu.cu -o build/temp.linux-x86_64-3.7/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/convolution_gpu.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-options '-fPIC' --expt-relaxed-constexpr --expt-extended-lambda -O3 -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_gcc\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1011\" -DTORCH_EXTENSION_NAME=_C -D_GLIBCXX_USE_CXX11_ABI=0 -gencode=arch=compute_75,code=sm_75 -std=c++14\n",
" /usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/boxing/impl/boxing.h(100): warning: integer conversion resulted in a change of sign\n",
"\n",
" /usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/op_registration/op_whitelist.h(39): warning: integer conversion resulted in a change of sign\n",
"\n",
" /usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/boxing/impl/boxing.h(100): warning: integer conversion resulted in a change of sign\n",
"\n",
" /usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/op_registration/op_whitelist.h(39): warning: integer conversion resulted in a change of sign\n",
"\n",
" /usr/local/cuda/bin/nvcc -I/usr/local/lib/python3.7/dist-packages/torch/include -I/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.7/dist-packages/torch/include/TH -I/usr/local/lib/python3.7/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src -I/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/3rdparty -I/usr/include/python3.7m -c /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/convolution_transpose_gpu.cu -o build/temp.linux-x86_64-3.7/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/convolution_transpose_gpu.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-options '-fPIC' --expt-relaxed-constexpr --expt-extended-lambda -O3 -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_gcc\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1011\" -DTORCH_EXTENSION_NAME=_C -D_GLIBCXX_USE_CXX11_ABI=0 -gencode=arch=compute_75,code=sm_75 -std=c++14\n",
" /usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/boxing/impl/boxing.h(100): warning: integer conversion resulted in a change of sign\n",
"\n",
" /usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/op_registration/op_whitelist.h(39): warning: integer conversion resulted in a change of sign\n",
"\n",
" /usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/boxing/impl/boxing.h(100): warning: integer conversion resulted in a change of sign\n",
"\n",
" /usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/op_registration/op_whitelist.h(39): warning: integer conversion resulted in a change of sign\n",
"\n",
" /usr/local/cuda/bin/nvcc -I/usr/local/lib/python3.7/dist-packages/torch/include -I/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.7/dist-packages/torch/include/TH -I/usr/local/lib/python3.7/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src -I/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/3rdparty -I/usr/include/python3.7m -c /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/pooling_avg_kernel.cu -o build/temp.linux-x86_64-3.7/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/pooling_avg_kernel.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-options '-fPIC' --expt-relaxed-constexpr --expt-extended-lambda -O3 -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_gcc\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1011\" -DTORCH_EXTENSION_NAME=_C -D_GLIBCXX_USE_CXX11_ABI=0 -gencode=arch=compute_75,code=sm_75 -std=c++14\n",
" /usr/local/cuda/bin/nvcc -I/usr/local/lib/python3.7/dist-packages/torch/include -I/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.7/dist-packages/torch/include/TH -I/usr/local/lib/python3.7/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src -I/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/3rdparty -I/usr/include/python3.7m -c /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/pooling_max_kernel.cu -o build/temp.linux-x86_64-3.7/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/pooling_max_kernel.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-options '-fPIC' --expt-relaxed-constexpr --expt-extended-lambda -O3 -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_gcc\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1011\" -DTORCH_EXTENSION_NAME=_C -D_GLIBCXX_USE_CXX11_ABI=0 -gencode=arch=compute_75,code=sm_75 -std=c++14\n",
" /usr/local/cuda/bin/nvcc -I/usr/local/lib/python3.7/dist-packages/torch/include -I/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.7/dist-packages/torch/include/TH -I/usr/local/lib/python3.7/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src -I/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/3rdparty -I/usr/include/python3.7m -c /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/local_pooling_gpu.cu -o build/temp.linux-x86_64-3.7/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/local_pooling_gpu.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-options '-fPIC' --expt-relaxed-constexpr --expt-extended-lambda -O3 -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_gcc\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1011\" -DTORCH_EXTENSION_NAME=_C -D_GLIBCXX_USE_CXX11_ABI=0 -gencode=arch=compute_75,code=sm_75 -std=c++14\n",
" /usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/boxing/impl/boxing.h(100): warning: integer conversion resulted in a change of sign\n",
"\n",
" /usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/op_registration/op_whitelist.h(39): warning: integer conversion resulted in a change of sign\n",
"\n",
" /usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/boxing/impl/boxing.h(100): warning: integer conversion resulted in a change of sign\n",
"\n",
" /usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/op_registration/op_whitelist.h(39): warning: integer conversion resulted in a change of sign\n",
"\n",
" /usr/local/cuda/bin/nvcc -I/usr/local/lib/python3.7/dist-packages/torch/include -I/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.7/dist-packages/torch/include/TH -I/usr/local/lib/python3.7/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src -I/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/3rdparty -I/usr/include/python3.7m -c /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/local_pooling_transpose_gpu.cu -o build/temp.linux-x86_64-3.7/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/local_pooling_transpose_gpu.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-options '-fPIC' --expt-relaxed-constexpr --expt-extended-lambda -O3 -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_gcc\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1011\" -DTORCH_EXTENSION_NAME=_C -D_GLIBCXX_USE_CXX11_ABI=0 -gencode=arch=compute_75,code=sm_75 -std=c++14\n",
" /usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/boxing/impl/boxing.h(100): warning: integer conversion resulted in a change of sign\n",
"\n",
" /usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/op_registration/op_whitelist.h(39): warning: integer conversion resulted in a change of sign\n",
"\n",
" /usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/boxing/impl/boxing.h(100): warning: integer conversion resulted in a change of sign\n",
"\n",
" /usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/op_registration/op_whitelist.h(39): warning: integer conversion resulted in a change of sign\n",
"\n",
" /usr/local/cuda/bin/nvcc -I/usr/local/lib/python3.7/dist-packages/torch/include -I/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.7/dist-packages/torch/include/TH -I/usr/local/lib/python3.7/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src -I/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/3rdparty -I/usr/include/python3.7m -c /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/global_pooling_gpu.cu -o build/temp.linux-x86_64-3.7/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/global_pooling_gpu.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-options '-fPIC' --expt-relaxed-constexpr --expt-extended-lambda -O3 -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_gcc\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1011\" -DTORCH_EXTENSION_NAME=_C -D_GLIBCXX_USE_CXX11_ABI=0 -gencode=arch=compute_75,code=sm_75 -std=c++14\n",
" /usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/boxing/impl/boxing.h(100): warning: integer conversion resulted in a change of sign\n",
"\n",
" /usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/op_registration/op_whitelist.h(39): warning: integer conversion resulted in a change of sign\n",
"\n",
" /usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/boxing/impl/boxing.h(100): warning: integer conversion resulted in a change of sign\n",
"\n",
" /usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/op_registration/op_whitelist.h(39): warning: integer conversion resulted in a change of sign\n",
"\n",
" /usr/local/cuda/bin/nvcc -I/usr/local/lib/python3.7/dist-packages/torch/include -I/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.7/dist-packages/torch/include/TH -I/usr/local/lib/python3.7/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src -I/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/3rdparty -I/usr/include/python3.7m -c /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/broadcast_kernel.cu -o build/temp.linux-x86_64-3.7/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/broadcast_kernel.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-options '-fPIC' --expt-relaxed-constexpr --expt-extended-lambda -O3 -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_gcc\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1011\" -DTORCH_EXTENSION_NAME=_C -D_GLIBCXX_USE_CXX11_ABI=0 -gencode=arch=compute_75,code=sm_75 -std=c++14\n",
" /usr/local/cuda/bin/nvcc -I/usr/local/lib/python3.7/dist-packages/torch/include -I/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.7/dist-packages/torch/include/TH -I/usr/local/lib/python3.7/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src -I/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/3rdparty -I/usr/include/python3.7m -c /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/broadcast_gpu.cu -o build/temp.linux-x86_64-3.7/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/broadcast_gpu.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-options '-fPIC' --expt-relaxed-constexpr --expt-extended-lambda -O3 -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_gcc\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1011\" -DTORCH_EXTENSION_NAME=_C -D_GLIBCXX_USE_CXX11_ABI=0 -gencode=arch=compute_75,code=sm_75 -std=c++14\n",
" /usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/boxing/impl/boxing.h(100): warning: integer conversion resulted in a change of sign\n",
"\n",
" /usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/op_registration/op_whitelist.h(39): warning: integer conversion resulted in a change of sign\n",
"\n",
" /usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/boxing/impl/boxing.h(100): warning: integer conversion resulted in a change of sign\n",
"\n",
" /usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/op_registration/op_whitelist.h(39): warning: integer conversion resulted in a change of sign\n",
"\n",
" /usr/local/cuda/bin/nvcc -I/usr/local/lib/python3.7/dist-packages/torch/include -I/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.7/dist-packages/torch/include/TH -I/usr/local/lib/python3.7/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src -I/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/3rdparty -I/usr/include/python3.7m -c /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/pruning_gpu.cu -o build/temp.linux-x86_64-3.7/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/pruning_gpu.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-options '-fPIC' --expt-relaxed-constexpr --expt-extended-lambda -O3 -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_gcc\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1011\" -DTORCH_EXTENSION_NAME=_C -D_GLIBCXX_USE_CXX11_ABI=0 -gencode=arch=compute_75,code=sm_75 -std=c++14\n",
" /usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/boxing/impl/boxing.h(100): warning: integer conversion resulted in a change of sign\n",
"\n",
" /usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/op_registration/op_whitelist.h(39): warning: integer conversion resulted in a change of sign\n",
"\n",
" /usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/boxing/impl/boxing.h(100): warning: integer conversion resulted in a change of sign\n",
"\n",
" /usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/op_registration/op_whitelist.h(39): warning: integer conversion resulted in a change of sign\n",
"\n",
" /usr/local/cuda/bin/nvcc -I/usr/local/lib/python3.7/dist-packages/torch/include -I/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.7/dist-packages/torch/include/TH -I/usr/local/lib/python3.7/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src -I/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/3rdparty -I/usr/include/python3.7m -c /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/interpolation_gpu.cu -o build/temp.linux-x86_64-3.7/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/interpolation_gpu.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-options '-fPIC' --expt-relaxed-constexpr --expt-extended-lambda -O3 -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_gcc\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1011\" -DTORCH_EXTENSION_NAME=_C -D_GLIBCXX_USE_CXX11_ABI=0 -gencode=arch=compute_75,code=sm_75 -std=c++14\n",
" /usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/boxing/impl/boxing.h(100): warning: integer conversion resulted in a change of sign\n",
"\n",
" /usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/op_registration/op_whitelist.h(39): warning: integer conversion resulted in a change of sign\n",
"\n",
" /usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/boxing/impl/boxing.h(100): warning: integer conversion resulted in a change of sign\n",
"\n",
" /usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/op_registration/op_whitelist.h(39): warning: integer conversion resulted in a change of sign\n",
"\n",
" /usr/local/cuda/bin/nvcc -I/usr/local/lib/python3.7/dist-packages/torch/include -I/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.7/dist-packages/torch/include/TH -I/usr/local/lib/python3.7/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src -I/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/3rdparty -I/usr/include/python3.7m -c /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/spmm.cu -o build/temp.linux-x86_64-3.7/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/spmm.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-options '-fPIC' --expt-relaxed-constexpr --expt-extended-lambda -O3 -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_gcc\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1011\" -DTORCH_EXTENSION_NAME=_C -D_GLIBCXX_USE_CXX11_ABI=0 -gencode=arch=compute_75,code=sm_75 -std=c++14\n",
" /usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/boxing/impl/boxing.h(100): warning: integer conversion resulted in a change of sign\n",
"\n",
" /usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/op_registration/op_whitelist.h(39): warning: integer conversion resulted in a change of sign\n",
"\n",
" /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/spmm.cu(102): warning: variable \"is_int64\" was declared but never referenced\n",
"\n",
" /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/spmm.cu(358): warning: variable \"is_int64\" was declared but never referenced\n",
"\n",
" /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/spmm.cu(465): warning: variable \"num_unique_keys\" was declared but never referenced\n",
" detected during instantiation of \"std::vector<at::Tensor, std::allocator<at::Tensor>> minkowski::coo_spmm_average<th_int_type>(const at::Tensor &, const at::Tensor &, int64_t, int64_t, const at::Tensor &, int64_t) [with th_int_type=int32_t]\"\n",
" (593): here\n",
"\n",
" /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/spmm.cu(465): warning: variable \"num_unique_keys\" was declared but never referenced\n",
" detected during instantiation of \"std::vector<at::Tensor, std::allocator<at::Tensor>> minkowski::coo_spmm_average<th_int_type>(const at::Tensor &, const at::Tensor &, int64_t, int64_t, const at::Tensor &, int64_t) [with th_int_type=int32_t]\"\n",
" (593): here\n",
"\n",
" /usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/boxing/impl/boxing.h(100): warning: integer conversion resulted in a change of sign\n",
"\n",
" /usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/op_registration/op_whitelist.h(39): warning: integer conversion resulted in a change of sign\n",
"\n",
" /usr/local/cuda/bin/nvcc -I/usr/local/lib/python3.7/dist-packages/torch/include -I/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.7/dist-packages/torch/include/TH -I/usr/local/lib/python3.7/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src -I/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/3rdparty -I/usr/include/python3.7m -c /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/gpu.cu -o build/temp.linux-x86_64-3.7/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/gpu.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-options '-fPIC' --expt-relaxed-constexpr --expt-extended-lambda -O3 -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_gcc\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1011\" -DTORCH_EXTENSION_NAME=_C -D_GLIBCXX_USE_CXX11_ABI=0 -gencode=arch=compute_75,code=sm_75 -std=c++14\n",
" /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/gpu.cu(124): warning: function \"minkowski::format_size\" was declared but never referenced\n",
"\n",
" x86_64-linux-gnu-gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O2 -Wall -g -fdebug-prefix-map=/build/python3.7-a56wZI/python3.7-3.7.10=. -fstack-protector-strong -Wformat -Werror=format-security -g -fdebug-prefix-map=/build/python3.7-a56wZI/python3.7-3.7.10=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/local/lib/python3.7/dist-packages/torch/include -I/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.7/dist-packages/torch/include/TH -I/usr/local/lib/python3.7/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src -I/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/3rdparty -I/usr/include/python3.7m -c /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/quantization.cpp -o build/temp.linux-x86_64-3.7/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/quantization.o -fopenmp -O3 -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_gcc\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1011\" -DTORCH_EXTENSION_NAME=_C -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++14\n",
" x86_64-linux-gnu-gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O2 -Wall -g -fdebug-prefix-map=/build/python3.7-a56wZI/python3.7-3.7.10=. -fstack-protector-strong -Wformat -Werror=format-security -g -fdebug-prefix-map=/build/python3.7-a56wZI/python3.7-3.7.10=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/local/lib/python3.7/dist-packages/torch/include -I/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.7/dist-packages/torch/include/TH -I/usr/local/lib/python3.7/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src -I/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/3rdparty -I/usr/include/python3.7m -c /tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/direct_max_pool.cpp -o build/temp.linux-x86_64-3.7/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/direct_max_pool.o -fopenmp -O3 -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_gcc\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1011\" -DTORCH_EXTENSION_NAME=_C -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++14\n",
" /usr/local/cuda/bin/nvcc -I/usr/local/lib/python3.7/dist-packages/torch/include -I/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.7/dist-packages/torch/include/TH -I/usr/local/lib/python3.7/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src -I/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/3rdparty -I/usr/include/python3.7m -c pybind/minkowski.cu -o build/temp.linux-x86_64-3.7/pybind/minkowski.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-options '-fPIC' --expt-relaxed-constexpr --expt-extended-lambda -O3 -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_gcc\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1011\" -DTORCH_EXTENSION_NAME=_C -D_GLIBCXX_USE_CXX11_ABI=0 -gencode=arch=compute_75,code=sm_75 -std=c++14\n",
" /usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/boxing/impl/boxing.h(100): warning: integer conversion resulted in a change of sign\n",
"\n",
" /usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/op_registration/op_whitelist.h(39): warning: integer conversion resulted in a change of sign\n",
"\n",
" /usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/boxing/impl/boxing.h(100): warning: integer conversion resulted in a change of sign\n",
"\n",
" /usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/op_registration/op_whitelist.h(39): warning: integer conversion resulted in a change of sign\n",
"\n",
" creating build/lib.linux-x86_64-3.7/MinkowskiEngineBackend\n",
" x86_64-linux-gnu-g++ -pthread -shared -Wl,-O1 -Wl,-Bsymbolic-functions -Wl,-Bsymbolic-functions -Wl,-z,relro -Wl,-Bsymbolic-functions -Wl,-z,relro -g -fdebug-prefix-map=/build/python3.7-a56wZI/python3.7-3.7.10=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-x86_64-3.7/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/math_functions_cpu.o build/temp.linux-x86_64-3.7/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/math_functions_gpu.o build/temp.linux-x86_64-3.7/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/coordinate_map_manager.o build/temp.linux-x86_64-3.7/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/coordinate_map_gpu.o build/temp.linux-x86_64-3.7/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/convolution_kernel.o build/temp.linux-x86_64-3.7/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/convolution_gpu.o build/temp.linux-x86_64-3.7/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/convolution_transpose_gpu.o build/temp.linux-x86_64-3.7/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/pooling_avg_kernel.o build/temp.linux-x86_64-3.7/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/pooling_max_kernel.o build/temp.linux-x86_64-3.7/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/local_pooling_gpu.o build/temp.linux-x86_64-3.7/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/local_pooling_transpose_gpu.o build/temp.linux-x86_64-3.7/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/global_pooling_gpu.o build/temp.linux-x86_64-3.7/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/broadcast_kernel.o build/temp.linux-x86_64-3.7/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/broadcast_gpu.o build/temp.linux-x86_64-3.7/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/pruning_gpu.o build/temp.linux-x86_64-3.7/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/interpolation_gpu.o build/temp.linux-x86_64-3.7/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/spmm.o build/temp.linux-x86_64-3.7/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/gpu.o build/temp.linux-x86_64-3.7/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/quantization.o build/temp.linux-x86_64-3.7/tmp/pip-install-nrmqg_h6/MinkowskiEngine/src/direct_max_pool.o build/temp.linux-x86_64-3.7/pybind/minkowski.o -L/usr/local/lib/python3.7/dist-packages/torch/lib -L/usr/local/cuda/lib64 -lcusparse -lopenblas -lc10 -ltorch -ltorch_cpu -ltorch_python -lcudart -lc10_cuda -ltorch_cuda -o build/lib.linux-x86_64-3.7/MinkowskiEngineBackend/_C.cpython-37m-x86_64-linux-gnu.so\n",
" running install_lib\n",
" creating /usr/local/lib/python3.7/dist-packages/MinkowskiEngineBackend\n",
" copying build/lib.linux-x86_64-3.7/MinkowskiEngineBackend/_C.cpython-37m-x86_64-linux-gnu.so -> /usr/local/lib/python3.7/dist-packages/MinkowskiEngineBackend\n",
" creating /usr/local/lib/python3.7/dist-packages/MinkowskiEngine\n",
" copying build/lib.linux-x86_64-3.7/MinkowskiEngine/MinkowskiConvolution.py -> /usr/local/lib/python3.7/dist-packages/MinkowskiEngine\n",
" copying build/lib.linux-x86_64-3.7/MinkowskiEngine/MinkowskiCommon.py -> /usr/local/lib/python3.7/dist-packages/MinkowskiEngine\n",
" copying build/lib.linux-x86_64-3.7/MinkowskiEngine/MinkowskiSparseTensor.py -> /usr/local/lib/python3.7/dist-packages/MinkowskiEngine\n",
" copying build/lib.linux-x86_64-3.7/MinkowskiEngine/MinkowskiKernelGenerator.py -> /usr/local/lib/python3.7/dist-packages/MinkowskiEngine\n",
" copying build/lib.linux-x86_64-3.7/MinkowskiEngine/MinkowskiOps.py -> /usr/local/lib/python3.7/dist-packages/MinkowskiEngine\n",
" copying build/lib.linux-x86_64-3.7/MinkowskiEngine/sparse_matrix_functions.py -> /usr/local/lib/python3.7/dist-packages/MinkowskiEngine\n",
" creating /usr/local/lib/python3.7/dist-packages/MinkowskiEngine/utils\n",
" copying build/lib.linux-x86_64-3.7/MinkowskiEngine/utils/gradcheck.py -> /usr/local/lib/python3.7/dist-packages/MinkowskiEngine/utils\n",
" copying build/lib.linux-x86_64-3.7/MinkowskiEngine/utils/quantization.py -> /usr/local/lib/python3.7/dist-packages/MinkowskiEngine/utils\n",
" copying build/lib.linux-x86_64-3.7/MinkowskiEngine/utils/coords.py -> /usr/local/lib/python3.7/dist-packages/MinkowskiEngine/utils\n",
" copying build/lib.linux-x86_64-3.7/MinkowskiEngine/utils/init.py -> /usr/local/lib/python3.7/dist-packages/MinkowskiEngine/utils\n",
" copying build/lib.linux-x86_64-3.7/MinkowskiEngine/utils/collation.py -> /usr/local/lib/python3.7/dist-packages/MinkowskiEngine/utils\n",
" copying build/lib.linux-x86_64-3.7/MinkowskiEngine/utils/__init__.py -> /usr/local/lib/python3.7/dist-packages/MinkowskiEngine/utils\n",
" creating /usr/local/lib/python3.7/dist-packages/MinkowskiEngine/modules\n",
" copying build/lib.linux-x86_64-3.7/MinkowskiEngine/modules/resnet_block.py -> /usr/local/lib/python3.7/dist-packages/MinkowskiEngine/modules\n",
" copying build/lib.linux-x86_64-3.7/MinkowskiEngine/modules/senet_block.py -> /usr/local/lib/python3.7/dist-packages/MinkowskiEngine/modules\n",
" copying build/lib.linux-x86_64-3.7/MinkowskiEngine/modules/__init__.py -> /usr/local/lib/python3.7/dist-packages/MinkowskiEngine/modules\n",
" copying build/lib.linux-x86_64-3.7/MinkowskiEngine/MinkowskiFunctional.py -> /usr/local/lib/python3.7/dist-packages/MinkowskiEngine\n",
" copying build/lib.linux-x86_64-3.7/MinkowskiEngine/MinkowskiCoordinateManager.py -> /usr/local/lib/python3.7/dist-packages/MinkowskiEngine\n",
" copying build/lib.linux-x86_64-3.7/MinkowskiEngine/MinkowskiBroadcast.py -> /usr/local/lib/python3.7/dist-packages/MinkowskiEngine\n",
" copying build/lib.linux-x86_64-3.7/MinkowskiEngine/MinkowskiInterpolation.py -> /usr/local/lib/python3.7/dist-packages/MinkowskiEngine\n",
" copying build/lib.linux-x86_64-3.7/MinkowskiEngine/MinkowskiPruning.py -> /usr/local/lib/python3.7/dist-packages/MinkowskiEngine\n",
" copying build/lib.linux-x86_64-3.7/MinkowskiEngine/MinkowskiNonlinearity.py -> /usr/local/lib/python3.7/dist-packages/MinkowskiEngine\n",
" copying build/lib.linux-x86_64-3.7/MinkowskiEngine/MinkowskiPooling.py -> /usr/local/lib/python3.7/dist-packages/MinkowskiEngine\n",
" copying build/lib.linux-x86_64-3.7/MinkowskiEngine/MinkowskiChannelwiseConvolution.py -> /usr/local/lib/python3.7/dist-packages/MinkowskiEngine\n",
" copying build/lib.linux-x86_64-3.7/MinkowskiEngine/diagnostics.py -> /usr/local/lib/python3.7/dist-packages/MinkowskiEngine\n",
" copying build/lib.linux-x86_64-3.7/MinkowskiEngine/MinkowskiTensorField.py -> /usr/local/lib/python3.7/dist-packages/MinkowskiEngine\n",
" copying build/lib.linux-x86_64-3.7/MinkowskiEngine/__init__.py -> /usr/local/lib/python3.7/dist-packages/MinkowskiEngine\n",
" copying build/lib.linux-x86_64-3.7/MinkowskiEngine/MinkowskiNormalization.py -> /usr/local/lib/python3.7/dist-packages/MinkowskiEngine\n",
" copying build/lib.linux-x86_64-3.7/MinkowskiEngine/MinkowskiTensor.py -> /usr/local/lib/python3.7/dist-packages/MinkowskiEngine\n",
" copying build/lib.linux-x86_64-3.7/MinkowskiEngine/MinkowskiNetwork.py -> /usr/local/lib/python3.7/dist-packages/MinkowskiEngine\n",
" copying build/lib.linux-x86_64-3.7/MinkowskiEngine/MinkowskiUnion.py -> /usr/local/lib/python3.7/dist-packages/MinkowskiEngine\n",
" byte-compiling /usr/local/lib/python3.7/dist-packages/MinkowskiEngine/MinkowskiConvolution.py to MinkowskiConvolution.cpython-37.pyc\n",
" byte-compiling /usr/local/lib/python3.7/dist-packages/MinkowskiEngine/MinkowskiCommon.py to MinkowskiCommon.cpython-37.pyc\n",
" byte-compiling /usr/local/lib/python3.7/dist-packages/MinkowskiEngine/MinkowskiSparseTensor.py to MinkowskiSparseTensor.cpython-37.pyc\n",
" byte-compiling /usr/local/lib/python3.7/dist-packages/MinkowskiEngine/MinkowskiKernelGenerator.py to MinkowskiKernelGenerator.cpython-37.pyc\n",
" byte-compiling /usr/local/lib/python3.7/dist-packages/MinkowskiEngine/MinkowskiOps.py to MinkowskiOps.cpython-37.pyc\n",
" byte-compiling /usr/local/lib/python3.7/dist-packages/MinkowskiEngine/sparse_matrix_functions.py to sparse_matrix_functions.cpython-37.pyc\n",
" byte-compiling /usr/local/lib/python3.7/dist-packages/MinkowskiEngine/utils/gradcheck.py to gradcheck.cpython-37.pyc\n",
" byte-compiling /usr/local/lib/python3.7/dist-packages/MinkowskiEngine/utils/quantization.py to quantization.cpython-37.pyc\n",
" byte-compiling /usr/local/lib/python3.7/dist-packages/MinkowskiEngine/utils/coords.py to coords.cpython-37.pyc\n",
" byte-compiling /usr/local/lib/python3.7/dist-packages/MinkowskiEngine/utils/init.py to init.cpython-37.pyc\n",
" byte-compiling /usr/local/lib/python3.7/dist-packages/MinkowskiEngine/utils/collation.py to collation.cpython-37.pyc\n",
" byte-compiling /usr/local/lib/python3.7/dist-packages/MinkowskiEngine/utils/__init__.py to __init__.cpython-37.pyc\n",
" byte-compiling /usr/local/lib/python3.7/dist-packages/MinkowskiEngine/modules/resnet_block.py to resnet_block.cpython-37.pyc\n",
" byte-compiling /usr/local/lib/python3.7/dist-packages/MinkowskiEngine/modules/senet_block.py to senet_block.cpython-37.pyc\n",
" byte-compiling /usr/local/lib/python3.7/dist-packages/MinkowskiEngine/modules/__init__.py to __init__.cpython-37.pyc\n",
" byte-compiling /usr/local/lib/python3.7/dist-packages/MinkowskiEngine/MinkowskiFunctional.py to MinkowskiFunctional.cpython-37.pyc\n",
" byte-compiling /usr/local/lib/python3.7/dist-packages/MinkowskiEngine/MinkowskiCoordinateManager.py to MinkowskiCoordinateManager.cpython-37.pyc\n",
" byte-compiling /usr/local/lib/python3.7/dist-packages/MinkowskiEngine/MinkowskiBroadcast.py to MinkowskiBroadcast.cpython-37.pyc\n",
" byte-compiling /usr/local/lib/python3.7/dist-packages/MinkowskiEngine/MinkowskiInterpolation.py to MinkowskiInterpolation.cpython-37.pyc\n",
" byte-compiling /usr/local/lib/python3.7/dist-packages/MinkowskiEngine/MinkowskiPruning.py to MinkowskiPruning.cpython-37.pyc\n",
" byte-compiling /usr/local/lib/python3.7/dist-packages/MinkowskiEngine/MinkowskiNonlinearity.py to MinkowskiNonlinearity.cpython-37.pyc\n",
" byte-compiling /usr/local/lib/python3.7/dist-packages/MinkowskiEngine/MinkowskiPooling.py to MinkowskiPooling.cpython-37.pyc\n",
" byte-compiling /usr/local/lib/python3.7/dist-packages/MinkowskiEngine/MinkowskiChannelwiseConvolution.py to MinkowskiChannelwiseConvolution.cpython-37.pyc\n",
" byte-compiling /usr/local/lib/python3.7/dist-packages/MinkowskiEngine/diagnostics.py to diagnostics.cpython-37.pyc\n",
" byte-compiling /usr/local/lib/python3.7/dist-packages/MinkowskiEngine/MinkowskiTensorField.py to MinkowskiTensorField.cpython-37.pyc\n",
" byte-compiling /usr/local/lib/python3.7/dist-packages/MinkowskiEngine/__init__.py to __init__.cpython-37.pyc\n",
" byte-compiling /usr/local/lib/python3.7/dist-packages/MinkowskiEngine/MinkowskiNormalization.py to MinkowskiNormalization.cpython-37.pyc\n",
" byte-compiling /usr/local/lib/python3.7/dist-packages/MinkowskiEngine/MinkowskiTensor.py to MinkowskiTensor.cpython-37.pyc\n",
" byte-compiling /usr/local/lib/python3.7/dist-packages/MinkowskiEngine/MinkowskiNetwork.py to MinkowskiNetwork.cpython-37.pyc\n",
" byte-compiling /usr/local/lib/python3.7/dist-packages/MinkowskiEngine/MinkowskiUnion.py to MinkowskiUnion.cpython-37.pyc\n",
" running install_egg_info\n",
" running egg_info\n",
" writing MinkowskiEngine.egg-info/PKG-INFO\n",
" writing dependency_links to MinkowskiEngine.egg-info/dependency_links.txt\n",
" writing requirements to MinkowskiEngine.egg-info/requires.txt\n",
" writing top-level names to MinkowskiEngine.egg-info/top_level.txt\n",
" reading manifest file 'MinkowskiEngine.egg-info/SOURCES.txt'\n",
" reading manifest template 'MANIFEST.in'\n",
" writing manifest file 'MinkowskiEngine.egg-info/SOURCES.txt'\n",
" Copying MinkowskiEngine.egg-info to /usr/local/lib/python3.7/dist-packages/MinkowskiEngine-0.5.2-py3.7.egg-info\n",
" running install_scripts\n",
" writing list of installed files to '/tmp/pip-record-oecir8zv/install-record.txt'\n",
" Running setup.py install for MinkowskiEngine ... \u001b[?25l\u001b[?25hdone\n",
" Removing source in /tmp/pip-install-nrmqg_h6/MinkowskiEngine\n",
"Successfully installed MinkowskiEngine-0.5.2\n",
"Cleaning up...\n",
"Removed build tracker '/tmp/pip-req-tracker-be61vixc'\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "qs0Rz6eoUlAk",
"colab": {
"base_uri": "https://localhost:8080/"
},
"outputId": "96d7e47d-8695-42ac-ffdd-e3c3a41d364d"
},
"source": [
"!pip install open3d"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"text": [
"Collecting open3d\n",
"\u001b[?25l Downloading https://files.pythonhosted.org/packages/4e/9c/dd30378d9334396894a02c296d74b265fba0ff85838ceef12385cd4ebff9/open3d-0.12.0-cp37-cp37m-manylinux2014_x86_64.whl (188.4MB)\n",
"\u001b[K |████████████████████████████████| 188.4MB 84kB/s \n",
"\u001b[?25hRequirement already satisfied: matplotlib in /usr/local/lib/python3.7/dist-packages (from open3d) (3.2.2)\n",
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"Requirement already satisfied: pandas in /usr/local/lib/python3.7/dist-packages (from open3d) (1.1.5)\n",
"Collecting addict\n",
" Downloading https://files.pythonhosted.org/packages/6a/00/b08f23b7d7e1e14ce01419a467b583edbb93c6cdb8654e54a9cc579cd61f/addict-2.4.0-py3-none-any.whl\n",
"Collecting plyfile\n",
" Downloading https://files.pythonhosted.org/packages/03/6e/cb64d254c6d474a7cf636a7c7e318ab7c4ec8e4082cabaa2aab81f9b6a65/plyfile-0.7.3-py3-none-any.whl\n",
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"Installing collected packages: addict, plyfile, open3d\n",
"Successfully installed addict-2.4.0 open3d-0.12.0 plyfile-0.7.3\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "a0WkL7dTL5hM",
"outputId": "a643c79a-1e73-4c37-a60b-4e89075c5337"
},
"source": [
"!python -m examples.classification_modelnet40 --network pointnet"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"text": [
"===================ModelNet40 Dataset===================\n",
"Training with translation 0.2\n",
"Evaluating with translation 0.0\n",
"=============================================\n",
"\n",
"\n",
"===================Network===================\n",
"ResFieldNet14(\n",
" (field_network): Sequential(\n",
" (0): MinkowskiSinusoidal()\n",
" (1): MinkowskiBatchNorm(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
" (2): MinkowskiReLU()\n",
" (3): MinkowskiLinear(in_features=32, out_features=32, bias=True)\n",
" (4): MinkowskiBatchNorm(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
" (5): MinkowskiReLU()\n",
" (6): MinkowskiToSparseTensor()\n",
" )\n",
" (field_network2): Sequential(\n",
" (0): MinkowskiSinusoidal()\n",
" (1): MinkowskiBatchNorm(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
" (2): MinkowskiReLU()\n",
" (3): MinkowskiLinear(in_features=64, out_features=64, bias=True)\n",
" (4): MinkowskiBatchNorm(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
" (5): MinkowskiReLU()\n",
" (6): MinkowskiToSparseTensor()\n",
" )\n",
" (conv1): Sequential(\n",
" (0): MinkowskiConvolution(in=64, out=64, kernel_size=[3, 3, 3], stride=[2, 2, 2], dilation=[1, 1, 1])\n",
" (1): MinkowskiInstanceNorm(nchannels=64)\n",
" (2): MinkowskiReLU()\n",
" (3): MinkowskiMaxPooling(kernel_size=[2, 2, 2], stride=[2, 2, 2], dilation=[1, 1, 1])\n",
" )\n",
" (layer1): Sequential(\n",
" (0): BasicBlock(\n",
" (conv1): MinkowskiConvolution(in=64, out=64, kernel_size=[3, 3, 3], stride=[2, 2, 2], dilation=[1, 1, 1])\n",
" (norm1): MinkowskiBatchNorm(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
" (conv2): MinkowskiConvolution(in=64, out=64, kernel_size=[3, 3, 3], stride=[1, 1, 1], dilation=[1, 1, 1])\n",
" (norm2): MinkowskiBatchNorm(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
" (relu): MinkowskiReLU()\n",
" (downsample): Sequential(\n",
" (0): MinkowskiConvolution(in=64, out=64, kernel_size=[1, 1, 1], stride=[2, 2, 2], dilation=[1, 1, 1])\n",
" (1): MinkowskiBatchNorm(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
" )\n",
" )\n",
" )\n",
" (layer2): Sequential(\n",
" (0): BasicBlock(\n",
" (conv1): MinkowskiConvolution(in=64, out=128, kernel_size=[3, 3, 3], stride=[2, 2, 2], dilation=[1, 1, 1])\n",
" (norm1): MinkowskiBatchNorm(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
" (conv2): MinkowskiConvolution(in=128, out=128, kernel_size=[3, 3, 3], stride=[1, 1, 1], dilation=[1, 1, 1])\n",
" (norm2): MinkowskiBatchNorm(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
" (relu): MinkowskiReLU()\n",
" (downsample): Sequential(\n",
" (0): MinkowskiConvolution(in=64, out=128, kernel_size=[1, 1, 1], stride=[2, 2, 2], dilation=[1, 1, 1])\n",
" (1): MinkowskiBatchNorm(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
" )\n",
" )\n",
" )\n",
" (layer3): Sequential(\n",
" (0): BasicBlock(\n",
" (conv1): MinkowskiConvolution(in=128, out=256, kernel_size=[3, 3, 3], stride=[2, 2, 2], dilation=[1, 1, 1])\n",
" (norm1): MinkowskiBatchNorm(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
" (conv2): MinkowskiConvolution(in=256, out=256, kernel_size=[3, 3, 3], stride=[1, 1, 1], dilation=[1, 1, 1])\n",
" (norm2): MinkowskiBatchNorm(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
" (relu): MinkowskiReLU()\n",
" (downsample): Sequential(\n",
" (0): MinkowskiConvolution(in=128, out=256, kernel_size=[1, 1, 1], stride=[2, 2, 2], dilation=[1, 1, 1])\n",
" (1): MinkowskiBatchNorm(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
" )\n",
" )\n",
" )\n",
" (layer4): Sequential(\n",
" (0): BasicBlock(\n",
" (conv1): MinkowskiConvolution(in=256, out=512, kernel_size=[3, 3, 3], stride=[2, 2, 2], dilation=[1, 1, 1])\n",
" (norm1): MinkowskiBatchNorm(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
" (conv2): MinkowskiConvolution(in=512, out=512, kernel_size=[3, 3, 3], stride=[1, 1, 1], dilation=[1, 1, 1])\n",
" (norm2): MinkowskiBatchNorm(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
" (relu): MinkowskiReLU()\n",
" (downsample): Sequential(\n",
" (0): MinkowskiConvolution(in=256, out=512, kernel_size=[1, 1, 1], stride=[2, 2, 2], dilation=[1, 1, 1])\n",
" (1): MinkowskiBatchNorm(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
" )\n",
" )\n",
" )\n",
" (conv5): Sequential(\n",
" (0): MinkowskiDropout()\n",
" (1): MinkowskiConvolution(in=512, out=512, kernel_size=[3, 3, 3], stride=[3, 3, 3], dilation=[1, 1, 1])\n",
" (2): MinkowskiInstanceNorm(nchannels=512)\n",
" (3): MinkowskiGELU()\n",
" )\n",
" (glob_pool): MinkowskiGlobalMaxPooling(mode=PoolingMode.GLOBAL_MAX_POOLING_PYTORCH_INDEX)\n",
" (final): MinkowskiLinear(in_features=512, out_features=40, bias=True)\n",
")\n",
"=============================================\n",
"\n",
"\n",
"Adam (\n",
"Parameter Group 0\n",
" amsgrad: False\n",
" betas: (0.9, 0.999)\n",
" eps: 1e-08\n",
" initial_lr: 0.001\n",
" lr: 0.001\n",
" weight_decay: 0\n",
")\n",
"<torch.optim.lr_scheduler.CosineAnnealingLR object at 0x7f9f9625b9d0>\n",
"/content/MinkowskiEngine/examples/pointnet.py:219: H5pyDeprecationWarning: The default file mode will change to 'r' (read-only) in h5py 3.0. To suppress this warning, pass the mode you need to h5py.File(), or set the global default h5.get_config().default_file_mode, or set the environment variable H5PY_DEFAULT_READONLY=1. Available modes are: 'r', 'r+', 'w', 'w-'/'x', 'a'. See the docs for details.\n",
" with h5py.File(h5_name) as f:\n",
"/content/MinkowskiEngine/MinkowskiEngine/MinkowskiSparseTensor.py:288: UserWarning: coordinates implicitly converted to torch.IntTensor. To remove this warning, use `.int()` to convert the coords into an torch.IntTensor\n",
" + \"coords into an torch.IntTensor\"\n",
"SparseTensor(\n",
" coordinates=tensor([[-1, 0, -1],\n",
" [ 0, 0, 0],\n",
" [-1, -1, 0],\n",
" [ 0, 0, -1],\n",
" [-1, -1, -1],\n",
" [-1, 0, 0],\n",
" [ 0, -1, 0],\n",
" [ 0, -1, -1]], dtype=torch.int32)\n",
" features=tensor([[-0.6400, 0.4102, -0.0917],\n",
" [ 0.5566, 0.3819, 0.2431],\n",
" [-0.6735, -0.3931, 0.2309],\n",
" [ 0.0071, 0.3728, -0.0990],\n",
" [-0.6857, -0.0427, -0.2021],\n",
" [-0.1697, 0.3722, 0.1271],\n",
" [ 0.0444, -0.2164, 0.5490],\n",
" [ 0.5727, -0.1144, -0.1766]])\n",
" coordinate_map_key=coordinate map key:[1, 1]\n",
" coordinate_manager=CoordinateMapManagerCPU(\n",
"\t[1, 1, \b\b]:\tCoordinateMapCPU:8x3\n",
"\talgorithm=MinkowskiAlgorithm.DEFAULT\n",
" )\n",
" spatial dimension=2)\n",
"Traceback (most recent call last):\n",
" File \"/usr/lib/python3.7/runpy.py\", line 193, in _run_module_as_main\n",
" \"__main__\", mod_spec)\n",
" File \"/usr/lib/python3.7/runpy.py\", line 85, in _run_code\n",
" exec(code, run_globals)\n",
" File \"/content/MinkowskiEngine/examples/classification_modelnet40.py\", line 375, in <module>\n",
" train(net, device, config)\n",
" File \"/content/MinkowskiEngine/examples/classification_modelnet40.py\", line 303, in train\n",
" net(inputs)\n",
" File \"/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py\", line 727, in _call_impl\n",
" result = self.forward(*input, **kwargs)\n",
" File \"/content/MinkowskiEngine/examples/resnet.py\", line 210, in forward\n",
" otensor = self.field_network(x)\n",
" File \"/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py\", line 727, in _call_impl\n",
" result = self.forward(*input, **kwargs)\n",
" File \"/usr/local/lib/python3.7/dist-packages/torch/nn/modules/container.py\", line 117, in forward\n",
" input = module(input)\n",
" File \"/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py\", line 727, in _call_impl\n",
" result = self.forward(*input, **kwargs)\n",
" File \"/content/MinkowskiEngine/MinkowskiEngine/MinkowskiOps.py\", line 407, in forward\n",
" \"Unsupported type. Only TensorField and torch.Tensor are supported\"\n",
"ValueError: Unsupported type. Only TensorField and torch.Tensor are supported\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "MrfqDFxt1VTe"
},
"source": [
""
],
"execution_count": null,
"outputs": []
}
]
}