#!/usr/bin/env python3 # Copyright (c) 2020-2022, NVIDIA CORPORATION. All rights reserved. # # Redistribution and use in source and binary forms, with or without modification, are permitted # provided that the following conditions are met: # * Redistributions of source code must retain the above copyright notice, this list of # conditions and the following disclaimer. # * Redistributions in binary form must reproduce the above copyright notice, this list of # conditions and the following disclaimer in the documentation and/or other materials # provided with the distribution. # * Neither the name of the NVIDIA CORPORATION nor the names of its contributors may be used # to endorse or promote products derived from this software without specific prior written # permission. # # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR # IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND # FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL NVIDIA CORPORATION BE LIABLE # FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, # BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; # OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, # STRICT LIABILITY, OR TOR (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. import torch import tinycudann as tcnn net = tcnn.Network( n_input_dims=3, n_output_dims=3, network_config={ "otype": "FullyFusedMLP", "activation": "ReLU", "output_activation": "None", "n_neurons": 16, "n_hidden_layers": 2, }, ).cuda() x = torch.rand(256, 3, device='cuda') y = net(x) y.sum().backward() # OK x2 = torch.rand(256, 3, device='cuda') y = net(x) y2 = net(x2) (y + y2).sum().backward() # RuntimeError: Must call forward() before calling backward() print("success!")