Release.

LICENSE.md

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+# NVIDIA Source Code License for DiffRL
+
+## 1. Definitions
+
+“Licensor” means any person or entity that distributes its Work.
+“Software” means the original work of authorship made available under this License.
+“Work” means the Software and any additions to or derivative works of the Software that are made available under this License.
+The terms “reproduce,” “reproduction,” “derivative works,” and “distribution” have the meaning as provided under U.S. copyright law; provided, however, that for the purposes of this License, derivative works shall not include works that remain separable from, or merely link (or bind by name) to the interfaces of, the Work.
+Works, including the Software, are “made available” under this License by including in or with the Work either (a) a copyright notice referencing the applicability of this License to the Work, or (b) a copy of this License.
+
+## 2. License Grant
+
+2.1 Copyright Grant. Subject to the terms and conditions of this License, each Licensor grants to you a perpetual, worldwide, non-exclusive, royalty-free, copyright license to reproduce, prepare derivative works of, publicly display, publicly perform, sublicense and distribute its Work and any resulting derivative works in any form.
+
+## 3. Limitations
+
+3.1 Redistribution. You may reproduce or distribute the Work only if (a) you do so under this License, (b) you include a complete copy of this License with your distribution, and (c) you retain without modification any copyright, patent, trademark, or attribution notices that are present in the Work.
+
+3.2 Derivative Works. You may specify that additional or different terms apply to the use, reproduction, and distribution of your derivative works of the Work (“Your Terms”) only if (a) Your Terms provide that the use limitation in Section 3.3 applies to your derivative works, and (b) you identify the specific derivative works that are subject to Your Terms. Notwithstanding Your Terms, this License (including the redistribution requirements in Section 3.1) will continue to apply to the Work itself.
+
+3.3 Use Limitation. The Work and any derivative works thereof only may be used or intended for use non-commercially. Notwithstanding the foregoing, NVIDIA and its affiliates may use the Work and any derivative works commercially. As used herein, “non-commercially” means for research or evaluation purposes only.
+
+3.4 Patent Claims. If you bring or threaten to bring a patent claim against any Licensor (including any claim, cross-claim or counterclaim in a lawsuit) to enforce any patents that you allege are infringed by any Work, then your rights under this License from such Licensor (including the grant in Section 2.1) will terminate immediately.
+
+3.5 Trademarks. This License does not grant any rights to use any Licensor’s or its affiliates’ names, logos, or trademarks, except as necessary to reproduce the notices described in this License.
+
+3.6 Termination. If you violate any term of this License, then your rights under this License (including the grant in Section 2.1) will terminate immediately.
+
+## 4. Disclaimer of Warranty.
+
+THE WORK IS PROVIDED “AS IS” WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, EITHER EXPRESS OR IMPLIED, INCLUDING WARRANTIES OR CONDITIONS OF 
+MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE, TITLE OR NON-INFRINGEMENT. YOU BEAR THE RISK OF UNDERTAKING ANY ACTIVITIES UNDER THIS LICENSE. 
+
+## 5. Limitation of Liability.
+
+EXCEPT AS PROHIBITED BY APPLICABLE LAW, IN NO EVENT AND UNDER NO LEGAL THEORY, WHETHER IN TORT (INCLUDING NEGLIGENCE), CONTRACT, OR OTHERWISE SHALL ANY LICENSOR BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES ARISING OUT OF OR RELATED TO THIS LICENSE, THE USE OR INABILITY TO USE THE WORK (INCLUDING BUT NOT LIMITED TO LOSS OF GOODWILL, BUSINESS INTERRUPTION, LOST PROFITS OR DATA, COMPUTER FAILURE OR MALFUNCTION, OR ANY OTHER COMM ERCIAL DAMAGES OR LOSSES), EVEN IF THE LICENSOR HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGES.

dflex/README.md

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+# A Differentiable Multiphysics Engine for PyTorch
+
+dFlex is a physics engine for Python. It is written entirely in PyTorch and supports reverse mode differentiation w.r.t. to any simulation inputs.
+
+It includes a USD-based visualization library (`dflex.render`), which can generate time-sampled USD files, or update an existing stage on-the-fly.
+
+## Prerequisites
+
+* Python 3.6
+* PyTorch 1.4.0 or higher
+* Pixar USD lib (for visualization)
+
+Pre-built USD Python libraries can be downloaded from https://developer.nvidia.com/usd, once they are downloaded you should follow the instructions to add them to your PYTHONPATH environment variable.
+
+## Using the built-in backend
+
+By default dFlex uses the built-in PyTorch cpp-extensions mechanism to compile auto-generated simulation kernels. 
+
+- Windows users should ensure they have Visual Studio 2019 installed
+
+## Setup and Running
+
+To use the engine you can import first the simulation module:
+
+```python
+    import dflex.sim
+```
+
+To build physical models there is a helper class available in `dflex.sim.ModelBuilder`. This can be used to create models programmatically from Python. For example, to create a chain of particles:
+
+```python
+    builder = dflex.sim.ModelBuilder()
+
+    # anchor point (zero mass)
+    builder.add_particle((0, 1.0, 0.0), (0.0, 0.0, 0.0), 0.0)
+
+    # build chain
+    for i in range(1,10):
+        builder.add_particle((i, 1.0, 0.0), (0.0, 0.0, 0.0), 1.0)
+        builder.add_spring(i-1, i, 1.e+3, 0.0, 0)
+
+    # add ground plane
+    builder.add_shape_plane((0.0, 1.0, 0.0, 0.0), 0)
+```
+
+Once you have built your model you must convert it to a finalized PyTorch simulation data structure using `finalize()`:
+
+```python
+    model = builder.finalize('cpu')
+```
+
+
+The model object represents static (non-time varying) data such as constraints, collision shapes, etc. The model is stored in PyTorch tensors, allowing differentiation with respect to both model and state.
+
+## Time Stepping
+
+To advance the simulation forward in time (forward dynamics), we use an `integrator` object. dFlex currently offers semi-implicit and fully implicit (planned), via. the `dflex.sim.ExplicitIntegrator`, and `dflex.sim.ImplicitIntegrator` classes as follows:
+
+```python
+    sim_dt = 1.0/60.0
+    sim_steps = 100
+
+    integrator = dflex.sim.ExplicitIntegrator()
+
+    for i in range(0, sim_steps):
+        state = integrator.forward(model, state, sim_dt)
+```
+
+## Rendering
+
+To visualize the scene dFlex supports a USD-based update via. the `dflex.render.UsdRenderer` class. To create a renderer you must first create the USD stage, and the physical model.
+
+```python
+    import dflex.render
+
+    stage = Usd.Stage.CreateNew("test.usda")
+
+    renderer = dflex.render.UsdRenderer(model, stage)
+    renderer.draw_points = True
+    renderer.draw_springs = True
+    renderer.draw_shapes = True
+```
+
+Each frame the renderer should be updated with the current model state and the current elapsed simulation time:
+
+```python
+    renderer.update(state, sim_time)
+```
+
+## Contact
+
+Miles Macklin ([email protected])

dflex/dflex.egg-info/PKG-INFO

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+Metadata-Version: 2.1
+Name: dflex
+Version: 0.0.1
+Summary: Differentiable Multiphysics for Python
+Author: NVIDIA
+Author-email: [email protected]
+License: UNKNOWN
+Platform: UNKNOWN
+Classifier: Programming Language :: Python :: 3
+Classifier: Operating System :: OS Independent
+Description-Content-Type: text/markdown
+
+UNKNOWN
+

dflex/dflex.egg-info/SOURCES.txt

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+README.md
+setup.py
+dflex/__init__.py
+dflex/adjoint.h
+dflex/adjoint.py
+dflex/config.py
+dflex/mat22.h
+dflex/mat33.h
+dflex/matnn.h
+dflex/model.py
+dflex/quat.h
+dflex/render.py
+dflex/sim.py
+dflex/spatial.h
+dflex/util.py
+dflex/vec2.h
+dflex/vec3.h
+dflex.egg-info/PKG-INFO
+dflex.egg-info/SOURCES.txt
+dflex.egg-info/dependency_links.txt
+dflex.egg-info/requires.txt
+dflex.egg-info/top_level.txt

dflex/dflex.egg-info/dependency_links.txt

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+

dflex/dflex.egg-info/requires.txt

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+ninja
+torch

dflex/dflex.egg-info/top_level.txt

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+dflex

dflex/dflex/__init__.py

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+# Copyright (c) 2022 NVIDIA CORPORATION.  All rights reserved.
+# NVIDIA CORPORATION and its licensors retain all intellectual property
+# and proprietary rights in and to this software, related documentation
+# and any modifications thereto.  Any use, reproduction, disclosure or
+# distribution of this software and related documentation without an express
+# license agreement from NVIDIA CORPORATION is strictly prohibited.
+
+from dflex.sim import *
+from dflex.render import *
+from dflex.adjoint import compile
+
+from dflex.util import *
+
+# compiles kernels
+kernel_init()