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project/ManiSkill3/src/maniskill2_benchmark/cfdp_experiment/cfdp/extern/pytorch3d/.github/ISSUE_TEMPLATE/questions-help.md

@@ -0,0 +1,21 @@
+---
+name: "❓ Questions"
+about: How do I do X with PyTorch3D? How does PyTorch3D do X?
+
+---
+
+## ❓ Questions on how to use PyTorch3D
+
+<!-- A clear and concise description of the question you need help with. -->
+
+
+NOTE: Please look at the existing list of Issues tagged with the label ['question`](https://github.com/facebookresearch/pytorch3d/issues?q=label%3Aquestion) or ['how-to`](https://github.com/facebookresearch/pytorch3d/issues?q=label%3A%22how+to%22). **Only open a new issue if you cannot find an answer there**.
+
+Also note the following:
+
+1. If you encountered any errors or unexpected issues while using PyTorch3D and need help resolving them,
+   please use the "Bugs / Unexpected behaviors" issue template.
+
+2. We do not answer general machine learning / computer vision questions that are not specific to
+   PyTorch3D, such as how a model works or what algorithm/methods can be
+   used to achieve X.

project/ManiSkill3/src/maniskill2_benchmark/cfdp_experiment/cfdp/extern/pytorch3d/dev/linter.sh

@@ -0,0 +1,40 @@
+#!/bin/bash -e
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the BSD-style license found in the
+# LICENSE file in the root directory of this source tree.
+
+# Run this script at project root by "./dev/linter.sh" before you commit
+
+DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )"
+DIR=$(dirname "${DIR}")
+
+if [[ -f "${DIR}/TARGETS" ]]
+then
+  pyfmt "${DIR}"
+else
+# run usort externally only
+  echo "Running usort..."
+  usort  "${DIR}"
+fi
+
+echo "Running black..."
+black "${DIR}"
+
+echo "Running flake..."
+flake8 "${DIR}" || true
+
+echo "Running clang-format ..."
+clangformat=$(command -v clang-format-8 || echo clang-format)
+find "${DIR}" -regex ".*\.\(cpp\|c\|cc\|cu\|cuh\|cxx\|h\|hh\|hpp\|hxx\|tcc\|mm\|m\)" -print0 | xargs -0 "${clangformat}" -i
+
+# Run arc and pyre internally only.
+if [[ -f "${DIR}/TARGETS" ]]
+then
+  (cd "${DIR}"; command -v arc > /dev/null && arc lint) || true
+
+  echo "Running pyre..."
+  echo "To restart/kill pyre server, run 'pyre restart' or 'pyre kill' in fbcode/"
+  ( cd ~/fbsource/fbcode; pyre -l vision/fair/pytorch3d/ )
+fi

project/ManiSkill3/src/maniskill2_benchmark/cfdp_experiment/cfdp/extern/pytorch3d/dev/run_tutorials.sh

@@ -0,0 +1,56 @@
+#!/usr/bin/bash
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the BSD-style license found in the
+# LICENSE file in the root directory of this source tree.
+
+# This script is for running some of the tutorials using the nightly build in
+# an isolated environment. It is designed to be run in docker.
+
+# If you run this script in this directory with
+#   sudo docker run --runtime=nvidia -it --rm -v $PWD/../docs/tutorials:/notebooks -v $PWD:/loc pytorch/conda-cuda bash /loc/run_tutorials.sh | tee log.txt
+# it should execute some tutorials with the nightly build and resave them, and
+# save a log in the current directory.
+
+# We use nbconvert. runipy would be an alternative but it currently doesn't
+# work well with plotly.
+
+set -e
+
+conda init bash
+# shellcheck source=/dev/null
+source ~/.bashrc
+conda create -y -n myenv python=3.8 matplotlib ipython ipywidgets nbconvert
+conda activate myenv
+conda install -y -c iopath iopath
+conda install -y -c pytorch pytorch=1.6.0 cudatoolkit=10.1 torchvision
+conda install -y -c pytorch3d-nightly pytorch3d
+pip install plotly scikit-image
+
+for notebook in /notebooks/*.ipynb
+do
+    name=$(basename "$notebook")
+
+    if [[ "$name" == "dataloaders_ShapeNetCore_R2N2.ipynb" ]]
+    then
+        #skip as data not easily available
+        continue
+    fi
+    if [[ "$name" == "render_densepose.ipynb" ]]
+    then
+        #skip as data not easily available
+        continue
+    fi
+
+    #comment the lines which install torch, torchvision and pytorch3d
+    sed -Ei '/(torchvision)|(pytorch3d)/ s/!pip/!#pip/' "$notebook"
+    #Don't let tqdm use widgets
+    sed -i 's/from tqdm.notebook import tqdm/from tqdm import tqdm/' "$notebook"
+
+    echo
+    echo "###   ###   ###"
+    echo "starting $name"
+    time jupyter nbconvert --to notebook --inplace --ExecutePreprocessor.kernel_name=python3 --execute "$notebook" || true
+    echo "ending $name"
+done

project/ManiSkill3/src/maniskill2_benchmark/cfdp_experiment/cfdp/extern/pytorch3d/dev/test_list.py

@@ -0,0 +1,65 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the BSD-style license found in the
+# LICENSE file in the root directory of this source tree.
+
+import ast
+from pathlib import Path
+from typing import List
+
+
+"""
+This module outputs a list of tests for completion.
+It has no dependencies.
+"""
+
+
+def get_test_files() -> List[Path]:
+    root = Path(__file__).parent.parent
+    dirs = ["tests", "projects/implicitron_trainer"]
+    return [i for dir in dirs for i in (root / dir).glob("**/test*.py")]
+
+
+def tests_from_file(path: Path, base: str) -> List[str]:
+    """
+    Returns all the tests in the given file, in format
+    expected as arguments when running the tests.
+    e.g.
+        file_stem
+        file_stem.TestFunctionality
+        file_stem.TestFunctionality.test_f
+        file_stem.TestFunctionality.test_g
+    """
+    with open(path) as f:
+        node = ast.parse(f.read())
+    out = [base]
+    for cls in node.body:
+        if not isinstance(cls, ast.ClassDef):
+            continue
+        if not cls.name.startswith("Test"):
+            continue
+        class_base = base + "." + cls.name
+        out.append(class_base)
+        for method in cls.body:
+            if not isinstance(method, ast.FunctionDef):
+                continue
+            if not method.name.startswith("test"):
+                continue
+            out.append(class_base + "." + method.name)
+    return out
+
+
+def main() -> None:
+    files = get_test_files()
+    test_root = Path(__file__).parent.parent
+    all_tests = []
+    for f in files:
+        file_base = str(f.relative_to(test_root))[:-3].replace("/", ".")
+        all_tests.extend(tests_from_file(f, file_base))
+    for test in sorted(all_tests):
+        print(test)
+
+
+if __name__ == "__main__":
+    main()

project/ManiSkill3/src/maniskill2_benchmark/cfdp_experiment/cfdp/extern/pytorch3d/docs/modules/implicitron/models/global_encoder/autodecoder.rst

@@ -0,0 +1,9 @@
+pytorch3d.implicitron.models.global_encoder.autodecoder
+=======================================================
+
+autodecoder
+
+.. automodule:: pytorch3d.implicitron.models.global_encoder.autodecoder
+    :members:
+    :undoc-members:
+    :show-inheritance:

project/ManiSkill3/src/maniskill2_benchmark/cfdp_experiment/cfdp/extern/pytorch3d/docs/modules/implicitron/models/global_encoder/global_encoder.rst

@@ -0,0 +1,9 @@
+pytorch3d.implicitron.models.global_encoder.global_encoder
+==========================================================
+
+global_encoder
+
+.. automodule:: pytorch3d.implicitron.models.global_encoder.global_encoder
+    :members:
+    :undoc-members:
+    :show-inheritance:

project/ManiSkill3/src/maniskill2_benchmark/cfdp_experiment/cfdp/extern/pytorch3d/docs/modules/implicitron/models/global_encoder/index.rst

@@ -0,0 +1,7 @@
+pytorch3d.implicitron.models.global_encoder
+===========================================
+
+.. toctree::
+
+    autodecoder
+    global_encoder

project/ManiSkill3/src/maniskill2_benchmark/cfdp_experiment/cfdp/extern/pytorch3d/docs/modules/implicitron/models/implicit_function/utils.rst

@@ -0,0 +1,9 @@
+pytorch3d.implicitron.models.implicit_function.utils
+====================================================
+
+utils
+
+.. automodule:: pytorch3d.implicitron.models.implicit_function.utils
+    :members:
+    :undoc-members:
+    :show-inheritance:

project/ManiSkill3/src/maniskill2_benchmark/cfdp_experiment/cfdp/extern/pytorch3d/docs/modules/implicitron/models/view_pooler/feature_aggregator.rst

@@ -0,0 +1,9 @@
+pytorch3d.implicitron.models.view_pooler.feature_aggregator
+===========================================================
+
+feature_aggregator
+
+.. automodule:: pytorch3d.implicitron.models.view_pooler.feature_aggregator
+    :members:
+    :undoc-members:
+    :show-inheritance:

project/ManiSkill3/src/maniskill2_benchmark/cfdp_experiment/cfdp/extern/pytorch3d/docs/modules/renderer/mesh/clip.rst

@@ -0,0 +1,9 @@
+pytorch3d.renderer.mesh.clip
+============================
+
+clip
+
+.. automodule:: pytorch3d.renderer.mesh.clip
+    :members:
+    :undoc-members:
+    :show-inheritance:

project/ManiSkill3/src/maniskill2_benchmark/cfdp_experiment/cfdp/pytorch3d/docs/modules/implicitron/data_basics.rst

@@ -0,0 +1,29 @@
+pytorch3d.implicitron.dataset in general
+========================================
+
+Basics of data for implicitron
+
+.. automodule:: pytorch3d.implicitron.dataset.dataset_base
+    :members:
+    :undoc-members:
+    :show-inheritance:
+
+.. automodule:: pytorch3d.implicitron.dataset.dataset_map_provider
+    :members:
+    :undoc-members:
+    :show-inheritance:
+
+.. automodule:: pytorch3d.implicitron.dataset.data_loader_map_provider
+    :members:
+    :undoc-members:
+    :show-inheritance:
+
+.. automodule:: pytorch3d.implicitron.dataset.data_source
+    :members:
+    :undoc-members:
+    :show-inheritance:
+
+.. automodule:: pytorch3d.implicitron.dataset.scene_batch_sampler
+    :members:
+    :undoc-members:
+    :show-inheritance:

project/ManiSkill3/src/maniskill2_benchmark/cfdp_experiment/cfdp/pytorch3d/docs/modules/implicitron/datasets.rst

@@ -0,0 +1,29 @@
+pytorch3d.implicitron.dataset specific datasets
+===============================================
+
+specific datasets
+
+.. automodule:: pytorch3d.implicitron.dataset.blender_dataset_map_provider
+    :members:
+    :undoc-members:
+    :show-inheritance:
+
+.. automodule:: pytorch3d.implicitron.dataset.json_index_dataset_map_provider
+    :members:
+    :undoc-members:
+    :show-inheritance:
+
+.. automodule:: pytorch3d.implicitron.dataset.json_index_dataset_map_provider_v2
+    :members:
+    :undoc-members:
+    :show-inheritance:
+
+.. automodule:: pytorch3d.implicitron.dataset.llff_dataset_map_provider
+    :members:
+    :undoc-members:
+    :show-inheritance:
+
+.. automodule:: pytorch3d.implicitron.dataset.rendered_mesh_dataset_map_provider
+    :members:
+    :undoc-members:
+    :show-inheritance:

project/ManiSkill3/src/maniskill2_benchmark/cfdp_experiment/cfdp/pytorch3d/docs/modules/implicitron/evaluation.rst

@@ -0,0 +1,14 @@
+pytorch3d.implicitron.evaluation
+================================
+
+evaluation
+
+.. automodule:: pytorch3d.implicitron.evaluation.evaluate_new_view_synthesis
+    :members:
+    :undoc-members:
+    :show-inheritance:
+
+.. automodule:: pytorch3d.implicitron.evaluation.evaluator
+    :members:
+    :undoc-members:
+    :show-inheritance:

project/ManiSkill3/src/maniskill2_benchmark/cfdp_experiment/cfdp/pytorch3d/docs/modules/implicitron/index.rst

@@ -0,0 +1,10 @@
+pytorch3d.implicitron
+=====================
+
+.. toctree::
+
+    models/index.rst
+    data_basics
+    datasets
+    evaluation
+    tools

project/ManiSkill3/src/maniskill2_benchmark/cfdp_experiment/cfdp/pytorch3d/docs/modules/implicitron/models/view_pooler/feature_aggregator.rst

@@ -0,0 +1,9 @@
+pytorch3d.implicitron.models.view_pooler.feature_aggregator
+===========================================================
+
+feature_aggregator
+
+.. automodule:: pytorch3d.implicitron.models.view_pooler.feature_aggregator
+    :members:
+    :undoc-members:
+    :show-inheritance:

project/ManiSkill3/src/maniskill2_benchmark/cfdp_experiment/cfdp/pytorch3d/docs/modules/implicitron/models/view_pooler/index.rst

@@ -0,0 +1,8 @@
+pytorch3d.implicitron.models.view_pooler
+========================================
+
+.. toctree::
+
+    feature_aggregator
+    view_pooler
+    view_sampler

project/ManiSkill3/src/maniskill2_benchmark/cfdp_experiment/cfdp/pytorch3d/docs/modules/implicitron/models/view_pooler/view_pooler.rst

@@ -0,0 +1,9 @@
+pytorch3d.implicitron.models.view_pooler.view_pooler
+====================================================
+
+view_pooler
+
+.. automodule:: pytorch3d.implicitron.models.view_pooler.view_pooler
+    :members:
+    :undoc-members:
+    :show-inheritance:

project/ManiSkill3/src/maniskill2_benchmark/cfdp_experiment/cfdp/pytorch3d/docs/modules/implicitron/models/view_pooler/view_sampler.rst

@@ -0,0 +1,9 @@
+pytorch3d.implicitron.models.view_pooler.view_sampler
+=====================================================
+
+view_sampler
+
+.. automodule:: pytorch3d.implicitron.models.view_pooler.view_sampler
+    :members:
+    :undoc-members:
+    :show-inheritance:

project/ManiSkill3/src/maniskill2_benchmark/cfdp_experiment/cfdp/pytorch3d/docs/modules/implicitron/tools.rst

@@ -0,0 +1,64 @@
+pytorch3d.implicitron.tools
+===========================
+
+Tools for implicitron
+
+.. automodule:: pytorch3d.implicitron.tools.camera_utils
+    :members:
+    :undoc-members:
+    :show-inheritance:
+
+.. automodule:: pytorch3d.implicitron.tools.circle_fitting
+    :members:
+    :undoc-members:
+    :show-inheritance:
+
+.. automodule:: pytorch3d.implicitron.tools.config
+    :members:
+    :undoc-members:
+    :show-inheritance:
+
+.. automodule:: pytorch3d.implicitron.tools.eval_video_trajectory
+    :members:
+    :undoc-members:
+    :show-inheritance:
+
+.. automodule:: pytorch3d.implicitron.tools.image_utils
+    :members:
+    :undoc-members:
+    :show-inheritance:
+
+.. automodule:: pytorch3d.implicitron.tools.metric_utils
+    :members:
+    :undoc-members:
+    :show-inheritance:
+
+.. automodule:: pytorch3d.implicitron.tools.model_io
+    :members:
+    :undoc-members:
+    :show-inheritance:
+
+.. automodule:: pytorch3d.implicitron.tools.point_cloud_utils
+    :members:
+    :undoc-members:
+    :show-inheritance:
+
+.. automodule:: pytorch3d.implicitron.tools.rasterize_mc
+    :members:
+    :undoc-members:
+    :show-inheritance:
+
+.. automodule:: pytorch3d.implicitron.tools.stats
+    :members:
+    :undoc-members:
+    :show-inheritance:
+
+.. automodule:: pytorch3d.implicitron.tools.video_writer
+    :members:
+    :undoc-members:
+    :show-inheritance:
+
+.. automodule:: pytorch3d.implicitron.tools.vis_utils
+    :members:
+    :undoc-members:
+    :show-inheritance:

project/ManiSkill3/src/maniskill2_benchmark/cfdp_experiment/cfdp/pytorch3d/docs/modules/io.rst

@@ -0,0 +1,7 @@
+pytorch3d.io 
+===========================
+
+.. automodule:: pytorch3d.io
+    :members:
+    :undoc-members:
+    :show-inheritance:

project/ManiSkill3/src/maniskill2_benchmark/cfdp_experiment/cfdp/pytorch3d/docs/modules/renderer/blending.rst

@@ -0,0 +1,9 @@
+pytorch3d.renderer.blending
+===========================
+
+blending
+
+.. automodule:: pytorch3d.renderer.blending
+    :members:
+    :undoc-members:
+    :show-inheritance:

project/ManiSkill3/src/maniskill2_benchmark/cfdp_experiment/cfdp/pytorch3d/docs/modules/renderer/camera_conversions.rst

@@ -0,0 +1,9 @@
+pytorch3d.renderer.camera_conversions
+=====================================
+
+camera_conversions
+
+.. automodule:: pytorch3d.renderer.camera_conversions
+    :members:
+    :undoc-members:
+    :show-inheritance:

project/ManiSkill3/src/maniskill2_benchmark/cfdp_experiment/cfdp/pytorch3d/docs/modules/renderer/camera_utils.rst

@@ -0,0 +1,9 @@
+pytorch3d.renderer.camera_utils
+===============================
+
+camera_utils
+
+.. automodule:: pytorch3d.renderer.camera_utils
+    :members:
+    :undoc-members:
+    :show-inheritance:

project/ManiSkill3/src/maniskill2_benchmark/cfdp_experiment/cfdp/pytorch3d/docs/modules/renderer/cameras.rst

@@ -0,0 +1,9 @@
+pytorch3d.renderer.cameras
+==========================
+
+cameras
+
+.. automodule:: pytorch3d.renderer.cameras
+    :members:
+    :undoc-members:
+    :show-inheritance:

project/ManiSkill3/src/maniskill2_benchmark/cfdp_experiment/cfdp/pytorch3d/docs/modules/renderer/compositing.rst

@@ -0,0 +1,9 @@
+pytorch3d.renderer.compositing
+==============================
+
+compositing
+
+.. automodule:: pytorch3d.renderer.compositing
+    :members:
+    :undoc-members:
+    :show-inheritance:

project/ManiSkill3/src/maniskill2_benchmark/cfdp_experiment/cfdp/pytorch3d/docs/modules/renderer/implicit/harmonic_embedding.rst

@@ -0,0 +1,9 @@
+pytorch3d.renderer.implicit.harmonic_embedding
+==============================================
+
+harmonic_embedding
+
+.. automodule:: pytorch3d.renderer.implicit.harmonic_embedding
+    :members:
+    :undoc-members:
+    :show-inheritance:

project/ManiSkill3/src/maniskill2_benchmark/cfdp_experiment/cfdp/pytorch3d/docs/modules/renderer/implicit/index.rst

@@ -0,0 +1,11 @@
+pytorch3d.renderer.implicit
+===========================
+
+.. toctree::
+
+    harmonic_embedding
+    raymarching
+    raysampling
+    renderer
+    sample_pdf
+    utils

project/ManiSkill3/src/maniskill2_benchmark/cfdp_experiment/cfdp/pytorch3d/docs/modules/renderer/implicit/raymarching.rst

@@ -0,0 +1,9 @@
+pytorch3d.renderer.implicit.raymarching
+=======================================
+
+raymarching
+
+.. automodule:: pytorch3d.renderer.implicit.raymarching
+    :members:
+    :undoc-members:
+    :show-inheritance:

project/ManiSkill3/src/maniskill2_benchmark/cfdp_experiment/cfdp/pytorch3d/docs/modules/renderer/implicit/raysampling.rst

@@ -0,0 +1,9 @@
+pytorch3d.renderer.implicit.raysampling
+=======================================
+
+raysampling
+
+.. automodule:: pytorch3d.renderer.implicit.raysampling
+    :members:
+    :undoc-members:
+    :show-inheritance:

project/ManiSkill3/src/maniskill2_benchmark/cfdp_experiment/cfdp/pytorch3d/docs/modules/renderer/implicit/renderer.rst

@@ -0,0 +1,9 @@
+pytorch3d.renderer.implicit.renderer
+====================================
+
+renderer
+
+.. automodule:: pytorch3d.renderer.implicit.renderer
+    :members:
+    :undoc-members:
+    :show-inheritance:

project/ManiSkill3/src/maniskill2_benchmark/cfdp_experiment/cfdp/pytorch3d/docs/modules/renderer/implicit/sample_pdf.rst

@@ -0,0 +1,9 @@
+pytorch3d.renderer.implicit.sample_pdf
+======================================
+
+sample_pdf
+
+.. automodule:: pytorch3d.renderer.implicit.sample_pdf
+    :members:
+    :undoc-members:
+    :show-inheritance:

project/ManiSkill3/src/maniskill2_benchmark/cfdp_experiment/cfdp/pytorch3d/docs/modules/renderer/implicit/utils.rst

@@ -0,0 +1,9 @@
+pytorch3d.renderer.implicit.utils
+=================================
+
+utils
+
+.. automodule:: pytorch3d.renderer.implicit.utils
+    :members:
+    :undoc-members:
+    :show-inheritance:

project/ManiSkill3/src/maniskill2_benchmark/cfdp_experiment/cfdp/pytorch3d/docs/modules/renderer/index.rst

@@ -0,0 +1,19 @@
+pytorch3d.renderer
+==================
+
+.. toctree::
+
+    blending
+    camera_conversions
+    camera_utils
+    cameras
+    compositing
+    fisheyecameras
+    lighting
+    materials
+    splatter_blend
+    utils
+    implicit/index
+    mesh/index
+    opengl/index
+    points/index

project/ManiSkill3/src/maniskill2_benchmark/cfdp_experiment/cfdp/pytorch3d/docs/modules/renderer/lighting.rst

@@ -0,0 +1,9 @@
+pytorch3d.renderer.lighting
+===========================
+
+lighting
+
+.. automodule:: pytorch3d.renderer.lighting
+    :members:
+    :undoc-members:
+    :show-inheritance:

project/ManiSkill3/src/maniskill2_benchmark/cfdp_experiment/cfdp/pytorch3d/docs/modules/renderer/materials.rst

@@ -0,0 +1,9 @@
+pytorch3d.renderer.materials
+============================
+
+materials
+
+.. automodule:: pytorch3d.renderer.materials
+    :members:
+    :undoc-members:
+    :show-inheritance:

project/ManiSkill3/src/maniskill2_benchmark/cfdp_experiment/cfdp/pytorch3d/docs/modules/renderer/mesh/index.rst

@@ -0,0 +1,13 @@
+pytorch3d.renderer.mesh
+=======================
+
+.. toctree::
+
+    clip
+    rasterize_meshes
+    rasterizer
+    renderer
+    shader
+    shading
+    textures
+    utils

project/ManiSkill3/src/maniskill2_benchmark/cfdp_experiment/cfdp/pytorch3d/docs/modules/renderer/mesh/rasterize_meshes.rst

@@ -0,0 +1,9 @@
+pytorch3d.renderer.mesh.rasterize_meshes
+========================================
+
+rasterize_meshes
+
+.. automodule:: pytorch3d.renderer.mesh.rasterize_meshes
+    :members:
+    :undoc-members:
+    :show-inheritance:

project/ManiSkill3/src/maniskill2_benchmark/cfdp_experiment/cfdp/pytorch3d/docs/modules/renderer/mesh/renderer.rst

@@ -0,0 +1,9 @@
+pytorch3d.renderer.mesh.renderer
+================================
+
+renderer
+
+.. automodule:: pytorch3d.renderer.mesh.renderer
+    :members:
+    :undoc-members:
+    :show-inheritance:

project/ManiSkill3/src/maniskill2_benchmark/cfdp_experiment/cfdp/pytorch3d/docs/modules/renderer/points/compositor.rst

@@ -0,0 +1,9 @@
+pytorch3d.renderer.points.compositor
+====================================
+
+compositor
+
+.. automodule:: pytorch3d.renderer.points.compositor
+    :members:
+    :undoc-members:
+    :show-inheritance:

project/ManiSkill3/src/maniskill2_benchmark/cfdp_experiment/cfdp/pytorch3d/docs/modules/renderer/points/index.rst

@@ -0,0 +1,10 @@
+pytorch3d.renderer.points
+=========================
+
+.. toctree::
+
+    compositor
+    rasterize_points
+    rasterizer
+    renderer
+    pulsar/index

project/ManiSkill3/src/maniskill2_benchmark/cfdp_experiment/cfdp/pytorch3d/docs/modules/renderer/points/rasterize_points.rst

@@ -0,0 +1,9 @@
+pytorch3d.renderer.points.rasterize_points
+==========================================
+
+rasterize_points
+
+.. automodule:: pytorch3d.renderer.points.rasterize_points
+    :members:
+    :undoc-members:
+    :show-inheritance:

project/ManiSkill3/src/maniskill2_benchmark/cfdp_experiment/cfdp/pytorch3d/docs/modules/renderer/points/rasterizer.rst

@@ -0,0 +1,9 @@
+pytorch3d.renderer.points.rasterizer
+====================================
+
+rasterizer
+
+.. automodule:: pytorch3d.renderer.points.rasterizer
+    :members:
+    :undoc-members:
+    :show-inheritance:

project/ManiSkill3/src/maniskill2_benchmark/cfdp_experiment/cfdp/pytorch3d/docs/modules/renderer/points/renderer.rst

@@ -0,0 +1,9 @@
+pytorch3d.renderer.points.renderer
+==================================
+
+renderer
+
+.. automodule:: pytorch3d.renderer.points.renderer
+    :members:
+    :undoc-members:
+    :show-inheritance:

project/ManiSkill3/src/maniskill2_benchmark/cfdp_experiment/cfdp/pytorch3d/docs/modules/renderer/splatter_blend.rst

@@ -0,0 +1,9 @@
+pytorch3d.renderer.splatter_blend
+=================================
+
+splatter_blend
+
+.. automodule:: pytorch3d.renderer.splatter_blend
+    :members:
+    :undoc-members:
+    :show-inheritance:

project/ManiSkill3/src/maniskill2_benchmark/cfdp_experiment/cfdp/pytorch3d/docs/modules/renderer/utils.rst

@@ -0,0 +1,9 @@
+pytorch3d.renderer.utils
+========================
+
+utils
+
+.. automodule:: pytorch3d.renderer.utils
+    :members:
+    :undoc-members:
+    :show-inheritance:

project/ManiSkill3/src/maniskill2_benchmark/cfdp_experiment/cfdp/pytorch3d/docs/modules/transforms.rst

@@ -0,0 +1,7 @@
+pytorch3d.transforms 
+===========================
+
+.. automodule:: pytorch3d.transforms
+    :members:
+    :undoc-members:
+    :show-inheritance:

project/ManiSkill3/src/maniskill2_benchmark/cfdp_experiment/cfdp/pytorch3d/projects/__init__.py

@@ -0,0 +1,5 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the BSD-style license found in the
+# LICENSE file in the root directory of this source tree.

project/ManiSkill3/src/maniskill2_benchmark/cfdp_experiment/cfdp/pytorch3d/pytorch3d/ops/laplacian_matrices.py

@@ -0,0 +1,177 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the BSD-style license found in the
+# LICENSE file in the root directory of this source tree.
+
+# pyre-unsafe
+
+from typing import Tuple
+
+import torch
+
+
+# ------------------------ Laplacian Matrices ------------------------ #
+# This file contains implementations of differentiable laplacian matrices.
+# These include
+# 1) Standard Laplacian matrix
+# 2) Cotangent Laplacian matrix
+# 3) Norm Laplacian matrix
+# -------------------------------------------------------------------- #
+
+
+def laplacian(verts: torch.Tensor, edges: torch.Tensor) -> torch.Tensor:
+    """
+    Computes the laplacian matrix.
+    The definition of the laplacian is
+    L[i, j] =    -1       , if i == j
+    L[i, j] = 1 / deg(i)  , if (i, j) is an edge
+    L[i, j] =    0        , otherwise
+    where deg(i) is the degree of the i-th vertex in the graph.
+
+    Args:
+        verts: tensor of shape (V, 3) containing the vertices of the graph
+        edges: tensor of shape (E, 2) containing the vertex indices of each edge
+    Returns:
+        L: Sparse FloatTensor of shape (V, V)
+    """
+    V = verts.shape[0]
+
+    e0, e1 = edges.unbind(1)
+
+    idx01 = torch.stack([e0, e1], dim=1)  # (E, 2)
+    idx10 = torch.stack([e1, e0], dim=1)  # (E, 2)
+    idx = torch.cat([idx01, idx10], dim=0).t()  # (2, 2*E)
+
+    # First, we construct the adjacency matrix,
+    # i.e. A[i, j] = 1 if (i,j) is an edge, or
+    # A[e0, e1] = 1 &  A[e1, e0] = 1
+    ones = torch.ones(idx.shape[1], dtype=torch.float32, device=verts.device)
+    A = torch.sparse_coo_tensor(idx, ones, (V, V), dtype=torch.float32)
+
+    # the sum of i-th row of A gives the degree of the i-th vertex
+    deg = torch.sparse.sum(A, dim=1).to_dense()
+
+    # We construct the Laplacian matrix by adding the non diagonal values
+    # i.e. L[i, j] = 1 ./ deg(i) if (i, j) is an edge
+    deg0 = deg[e0]
+    # pyre-fixme[58]: `/` is not supported for operand types `float` and `Tensor`.
+    deg0 = torch.where(deg0 > 0.0, 1.0 / deg0, deg0)
+    deg1 = deg[e1]
+    # pyre-fixme[58]: `/` is not supported for operand types `float` and `Tensor`.
+    deg1 = torch.where(deg1 > 0.0, 1.0 / deg1, deg1)
+    val = torch.cat([deg0, deg1])
+    L = torch.sparse_coo_tensor(idx, val, (V, V), dtype=torch.float32)
+
+    # Then we add the diagonal values L[i, i] = -1.
+    idx = torch.arange(V, device=verts.device)
+    idx = torch.stack([idx, idx], dim=0)
+    ones = torch.ones(idx.shape[1], dtype=torch.float32, device=verts.device)
+    L -= torch.sparse_coo_tensor(idx, ones, (V, V), dtype=torch.float32)
+
+    return L
+
+
+def cot_laplacian(
+    verts: torch.Tensor, faces: torch.Tensor, eps: float = 1e-12
+) -> Tuple[torch.Tensor, torch.Tensor]:
+    """
+    Returns the Laplacian matrix with cotangent weights and the inverse of the
+    face areas.
+
+    Args:
+        verts: tensor of shape (V, 3) containing the vertices of the graph
+        faces: tensor of shape (F, 3) containing the vertex indices of each face
+    Returns:
+        2-element tuple containing
+        - **L**: Sparse FloatTensor of shape (V,V) for the Laplacian matrix.
+           Here, L[i, j] = cot a_ij + cot b_ij iff (i, j) is an edge in meshes.
+           See the description above for more clarity.
+        - **inv_areas**: FloatTensor of shape (V,) containing the inverse of sum of
+           face areas containing each vertex
+    """
+    V, F = verts.shape[0], faces.shape[0]
+
+    face_verts = verts[faces]
+    v0, v1, v2 = face_verts[:, 0], face_verts[:, 1], face_verts[:, 2]
+
+    # Side lengths of each triangle, of shape (sum(F_n),)
+    # A is the side opposite v1, B is opposite v2, and C is opposite v3
+    A = (v1 - v2).norm(dim=1)
+    B = (v0 - v2).norm(dim=1)
+    C = (v0 - v1).norm(dim=1)
+
+    # Area of each triangle (with Heron's formula); shape is (sum(F_n),)
+    s = 0.5 * (A + B + C)
+    # note that the area can be negative (close to 0) causing nans after sqrt()
+    # we clip it to a small positive value
+    # pyre-fixme[16]: `float` has no attribute `clamp_`.
+    area = (s * (s - A) * (s - B) * (s - C)).clamp_(min=eps).sqrt()
+
+    # Compute cotangents of angles, of shape (sum(F_n), 3)
+    A2, B2, C2 = A * A, B * B, C * C
+    cota = (B2 + C2 - A2) / area
+    cotb = (A2 + C2 - B2) / area
+    cotc = (A2 + B2 - C2) / area
+    cot = torch.stack([cota, cotb, cotc], dim=1)
+    cot /= 4.0
+
+    # Construct a sparse matrix by basically doing:
+    # L[v1, v2] = cota
+    # L[v2, v0] = cotb
+    # L[v0, v1] = cotc
+    ii = faces[:, [1, 2, 0]]
+    jj = faces[:, [2, 0, 1]]
+    idx = torch.stack([ii, jj], dim=0).view(2, F * 3)
+    L = torch.sparse_coo_tensor(idx, cot.view(-1), (V, V), dtype=torch.float32)
+
+    # Make it symmetric; this means we are also setting
+    # L[v2, v1] = cota
+    # L[v0, v2] = cotb
+    # L[v1, v0] = cotc
+    L += L.t()
+
+    # For each vertex, compute the sum of areas for triangles containing it.
+    idx = faces.view(-1)
+    inv_areas = torch.zeros(V, dtype=torch.float32, device=verts.device)
+    val = torch.stack([area] * 3, dim=1).view(-1)
+    inv_areas.scatter_add_(0, idx, val)
+    idx = inv_areas > 0
+    # pyre-fixme[58]: `/` is not supported for operand types `float` and `Tensor`.
+    inv_areas[idx] = 1.0 / inv_areas[idx]
+    inv_areas = inv_areas.view(-1, 1)
+
+    return L, inv_areas
+
+
+def norm_laplacian(
+    verts: torch.Tensor, edges: torch.Tensor, eps: float = 1e-12
+) -> torch.Tensor:
+    """
+    Norm laplacian computes a variant of the laplacian matrix which weights each
+    affinity with the normalized distance of the neighboring nodes.
+    More concretely,
+    L[i, j] = 1. / wij where wij = ||vi - vj|| if (vi, vj) are neighboring nodes
+
+    Args:
+        verts: tensor of shape (V, 3) containing the vertices of the graph
+        edges: tensor of shape (E, 2) containing the vertex indices of each edge
+    Returns:
+        L: Sparse FloatTensor of shape (V, V)
+    """
+    edge_verts = verts[edges]  # (E, 2, 3)
+    v0, v1 = edge_verts[:, 0], edge_verts[:, 1]
+
+    # Side lengths of each edge, of shape (E,)
+    w01 = torch.reciprocal((v0 - v1).norm(dim=1) + eps)
+
+    # Construct a sparse matrix by basically doing:
+    # L[v0, v1] = w01
+    # L[v1, v0] = w01
+    e01 = edges.t()  # (2, E)
+
+    V = verts.shape[0]
+    L = torch.sparse_coo_tensor(e01, w01, (V, V), dtype=torch.float32)
+    L = L + L.t()
+
+    return L

project/ManiSkill3/src/maniskill2_benchmark/cfdp_experiment/cfdp/pytorch3d/pytorch3d/ops/mesh_face_areas_normals.py

@@ -0,0 +1,68 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the BSD-style license found in the
+# LICENSE file in the root directory of this source tree.
+
+# pyre-unsafe
+
+import torch
+from pytorch3d import _C
+from torch.autograd import Function
+from torch.autograd.function import once_differentiable
+
+
+class _MeshFaceAreasNormals(Function):
+    """
+    Torch autograd Function wrapper for face areas & normals C++/CUDA implementations.
+    """
+
+    @staticmethod
+    def forward(ctx, verts, faces):
+        """
+        Args:
+            ctx: Context object used to calculate gradients.
+            verts: FloatTensor of shape (V, 3), representing the packed
+                batch verts tensor.
+            faces: LongTensor of shape (F, 3), representing the packed
+                batch faces tensor
+        Returns:
+            areas: FloatTensor of shape (F,) with the areas of each face
+            normals: FloatTensor of shape (F,3) with the normals of each face
+        """
+        if not (verts.dim() == 2):
+            raise ValueError("verts need to be of shape Vx3.")
+        if not (verts.shape[1] == 3):
+            raise ValueError("verts need to be of shape Vx3.")
+        if not (faces.dim() == 2):
+            raise ValueError("faces need to be of shape Fx3.")
+        if not (faces.shape[1] == 3):
+            raise ValueError("faces need to be of shape Fx3.")
+        if not (faces.dtype == torch.int64):
+            raise ValueError("faces need to be of type torch.int64.")
+        # TODO(gkioxari) Change cast to floats once we add support for doubles.
+        if not (verts.dtype == torch.float32):
+            verts = verts.float()
+
+        ctx.save_for_backward(verts, faces)
+        areas, normals = _C.face_areas_normals_forward(verts, faces)
+        return areas, normals
+
+    @staticmethod
+    @once_differentiable
+    def backward(ctx, grad_areas, grad_normals):
+        grad_areas = grad_areas.contiguous()
+        grad_normals = grad_normals.contiguous()
+        verts, faces = ctx.saved_tensors
+        # TODO(gkioxari) Change cast to floats once we add support for doubles.
+        if not (grad_areas.dtype == torch.float32):
+            grad_areas = grad_areas.float()
+        if not (grad_normals.dtype == torch.float32):
+            grad_normals = grad_normals.float()
+        grad_verts = _C.face_areas_normals_backward(
+            grad_areas, grad_normals, verts, faces
+        )
+        return grad_verts, None
+
+
+mesh_face_areas_normals = _MeshFaceAreasNormals.apply