v0.4.2

Squashed commit of the following: commit 48044e6c46a23337c7f64fd9b1c3075433ceb5b4 Author: Chris Choy <chrischoy@ai.stanford.edu> Date: Fri Mar 13 20:52:57 2020 -0700 minor updates commit 0084e80c00df63f12561cd63c4503dd5bf413d10 Author: Chris Choy <chrischoy@ai.stanford.edu> Date: Fri Mar 13 17:30:02 2020 -0700 minor doc updates
NVIDIA · Mar 14, 2020 · d212be8 · d212be8
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diff --git a/CHANGELOG.md b/CHANGELOG.md
@@ -1,26 +1,27 @@
 # Change Log
 
-## [master] - 2020-03-05
+## [0.4.2] - 2020-03-13
 
 ### Added
 
+- Completion and VAE examples
 - GPU version of getKernelMap: getKernelMapGPU
 
-
 ### Changed
 
 - Fix dtype double to float on the multi-gpu example
 - Remove the dimension input argument on GlobalPooling, Broadcast functions
 - Kernel map generation has tensor stride > 0 check
 - Fix `SparseTensor.set_tensor_stride`
 - Track whether the batch indices are set first when initializing coords, The initial batch indices will be used throughout the lifetime of a sparse tensor
-- Add warning on ModelNet40 training (Issue #86)
+- Add a memory warning on ModelNet40 training example (Issue #86)
 - Update the readme, definition
 - Fix an error in examples.convolution
 - Changed `features_at`, `coordinates_at` to take a batch index not the index of the unique batch indices. (Issue #100)
 - Fix an error torch.range --> torch.arange in `sparse_quantize` (Issue #101)
 - Fix BLAS installation link error (Issue #94)
 - Fix `MinkowskiBroadcast` and `MinkowskiBroadcastConcatenation` to use arbitrary channel sizes
+- Fix `pointnet.py` example (Issue #103)
 
 
 ## [0.4.1] - 2020-01-28

diff --git a/MinkowskiEngine/MinkowskiNormalization.py b/MinkowskiEngine/MinkowskiNormalization.py
@@ -225,8 +225,7 @@ def backward(ctx, out_grad):
         cpp_coords_manager = coords_manager.CPPCoordsManager
 
         # 1/N \sum dout
-        mean_dout, num_nonzero = gpool_forward(out_grad,
-                                               cpp_in_coords_key,
+        mean_dout, num_nonzero = gpool_forward(out_grad, cpp_in_coords_key,
                                                cpp_glob_coords_key,
                                                cpp_coords_manager, True,
                                                ctx.mode.value)
@@ -257,7 +256,7 @@ def backward(ctx, out_grad):
 
 class MinkowskiStableInstanceNorm(Module):
 
-    def __init__(self, num_features, dimension=-1):
+    def __init__(self, num_features):
         Module.__init__(self)
         self.num_features = num_features
         self.eps = 1e-6
@@ -269,11 +268,10 @@ def __init__(self, num_features, dimension=-1):
         self.glob_sum2 = MinkowskiBroadcastAddition()
         self.glob_mean = MinkowskiGlobalPooling()
         self.glob_times = MinkowskiBroadcastMultiplication()
-        self.dimension = dimension
         self.reset_parameters()
 
     def __repr__(self):
-        s = f'(nchannels={self.num_features}, D={self.dimension})'
+        s = f'(nchannels={self.num_features})'
         return self.__class__.__name__ + s
 
     def reset_parameters(self):
@@ -313,8 +311,7 @@ def __init__(self, num_features, mode=GlobalPoolingMode.AUTO):
 
             num_features (int): the dimension of the input feautres.
 
-            dimension (int): the spatial dimension of the input tensor.
-
+            mode (GlobalPoolingModel, optional): The internal global pooling computation mode.
         """
         Module.__init__(self)
         self.num_features = num_features

diff --git a/MinkowskiEngine/__init__.py b/MinkowskiEngine/__init__.py
@@ -21,7 +21,7 @@
 # Please cite "4D Spatio-Temporal ConvNets: Minkowski Convolutional Neural
 # Networks", CVPR'19 (https://arxiv.org/abs/1904.08755) if you use any part
 # of the code.
-__version__ = "0.4.1"
+__version__ = "0.4.2"
 
 import os
 import sys

diff --git a/README.md b/README.md
@@ -3,7 +3,7 @@
 
 # Minkowski Engine
 
-[![PyPI Version][pypi-image]][pypi-url][![Join the chat at https://gitter.im/MinkowskiEngineGitter/general](https://badges.gitter.im/Join%20Chat.svg)](https://gitter.im/MinkowskiEngineGitter/general)
+[![PyPI Version][pypi-image]][pypi-url] [![Join the chat at https://gitter.im/MinkowskiEngineGitter/general](https://badges.gitter.im/Join%20Chat.svg)](https://gitter.im/MinkowskiEngineGitter/general)
 
 The Minkowski Engine is an auto-differentiation library for sparse tensors. It supports all standard neural network layers such as convolution, pooling, unpooling, and broadcasting operations for sparse tensors. For more information, please visit [the documentation page](http://stanfordvl.github.io/MinkowskiEngine/overview.html).
 

diff --git a/docs/.gitignore b/docs/.gitignore
@@ -1,4 +1,3 @@
 source
 _build
 _static
-_template
diff --git a/docs/conf.py b/docs/conf.py
@@ -1,5 +1,7 @@
 import os
 import sys
+# import pkg_resources
+# pkg_resources.require('MinkowskiEngine==0.4.2a1')
 import MinkowskiEngine as ME
 
 from recommonmark.parser import CommonMarkParser
@@ -18,9 +20,9 @@
 # add these directories to sys.path here. If the directory is relative to the
 # documentation root, use os.path.abspath to make it absolute, like shown here.
 #
-sys.path.insert(0, os.path.abspath('../'))
+# sys.path.insert(0, os.path.abspath('../'))
 sys.path.insert(0, os.path.abspath('../../'))
-autodoc_mock_imports = ['MinkowskiEngine.examples']
+# autodoc_mock_imports = ['MinkowskiEngine.examples']
 
 
 # -- Project information -----------------------------------------------------
@@ -75,7 +77,7 @@
 # List of patterns, relative to source directory, that match files and
 # directories to ignore when looking for source files.
 # This pattern also affects html_static_path and html_extra_path.
-exclude_patterns = ['_build', 'Thumbs.db', '.DS_Store']
+exclude_patterns = ['_build', 'README.md', 'Thumbs.db', '.DS_Store']
 
 # The name of the Pygments (syntax highlighting) style to use.
 pygments_style = None

diff --git a/docs/overview.md b/docs/overview.md
@@ -3,7 +3,7 @@
 
 # Minkowski Engine
 
-[![PyPI Version][pypi-image]][pypi-url][![Join the chat at https://gitter.im/MinkowskiEngineGitter/general](https://badges.gitter.im/Join%20Chat.svg)](https://gitter.im/MinkowskiEngineGitter/general)
+[![PyPI Version][pypi-image]][pypi-url] [![Join the chat at https://gitter.im/MinkowskiEngineGitter/general](https://badges.gitter.im/Join%20Chat.svg)](https://gitter.im/MinkowskiEngineGitter/general)
 
 The Minkowski Engine is an auto-differentiation library for sparse tensors. It supports all standard neural network layers such as convolution, pooling, unpooling, and broadcasting operations for sparse tensors. For more information, please visit [the documentation page](http://stanfordvl.github.io/MinkowskiEngine/overview.html).
 

diff --git a/docs/sparse_tensor_network.rst b/docs/sparse_tensor_network.rst
@@ -38,10 +38,16 @@ We use the generalized convolution not only on the 3D
 spatial axes, but on any arbitrary dimensions, or also on the temporal axis, which is proven to be more
 effective than recurrent neural networks (RNN) in some applications.
 
-Specifically, we the generalize convolution for generic input and
-output coordinates, and for arbitrary kernel shapes. The generalized convolution
+Specifically, we generalize convolution for generic input and output coordinates, and for arbitrary kernel shapes. It allows extending a sparse tensor network to extremely high-dimensional spaces and dynamically generate coordinates for generative tasks.
+Also, the generalized convolution
 encompasses not only all sparse convolutions but also the
-conventional dense convolutions. Let :math:`x^{\text{in}}_\mathbf{u} \in
+conventional dense convolutions. We list some of characteristics and applications of generalized convolution below.
+
+- Sparse tensors for convolution kernels allow high-dimensional convolutions with specialized kernels `[3] <https://arxiv.org/abs/1904.08755>`_
+- Arbitrary input coordinates generalized convolution encompasses all discrete convolutions
+- Arbitrary output coordinates allows dynamic coordinate generation and generative networks `[reconstruction and completion networks] <https://github.com/StanfordVL/MinkowskiEngine#example-networks>`_
+
+Let :math:`x^{\text{in}}_\mathbf{u} \in
 \mathbb{R}^{N^\text{in}}` be an :math:`N^\text{in}`-dimensional input feature
 vector in a :math:`D`-dimensional space at :math:`\mathbf{u} \in \mathbb{R}^D`
 (a D-dimensional coordinate), and convolution kernel weights be

diff --git a/setup.py b/setup.py
@@ -103,7 +103,8 @@ def run_command(*args):
         raise ImportError(' \
 \nBLAS not found from numpy.distutils.system_info.get_info. \
 \nPlease specify BLAS with: python setup.py install --blas=openblas" \
-\nfor more information, please visit https://github.com/StanfordVL/MinkowskiEngine/wiki/Installation')
+\nfor more information, please visit https://github.com/StanfordVL/MinkowskiEngine/wiki/Installation'
+                         )
 
 print(f'\nUsing BLAS={BLAS}')
 
@@ -151,4 +152,24 @@ def run_command(*args):
         'Convolutional Neural Networks', '3D Vision', 'Deep Learning'
     ],
     zip_safe=False,
+    classifiers=[
+        # https://pypi.org/classifiers/
+        'Environment :: Console',
+        'Development Status :: 3 - Alpha',
+        'Intended Audience :: Developers',
+        'Intended Audience :: Other Audience',
+        'Intended Audience :: Science/Research',
+        'License :: OSI Approved :: MIT License',
+        'Natural Language :: English',
+        'Programming Language :: C++',
+        'Programming Language :: Python :: 3.6',
+        'Programming Language :: Python :: 3.7',
+        'Programming Language :: Python :: 3.8',
+        'Topic :: Multimedia :: Graphics',
+        'Topic :: Scientific/Engineering',
+        'Topic :: Scientific/Engineering :: Artificial Intelligence',
+        'Topic :: Scientific/Engineering :: Mathematics',
+        'Topic :: Scientific/Engineering :: Physics',
+        'Topic :: Scientific/Engineering :: Visualization',
+    ],
     python_requires='>=3.6')