CPU ONLY build and minor doc changes

chrischoy · chrischoy · commit 0598858c3736 · 2019-12-25T02:19:15.000-08:00
Squashed commit of the following:

commit 26fb9f310e9a62e9775b7e6a2aabd424d0d8e521
Author: Chris Choy &lt;chrischoy@ai.stanford.edu&gt;
Date:   Wed Dec 25 02:12:18 2019 -0800

    manifest, CPU update

commit 1bc1456ccb0281486c0d08c2e5626bb4ee3047ff
Author: Chris Choy &lt;chrischoy@ai.stanford.edu&gt;
Date:   Wed Dec 25 00:13:47 2019 -0800

    CPU ONLY build

commit 0f8b07253c4a24683f9dcd0d67a03e926aa20a5d
Author: Chris Choy &lt;chrischoy@ai.stanford.edu&gt;
Date:   Tue Dec 24 23:37:03 2019 -0800

    minor update on training doc

commit 31766060189b49c2aeceb0584f579e8ae26afc5e
Author: Chris Choy &lt;chrischoy@ai.stanford.edu&gt;
Date:   Tue Dec 24 13:45:48 2019 -0800

    update sparse_quantize doc
diff --git a/CHANGELOG.md b/CHANGELOG.md
@@ -1,33 +1,39 @@
 # Change Log
 
 
-## [nightly] - 2019-12-24
+## [0.3.2] - 2019-12-25
 
+### Added
 - Synchronized Batch Norm: `ME.MinkowskiSyncBatchNorm`
     - `ME.MinkowskiSyncBatchNorm.convert_sync_batchnorm` converts a MinkowskiNetwork automatically to use synched batch norm.
 - `examples/multigpu.py` update for `ME.MinkowskiSynchBatchNorm`.
+- Add `MinkowskiUnion`
+- Add CoordsManager functions
+    - `get_batch_size`
+    - `get_batch_indices`
+    - `set_origin_coords_key`
+- Add `quantize_th`, `quantize_label_th`
+- Add MANIFEST
+
+### Changed
+
+- Update `MinkowskiUnion`, `MinkowskiPruning` docs
 - Update multigpu documentation
 - Update GIL release
+- Use cudaMalloc instead of `at::Tensor` for GPU memory management for illegal memory access, invalid arg.
 - Minor error fixes on `examples/modelnet40.py`
 - CoordsMap size initialization updates
-- Add `MinkowskiUnion`
-- Update `MinkowskiUnion`, `MinkowskiPruning` docs
-- Use cudaMalloc instead of `at::Tensor` for GPU memory management for illegal memory access, invalid arg.
 - Region hypercube iterator with even numbered kernel
 - Fix global reduction in-out map with non contiguous batch indices
 - GlobalPooling with torch reduction
-- Add CoordsManager functions
-    - `get_batch_size`
-    - `get_batch_indices`
-    - `set_origin_coords_key`
 - Update CoordsManager function `get_row_indices_per_batch` to return a list of `torch.LongTensor` for mapping indices. The corresponding batch indices is accessible by `get_batch_indices`.
 - Update `MinkowskiBroadcast`, `MinkowskiBroadcastConcatenation` to use row indices per batch (`getRowIndicesPerBatch`)
 - Update `SparseTensor`
     - `allow_duplicate_coords` argument support
     - update documentation, add unittest
-- Add `quantize_th`, `quantize_label_th`
 - Update the training demo and documentation.
 - Update `MinkowskiInstanceNorm`: no `dimension` argument.
+- Fix CPU only build
 
 
 ## [0.3.1] - 2019-12-15
diff --git a/MANIFEST.in b/MANIFEST.in
@@ -0,0 +1,3 @@
+Makefile
+recursive-include src *.hpp *.cpp *.cu *.cuh *.h
+recursive-include pybind *.hpp *.cpp
diff --git a/Makefile b/Makefile
@@ -4,7 +4,7 @@
 # Pretty build
 Q ?= @
 
-# Uncomment for CPU only build. Also uncomment the line 66 setup.py.
+# Uncomment for CPU only build. From the command line, `python setup.py install --cpu_only`
 # CPU_ONLY := 1
 
 CXX := g++
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__ = "0.3.1"
+__version__ = "0.3.2"
 
 import os
 import sys
diff --git a/MinkowskiEngine/utils/quantization.py b/MinkowskiEngine/utils/quantization.py
@@ -110,9 +110,12 @@ def sparse_quantize(coords,
         :attr:`labels` (:attr:`numpy.ndarray` or :attr:`torch.IntTensor`,
         optional): integer labels associated to eah coordinates.  Must have the
         same container as `coords` (i.e. if `coords` is a torch.Tensor,
-        `labels` must also be a torch.Tensor).
+        `labels` must also be a torch.Tensor). For classification where a set
+        of points are mapped to one label, do not feed the labels.
 
-        :attr:`ignore_label` (:attr:`int`, optional): the int value of the IGNORE LABEL..
+        :attr:`ignore_label` (:attr:`int`, optional): the int value of the
+        IGNORE LABEL.
+        :attr:`torch.nn.CrossEntropyLoss(ignore_index=ignore_label)`
 
         :attr:`return_index` (:attr:`bool`, optional): True if you want the indices of the
         quantized coordinates. False by default.
@@ -123,11 +126,19 @@ def sparse_quantize(coords,
 
      Example::
 
+        >>> # Segmentation
         >>> criterion = torch.nn.CrossEntropyLoss(ignore_index=-100)
         >>> coords, feats, labels = MinkowskiEngine.utils.sparse_quantize(
         >>>     coords, feats, labels, ignore_label=-100, quantization_size=0.1)
         >>> output = net(MinkowskiEngine.SparseTensor(feats, coords))
         >>> loss = criterion(output.F, labels.long())
+        >>>
+        >>> # Classification
+        >>> criterion = torch.nn.CrossEntropyLoss(ignore_index=-100)
+        >>> coords, feats = MinkowskiEngine.utils.sparse_quantize(coords, feats)
+        >>> output = net(MinkowskiEngine.SparseTensor(feats, coords))
+        >>> loss = criterion(output.F, labels.long())
+
 
     """
     assert isinstance(coords, np.ndarray) or isinstance(coords, torch.Tensor), \
diff --git a/docs/demo/training.rst b/docs/demo/training.rst
@@ -35,12 +35,16 @@ In this example, let's create a random dataset that generates a noisy line.
            # Drop some samples
            xs_data = self._sample_xs(self.num_data)
            ys_data = angle * xs_data + intercept + self._sample_noise(
-               xs_data, [0, 1])
+               self.num_data, [0, 0.1])
+
+           noise = 4 * (self.rng.rand(self.num_noise, 2) - 0.5)
 
            # Concatenate data
-           input = np.hstack([xs_data, ys_data])
-           feats = np.random.rand(self.num_data, 1)
-           labels = np.ones((self.num_data, 1)).astype(np.int32)
+           input = np.vstack([np.hstack([xs_data, ys_data]), noise])
+           feats = input
+           labels = np.vstack(
+               [np.ones((self.num_data, 1)),
+                np.zeros((self.num_noise, 1))]).astype(np.int32)
 
            ...
 
diff --git a/docs/quick_start.md b/docs/quick_start.md
@@ -38,6 +38,4 @@ room.
 
 ## CPU only compilation
 
-1. Uncomment line 8 of the Makefile to enable the flag, `CPU_ONLY`.
-2. Uncomment line 57 of the `setup.py` to enable the flag, `CPU_ONLY`.
-3. `python setup.py install`
+`python setup.py install --cpu_only`
diff --git a/setup.py b/setup.py
@@ -2,8 +2,9 @@
 import os
 import re
 import subprocess
+from sys import argv
 from setuptools import setup
-from torch.utils.cpp_extension import CUDAExtension, BuildExtension
+from torch.utils.cpp_extension import CppExtension, CUDAExtension, BuildExtension
 
 from distutils.sysconfig import get_python_inc
 
@@ -28,20 +29,39 @@ def run_command(*args):
     subprocess.call(args)
 
 
-run_command('make', 'clean')
-run_command('make', '-j%d' % min(os.cpu_count(), 12))
+# For cpu only build
+CPU_ONLY = '--cpu_only' in argv
+KEEP_OBJS = '--keep_objs' in argv
+
+Extension = CUDAExtension
+compile_args = ['make', '-j%d' % min(os.cpu_count(), 12)]
+extra_compile_args = ['-Wno-deprecated-declarations']
+# extra_compile_args+=['-g']  # Uncomment for debugging
+if CPU_ONLY:
+    argv.remove('--cpu_only')
+    compile_args += ['CPU_ONLY=1']
+    extra_compile_args += ['-DCPU_ONLY']
+    Extension = CppExtension
+
+if KEEP_OBJS:
+    argv.remove('--keep_objs')
+
+if not KEEP_OBJS:
+    run_command('make', 'clean')
+
+run_command(*compile_args)
 
 # Python interface
 setup(
     name='MinkowskiEngine',
     version=find_version('MinkowskiEngine', '__init__.py'),
-    install_requires=['torch'],
+    install_requires=['torch', 'numpy'],
     packages=[
         'MinkowskiEngine', 'MinkowskiEngine.utils', 'MinkowskiEngine.modules'
     ],
     package_dir={'MinkowskiEngine': './MinkowskiEngine'},
     ext_modules=[
-        CUDAExtension(
+        Extension(
             name='MinkowskiEngineBackend',
             include_dirs=['./', get_python_inc() + "/.."],
             sources=[
@@ -52,16 +72,19 @@ def run_command(*args):
                 'openblas',  # for other blas, replace openblas
             ],
             library_dirs=['objs'],
-            # extra_compile_args=['-g']  # Uncomment for debugging
-            extra_compile_args=['-Wno-deprecated-declarations'],
-            # extra_compile_args=['-DCPU_ONLY']  # Uncomment the following for CPU_ONLY build
+            extra_compile_args=extra_compile_args,
         )
     ],
     cmdclass={'build_ext': BuildExtension},
-    author='Christopher B. Choy',
+    author='Christopher Choy',
     author_email='chrischoy@ai.stanford.edu',
     description='Minkowski Engine, a Sparse Tensor Library for Neural Networks',
-    keywords='Minkowski Engine Sparse Tensor Library Convolutional Neural Networks',
+    long_description=read('README.md'),
+    long_description_content_type="text/markdown",
     url='https://github.com/StanfordVL/MinkowskiEngine',
+    keywords=[
+        'pytorch', 'Minkowski Engine', 'Sparse Tensor',
+        'Convolutional Neural Networks', '3D Vision', 'Deep Learning'
+    ],
     zip_safe=False,
-)
+    python_requires='>=3.6')

Original file line number	Diff line number	Diff line change
`@@ -0,0 +1,3 @@`
	`1`	`+Makefile`
	`2`	`+recursive-include src .hpp .cpp .cu .cuh *.h`
	`3`	`+recursive-include pybind .hpp .cpp`