AddLocations API

Introduce a setInputLocations (batch) API for sparse map construction.
0.1.0 => 0.1.1

.gitignore

@@ -6,4 +6,8 @@ t7/
 *.so
 build
 __pycache__
-pickle
+pickle
\ No newline at end of file
+*.pyc
+PyTorch/sparseconvnet.egg-info/
+PyTorch/sparseconvnet/SCN/__init__.py
+

PyTorch/setup.py

@@ -63,7 +63,7 @@ ffi.build()
 from setuptools import setup, find_packages
 setup(
     name='sparseconvnet',
-    version='0.1',
+    version='0.1.1',
     description='Submanifold (Spatially) Sparse Convolutional Networks https://arxiv.org/abs/1706.01307',
     author='Facebook AI Research',
     author_email='benjamingraham@fb.com',

PyTorch/sparseconvnet/SCN/generic/Geometry/Metadata.cpp

@@ -44,6 +44,48 @@ extern "C" void scn_D_(setInputSpatialLocation)(void **m,
                 THFloatTensor_data(vec), sizeof(float) * nPlanes);
   }
 }
+
+extern "C" void scn_D_(setInputSpatialLocations)(void **m,
+                                                THFloatTensor *features,
+                                                THLongTensor *locations,
+                                                THFloatTensor *vecs,
+                                                bool overwrite) {
+
+  assert(locations->size[0] == vecs->size[0] &&
+    "Location and vec length must be identical!");
+
+  SCN_INITIALIZE_AND_REFERENCE(Metadata<Dimension>, m)
+  auto &mp = _m.inputSG->mp;
+  auto &nActive = *_m.inputNActive;
+  auto nSamples = locations->size[0];
+  auto isMpEmpty = mp.empty();
+
+  if (isMpEmpty) {
+    auto nPlanes = vecs->size[1];
+
+    THFloatTensor_resize2d(features, nSamples, nPlanes);
+    std::memcpy(THFloatTensor_data(features),
+                THFloatTensor_data(vecs), sizeof(float) * nSamples * nPlanes);
+
+    mp.resize(nSamples);
+  }
+
+  for(unsigned int i = 0; i < nSamples; ++i) {
+    THLongTensor *location = THLongTensor_newSelect(locations, 0, i);
+    THFloatTensor *vec = THFloatTensor_newSelect(vecs, 0, i);
+
+    if (isMpEmpty) {
+      auto p = LongTensorToPoint<Dimension>(location);
+      mp.insert(std::make_pair(p, nActive++));
+    } else {
+      scn_D_(setInputSpatialLocation)(m, features, location, vec, overwrite);
+    }
+
+    THLongTensor_free(location);
+    THFloatTensor_free(vec);
+  }
+}
+
 extern "C" void
     scn_D_(createMetadataForDenseToSparse)(void **m, THLongTensor *spatialSize_,
                                            THLongTensor *pad_,

PyTorch/sparseconvnet/SCN/header_cpu.h

@@ -25,6 +25,9 @@ void scn_1_setInputSpatialSize(void **m, THLongTensor *spatialSize);
 void scn_1_setInputSpatialLocation(void **m, THFloatTensor *features,
                                    THLongTensor *location, THFloatTensor *vec,
                                    _Bool overwrite);
+void scn_1_setInputSpatialLocations(void **m, THFloatTensor *features,
+                                   THLongTensor *locations, THFloatTensor *vecs,
+                                   _Bool overwrite);
 double scn_2_addSampleFromThresholdedTensor(void **m, THFloatTensor *features_,
                                             THFloatTensor *tensor_,
                                             THLongTensor *offset_,
@@ -39,7 +42,10 @@ void scn_2_generateRuleBooks3s2(void **m);
 void scn_2_generateRuleBooks2s2(void **m);
 void scn_2_setInputSpatialSize(void **m, THLongTensor *spatialSize);
 void scn_2_setInputSpatialLocation(void **m, THFloatTensor *features,
-                                   THLongTensor *location, THFloatTensor *vec,
+                                   THLongTensor* location, THFloatTensor *vec,
+                                   _Bool overwrite);
+void scn_2_setInputSpatialLocations(void **m, THFloatTensor *features,
+                                   THLongTensor *locations, THFloatTensor *vecs,
                                    _Bool overwrite);
 double scn_3_addSampleFromThresholdedTensor(void **m, THFloatTensor *features_,
                                             THFloatTensor *tensor_,
@@ -57,6 +63,9 @@ void scn_3_setInputSpatialSize(void **m, THLongTensor *spatialSize);
 void scn_3_setInputSpatialLocation(void **m, THFloatTensor *features,
                                    THLongTensor *location, THFloatTensor *vec,
                                    _Bool overwrite);
+void scn_3_setInputSpatialLocations(void **m, THFloatTensor *features,
+                                   THLongTensor *locations, THFloatTensor *vecs,
+                                   _Bool overwrite);
 double scn_4_addSampleFromThresholdedTensor(void **m, THFloatTensor *features_,
                                             THFloatTensor *tensor_,
                                             THLongTensor *offset_,
@@ -73,6 +82,9 @@ void scn_4_setInputSpatialSize(void **m, THLongTensor *spatialSize);
 void scn_4_setInputSpatialLocation(void **m, THFloatTensor *features,
                                    THLongTensor *location, THFloatTensor *vec,
                                    _Bool overwrite);
+void scn_4_setInputSpatialLocations(void **m, THFloatTensor *features,
+                                   THLongTensor *locations, THFloatTensor *vecs,
+                                   _Bool overwrite);
 double scn_5_addSampleFromThresholdedTensor(void **m, THFloatTensor *features_,
                                             THFloatTensor *tensor_,
                                             THLongTensor *offset_,
@@ -89,6 +101,9 @@ void scn_5_setInputSpatialSize(void **m, THLongTensor *spatialSize);
 void scn_5_setInputSpatialLocation(void **m, THFloatTensor *features,
                                    THLongTensor *location, THFloatTensor *vec,
                                    _Bool overwrite);
+void scn_5_setInputSpatialLocations(void **m, THFloatTensor *features,
+                                   THLongTensor *locations, THFloatTensor *vecs,
+                                   _Bool overwrite);
 double scn_6_addSampleFromThresholdedTensor(void **m, THFloatTensor *features_,
                                             THFloatTensor *tensor_,
                                             THLongTensor *offset_,
@@ -105,6 +120,9 @@ void scn_6_setInputSpatialSize(void **m, THLongTensor *spatialSize);
 void scn_6_setInputSpatialLocation(void **m, THFloatTensor *features,
                                    THLongTensor *location, THFloatTensor *vec,
                                    _Bool overwrite);
+void scn_6_setInputSpatialLocations(void **m, THFloatTensor *features,
+                                   THLongTensor *locations, THFloatTensor *vecs,
+                                   _Bool overwrite);
 double scn_7_addSampleFromThresholdedTensor(void **m, THFloatTensor *features_,
                                             THFloatTensor *tensor_,
                                             THLongTensor *offset_,
@@ -121,6 +139,9 @@ void scn_7_setInputSpatialSize(void **m, THLongTensor *spatialSize);
 void scn_7_setInputSpatialLocation(void **m, THFloatTensor *features,
                                    THLongTensor *location, THFloatTensor *vec,
                                    _Bool overwrite);
+void scn_7_setInputSpatialLocations(void **m, THFloatTensor *features,
+                                   THLongTensor *locations, THFloatTensor *vecs,
+                                   _Bool overwrite);
 double scn_8_addSampleFromThresholdedTensor(void **m, THFloatTensor *features_,
                                             THFloatTensor *tensor_,
                                             THLongTensor *offset_,
@@ -136,6 +157,9 @@ void scn_8_generateRuleBooks2s2(void **m);
 void scn_8_setInputSpatialSize(void **m, THLongTensor *spatialSize);
 void scn_8_setInputSpatialLocation(void **m, THFloatTensor *features,
                                    THLongTensor *location, THFloatTensor *vec,
+                                  _Bool overwrite);
+void scn_8_setInputSpatialLocations(void **m, THFloatTensor *features,
+                                   THLongTensor *locations, THFloatTensor *vecs,
                                    _Bool overwrite);
 double scn_9_addSampleFromThresholdedTensor(void **m, THFloatTensor *features_,
                                             THFloatTensor *tensor_,
@@ -153,6 +177,9 @@ void scn_9_setInputSpatialSize(void **m, THLongTensor *spatialSize);
 void scn_9_setInputSpatialLocation(void **m, THFloatTensor *features,
                                    THLongTensor *location, THFloatTensor *vec,
                                    _Bool overwrite);
+void scn_9_setInputSpatialLocations(void **m, THFloatTensor *features,
+                                   THLongTensor *locations, THFloatTensor *vecs,
+                                   _Bool overwrite);
 double scn_10_addSampleFromThresholdedTensor(void **m, THFloatTensor *features_,
                                              THFloatTensor *tensor_,
                                              THLongTensor *offset_,
@@ -169,6 +196,9 @@ void scn_10_setInputSpatialSize(void **m, THLongTensor *spatialSize);
 void scn_10_setInputSpatialLocation(void **m, THFloatTensor *features,
                                     THLongTensor *location, THFloatTensor *vec,
                                     _Bool overwrite);
+void scn_10_setInputSpatialLocations(void **m, THFloatTensor *features,
+                                   THLongTensor *locations, THFloatTensor *vecs,
+                                   _Bool overwrite);
 void scn_cpu_float_AffineReluTrivialConvolution_updateOutput(
     THFloatTensor *input_features, THFloatTensor *output_features,
     THFloatTensor *affineWeight, THFloatTensor *affineBias,

PyTorch/sparseconvnet/legacy/inputBatch.py

@@ -9,7 +9,6 @@ from .metadata import Metadata
 from ..utils import toLongTensor, dim_fn
 from .sparseConvNetTensor import SparseConvNetTensor
 
-
 class InputBatch(SparseConvNetTensor):
     def __init__(self, dimension, spatial_size):
         self.dimension = dimension
@@ -33,6 +32,16 @@ class InputBatch(SparseConvNetTensor):
         dim_fn(self.dimension, 'setInputSpatialLocation')(
             self.metadata.ffi, self.features, location, vector, overwrite)
 
+    def setLocations(self, locations, vectors, overwrite=False):
+        assert locations.min() >= 0 and (self.spatial_size.expand_as(locations) - locations).min() > 0
+
+        dim_fn(self.dimension, 'setInputSpatialLocations')(
+            self.metadata.ffi, self.features, locations, vectors, overwrite)
+
+    def setLocations_(self, locations, vector, overwrite=False):
+        dim_fn(self.dimension, 'setInputSpatialLocations')(
+            self.metadata.ffi, self.features, locations, vectors, overwrite)
+
     def addSampleFromTensor(self, tensor, offset, threshold=0):
         self.nActive = dim_fn(
             self.dimension,

README.md

@@ -203,7 +203,7 @@ git clone git@github.com:facebookresearch/SparseConvNet.git
 then
 
 cd SparseConvNet/Torch/
-luarocks make sparseconvnet-0.1-0.rockspec
+luarocks make sparseconvnet-0.1-1.rockspec
 
 and/or
 

Torch/C.lua

@@ -49,6 +49,9 @@ return function (sparseconvnet)
   void scn_DIMENSION_setInputSpatialLocation(void **m,
     THFloatTensor *features, THLongTensor *location, THFloatTensor *vec,
     bool overwrite);
+  void scn_DIMENSION_setInputSpatialLocations(void **m,
+    THFloatTensor *features, THLongTensor *locations, THFloatTensor *vecs,
+    bool overwrite);
   ]]
 
   for DIMENSION = 1,10 do

Torch/InputBatch.lua

@@ -40,6 +40,18 @@ return function(sparseconvnet)
     C.dimensionFn(self.dimension,'setInputSpatialLocation')(self.metadata.ffi,
       self.features:cdata(), location:cdata(), vector:cdata(), overwrite)
   end
+  function InputBatch:setLocations(locations, vectors, overwrite)
+    --[[locations is a n_locations x self.dimensional length set of coordinates:
+    torch.LongStorage or a 2-D table]]
+    if type(locations)=='table' then
+      locations = torch.LongStorage(locations)
+    end
+
+    assert(locations:min()>=0 and (self.spatialSize:view(1, self.dimension):expandAs(locations)-locations):min()>0)
+
+    C.dimensionFn(self.dimension,'setInputSpatialLocations')(self.metadata.ffi,
+      self.features:cdata(), locations:cdata(), vectors:cdata(), overwrite)
+  end
   function InputBatch:precomputeMetadata(stride)
     if stride==2 then
       C.dimensionFn(self.dimension,'generateRuleBooks2s2')(self.metadata.ffi)

Torch/sparseconvnet-0.1-0.rockspec → Torch/sparseconvnet-0.1-1.rockspec

@@ -5,7 +5,7 @@
 -- LICENSE file in the root directory of this source tree.
 
 package = "sparseconvnet"
-version = "0.1-0"
+version = "0.1-1"
 
 source = {
   url = "",

examples/hello-world.lua

@@ -45,16 +45,24 @@ msg={
 }
 
 input:addSample()
+
+local locations = {}
+local featureVectors = {}
+
 for y,line in ipairs(msg) do
   for x = 1,string.len(line) do
     if string.sub(line,x,x) == 'O' then
-      local location = torch.LongTensor{x,y}
-      local featureVector = torch.FloatTensor{1}
-      input:setLocation(location,featureVector,0)
+      table.insert(locations, {x,y})
+      table.insert(featureVectors, {1})
     end
   end
 end
 
+input:setLocations(
+  torch.LongTensor(locations),
+  torch.FloatTensor(featureVectors),
+  0)
+
 --[[
 Optional: allow metadata preprocessing to be done in batch preparation threads
 to improve GPU utilization.

examples/hello-world.py

@@ -35,12 +35,20 @@ msg = [
     " X   X  X    X    X   X  X     X X X X   X  X  X  X  X    X  X  ",
     " X   X  XXX  XXX  XXX  XX       X   X     XX   X  X  XXX  XXX   "]
 input.addSample()
+
+locations = []
+features = []
+
 for y, line in enumerate(msg):
     for x, c in enumerate(line):
         if c == 'X':
-            location = torch.LongTensor([x, y])
-            featureVector = torch.FloatTensor([1])
-            input.setLocation(location, featureVector, 0)
+            locations.append([x,y])
+            features.append([1])
+
+locations = torch.LongTensor(locations)
+features = torch.FloatTensor(features)
+
+input.setLocations(locations, features, 0)
 
 # Optional: allow metadata preprocessing to be done in batch preparation threads
 # to improve GPU utilization.