Merge branch 'master_community' into log_boosting_fn

Author: breznak

API_CHANGELOG.md

@@ -105,6 +105,9 @@ This is obsolete. Use getRegion('name') instead.
 
     We also renamed the namespaces from `namespace nupic` to `namespace htm`.
 
+* SpatialPooler: removed param `numActiveColumnsPerInhArea`, as replaced by `localAreaDensity` which has better properties
+  (constant sparsity). PR #TODO
+
 
 ## Python API Changes
 

CHANGELOG.md

@@ -1,7 +1,10 @@
 # Changelog
 
-This file is no longer being updated.
-Instead see the [API_CHANGELOG](API_CHANGELOG.md).
+Also see [API_CHANGELOG](API_CHANGELOG.md).
+
+## 2.0.0
+* changed repository name from nupic.core to htm.core
+* Added support for Visual Studio 2019
 
 ## 1.1.0
 

CONTRIBUTING.md

@@ -7,7 +7,7 @@ The easiest way to contribute is to simply use this library and if you encounter
 
 ### Develop Nupic!
 If you'd like to develop this library itself, we have put together a list of tasks which don't require extensive knowledge of this library but nonetheless are important and need help.  Look for issues with the tag "newbie" which are a good starting point:
- * https://github.com/htm-community/nupic.cpp/labels/newbie
+ * https://github.com/htm-community/htm.core/labels/newbie
 
 ### Discuss Nupic!
 We are open to new ideas and would be happy to discuss them.  To start the conversation, open an issue and we can talk about it.

CommonCompilerConfig.cmake

@@ -154,7 +154,7 @@ set(COMMON_OS_LIBS)
 
 if(MSVC)
 	# MS Visual C
-	# on Windows using Visual Studio 2015, 2017   https://docs.microsoft.com/en-us/cpp/build/reference/compiler-options-listed-by-category
+	# on Windows using Visual Studio 2015, 2017, 2019   https://docs.microsoft.com/en-us/cpp/build/reference/compiler-options-listed-by-category
 	#  /permissive- forces standards behavior.  See https://docs.microsoft.com/en-us/cpp/build/reference/permissive-standards-conformance?view=vs-2017
 	#  /Zc:__cplusplus   This is required to force MSVC to pay attention to the standard setting and sets __cplusplus.
 	#                    NOTE: MSVC does not support C++11.  But does support C++14 and C++17.
@@ -239,13 +239,22 @@ else()
 
 	#
 	# Set linker (ld)
-	# use ld.gold if available
+	# These linkers are tried for faster linking performance
+	# use ld.gold, or lld if available
 	#
-	execute_process(COMMAND ld.gold --version RESULT_VARIABLE EXIT_CODE)
-	if(EXIT_CODE EQUAL 0)
+	execute_process(COMMAND ld.gold --version RESULT_VARIABLE EXIT_CODE_GOLD)
+	if(EXIT_CODE_GOLD EQUAL 0)
 	  message("Using ld.gold as LINKER.")
 	  set(CMAKE_LINKER "ld.gold")
+	  set(optimization_flags_cc ${optimization_flags_cc} -fuse-ld=gold)
 	endif()
+	execute_process(COMMAND ld.lld --version RESULT_VARIABLE EXIT_CODE_LLD)
+	execute_process(COMMAND ld.lld-9 --version RESULT_VARIABLE EXIT_CODE_LLD9)
+        if(EXIT_CODE_LLD EQUAL 0 OR EXIT_CODE_LLD9 EQUAL 0)
+          message("Using ld.lld as LINKER.")
+          set(CMAKE_LINKER "ld.lld")
+          set(optimization_flags_cc ${optimization_flags_cc} -fuse-ld=lld)
+        endif()
 
 
 	#
@@ -344,11 +353,10 @@ else()
                 set(optimization_flags_cc ${optimization_flags_cc} -march=native)
         endif()
         if(${CMAKE_CXX_COMPILER_ID} STREQUAL "GNU" AND NOT MINGW)
-                set(optimization_flags_cc ${optimization_flags_cc} -fuse-ld=gold)
                 # NOTE -flto must go together in both cc and ld flags; also, it's presently incompatible
                 # with the -g option in at least some GNU compilers (saw in `man gcc` on Ubuntu)
-                set(optimization_flags_cc ${optimization_flags_cc} -fuse-linker-plugin -flto-report -flto) #TODO fix LTO for clang
-                set(optimization_flags_lt ${optimization_flags_lt} -flto) #TODO LTO for clang too
+                set(optimization_flags_cc ${optimization_flags_cc} -fuse-linker-plugin -flto-report -flto -fno-fat-lto-objects) #TODO fix LTO for clang
+                set(optimization_flags_lt ${optimization_flags_lt} -flto -fno-fat-lto-objects) #TODO LTO for clang too
         endif()
 
 

README.md

@@ -1,16 +1,16 @@
 <img src="http://numenta.org/87b23beb8a4b7dea7d88099bfb28d182.svg" alt="NuPIC Logo" width=100/>
 
-# Community NuPIC.cpp repository (formerly [nupic.core](http://github.com/numenta/nupic.core))
+# htm.core
 
 [![Linux/OSX Build Status](https://travis-ci.org/htm-community/htm.core.svg?branch=master)](https://travis-ci.org/htm-community/htm.core)
 [![OSX CircleCI](https://circleci.com/gh/htm-community/htm.core/tree/master.svg?style=svg)](https://circleci.com/gh/htm-community/htm.core/tree/master)
 [![Windows Build status](https://ci.appveyor.com/api/projects/status/59f87and1x0ugss9/branch/master?svg=true)](https://ci.appveyor.com/project/htm-community/nupic-cpp/branch/master)
 
-This fork is a community version of the [nupic.core](https://github.com/numenta/nupic.core) C++ repository with Python bindings.
+This is a Community Fork of the [nupic.core](https://github.com/numenta/nupic.core) C++ repository, with Python bindings.
 
 ## Project Goals
 
-- Actively developed C++ core library for nupic.core (Numenta's repos are in maintenance mode only)
+- Actively developed C++ core library (Numenta's NuPIC repos are in maintenance mode only)
 - Clean, lean, optimized, and modern codebase
 - Stable and well tested code
 - Open and easier involvement of new ideas across HTM community (it's fun to contribute, we make master run stable, but are more open to experiments and larger revamps of the code if it proves useful).
@@ -42,11 +42,11 @@ in C++ library.
 
 ## Building from Source
 
-Fork or download the HTM-Community Nupic.cpp repository from https://github.com/htm-community/nupic.cpp
+Fork or download the HTM-Community htm.core repository from https://github.com/htm-community/htm.core
 
 ## Prerequisites
 
-- [CMake](http://www.cmake.org/)
+- [CMake](http://www.cmake.org/)  Version 3.8  (3.14 for Visual Studio 2019)
 - [Python](https://python.org/downloads/)
     - Version 3.4+
     - Version 2.7
@@ -125,10 +125,11 @@ make -j install
 
  * This will not build the Python interface.
 
-## Simple Build On Windows (MS Visual Studio 2017)
+## Simple Build On Windows (MS Visual Studio 2017 or 2019)
 
 After downloading the repository, do the following:
 
+ * NOTE: Visual Studio 2019 requires CMake version 3.14 or higher.
  * CD to the top of repository.
  * Double click on startupMSVC.bat
     - This will setup the build, create the solution file (build/scripts/htm.cpp.sln), and start MS Visual Studio.
@@ -161,12 +162,12 @@ docker build --build-arg arch=arm64 .
 
 ### Linux auto build @ TravisCI
 
- * [Build](https://travis-ci.org/htm-community/nupic.cpp)
+ * [Build](https://travis-ci.org/htm-community/htm.core)
  * [Config](./.travis.yml)
 
 ### Mac OS/X auto build @ CircleCI
 
- * [Build](https://circleci.com/gh/htm-community/nupic.cpp/tree/master)
+ * [Build](https://circleci.com/gh/htm-community/htm.core/tree/master)
  * [Config](./.circleci/config.yml)
  * Local Test Build: `circleci local execute --job build-and-test`
 
@@ -179,7 +180,7 @@ docker build --build-arg arch=arm64 .
 
 This uses Docker and QEMU to achieve an ARM64 build on CircleCI's x86 hardware.
 
- * **TODO!** [Build]()
+ * [Build](https://circleci.com/gh/htm-community/htm.core/tree/master)
  * [Config](./.circleci/config.yml)
  * Local Test Build: `circleci local execute --job arm64-build-test`
 

RELEASE.md

@@ -1,14 +1,5 @@
 # Release Process
 
-1. Select a green build in Bamboo that has the changes that you want to release
-2. Ensure that this build has the correct version in the VERSION file
-3. Create a Bamboo release with version matching the VERSION file in the repo
-4. Deploy the release in Bamboo. This will:
-    - Validate that the Bamboo release number matches the wheel versions.
-    - Push the wheels to PyPI
-    - Push the source archive to S3
-    - Create a Github release
-    - Tag the repo commit with the version
-    - Bump the VERSION file to the next bugfix release number
+Not doing releases yet.  
 
 :-) 

VERSION

@@ -1 +1 @@
-1.0.8.community0
+2.0.0

bindings/py/cpp_src/bindings/algorithms/py_Connections.cpp

@@ -143,6 +143,8 @@ R"(Returns pair of:
 
     py_Connections.def("raisePermanencesToThreshold", &Connections::raisePermanencesToThreshold);
 
+    py_Connections.def("synapseCompetition", &Connections::synapseCompetition);
+
     py_Connections.def("bumpSegment", &Connections::bumpSegment);
 
     py_Connections.def("destroyMinPermanenceSynapses", &Connections::destroyMinPermanenceSynapses);

bindings/py/cpp_src/bindings/algorithms/py_SpatialPooler.cpp

@@ -50,7 +50,6 @@ using namespace htm;
             , Real
             , bool
             , Real
-            , Int
             , UInt
             , Real
             , Real
@@ -112,22 +111,6 @@ Argument localAreaDensity The desired density of active columns within
         most N columns remain ON within a local inhibition area, where
         N = localAreaDensity * (total number of columns in inhibition
         area). 
-    If localAreaDensity is set to any value less than  0, 
-    output sparsity will be determined by the numActivePerInhArea.
-
-Argument numActiveColumnsPerInhArea An alternate way to control the sparsity of
-        active columns. When numActivePerInhArea > 0, the inhibition logic will insure that
-        at most 'numActivePerInhArea' columns remain ON within a local
-        inhibition area (the size of which is set by the internally
-        calculated inhibitionRadius). When using this method, as columns
-        learn and grow their effective receptive fields, the
-        inhibitionRadius will grow, and hence the net density of the
-        active columns will *decrease*. This is in contrast to the
-        localAreaDensity method, which keeps the density of active
-        columns the same regardless of the size of their receptive
-        fields.
-    If numActivePerInhArea is specified then 
-    localAreaDensity must be < 0, and vice versa.
 
 Argument stimulusThreshold This is a number specifying the minimum
         number of synapses that must be active in order for a column to
@@ -188,7 +171,6 @@ Argument wrapAround boolean value that determines whether or not inputs
             , py::arg("potentialPct") = 0.5
             , py::arg("globalInhibition") = false
             , py::arg("localAreaDensity") = 0.02f
-            , py::arg("numActiveColumnsPerInhArea") = -1
             , py::arg("stimulusThreshold") = 0
             , py::arg("synPermInactiveDec") = 0.01
             , py::arg("synPermActiveInc") = 0.1
@@ -212,8 +194,6 @@ Argument wrapAround boolean value that determines whether or not inputs
         py_SpatialPooler.def("getGlobalInhibition", &SpatialPooler::getGlobalInhibition);
         py_SpatialPooler.def("setGlobalInhibition", &SpatialPooler::setGlobalInhibition);
 
-        py_SpatialPooler.def("getNumActiveColumnsPerInhArea", &SpatialPooler::getNumActiveColumnsPerInhArea);
-        py_SpatialPooler.def("setNumActiveColumnsPerInhArea", &SpatialPooler::setNumActiveColumnsPerInhArea);
         py_SpatialPooler.def("getLocalAreaDensity", &SpatialPooler::getLocalAreaDensity);
         py_SpatialPooler.def("setLocalAreaDensity", &SpatialPooler::setLocalAreaDensity);
         py_SpatialPooler.def("getStimulusThreshold", &SpatialPooler::getStimulusThreshold);

docs/synapse_competition.docx

@@ -21,7 +21,7 @@
  'sdrc_alpha': 0.1,
  'sp': {'boostStrength': 3.0,
         'columnCount': 1638,
-        'numActiveColumnsPerInhArea': 72,
+        'localAreaDensity': 0.04395604395604396,
         'potentialPct': 0.85,
         'synPermActiveInc': 0.04,
         'synPermConnected': 0.13999999999999999,
@@ -63,8 +63,7 @@ def main(parameters=default_parameters, argv=None, verbose=True):
     potentialPct               = spParams["potentialPct"],
     potentialRadius            = encodingWidth,
     globalInhibition           = True,
-    localAreaDensity           = -1,
-    numActiveColumnsPerInhArea = spParams["numActiveColumnsPerInhArea"],
+    localAreaDensity           = spParams["localAreaDensity"],
     synPermInactiveDec         = spParams["synPermInactiveDec"],
     synPermActiveInc           = spParams["synPermActiveInc"],
     synPermConnected           = spParams["synPermConnected"],

py/htm/examples/hotgym.py

@@ -17,9 +17,9 @@
 
 import argparse
 import random
-import gzip
 import numpy as np
 import os
+import sys
 
 from htm.bindings.algorithms import SpatialPooler, Classifier
 from htm.bindings.sdr import SDR, Metrics
@@ -36,7 +36,7 @@ def int32(b):
         return i
 
     def load_labels(file_name):
-        with gzip.open(file_name, 'rb') as f:
+        with open(file_name, 'rb') as f:
             raw = f.read()
             assert(int32(raw[0:4]) == 2049)  # Magic number
             labels = []
@@ -46,7 +46,7 @@ def load_labels(file_name):
         return labels
 
     def load_images(file_name):
-        with gzip.open(file_name, 'rb') as f:
+        with open(file_name, 'rb') as f:
             raw = f.read()
             assert(int32(raw[0:4]) == 2051)    # Magic number
             num_imgs   = int32(raw[4:8])
@@ -67,32 +67,36 @@ def load_images(file_name):
             assert(len(raw) == data_start + img_size * num_imgs)   # All data should be used.
         return imgs
 
-    train_labels = load_labels(os.path.join(path, 'train-labels-idx1-ubyte.gz'))
-    train_images = load_images(os.path.join(path, 'train-images-idx3-ubyte.gz'))
-    test_labels  = load_labels(os.path.join(path, 't10k-labels-idx1-ubyte.gz'))
-    test_images  = load_images(os.path.join(path, 't10k-images-idx3-ubyte.gz'))
+    train_labels = load_labels(os.path.join(path, 'train-labels-idx1-ubyte'))
+    train_images = load_images(os.path.join(path, 'train-images-idx3-ubyte'))
+    test_labels  = load_labels(os.path.join(path, 't10k-labels-idx1-ubyte'))
+    test_images  = load_images(os.path.join(path, 't10k-images-idx3-ubyte'))
 
     return train_labels, train_images, test_labels, test_images
 
-
+# These parameters can be improved using parameter optimization,
+# see py/htm/optimization/ae.py
+# For more explanation of relations between the parameters, see 
+# src/examples/mnist/MNIST_CPP.cpp 
 default_parameters = {
-    'boostStrength': 7.80643753517375,
-    'columnDimensions': (35415,1),
-    'dutyCyclePeriod': 1321,
-    'localAreaDensity': 0.05361688506086096,
-    'minPctOverlapDutyCycle': 0.0016316043362658,
-    'potentialPct': 0.06799785776775163,
-    'stimulusThreshold': 8,
-    'synPermActiveInc': 0.01455789388651146,
-    'synPermConnected': 0.021649964738697944,
-    'synPermInactiveDec': 0.006442691852205935
+    'potentialRadius': 7,
+    'boostStrength': 7.0,
+    'columnDimensions': (28*28*8, 1),
+    'dutyCyclePeriod': 1402,
+    'localAreaDensity': 0.1,
+    'minPctOverlapDutyCycle': 0.2,
+    'potentialPct': 0.1,
+    'stimulusThreshold': 6,
+    'synPermActiveInc': 0.14,
+    'synPermConnected': 0.5,
+    'synPermInactiveDec': 0.02
 }
 
 
 def main(parameters=default_parameters, argv=None, verbose=True):
     parser = argparse.ArgumentParser()
     parser.add_argument('--data_dir', type=str,
-        default = os.path.join( os.path.dirname(__file__), 'MNIST_data'))
+        default = os.path.join( os.path.dirname(__file__), '..', '..', '..', 'build', 'ThirdParty', 'mnist_data', 'mnist-src'))
     args = parser.parse_args(args = argv)
 
     # Load data.
@@ -107,11 +111,10 @@ def main(parameters=default_parameters, argv=None, verbose=True):
     sp = SpatialPooler(
         inputDimensions            = enc.dimensions,
         columnDimensions           = parameters['columnDimensions'],
-        potentialRadius            = 99999999,
+        potentialRadius            = parameters['potentialRadius'],
         potentialPct               = parameters['potentialPct'],
         globalInhibition           = True,
         localAreaDensity           = parameters['localAreaDensity'],
-        numActiveColumnsPerInhArea = -1,
         stimulusThreshold          = int(round(parameters['stimulusThreshold'])),
         synPermInactiveDec         = parameters['synPermInactiveDec'],
         synPermActiveInc           = parameters['synPermActiveInc'],
@@ -143,10 +146,11 @@ def main(parameters=default_parameters, argv=None, verbose=True):
         sp.compute( enc, False, columns )
         if lbl == np.argmax( sdrc.infer( columns ) ):
             score += 1
+    score = score / len(test_data)
 
-    print('Score:', 100 * score / len(test_data), '%')
-    return score / len(test_data)
+    print('Score:', 100 * score, '%')
+    return score < 0.95
 
 
 if __name__ == '__main__':
-    main()
+    sys.exit( main() )