Attempt to resolve conflicts

Author: peter-ch

CMakeLists.txt

@@ -13,7 +13,8 @@ find_package(Boost COMPONENTS
     date_time
     system
     filesystem
-    python3
+    python36
+    numpy36
     serialization)
 if(Boost_FOUND)
     include_directories(${Boost_INCLUDE_DIRS})
@@ -23,35 +24,33 @@ include_directories(${PYTHON_INCLUDE_DIRS})
 
 add_definitions(-DUSE_BOOST_PYTHON)
 add_definitions(-DUSE_BOOST_RANDOM)
+add_definitions(-DVDEBUG)
+
+add_executable(MultiNEAT ${PROJECT_SOURCE_DIR}/src/Assert.h
+                         ${PROJECT_SOURCE_DIR}/src/Genes.h
+                         ${PROJECT_SOURCE_DIR}/src/Genome.cpp
+                         ${PROJECT_SOURCE_DIR}/src/Genome.h
+                         ${PROJECT_SOURCE_DIR}/src/Innovation.cpp
+                         ${PROJECT_SOURCE_DIR}/src/Innovation.h
+                         ${PROJECT_SOURCE_DIR}/src/Main.cpp
+                         ${PROJECT_SOURCE_DIR}/src/NeuralNetwork.cpp
+                         ${PROJECT_SOURCE_DIR}/src/NeuralNetwork.h
+                         ${PROJECT_SOURCE_DIR}/src/Parameters.cpp
+                         ${PROJECT_SOURCE_DIR}/src/Parameters.h
+                         ${PROJECT_SOURCE_DIR}/src/PhenotypeBehavior.cpp
+                         ${PROJECT_SOURCE_DIR}/src/PhenotypeBehavior.h
+                         ${PROJECT_SOURCE_DIR}/src/Population.cpp
+                         ${PROJECT_SOURCE_DIR}/src/Population.h
+                         ${PROJECT_SOURCE_DIR}/src/PythonBindings.cpp
+                         ${PROJECT_SOURCE_DIR}/src/Random.cpp
+                         ${PROJECT_SOURCE_DIR}/src/Random.h
+                         ${PROJECT_SOURCE_DIR}/src/Species.cpp
+                         ${PROJECT_SOURCE_DIR}/src/Species.h
+                         ${PROJECT_SOURCE_DIR}/src/Substrate.cpp
+                         ${PROJECT_SOURCE_DIR}/src/Substrate.h
+                         ${PROJECT_SOURCE_DIR}/src/Utils.cpp
+                         ${PROJECT_SOURCE_DIR}/src/Utils.h
+                         ${PROJECT_SOURCE_DIR}/src/Traits.h
+                         ${PROJECT_SOURCE_DIR}/src/Traits.cpp)
 
-set(SOURCE_FILES
-    src/Assert.h
-    src/Genes.h
-    src/Genome.cpp
-    src/Genome.h
-    src/Innovation.cpp
-    src/Innovation.h
-    src/Main.cpp
-    src/NeuralNetwork.cpp
-    src/NeuralNetwork.h
-    src/Parameters.cpp
-    src/Parameters.h
-    src/PhenotypeBehavior.cpp
-    src/PhenotypeBehavior.h
-    src/Population.cpp
-    src/Population.h
-    src/PythonBindings.cpp
-    src/Random.cpp
-    src/Random.h
-    src/Species.cpp
-    src/Species.h
-    src/Substrate.cpp
-    src/Substrate.h
-    src/Utils.cpp
-    src/Utils.h
-    src/Traits.h
-    src/Traits.cpp)
-
-
-add_executable(MultiNEAT ${SOURCE_FILES})
 target_link_libraries(MultiNEAT ${Boost_LIBRARIES} ${PYTHON_LIBRARIES} pthread)

MultiNEAT/__init__.py

@@ -21,17 +21,29 @@ def ZipFitness(genome_list, fitness_list):
 try:
     import networkx as nx
 
-    def Genome2NX(g):
+    def Genome2NX(g, with_inputs=False, with_weights=False):
 
         nts = g.GetNeuronTraits()
-        lts = g.GetLinkTraits()
+        lts = g.GetLinkTraits(with_weights)
         gr = nx.DiGraph()
 
         for i, tp, traits in nts:
-            gr.add_node( i, **traits)
-
-        for inp, outp, traits in lts:
-            gr.add_edge( inp, outp, **traits )
+            if with_inputs:
+                gr.add_node( i, **traits)
+            else:
+                # don't add traits on inputs
+                if tp != 'input':
+                    gr.add_node( i, **traits)
+                else:
+                    gr.add_node( i )
+
+        if not with_weights:
+            for inp, outp, traits in lts:
+                gr.add_edge( inp, outp, **traits)
+        else:
+            for inp, outp, traits, w in lts:
+                t = {**traits, 'w':w}
+                gr.add_edge( inp, outp, **t)
 
         gr.genome_traits = g.GetGenomeTraits()
 

MultiNEAT/viz.py

@@ -30,15 +30,12 @@ def AlmostEqual(a, b, margin):
 except:
     print('Install NumPy for visualization')
 
-
 try:
     import cv2
     cvnumpy_installed = True
 except:
     print ('Tip: install the OpenCV computer vision library (2.0+) with '
-           'Python bindings')
-    print ('     to get convenient neural network visualization to NumPy '
-           'arrays')
+           'Python bindings to get convenient neural network visualization to NumPy arrays.')
     cvnumpy_installed = False
 
 try:

examples/ball_keeper.py

@@ -298,7 +298,7 @@ def main():
 
 
     g = NEAT.Genome(0, 6, 0, 2, False, 
-                    NEAT.ActivationFunction.TANH, NEAT.ActivationFunction.UNSIGNED_SIGMOID, 0, params, 0)
+                    NEAT.ActivationFunction.TANH, NEAT.ActivationFunction.UNSIGNED_SIGMOID, 0, params, 0, 1)
     pop = NEAT.Population(g, params, True, 1.0, rnd.randint(0, 1000))
 
     best_genome_ever = None

examples/gym/lunar_lander.py

@@ -8,6 +8,7 @@
 import pickle
 import numpy as np
 import cv2
+from tqdm import tqdm
 
 rng = NEAT.RNG()
 rng.TimeSeed()
@@ -72,7 +73,7 @@
 render_during_training = 0
 
 g = NEAT.Genome(0, 8 +1, 0, 4, False,
-                NEAT.ActivationFunction.TANH, NEAT.ActivationFunction.TANH, 0, params, 0)
+                NEAT.ActivationFunction.TANH, NEAT.ActivationFunction.TANH, 0, params, 0, 1)
 pop = NEAT.Population(g, params, True, 1.0, rnd.randint(0, 1000))
 
 
@@ -129,7 +130,7 @@ def do_trial():
 
     for generation in range(20):
 
-        for i_episode, genome in enumerate(NEAT.GetGenomeList(pop)):
+        for i_episode, genome in tqdm(enumerate(NEAT.GetGenomeList(pop))):
 
             net = NEAT.NeuralNetwork()
             genome.BuildPhenotype(net)

examples/gym/walker.py

@@ -8,32 +8,33 @@
 import random as rnd
 import pickle
 import numpy as np
+from tqdm import tqdm
 import cv2
 
 substrate = NEAT.Substrate([(-1, -1), (-1, 0), (-1, 1)],
                            [(0, -1), (0, 0), (0, 1)],
                            [(1, 0)])
 
-substrate.m_allow_input_hidden_links = False;
-substrate.m_allow_input_output_links = False;
-substrate.m_allow_hidden_hidden_links = False;
-substrate.m_allow_hidden_output_links = False;
-substrate.m_allow_output_hidden_links = False;
-substrate.m_allow_output_output_links = False;
-substrate.m_allow_looped_hidden_links = False;
-substrate.m_allow_looped_output_links = False;
+substrate.m_allow_input_hidden_links = False
+substrate.m_allow_input_output_links = False
+substrate.m_allow_hidden_hidden_links = False
+substrate.m_allow_hidden_output_links = False
+substrate.m_allow_output_hidden_links = False
+substrate.m_allow_output_output_links = False
+substrate.m_allow_looped_hidden_links = False
+substrate.m_allow_looped_output_links = False
 
-substrate.m_allow_input_hidden_links = True;
-substrate.m_allow_input_output_links = False;
-substrate.m_allow_hidden_output_links = True;
-substrate.m_allow_hidden_hidden_links = False;
+substrate.m_allow_input_hidden_links = True
+substrate.m_allow_input_output_links = False
+substrate.m_allow_hidden_output_links = True
+substrate.m_allow_hidden_hidden_links = False
 
-substrate.m_hidden_nodes_activation = NEAT.ActivationFunction.SIGNED_SIGMOID;
-substrate.m_output_nodes_activation = NEAT.ActivationFunction.UNSIGNED_SIGMOID;
+substrate.m_hidden_nodes_activation = NEAT.ActivationFunction.SIGNED_SIGMOID
+substrate.m_output_nodes_activation = NEAT.ActivationFunction.UNSIGNED_SIGMOID
 
-substrate.m_with_distance = True;
+substrate.m_with_distance = True
 
-substrate.m_max_weight_and_bias = 8.0;
+substrate.m_max_weight_and_bias = 8.0
 
 try:
     x = pickle.dumps(substrate)
@@ -129,7 +130,7 @@ def main():
     generations = 10
 
     g = NEAT.Genome(0, 24 + 1 + 1, 0, 4, False,
-                    NEAT.ActivationFunction.TANH, NEAT.ActivationFunction.TANH, 0, params, 0)
+                    NEAT.ActivationFunction.TANH, NEAT.ActivationFunction.TANH, 0, params, 0, 1)
     pop = NEAT.Population(g, params, True, 1.0, rnd.randint(0, 1000))
     hof = []
     maxf_ever = 0
@@ -142,7 +143,7 @@ def main():
             #args = [x for x in NEAT.GetGenomeList(pop)]
             #dv.block=True
             #fitnesses = dv.map_sync(evaluate_genome, args)
-            for _, genome in enumerate(NEAT.GetGenomeList(pop)):
+            for _, genome in tqdm(enumerate(NEAT.GetGenomeList(pop))):
                 fitness = evaluate_genome(env, genome, trials)
                 fitnesses.append(fitness)
             for genome, fitness in zip(NEAT.GetGenomeList(pop), fitnesses):
@@ -184,10 +185,10 @@ def do_trial(env, net, render_during_training):
     net.Flush()
 
     f = 0
-    for t in range(300):
+    for t in range(500):
 
         if render_during_training:
-            time.sleep(0.001)
+            #time.sleep(0.001)
             env.render()
 
         # interact with NN

setup.py

@@ -1,6 +1,6 @@
-#!/usr/bin/python
+#!/usr/bin/python3
 
-from __future__ import print_function
+#from __future__ import print_function
 from setuptools import setup, Extension
 import sys
 import os
@@ -23,8 +23,8 @@ def _single_compile(obj):
     list(multiprocessing.pool.ThreadPool(N).imap(_single_compile,objects))
     return objects
 
-import distutils.ccompiler
-distutils.ccompiler.CCompiler.compile=parallelCCompile
+#import distutils.ccompiler
+#distutils.ccompiler.CCompiler.compile=parallelCCompile
 
 
 ''' Note:
@@ -57,7 +57,8 @@ def getExtensions():
                'src/Utils.cpp']
 
     extra = ['-march=native',
-             '-g'
+             '-mtune=native',
+             '-g',
              ]
 
     if platform == 'darwin':
@@ -112,19 +113,25 @@ def getExtensions():
         if is_python_2:
             libs += ['boost_python', "boost_numpy"]
         else:
-            libs += ['boost_python3', "boost_numpy3"]  # in Ubuntu 14 there is only 'boost_python-py34'
+            # with boost 1.67 you need boost_python3x and boost_numpy3x where x is python version 3.x 
+            libs += ['boost_python36', "boost_numpy36"]  # in Ubuntu 14 there is only 'boost_python-py34'
 
         # for Windows with mingw
         # libraries= ['libboost_python-mgw48-mt-1_58',
         #            'libboost_serialization-mgw48-mt-1_58'],
         # include_dirs = ['C:/MinGW/include', 'C:/Users/Peter/Desktop/boost_1_58_0'],
         # library_dirs = ['C:/MinGW/lib', 'C:/Users/Peter/Desktop/boost_1_58_0/stage/lib'],
-        extra.extend(['-DUSE_BOOST_PYTHON', '-DUSE_BOOST_RANDOM'])
-        extensionsList.append(Extension('MultiNEAT._MultiNEAT',
-                                        sources,
-                                        libraries=libs,
-                                        extra_compile_args=extra)
-                              )
+        extra.extend(['-DUSE_BOOST_PYTHON', '-DUSE_BOOST_RANDOM', #'-O0',
+                      #'-DVDEBUG',
+                      ])
+        exx = Extension('MultiNEAT._MultiNEAT',
+                        sources,
+                        libraries=libs,
+                        extra_compile_args=extra)
+        print(dir(exx))
+        print(exx)
+        print(exx.extra_compile_args)
+        extensionsList.append(exx)
     else:
         raise AttributeError('Unknown tool: {}'.format(build_sys))