def completeConfiguration(self, props):
self.num_java_threads = props.getValue(self.p_num_java_threads)
self.num_sim_GPU = props.getValue(self.p_num_sim_GPU)
self.use_GPU_for_creation = props.getValue(self.p_use_GPU_for_creation)
NodeThreadPool.setNumJavaThreads(self.num_java_threads)
NEFGPUInterface.setRequestedNumDevices(self.num_sim_GPU)
WeightedCostApproximator.setUseGPU(self.use_GPU_for_creation)
def completeConfiguration(self,props):
self.num_java_threads=props.getValue(self.p_num_java_threads)
self.num_sim_GPU=props.getValue(self.p_num_sim_GPU)
self.use_GPU_for_creation=props.getValue(self.p_use_GPU_for_creation)
NodeThreadPool.setNumJavaThreads(self.num_java_threads)
NEFGPUInterface.setRequestedNumDevices(self.num_sim_GPU)
WeightedCostApproximator.setUseGPU(self.use_GPU_for_creation)
def start():
(options, args) = parse_args()
logging.basicConfig(filename=options.logfile, filemode='w', level=logging.INFO)
logging.info("Parameters: " + str(options) + str(args))
command_line = 'cl' in args
if options.dry_run:
dry_run(options.results_file)
NodeThreadPool.setNumJavaThreads(options.threads)
if options.reduced_mode:
reduced_run(options)
else:
normal_run(options)
def start():
(options, args) = parse_args()
logging.basicConfig(filename=options.logfile,
filemode='w',
level=logging.INFO)
logging.info("Parameters: " + str(options) + str(args))
command_line = 'cl' in args
if options.dry_run:
dry_run(options.results_file)
NodeThreadPool.setNumJavaThreads(options.threads)
if options.reduced_mode:
reduced_run(options)
else:
normal_run(options)
data.record_sparsity(nav_agent.getNode("QNetwork").getNode("state_pop").getOrigin("AXON"), filter=filter)
data.record_avg(ctrl_agent.getNode("QNetwork").getNode("valdiff").getOrigin("X"), filter=filter)
data.record_avg(ctrl_agent.getNode("ErrorNetwork").getOrigin("error"), filter=filter)
data.record_avg(ctrl_agent.getNode("BGNetwork").getNode("weight_actions").getNode("0").getOrigin("AXON"), filter=filter)
data.record_avg(ctrl_agent.getNode("BGNetwork").getNode("weight_actions").getNode("1").getOrigin("AXON"), filter=filter)
net.add_to_nengo()
# net.view()
net.run(2000)
def run_workTermReport():
# run a bunch of configs
config = {"time": {"linear": "please"}}
# start at twice the normal scale and then let it degrade
NodeThreadPool.setNumJavaThreads(8) #Set it equal to the number of cores?
#run_deliveryenvironment({"learningrate": 9e-10, "discount": 0.1, "Qradius": 2.0,
# "load_weights": os.path.join("weights", "contextgrid_decoder", "SMDPAgent")},
# {"learningrate": 9e-10, "discount": 0.1, "load_weights": None},
# seed=1)
#run_contextenvironment({"learningrate":9e-10, "discount":0.1, "Qradius":2.0,
# "load_weights":None},
# seed=0)
#gen_evalpoints("contextbmp_evalpoints", seed=0)
#run_flat_delivery({"learningrate":9e-10, "discount":0.1, "Qradius":2.0,
# "load_weights":os.path.join("delivery", "flat", "NavAgent")},
# seed=2)
