type=int,
help='GPU for integration [default:3]')
args = parser.parse_args()
dt = 1e-4
dur = 1.4
Nt = int(dur / dt)
file_name = None
screen = False
if args.log.lower() in ['file', 'both']:
file_name = 'neurokernel.log'
if args.log.lower() in ['screen', 'both']:
screen = True
logger = base.setup_logger(file_name, screen)
if args.port_data is None and args.port_ctrl is None:
port_data = get_random_port()
port_ctrl = get_random_port()
else:
port_data = args.port_data
port_ctrl = args.port_ctrl
man = core.Manager(port_data, port_ctrl)
man.add_brok()
# Load configurations for lamina, medulla and antennal lobe models:
(n_dict_al, s_dict_al) = LPU.lpu_parser('./data/antennallobe.gexf.gz')
lpu_al = LPU(dt,
n_dict_al,
help='Number of sensory neurons associated with LPU 0 [default: %s]' % N_sensory)
parser.add_argument('-n', '--num_local', default=N_local, type=int,
help='Number of local neurons in each LPU [default: %s]' % N_local)
parser.add_argument('-o', '--num_output', default=N_output, type=int,
help='Number of output neurons in each LPU [default: %s]' % N_output)
parser.add_argument('-u', '--num_lpus', default=num_lpus, type=int,
help='Number of LPUs [default: %s]' % num_lpus)
args = parser.parse_args()
file_name = None
screen = False
if args.log.lower() in ['file', 'both']:
file_name = 'neurokernel.log'
if args.log.lower() in ['screen', 'both']:
screen = True
logger = setup_logger(file_name, screen)
# Set number of local and projection neurons in each LPU:
N = args.num_lpus
neu_dict = {i: [0, args.num_local, args.num_output] for i in xrange(N)}
# Only LPU 0 receives input and should therefore be associated with a population
# of sensory neurons:
neu_dict[0][0] = args.num_sensory
# Create input signal for LPU 0:
in_file_name_0 = 'generic_input.h5'
g.create_input(in_file_name_0, neu_dict[0][0], dt, dur, start, stop, I_max)
# Store info for all instantiated LPUs in the following dict:
lpu_dict = {}
)
parser.add_argument("-s", "--steps", default=steps, type=int, help="Number of steps [default: %s]" % steps)
parser.add_argument("-d", "--port_data", default=None, type=int, help="Data port [default: randomly selected]")
parser.add_argument("-c", "--port_ctrl", default=None, type=int, help="Control port [default: randomly selected]")
parser.add_argument("-a", "--lam_dev", default=0, type=int, help="GPU for lamina lobe [default: 0]")
parser.add_argument("-m", "--med_dev", default=1, type=int, help="GPU for medulla [default: 1]")
args = parser.parse_args()
file_name = None
screen = False
if args.log.lower() in ["file", "both"]:
file_name = "neurokernel.log"
if args.log.lower() in ["screen", "both"]:
screen = True
logger = base.setup_logger(file_name, screen)
if args.port_data is None and args.port_ctrl is None:
port_data = get_random_port()
port_ctrl = get_random_port()
else:
port_data = args.port_data
port_ctrl = args.port_ctrl
man = core.Manager(port_data, port_ctrl)
man.add_brok()
(n_dict_lam, s_dict_lam) = lpu_parser("./data/lamina.gexf.gz")
lpu_lam = LPU(
dt,
n_dict_lam,
num_lpus = 2
num_gpot = 100
num_spike = 100
max_steps = 100
parser = argparse.ArgumentParser()
parser.add_argument('--debug', default=False,
dest='debug', action='store_true',
help='Enable debug mode.')
parser.add_argument('-l', '--log', default='none', type=str,
help='Log output to screen [file, screen, both, or none; default:none]')
parser.add_argument('-u', '--num_lpus', default=num_lpus, type=int,
help='Number of LPUs [default: %s]' % num_lpus)
parser.add_argument('-s', '--num_spike', default=num_spike, type=int,
help='Number of spiking ports [default: %s]' % num_spike)
parser.add_argument('-g', '--num_gpot', default=num_gpot, type=int,
help='Number of graded potential ports [default: %s]' % num_gpot)
parser.add_argument('-m', '--max_steps', default=max_steps, type=int,
help='Maximum number of steps [default: %s]' % max_steps)
args = parser.parse_args()
file_name = None
screen = False
if args.log.lower() in ['file', 'both']:
file_name = 'neurokernel.log'
if args.log.lower() in ['screen', 'both']:
screen = True
logger = setup_logger(file_name=file_name, screen=screen, multiline=True)
print emulate(args.num_lpus, args.num_spike, args.num_gpot, args.max_steps)
if args.medulla_device:
dev2 = int(args.medulla_device)
else:
dev2 = 1
if args.steps:
steps = int(args.steps)
else:
steps = 10000
dt = 1e-4
dur = 1.0
Nt = 10000 # int(dur/dt)
logger = base.setup_logger()
man = core.Manager(port_data=data_port, port_ctrl=ctrl_port)
man.add_brok()
(n_dict_lam, s_dict_lam) = lpu_parser("./config_files/lamina.gexf")
lam = LPU(
dt,
n_dict_lam,
s_dict_lam,
input_file="videos/flicker_stripe_same6.h5",
output_file="lamina_output.h5",
port_ctrl=man.port_ctrl,
port_data=man.port_data,
device=dev1,
id="lamina",
help='Number of output neurons in each LPU [default: %s]' %
N_output)
parser.add_argument('-u',
'--num_lpus',
default=num_lpus,
type=int,
help='Number of LPUs [default: %s]' % num_lpus)
args = parser.parse_args()
file_name = None
screen = False
if args.log.lower() in ['file', 'both']:
file_name = 'neurokernel.log'
if args.log.lower() in ['screen', 'both']:
screen = True
logger = setup_logger(file_name, screen)
# Set number of local and projection neurons in each LPU:
N = args.num_lpus
neu_dict = {i: [0, args.num_local, args.num_output] for i in xrange(N)}
# Only LPU 0 receives input and should therefore be associated with a population
# of sensory neurons:
neu_dict[0][0] = args.num_sensory
# Create input signal for LPU 0:
in_file_name_0 = 'generic_input.h5'
g.create_input(in_file_name_0, neu_dict[0][0], dt, dur, start, stop, I_max)
# Store info for all instantiated LPUs in the following dict:
lpu_dict = {}
