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import ctypes
import numpy
import torch
import random
LIF_DISCRETE = 0
#load the spires library
spires_lib = ctypes.CDLL("../spires/lib/libspires.so")
# C signautes for creating reservoir
spires_lib.create_reservoir.argtypes = [
ctypes.c_size_t,
ctypes.c_size_t,
ctypes.c_size_t,
ctypes.c_double,
ctypes.c_double,
ctypes.c_double,
ctypes.c_double,
ctypes.c_double,
ctypes.c_int,
ctypes.c_int,
ctypes.POINTER(ctypes.c_double)
]
spires_lib.create_reservoir.restype = ctypes.c_void_p
# C signatures for reservoir destruction
spires_lib.free_reservoir.argtypes = [ctypes.c_void_p]
spires_lib.free_reservoir.restype = None
# C signatures for step reservoir function
spires_lib.update_neuron.argtypes = [
ctypes.c_void_p, #Pointer to spires reservoir struct
ctypes.c_int,
ctypes.c_double,
ctypes.c_double
]
spires_lib.update_neuron.restype = None
# C signatures for get neuron spike function
spires_lib.read_reservoir_spikes.argtypes = [
ctypes.c_void_p,
ctypes.POINTER(ctypes.c_float)
]
spires_lib.read_reservoir_spikes.restype = None
def init_spires_reservoir(reservoir_size):
print("Creating spires reservoir")
neuron_parameters = (ctypes.c_double * 4)(0.0, 1.0, 0.2, 0.5)
c_neuron_parameters = ctypes.cast(neuron_parameters, ctypes.POINTER(ctypes.c_double))
reservoir_ptr = spires_lib.create_reservoir(
ctypes.c_size_t(int(reservoir_size)), # num neurons
ctypes.c_size_t(int(reservoir_size)), # num neurons
ctypes.c_size_t(2), # num_outputs
ctypes.c_double(0), # spectral radius
ctypes.c_double(0.8), # ei_ratio
ctypes.c_double(1.0), # input_strength
ctypes.c_double(0.0), # connectivity
ctypes.c_double(1.0), # dt
ctypes.c_int(1), # connectivity type ( 1 = sparse)
ctypes.c_int(LIF_DISCRETE), # neuron type
c_neuron_parameters # neuron params
)
#allocate empty void pointer, (reservoir will go here)
if not reservoir_ptr:
raise RuntimeError(f"Spires faile to initialize the reservoir: {status_code}")
else:
print("Spires reservoir initialized")
# reservoir_ptr._keep_alive = neuron_parameters
return reservoir_ptr
def free_spires_reservoir(reservoir_ptr):
print("Freeing the spires reservoir")
spires_lib.free_reservoir(reservoir_ptr)
return 0
#change currents from tensor to a flat C pointer array for spires to read
def send_currents_to_spires(reservoir_ptr, currents_tensor):
# print("Sending currents to spires")
# ----- extract from pytorhc graph -----
# .detach() removes it from auto gradient tracking
# .cpu() make sure data is in RAM, not VRAM
# .numpy() maps it to numpy array
# ----- makes suren layout matches 64 bit double C-array -----
# .astype(npfloat64) forces standard CC float precistion
# .flatten() makes sure the memory is a 1D block
numpy_array = currents_tensor.detach().cpu().numpy().astype(numpy.float64).flatten()
some_ptr = ctypes.cast(reservoir_ptr, ctypes.POINTER(ctypes.POINTER(ctypes.c_void_p)))
neurons_array = some_ptr[0]
# print("updating the neurons")
for i in range(len(numpy_array)):
neuron_ptr = neurons_array[i]
input_current = numpy_array[i]
spires_lib.update_neuron(neuron_ptr, LIF_DISCRETE, input_current, 1.0)
return numpy_array
def read_spikes_from_spires(reservoir_ptr, size=0):
# print("Recieved spikes from spires")
#didnt do any safety checking womp womp
returned_spikes = numpy.zeros(size, dtype=numpy.float64)
c_spike_ptr = returned_spikes.ctypes.data_as(ctypes.POINTER(ctypes.c_float))
spires_lib.read_reservoir_spikes(reservoir_ptr, c_spike_ptr)
return returned_spikes
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