def count_neucon2(filelist):
layers = []
max_con = []
assert len(filelist) != 0
f = open(os.path.join(info.get_output_path(), filelist[0]), 'rb')
cons = pk.load(f, encoding='iso-8859-1')
# cons=pk.load(f)
dst = set()
for con in cons:
dst.add(con[1])
layers.append(len(dst))
# print(layers)
f.close()
for file in filelist[1:]:
f = open(os.path.join(info.get_output_path(), file), 'rb')
cons = pk.load(f, encoding='iso-8859-1')
print(len(cons))
dst = set()
maxsou = -1
for con in cons:
dst.add(con[1])
if con[0] > maxsou:
maxsou = int(con[0])
layers.append(len(dst))
cnt_con = np.zeros(((maxsou + 1), ))
for con in cons:
cnt_con[int(con[0])] += 1
maxnum = np.max(cnt_con)
max_con.append(int(maxnum))
f.close()
max_con.append(1)
return layers, max_con
def count_neucon(filelist):
layers = []
avg_con = []
assert len(filelist) != 0
f = open(os.path.join(info.get_output_path(), filelist[0]),
'rb') # one-to-one
cons = pk.load(f) # 从文件变为python对
dst = set() # 创建一个无序不重复元素集
for con in cons:
dst.add(con[1])
layers.append(len(dst))
f.close()
for file in filelist[1:]:
f = open(os.path.join(info.get_output_path(), file), 'rb')
cons = pk.load(f)
print(len(cons))
dst = set()
for con in cons:
dst.add(con[1])
avg_con.append(int(math.ceil(len(cons) / float(layers[-1]))))
layers.append(len(dst))
f.close()
avg_con.append(1)
return layers, avg_con
def neuron_link(connfiles, netDepth, layers, nodes):
neuron_id = [] # 神经元的node号码
neuron_dst = [] # 神经元的目的神经元
node_link = []
# link_to = []
for i in range(netDepth - 2):
x_loop = []
for j in range(nodes[i]):
x_loop.append([])
node_link.append(x_loop)
# for i in range(netDepth - 2):
# x_loop = []
# for j in range(nodes[i + 1]):
# x_loop.append([])
# link_to.append(x_loop)
# link_to.append([[]])
# print(link_to)
for i in range(netDepth - 1):
neuron_num = int(math.ceil(layers[i] / float(nodes[i])))
# print('neuron_num:',neuron_num)
neuron_ii = []
layer_dst = []
for j in range(layers[i]):
neuron_ii.append(j // neuron_num)
layer_dst.append([])
neuron_id.append(neuron_ii)
neuron_dst.append(layer_dst)
# print(neuron_id)
if i != netDepth - 2:
f = open(os.path.join(info.get_output_path(), connfiles[i + 1]),
'rb')
# print(f)
# conn = np.array(pk.load(f))
conn = np.array(pk.load(f, encoding='iso-8859-1'))
for line in conn:
src = int(line[0])
dst = int(line[1])
neuron_dst[i][src].append(dst)
for i in range(netDepth - 2):
# neuron_num = int(math.ceil(layers[i+1] / float(nodes[i+1]))) # 下一层
for j in range(layers[i]):
src_id = neuron_id[i][j]
for k in range(len(neuron_dst[i][j])):
dst = neuron_dst[i][j][k]
dst_id = neuron_id[i + 1][dst]
if dst_id not in node_link[i][src_id]:
node_link[i][src_id].append(dst_id)
# if src_id not in link_to[i][dst_id]:
# link_to[i][dst_id].append(src_id)
# for i in range(nodes[-1]):
# node_link[netDepth - 2][i].append(0)
# link_to[netDepth - 2][0].append(i)
return node_link
def gen_inputdata(cons,
spikes,
input_node_map,
maxtime,
filename="input.txt",
row_file="row.txt",
grid_size=64):
'''
cons:连接文件
spikes:输入脉冲文件
input_node_map:第一层神经元的分布情况
maxtime：运行时间
return：input.txt, row.txt
'''
f = open(os.path.join(info.get_output_path(), filename), "w")
inputnodes = []
for k in input_node_map:
inputnodes.append(
node_input(k, cons, input_node_map[k], grid_size=grid_size))
connections = change_format(cons)
times = spike_time(spikes, maxtime)
count = 0
res = []
in_head = '40000'
for i in range(maxtime + 1)[1:]:
res.append(count)
neu_set = times[i]
for node in inputnodes:
tmp = node.gen_input(neu_set, connections)
tmp2 = node.get_headpack()
body_pack_head = node.get_bodypackhead()
tail_pack_head = node.get_tailpackhead()
ss = "%011x" % tmp2 # head
f.write(in_head + ss + '\n')
count += 1
flag = 0
sig = 0
if len(tmp) != 0:
for wt in tmp[:len(tmp) - 1]:
if flag == 0:
flag = 1
sig = wt
else:
flag = 0
ss = "%011x" % (((sig << 16) | wt) + body_pack_head)
f.write(in_head + ss + '\n')
count += 1
if flag == 1:
ss = "%011x" % (((sig << 16) | tmp[-1]) + tail_pack_head)
f.write(in_head + ss + '\n')
count += 1
else:
sig = tmp[-1]
ss = "%011x" % (((sig << 16) | 0) + tail_pack_head)
f.write(in_head + ss + '\n')
count += 1
else:
ss = "%011x" % tail_pack_head
f.write(in_head + ss + '\n')
count += 1
res.append(count)
f.close()
frow = open(os.path.join(info.get_output_path(), row_file), "w")
ttt = 1
for i in res[1:]:
frow.write(str(hex(i))[2:] + '\n') # rownum time
# frow.write(str(hex(i))[2:]+' '+str(ttt)+'\n') #rownum time
ttt += 1
frow.close()
ttt = 1
for i in res[1:]:
row_list.append(str(hex(i))[2:])
# frow.write(str(hex(i))[2:]+' '+str(ttt)+'\n') #rownum time
ttt += 1
return input_list, row_list
if __name__ == '__main__':
import pickle
import numpy as np
# 加载输入层
fpkl = open(
os.path.join(info.get_output_path(), './connection/input_conv1.pkl'),
'rb')
in_conv1 = pickle.load(fpkl, encoding='iso-8859-1')
fpkl.close()
# 加载spikes
fspk = open(
os.path.join(info.get_output_path(), './input/spikeTrains.pkl'), 'rb')
spikes = pickle.load(fspk, encoding='iso-8859-1')
fspk.close
input_node_map = {}
# node分配列表
layer = []
node_list = []
for x in range(8):
def gen_config_file(self, filename, leaksign=0):
f = open(filename, 'w')
rf = open(os.path.join(info.get_output_path(), "re_config.txt"), "w")
# f.write(str+'\n')
for node in self.nodes:
"""
set registers and memory
"""
# print(node.get_packlength())
# print(node,node.x,node.y,node.zero_ref)
tmp = node.get_headpack()
# print("%011x" % tmp)
body_pack_head = node.get_bodypackhead()
tail_pack_head = node.get_tailpackhead()
con_head = '40000'
ss = "%011x" % tmp # head
f.write(con_head + ss + '\n')
rf.write(con_head + ss + '\n')
# set neunum first and then clear
tmp = node.setr_neuronnum()
for t in tmp:
ss = "%011x" % (t + body_pack_head)
f.write(con_head + ss + '\n')
rf.write(con_head + ss + '\n')
tmp = node.setr_status()
for t in tmp:
ss = "%011x" % (t + body_pack_head)
f.write(con_head + ss + '\n')
rf.write(con_head + ss + '\n')
tmp = node.setr_vth()
for t in tmp:
ss = "%011x" % (t + body_pack_head)
f.write(con_head + ss + '\n')
rf.write(con_head + ss + '\n')
tmp = node.setr_leak()
for t in tmp:
ss = "%011x" % (t + body_pack_head)
f.write(con_head + ss + '\n')
rf.write(con_head + ss + '\n')
tmp = node.setr_mode(leaksign=leaksign)
for t in tmp:
ss = "%011x" % (t + body_pack_head)
f.write(con_head + ss + '\n')
rf.write(con_head + ss + '\n')
tmp = node.setr_linker_baddr()
for t in tmp:
ss = "%011x" % (t + body_pack_head)
f.write(con_head + ss + '\n')
rf.write(con_head + ss + '\n')
tmp = node.setr_packet_baddr()
for t in tmp:
ss = "%011x" % (t + body_pack_head)
f.write(con_head + ss + '\n')
rf.write(con_head + ss + '\n')
tmp = node.setr_nizeroref()
for t in tmp:
ss = "%011x" % (t + body_pack_head)
f.write(con_head + ss + '\n')
rf.write(con_head + ss + '\n')
tmp = node.setr_nidelay()
for index, t in enumerate(tmp):
if index == len(tmp) - 1 and not self.mmc:
ss = "%011x" % (t + tail_pack_head)
else:
ss = "%011x" % (t + body_pack_head)
f.write(con_head + ss + '\n')
for index, t in enumerate(tmp):
if index == len(tmp) - 1:
ss = "%011x" % (t + tail_pack_head)
else:
ss = "%011x" % (t + body_pack_head)
rf.write(con_head + ss + '\n')
if self.mmc:
linker, data = node.cal_addr()
for d in linker:
h = (1 << 31) | (node.npu_m << 29) | d[0]
ss = "%011x" % (h + body_pack_head)
f.write(con_head + ss + '\n')
ss = "%011x" % (d[1] + body_pack_head)
f.write(con_head + ss + '\n')
for index, d in enumerate(data):
h = (1 << 31) | (node.npu_m << 29) | d[0]
ss = "%011x" % (h + body_pack_head)
f.write(con_head + ss + '\n')
if index == len(data) - 1:
ss = "%011x" % (d[1] + tail_pack_head)
else:
ss = "%011x" % (d[1] + body_pack_head)
f.write(con_head + ss + '\n')
# tmp=node.setr_nizeroref()
# ss="%011x" % (tmp[0]+body_pack_head)
# f.write(ss+'\n')
# ss="%011x" % (tmp[1]+tail_pack_head)
# f.write(ss+'\n')
if self.enable:
for node in self.nodes:
# print("aaaaaaaaaaaaa")
tmp = node.get_headpack()
body_pack_head = node.get_bodypackhead()
tail_pack_head = node.get_tailpackhead()
ss = "%011x" % tmp # head
f.write(con_head + ss + '\n')
rf.write(con_head + ss + '\n')
tmp = node.setr_status(1, 1)
ss = "%011x" % (tmp[0] + body_pack_head)
f.write(con_head + ss + '\n')
rf.write(con_head + ss + '\n')
ss = "%011x" % (tmp[1] + tail_pack_head)
f.write(con_head + ss + '\n')
rf.write(con_head + ss + '\n')
f.close()