def fig5(self, ext='pdf'):
# the matric of positions
dxs = [0, 0.5, ldots_span, 1]
xs = np.cumsum(dxs)
dys = [0, 0.7, 0.7]
ys = -np.cumsum(dys)
nodes = np.zeros([len(xs), len(ys)], dtype='O')
with viznet.DynamicShow(figsize=(6,3), filename='_fig5.%s'%ext) as ds:
for i, x in enumerate(xs):
if x==0:
brush = dot
else:
brush = mpo
for j, y in enumerate(ys):
if j==1 and brush is not dot:
brush_ = invis_mini
else:
brush_ = brush
nodes[i, j] = brush_ >> (x, y)
# horizontal lines
for j in [0, 2]:
for i in range(len(xs)-1):
if i == 1:
connect_ldots(nodes[i, j], nodes[i+1, j])
else:
edge >> (nodes[i, j], nodes[i+1, j])
# vertical lines
for i in range(len(xs)):
for j in range(len(ys)-1):
edge >> (nodes[i,j], nodes[i, j+1])
def fig4(self, ext='pdf'):
node_list = []
node_list2 = []
dxs = [0, ldots_span, 1, 1, 1, ldots_span]
xs = np.cumsum(dxs)
with viznet.DynamicShow(figsize=(6,3), filename='_fig4.%s'%ext) as ds:
for i, x in enumerate(xs):
if i == 2 or i==3:
brush = invis
else:
brush = mpo
node_list.append(brush >> (x, 0))
if i == 2:
mpo2 = hbar >> ((xs[2]+xs[3])/2., -dy)
node_list2.append(mpo2)
elif i == 3:
node_list2.append(mpo2)
else:
node_list2.append(mpo >> (x, -dy))
# horizontal lines
for nlist in [node_list, node_list2]:
connect_ldots(nlist[0], nlist[1])
connect_ldots(nlist[4], nlist[5])
edge >> (nlist[1], nlist[2])
edge >> (nlist[3], nlist[4])
# vertical lines
for node, node2 in zip(node_list, node_list2):
edge >> (node, node2.pin('top', align=node))
def cgraph_layer(output='png'):
'''computation graph for a typical single layer.'''
with viznet.DynamicShow(figsize=(5, 4),
filename='_cg_layer.%s' % output) as ds:
output = viznet.NodeBrush('nn.output', ds.ax)
input = viznet.NodeBrush('nn.input', ds.ax)
op = viznet.NodeBrush('basic', ds.ax)
edge = viznet.EdgeBrush('->', ds.ax)
x = input >> (0, 0)
x.text('$x$')
dot = op >> (1, 0)
dot.text('dot')
dot.text('$f(W,x)=Wx$', 'top')
W = input >> (1, -1)
W.text('$W$')
edge >> (x, dot)
edge >> (W, dot)
b = input >> (2, -1)
b.text('$b$')
plus = op >> (2, 0)
plus.text('$+$')
edge >> (dot, plus)
edge >> (b, plus)
sigmoid = output >> (3, 0)
sigmoid.text(r'$\sigma$')
edge >> (plus, sigmoid)
def cgraph_mnist_full(output='png'):
'''computation graph for simple mnist network.'''
with viznet.DynamicShow(figsize=(3, 6),
filename='_cg_mnist_full.%s' % output) as ds:
output = viznet.NodeBrush('nn.output', ds.ax)
input = viznet.NodeBrush('nn.input', ds.ax)
op = viznet.NodeBrush('basic', ds.ax)
edge = viznet.EdgeBrush('->', ds.ax)
x = input >> (0, 0)
x.text('$x$')
dot = op >> (0, -1)
dot.text('dot')
W = input >> (-1, -1)
W.text('$W$')
edge >> (x, dot)
edge >> (W, dot)
b = input >> (-1, -2)
b.text('$b$')
plus = op >> (0, -2)
plus.text('$+$')
edge >> (dot, plus)
edge >> (b, plus)
softmax = op >> (0, -3)
softmax.text(r'Softmax', 'left')
edge >> (plus, softmax)
crossentropy = op >> (0, -4)
crossentropy.text(r'CrossEntropy', 'left')
y = input >> (1, -4)
y.text(r'$y$')
edge >> (softmax, crossentropy)
edge >> (y, crossentropy)
mean = output >> (0, -5)
mean.text(r'Mean')
edge >> (crossentropy, mean)
def framework(self):
with viznet.DynamicShow(figsize=(6, 4),
filename="framework.png") as dp:
grid = viznet.Grid((3.0, 1.5), offset=(2, 2))
edge = EdgeBrush('->', lw=2., color='r')
# define an mpo
mpo = NodeBrush('box',
color='cyan',
roundness=0.2,
size=(1.0, 0.4))
# generate two mpos
Const = mpo >> grid[0:2, 0:1]
Const.text('LuxurySparse')
Intrinsics = mpo >> grid[3:5, 0:1]
Intrinsics.text('Binary Op')
Intrinsics = mpo >> grid[6:8, 0:1]
Intrinsics.text('Cache Server')
Register = mpo >> grid[3:5, 2:3]
Register.text('Register')
Block = mpo >> grid[0:8, 4:5]
Block.text('Blocks (Operator Tree)')
Extensions = mpo >> grid[4.5:8, 6:7]
Extensions.text('Boost & Extensions')
Interface = mpo >> grid[0:3.5, 6:7]
Interface.text('Interface')
Applications = mpo >> grid[0:8, 8:9]
Applications.text('Applications')
def logo3():
viznet.setting.node_setting['inner_lw'] = 0
viznet.setting.node_setting['lw'] = 0
npoint = 60
nedge = 50
angle = random(npoint) * 2 * np.pi
#r = np.exp(randn(npoint)*0.4)
r = np.sqrt(randn(npoint))
xy = np.array([r * np.cos(angle), r * np.sin(angle)]).T
#xy = randn(npoint, 2)*0.5
with viznet.DynamicShow(figsize=(4, 4), filename='_logo3.png') as ds:
#body = viznet.NodeBrush('tn.mps', size='huge', color='#AACCFF') >> (0, 0)
dot = viznet.NodeBrush('tn.mps', size='tiny')
node_list = []
for i, p in enumerate(xy):
dot.color = random(3) * 0.5 + 0.5
dot.zorder = 100 + i * 2
dot.size = 0.05 + 0.08 * random()
node_list.append(dot >> p)
dis_mat = np.linalg.norm(xy - xy[:, None, :], axis=-1)
tree = minimum_spanning_tree(dis_mat).tocoo()
for i, j in zip(tree.row, tree.col):
n1, n2 = node_list[i], node_list[j]
viznet.EdgeBrush(
choice(['.>.', '.>.']),
lw=1,
color=random([3]) * 0.4,
zorder=(n1.obj.zorder + n2.obj.zorder) / 2) >> (n1, n2)
def fig1(self, ext='pdf'):
with viznet.DynamicShow(figsize=(3,2), filename='_fig1.%s'%ext) as ds:
mpo2 = box >> (0.5, 0)
leg(mpo2, 'left', (-leg_length, 0))
leg(mpo2, 'right', (leg_length, 0))
for i in range(2):
node = invis >> (i, -dy)
edge >> (mpo2.pin('bottom', align=node), node)
def logo1():
with viznet.DynamicShow(figsize=(4, 4), filename='_logo1.png') as ds:
n1 = viznet.NodeBrush('tn.dia', color='#CC3333') >> (0, 0)
n2 = viznet.NodeBrush('qc.cross') >> (1, 0)
n3 = viznet.NodeBrush('tn.mpo', size=0.25) >> (1, 1)
n4 = viznet.NodeBrush('nn.memory') >> (0, 1)
viznet.EdgeBrush('<.>') >> (n1, n2)
viznet.EdgeBrush('<.>') >> (n2, n3)
viznet.EdgeBrush('-<=') >> (n3, n4)
viznet.EdgeBrush('=>-') >> (n4, n1)
def fig2(self, ext='pdf'):
nrow, ncol = 2, 3
nodes = np.zeros([nrow, ncol], dtype='O')
with viznet.DynamicShow(figsize=(5,3), filename='_fig2.%s'%ext) as ds:
for i in range(nrow):
for j in range(ncol):
nodes[i, j] = mpo >> (j*ldots_span, i)
# horizontal lines
for i in range(nrow):
for j in range(ncol-1):
connect_ldots(nodes[i, j], nodes[i, j+1])
# vertical lines
for j in range(ncol):
for i in range(nrow-1):
edge >> (nodes[i,j], nodes[i+1, j])
def cgraph_illu(output='png'):
'''computation graph for simple mnist network.'''
dx = 1
dy = 1
with viznet.DynamicShow(figsize=(3, 2),
filename='_cg_illu.%s' % output) as ds:
op = viznet.NodeBrush('basic', ds.ax)
edge = viznet.EdgeBrush('->', ds.ax)
func1 = op >> (dx, 0)
func1.text('$f$')
inv1 = viznet.edgenode.Pin([0, 0])
e1 = edge >> (inv1, func1)
e1.text('input', 'top')
func2 = op >> (0, -dy)
func2.text('$f$')
inv2 = viznet.edgenode.Pin([dx, -dy])
e2 = edge >> (func2, inv2)
e2.text('output', 'top')
def logo4(partly):
viznet.setting.node_setting['inner_lw'] = 0
viznet.setting.node_setting['lw'] = 2
with viznet.DynamicShow(figsize=(4, 4), filename='_logo4.svg') as ds:
dot = viznet.NodeBrush('box', size=0.5, roundness=0.2)
tall = 5
xs = np.zeros(tall)
ys = np.arange(tall)
dot.color = '#333333'
for x, y in zip(xs, ys):
dot >> (x, y)
xs = [-1, 0, 1]
ys = (tall - 2) * np.ones(3)
dot.color = '#FF9933'
for x, y in zip(xs, ys):
dot >> (x, y)
xs = [1, 2, 2, 2]
ys = [2, 2, 1, 0]
dot.color = '#333333'
for x, y in zip(xs, ys):
dot >> (x, y)
if not partly:
x0 = 5
xs = x0 + np.arange(3)
ys = [3, 3, 3]
dot.color = '#333333'
for x, y in zip(xs, ys):
dot >> (x, y)
ys = [1, 1, 1]
dot.color = '#333333'
for x, y in zip(xs, ys):
dot >> (x, y)
x0 += 5
xs = np.ones(tall) * x0
ys = np.arange(tall)
dot.color = '#333333'
for x, y in zip(xs, ys):
dot >> (x, y)
def fig0(self, ext='pdf'):
# the matric of positions
dxs = [0, 1, ldots_span]
xs = np.cumsum(dxs)
node_list = []
with viznet.DynamicShow(figsize=(6,3), filename='_fig0.%s'%ext) as ds:
for i, x in enumerate(xs):
node_list.append(mpo>>(x, 0))
# horizontal lines
for i in range(len(xs)-1):
if i == 1:
connect_ldots(node_list[i], node_list[i+1])
else:
edge >> (node_list[i], node_list[i+1])
# vertical lines
for node in node_list:
leg(node, 'bottom', offset=(0, -leg_length))
def logo2():
viznet.setting.node_setting['inner_lw'] = 0
viznet.setting.node_setting['lw'] = 0
with viznet.DynamicShow(figsize=(4, 4), filename='_logo2.png') as ds:
body = viznet.NodeBrush('tn.dia', size=1, color='#44CCFF') >> (0, 0)
b1 = viznet.NodeBrush('tn.mpo', size='large',
color='#5588CC') >> (0, 0)
b2 = viznet.NodeBrush('tn.dia', size='small',
color='#331133') >> (0, 0)
viznet.setting.node_setting['inner_lw'] = 2
l = 1.0
brush = viznet.NodeBrush('qc.cross', rotate=np.pi / 4.)
n1 = brush >> (l, l)
n2 = brush >> (-l, l)
n3 = brush >> (-l, -l)
n4 = brush >> (l, -l)
viznet.EdgeBrush('.>-', lw=2) >> (body, n1)
viznet.EdgeBrush('.>-', lw=2) >> (body, n2)
viznet.EdgeBrush('.>-', lw=2) >> (body, n3)
viznet.EdgeBrush('.>-', lw=2) >> (body, n4)
def fig3(self, ext='pdf'):
node_list = []
dxs = [0, ldots_span, 1, 1, 1, ldots_span]
xs = np.cumsum(dxs)
with viznet.DynamicShow(figsize=(6,3), filename='_fig3.%s'%ext) as ds:
for i, x in enumerate(xs):
if i == 2 or i==3:
brush = invis
else:
brush = mpo
node_list.append(brush >> (x, 0))
# horizontal lines
connect_ldots(node_list[0], node_list[1])
connect_ldots(node_list[4], node_list[5])
edge >> (node_list[1], node_list[2])
edge >> (node_list[3], node_list[4])
# vertical lines
for node in node_list:
leg(node, 'bottom', offset=(0, -leg_length))
def simple():
'''(x1+x2)*x3'''
num_node_visible = 6
node = viznet.NodeBrush('nn.input', size='normal')
op = viznet.NodeBrush('basic', size='small')
edge = viznet.EdgeBrush('->-')
with viznet.DynamicShow((4, 3), '_simple_cg.png') as d:
# define brushes
x1 = node >> (0, 0)
x2 = node >> (0, 1)
add = op >> (1, 0.5)
edge >> (x1, add)
edge >> (x2, add)
x3 = node >> (1, 1.5)
prod = op >> (2, 1.0)
edge >> (x3, prod)
edge >> (add, prod)
prod.text(r'$\times$')
add.text(r'$+$')
x1.text('$x_1$')
x2.text('$x_2$')
x3.text('$x_3$')
