def conc(name, prev, offset=(1, 0, 0), conn=True):
layer = tikz.concatenate(name='{}'.format(name),
to='{}'.format(prev),
offset='{}'.format(offset))
if conn:
tikz.short_connection('{}'.format(prev), '{}'.format(name))
return layer
def res(num,
name,
bottom,
top,
start_no=0,
z_label='',
n_filter=64,
offset=(0, 0, 0),
size=(32, 32, 3.5),
opacity=0.5):
layers = []
layer_names = [*['{}_{}'.format(name, i) for i in range(num - 1)], top]
for name in layers:
layer = [
tikz.conv(name='{}'.format(name),
offset=offset,
to='{}-east'.format(bottom),
z_label=z_label,
n_filter=str(n_filter),
width=size[2],
height=size[0],
depth=size[1]),
tikz.short_connection('{}'.format(bottom), '{}'.format(name))
]
bottom = name
layers += layer
layers += [
tikz.skip(of=layer_names[1], to=layer_names[-2], pos=1.25),
]
return layers
def mult(name, prev, offset=(1, 0, 0), conn=True):
layer = tikz.multiply(name='{}'.format(name),
to='{}'.format(prev),
offset='{}'.format(offset))
if conn:
layer += tikz.short_connection('{}'.format(prev), '{}'.format(name))
return layer
def upsample(name,
prev='',
z_label='',
n_filter=64,
offset=(1, 0, 0),
size=(32, 32),
width=0,
opacity=0.5,
caption='',
conn=True,
anchor='-east',
anchor_of='-west'):
"""
Generate upsampling layer
Arguments:
name {str} -- layer name
Keyword Arguments:
prev {string} -- name of previous layer
z_label {str} -- label along the z axis of the layer (default: '')
n_filter {int} -- number of filters (default: {64})
offset {str} -- offset between layers (default: {(1,0,0)})
size {tuple} -- size (default: {(32,32)})
width {int} -- width of layers in graph (default: {0})
opacity {float} -- opacity (default: {0.5})
caption {str} -- layer caption (default: {''})
opacity {float} -- opacity (default: {0.5})
conn {bool} -- draw short connection from prev layer (default: {False})
anchor {str} -- position of anchor (default: {'-east'})
Returns:
layer {list} -- list of graph elements
"""
# if names are equal with incrementing numbers, assume name
if not prev:
prev_s = name.split('_')
prev = '{}_{}'.format(prev_s[0], str(int(prev_s[1]) - 1))
if not width:
width = log(n_filter, 4)
if not isinstance(size, tuple):
size = (size, size)
layer = tikz.upsample(
name='{}'.format(name),
z_label=z_label,
n_filter=(n_filter),
offset=offset,
caption=caption,
to='{}{}'.format(prev, anchor),
width=width,
size_1=size,
size_2=(2 * size[0], 2 * size[1]),
)
if conn:
layer += tikz.short_connection(of=prev,
to='{}_0'.format(name),
anchor_of=anchor_of)
return layer
def conv_pool(name,
prev='',
z_label='',
n_filter=64,
offset=(1, 0, 0),
size=(32, 32),
width=0,
caption='',
conn=True,
opacity=0.5,
anchor='-east'):
"""
Generate a convolution layer together with relu activation and pooling
Arguments:
name {str} -- layer name
Keyword Arguments:
prev {str} -- name of previous layer (default: {''})
z_label {str} -- label along the z axis of the layer (default: '')
n_filter {int} -- number of filters (default: {64})
offset {tuple} -- offset to previous layer (default: {(1,0,0)})
size {tuple} -- size (default: {(32,32)})
width {str} -- width of layers in graph (default: {'0'})
caption {str} -- layer caption (default: {''})
conn {bool} -- draw short connection from prev layer (default: {False})
anchor {str} -- position of anchor (default: {'-east'})
Returns:
layer {list} -- list of graph elements
"""
if not isinstance(size, tuple):
size = (size, size)
layer = tikz.conv_relu(
name='{}'.format(name),
z_label=z_label,
n_filter=(n_filter),
offset=offset,
caption=caption,
to='{}{}'.format(prev, anchor),
width=width,
size=size,
)
layer += tikz.pool(name='{}'.format(name),
offset=(0, 0, 0),
to='{}-east'.format(name),
width=1,
height=size[0] - int(size[0] / 4),
depth=size[1] - int(size[0] / 4),
opacity=opacity)
if conn:
layer += tikz.short_connection('{}'.format(prev), '{}'.format(name))
return layer
def block_unconv(name,
bottom,
top,
z_label='',
n_filter=64,
offset=(1, 0, 0),
size=(32, 32, 3.5),
opacity=0.5):
layers = tikz.unpool(name='unpool_{}'.format(name),
offset=offset,
to='({}-east)'.format(bottom),
width=1,
height=size[0],
depth=size[1],
opacity=opacity)
layers += tikz.conv_res(name='ccr_res_{}'.format(name),
offset='(0,0,0)',
to='(unpool_{}-east)'.format(name),
z_label=z_label,
n_filter=str(n_filter),
width=size[2],
height=size[0],
depth=size[1],
opacity=opacity)
layers += tikz.conv(name='ccr_{}'.format(name),
offset='(0,0,0)',
to='(ccr_res_{}-east)'.format(name),
z_label=z_label,
n_filter=str(n_filter),
width=size[2],
height=size[0],
depth=size[1])
layers += tikz.conv_res(name='ccr_res_c_{}'.format(name),
offset='(0,0,0)',
to='(ccr_{}-east)'.format(name),
z_label=z_label,
n_filter=str(n_filter),
width=size[2],
height=size[0],
depth=size[1],
opacity=opacity)
layers += tikz.conv(name='{}'.format(top),
offset='(0,0,0)',
to='(ccr_res_c_{}-east)'.format(name),
z_label=z_label,
n_filter=str(n_filter),
width=size[2],
height=size[0],
depth=size[1])
layers += tikz.short_connection('{}'.format(bottom),
'unpool_{}'.format(name))
return layers
def conv(name,
prev='',
z_label='',
n_filter=64,
offset=(1, 0, 0),
size=(32, 32),
width=0,
caption=' ',
conn=True,
anchor='-east'):
"""
Generate a convolution layer
Arguments:
name {str} -- layer name
Keyword Arguments:
prev {str} -- name of previous layer (default: {''})
z_label {str} -- label along the z axis of the layer (default: '')
n_filter {int} -- number of filters (default: {64})
offset {tuple} -- offset to previous layer (default: {(1,0,0)})
size {tuple} -- size (default: {(32,32)})
width {str} -- width of layers in graph (default: {'0'})
caption {str} -- layer caption (default: {''})
conn {bool} -- draw short connection from prev layer (default: {False})
anchor {str} -- position of anchor (default: {'-east'})
Returns:
layer {list} -- list of graph elements
"""
if not isinstance(size, tuple):
size = (size, size)
if not prev:
# assuming that layer names are given in a uniform way with incrementing numbers
prev_s = name.split('_')
prev = '{}_{}'.format(prev_s[0], str(int(prev_s[1]) - 1))
if not width:
width = log(n_filter, 4)
layer = tikz.conv(
name='{}'.format(name),
z_label=z_label,
n_filter=(n_filter),
offset=offset,
caption=caption,
to='{}{}'.format(prev, anchor),
width=width,
size=size,
)
if conn:
layer += tikz.short_connection('{}'.format(prev), '{}'.format(name))
return layer
def shortcut(name,
prev,
offset=(1, 0, 0),
size=[40, 40],
anchor='-east',
caption='',
z_label='',
conn=True):
layer = tikz.shortcut(name='{}'.format(name),
z_label=z_label,
to='{}{}'.format(prev, anchor),
offset='{}'.format(offset),
caption=caption,
size=size)
if conn:
layer += tikz.short_connection(of=prev, to=name)
return layer
def yolo(name,
prev='',
z_label='',
n_filter=64,
offset='(-1,0,4)',
size=[32, 32],
width=1,
scale=32,
caption=' ',
conn=True,
anchor='-east',
image=False,
path='\\input_image',
grid=False,
steps=1):
if not prev:
# if names are equal with incrementing numbers, assume name
prev_s = name.split('_')
prev = '{}_{}'.format(prev_s[0], str(int(prev_s[1]) - 1))
if not width:
width = log(n_filter, 4)
layer = tikz.detect(name='{}'.format(name),
z_label=z_label,
n_filter=(n_filter),
offset=offset,
caption=caption,
to='{}{}'.format(prev, anchor),
width=width,
size=size)
if image:
layer += tikz.image('image_{}'.format(name),
path,
to=(name + anchor),
size=[(size[0] / 5), (size[1] / 5)])
if grid:
layer += tikz.grid('grid_{}'.format(name),
'image_{}'.format(name),
size=[(size[0] / 5), (size[1] / 5)],
steps=steps)
if conn:
layer += tikz.short_connection('{}'.format(prev),
'{}'.format(name),
anchor_of='-near',
anchor_to='-far')
return layer
def create_architecture():
input = 40
arch = []
arch += tikz.start()
arch += tikz.image(name='image_0',
file='\\input_image',
to=('-4,0,0'),
size=(10, 10))
arch += blocks.conv_relu(name='conv_0',
prev='0,0,0',
s_filter='I',
size=(input, input),
caption='0',
n_filter=32,
anchor='')
arch += tikz.short_connection(of='image_0',
to='conv_0',
anchor_of='',
anchor_to='-west')
arch += [
*blocks.multi_conv_relu(num=3,
name='conv',
prev='conv_0',
layer_num=1,
name_start=1,
n_filter=[64, 32, 64],
s_filter='I/2',
offset='(3,0,0)',
size=(input / 2, input / 2),
conn=True)
]
arch += tikz.resample('conv_0', 'conv_1')
# shortcut1
arch += [
*blocks.shortcut(name='short_4',
prev='conv_3',
offset='(1.75,0,0)',
size=(input / 2, input / 2),
caption='4'),
tikz.short_connection(of='conv_3', to='short_4'),
tikz.long_connection('conv_1',
'short_4',
pos=1.3,
anchor_to='-northwest')
]
arch += blocks.multi_conv_relu(num=3,
name='conv',
prev='short_4',
layer_num=5,
name_start=5,
n_filter=[128, 64, 128],
size=(input / 4, input / 4),
conn=True,
offset='(1.5,0,0)')
# downsample
arch += tikz.resample(of='short_4', to='conv_5')
arch += [
*blocks.shortcut(name='short_8',
prev='conv_7',
size=(input / 4, input / 4),
caption='8',
s_filter='I/4'),
tikz.long_connection('conv_5', 'short_8', pos=1.5),
tikz.short_connection(of='conv_7', to='short_8')
]
arch += [
*blocks.shortcut(name='short_11',
prev='short_8',
size=(input / 8, input / 8),
caption='11',
s_filter='I/8')
]
arch += tikz.ellipsis(of='short_8', to='short_11')
arch += [
*blocks.shortcut(name='short_36',
prev='short_11',
size=(input / 16, input / 16),
caption='36')
]
arch += tikz.ellipsis(of='short_11', to='short_36')
arch += [
*blocks.shortcut(name='short_61',
prev='short_36',
size=(input / 32, input / 32),
caption='61')
]
arch += tikz.ellipsis(of='short_36', to='short_61')
# first yolo layer
arch += [
*blocks.conv_relu(name='conv_79',
prev='short_61',
n_filter=(512),
size=(input / 32, input / 32),
caption='79')
]
arch += tikz.ellipsis(of='short_61', to='conv_79')
arch += [
*blocks.multi_conv_relu_z(num=3,
name='conv',
prev='conv_79',
layer_num=80,
name_start=80,
n_filter=[512, 1024, 256],
s_filter='I/32',
size=(input / 32, input / 32),
conn=True,
offset=3)
]
arch += [
*blocks.yolo(name='yolo_83',
prev='conv_82',
n_filter=(256),
size=(input / 32, input / 32),
caption='83',
offset='(-0.75, 0, 3)',
image=True,
conn=True,
grid=True)
]
# resample
arch += [
*blocks.conv_relu(name='conv_85',
prev='conv_79',
n_filter=(256),
size=(input / 32, input / 32),
caption='85',
conn=True)
]
arch += [
*blocks.upsample(name='conv_86',
prev='conv_85',
s_filter='I/16',
n_filter=(256),
size=(input / 32, input / 32),
caption='86',
conn=True)
]
arch += [*blocks.conc(name='conc_87', prev='conv_86', offset='(1.25,0,0)')]
arch += tikz.long_connection(of='short_61', to='conc_87', pos=3)
# second yolo layer
arch += [
*blocks.conv_relu(name='conv_90',
prev='conc_87',
n_filter=(512),
size=(input / 16, input / 16),
caption='90')
]
arch += tikz.ellipsis(of='conc_87', to='conv_90')
arch += [
*blocks.multi_conv_relu_z(num=3,
name='conv',
prev='conv_90',
layer_num=91,
name_start=91,
n_filter=[256, 512, 256],
s_filter='I/16',
size=(input / 16, input / 16),
conn=True,
offset=3)
]
arch += [
*blocks.yolo(name='yolo_94',
prev='conv_93',
n_filter=(256),
size=(input / 16, input / 16),
caption='94',
offset='(-0.75, 0, 3)',
image=True,
conn=True,
grid=True)
]
# resample
arch += [
*blocks.conv_relu(name='conv_96',
prev='conv_90',
n_filter=(128),
size=(input / 16, input / 16),
caption='96',
conn=True)
]
arch += [
*blocks.upsample(name='conv_97',
prev='conv_96',
s_filter='I/8',
n_filter=(128),
size=(input / 16, input / 16),
caption='97',
conn=True)
]
arch += [*blocks.conc(name='conc_98', prev='conv_97', offset=(1.25, 0, 0))]
arch += tikz.long_connection(of='short_36', to='conc_98', pos=3.25)
# third yolo layer
arch += [
*blocks.conv_relu(name='conv_102',
prev='conc_98',
n_filter=(512),
size=(input / 8, input / 8),
caption='103')
]
arch += tikz.ellipsis(of='conc_98', to='conv_102')
arch += [
*blocks.multi_conv_relu_z(num=3,
name='conv',
prev='conv_102',
layer_num=103,
name_start=103,
n_filter=[128, 256, 256],
s_filter='I/8',
size=(input / 8, input / 8),
conn=True,
offset=4)
]
arch += [
*blocks.yolo(name='yolo_106',
prev='conv_105',
n_filter=(256),
size=(input / 8, input / 8),
caption='106',
offset='(-1, 0, 4)',
image=True,
conn=True,
grid=True)
]
# resample
arch += [
*blocks.conv_relu(name='conv_108',
prev='conv_102',
n_filter=(128),
size=(input / 8, input / 8),
caption='108',
conn=True)
]
arch += [
*blocks.upsample(name='conv_109',
prev='conv_108',
s_filter='I/4',
n_filter=(128),
size=(input / 8, input / 8),
caption='109',
conn=True)
]
arch += [
*blocks.conc(name='conc_110', prev='conv_109', offset=(1.25, 0, 0))
]
arch += tikz.long_connection(of='short_11', to='conc_110', pos=3)
# forth yolo layer
arch += [
*blocks.conv_relu(name='conv_114',
prev='conc_110',
n_filter=(512),
size=(input / 4, input / 4),
caption='114')
]
arch += tikz.ellipsis(of='conc_110', to='conv_114')
arch += [
*blocks.multi_conv_relu_z(num=3,
name='conv',
prev='conv_114',
layer_num=115,
name_start=115,
n_filter=[64, 128, 256],
s_filter='I/4',
size=(input / 4, input / 4),
conn=True,
offset=6)
]
arch += [
*blocks.yolo(name='yolo_4',
prev='conv_117',
n_filter=(256),
size=(input / 4, input / 4),
caption='118',
offset='(-0.75, 0, 6)',
image=True,
conn=True,
grid=True,
steps=13)
]
# resample
arch += [
*blocks.conv_relu(name='conv_120',
prev='conv_114',
n_filter=(128),
size=(input / 4, input / 4),
caption='120',
conn=True)
]
arch += [
*blocks.upsample(name='conv_121',
prev='conv_120',
s_filter='I/2',
n_filter=(128),
size=(input / 4, input / 4),
caption='121',
conn=True)
]
arch += [
*blocks.conc(name='conc_122', prev='conv_121', offset=(1.5, 0, 0))
]
arch += tikz.long_connection(of='short_4',
to='conc_122',
pos=1.5,
anchor_of_1='-southeast',
anchor_of_2='-northeast')
# fith yolo layer
arch += [
*blocks.conv_relu(name='conv_126',
prev='conc_122',
n_filter=(128),
size=(input / 2, input / 2),
caption='126',
offset='(2,0,0)')
]
arch += tikz.ellipsis(of='conc_122', to='conv_126')
arch += [
*blocks.multi_conv_relu_z(num=3,
name='conv',
prev='conv_126',
layer_num=127,
name_start=127,
n_filter=[32, 64, 256],
s_filter='I/2',
size=(input / 2, input / 2),
conn=True,
offset=8)
]
arch += [
*blocks.yolo(name='yolo_130',
prev='conv_129',
n_filter=(256),
size=(input / 2, input / 2),
caption='130',
offset='(-0.5, 0, 8)',
image=True,
conn=True,
grid=True,
steps=20)
]
arch += tikz.legend()
arch += tikz.env_end()
return arch
def multi_conv_relu_z(num,
name,
prev,
layer_num=0,
z_label='',
n_filter='',
name_start=0,
offset=(1, 0, 0),
width='0',
size=(32, 32),
opacity=0.5,
conn=True,
anchor='-east'):
"""Generate multiple convolution layers with relu activation along the z axis
Arguments:
num {int} -- number of layers
name {string} -- block name
prev {string} -- name of previous layer
Keyword Arguments:
layer_num {int} -- layer number in the network (default: {0})
z_label {str} -- label along the z axis of the layer (default: '')
n_filter {int} -- number of filters (default: {64})
name_start {int} -- number of the first layer, succeeding layers get incrementing numbers (default: {0})
offset {str} -- offset between layers (default: {(1,0,0)})
width {str} -- width of layers in graph (default: {'0'})
size {tuple} -- [description] (default: {(32,32)})
opacity {float} -- [description] (default: {0.5})
conn {bool} -- [description] (default: {False})
anchor {str} -- [description] (default: {'-east'})
Returns:
layers {list} -- list of graph elements
"""
layers = []
j = 0
layer_names = [
*[
'{}_{}'.format(name, i)
for i in range(name_start, num + name_start)
]
]
if not isinstance(n_filter, list):
n_filter = [n_filter] * num
if isinstance(offset, int):
offset_str = '({},{},{})'.format(-(4 / offset), 0, offset)
else:
offset_str = offset
if not isinstance(size, tuple):
size = (size, size)
# first layer
layer = [
tikz.conv_relu(name='{}'.format(layer_names[0]),
offset=offset_str,
to='{}{}'.format(prev, anchor),
size=size,
width=log(n_filter[j], 4))
]
j += 1
layers = layer
if conn:
layers += tikz.short_connection(of=prev,
to=layer_names[0],
anchor_of='-near',
anchor_to='-far')
prev = layer_names[0]
# middle layers
for l_name in layer_names[1:-1]:
layer = [
tikz.conv_relu(name='{}'.format(l_name),
offset=offset_str,
to='{}{}'.format(prev, anchor),
size=size,
width=log(n_filter[j], 4))
]
layers += layer
j += 1
if conn:
layers += tikz.short_connection(of=prev,
to=l_name,
anchor_of='-near',
anchor_to='-far')
prev = l_name
# last layer
layer = [
tikz.conv_relu(name='{}'.format(layer_names[-1]),
caption=str(layer_num + j),
offset=offset_str,
to='{}{}'.format(prev, anchor),
z_label=z_label,
n_filter=n_filter[j],
size=size,
width=log(n_filter[j], 4))
]
layers += layer
if conn:
layers += tikz.short_connection(of=prev,
to=layer_names[-1],
anchor_of='-near',
anchor_to='-far')
return layers
def bottleneck(num,
name,
prev,
layer_num=0,
z_label='',
n_filter=64,
name_start=0,
offset=(1, 0, 0),
width=0,
size=(32, 32),
opacity=0.5,
conn=True,
anchor='-east',
ellipsis=False,
pos=1.5):
"""Generate multiple convolution layers with relu activation
Arguments:
num {int} -- number of layers
name {string} -- block name
prev {string} -- name of previous layer
Keyword Arguments:
layer_num {int} -- layer number in the network (default: {0})
z_label {str} -- label along the z axis of the layer (default: '')
n_filter {int} -- number of filters (default: {64})
name_start {int} -- number of the first layer, succeeding layers get incrementing numbers (default: {0})
offset {tuple} -- offset between layers (default: {(1,0,0)})
width {int} -- width of layers in graph (default: {0})
size {tuple} -- size (default: {(32,32)})
opacity {float} -- opacity (default: {0.5})
conn {bool} -- draw short connection from prev layer (default: {True})
anchor {str} -- position of anchor (default: {'-east'})
ellipsis {bool} -- draw an ellipsis before the first layer (default: {False})
pos {int} -- position of the long connection (default: {1.5})
Returns:
layers {list} -- list of graph elements
"""
layers = []
j = 0
prev_layer = prev
layer_names = [
*[
'{}_{}'.format(name, i)
for i in range(name_start, num + name_start)
]
]
if not isinstance(n_filter, list):
n_filter = [n_filter] * num
if not isinstance(size, tuple):
size = (size, size)
# first layer
layer = [
tikz.conv_relu(name='{}'.format(layer_names[0]),
caption=str(layer_num + j),
offset=offset,
to='{}{}'.format(prev, anchor),
n_filter=n_filter[j],
size=size,
width=log(n_filter[j], 4))
]
j += 1
layers = layer
if conn:
layers += tikz.short_connection(prev,
layer_names[0],
name='({}_connection)'.format(name),
options='pos=0.55')
if ellipsis:
layers += tikz.ellipsis(prev, layer_names[0])
layers += r'''
\coordinate [shift={(-0.25,0,0)}] (''' + name + '''_connection) at (''' + layer_names[
0] + '''-west);
'''
prev = layer_names[0]
# middle layers
for l_name in layer_names[1:-1]:
layer = [
tikz.conv_relu(name='{}'.format(l_name),
caption=str(layer_num + j),
offset='(0,0,0)',
to='{}{}'.format(prev, anchor),
n_filter=n_filter[j],
size=size,
width=log(n_filter[j], 4))
]
prev = l_name
layers += layer
j += 1
# last layer
layer = [
tikz.conv_relu(name='{}'.format(layer_names[-1]),
caption=str(layer_num + j),
offset='(0,0,0)',
to='{}{}'.format(prev, anchor),
z_label=z_label,
n_filter=n_filter[j],
size=size,
width=log(n_filter[j], 4))
]
layers += layer
prev = layer_names[-1]
# layers += tikz.relu(
# name='{}_relu'.format(layer_names[-1]),
# to='{}{}'.format(prev, anchor),
# offset=(1, 0, 0),
# size=size)
# layers += tikz.short_connection('{}'.format(layer_names[-1]), '{}_relu'.format(layer_names[-1]))
layers += tikz.long_connection_reversed('{}'.format(layer_names[-1]),
'{}_connection'.format(name),
pos=pos,
anchor_to='')
return layers
def multi_conv_relu(num,
name,
prev,
layer_num=0,
z_label='',
n_filter=64,
name_start=0,
offset=(1, 0, 0),
width=0,
size=(32, 32),
opacity=0.5,
conn=True,
anchor='-east'):
"""Generate multiple convolution layers with relu activation
Arguments:
num {int} -- number of layers
name {string} -- block name
prev {string} -- name of previous layer
Keyword Arguments:
layer_num {int} -- layer number in the network for the caption (default: {0})
z_label {str} -- label along the z axis of the layer (default: '')
n_filter {int} -- number of filters (default: {64})
name_start {int} -- number of the first layer, succeeding layers get incrementing numbers (default: {0})
offset {tuple} -- offset between layers (default: {(1,0,0)})
width {int} -- width of layers in graph (default: {0})
size {tuple} -- size (default: {(32,32)})
opacity {float} -- opacity (default: {0.5})
conn {bool} -- draw short connection from prev layer (default: {False})
anchor {str} -- position of anchor (default: {'-east'})
Returns:
layers {list} -- list of graph elements
"""
layers = []
j = 0
layer_names = [
*[
'{}_{}'.format(name, i)
for i in range(name_start, num + name_start)
]
]
if not isinstance(n_filter, list):
n_filter = [n_filter] * num
if not isinstance(size, tuple):
size = (size, size)
# first layer
layer = [
tikz.conv_relu(name='{}'.format(layer_names[0]),
caption=str(layer_num + j) if layer_num else '',
offset=offset,
to='{}{}'.format(prev, anchor),
n_filter=n_filter[j],
size=size,
width=log(n_filter[j], 4))
]
j += 1
layers = layer
if conn:
layers += tikz.short_connection(prev, layer_names[0])
prev = layer_names[0]
# middle layers
for l_name in layer_names[1:-1]:
layer = [
tikz.conv_relu(name='{}'.format(l_name),
caption=str(layer_num + j) if layer_num else '',
offset='(0,0,0)',
to='{}{}'.format(prev, anchor),
n_filter=n_filter[j],
size=size,
width=log(n_filter[j], 4))
]
prev = l_name
layers += layer
j += 1
# last layer
layer = [
tikz.conv_relu(name='{}'.format(layer_names[-1]),
caption=str(layer_num + j) if layer_num else '',
offset='(0,0,0)',
to='{}{}'.format(prev, anchor),
z_label=z_label,
n_filter=n_filter[j],
size=size,
width=log(n_filter[j], 4))
]
layers += layer
return layers
def conv_relu(name,
prev='',
z_label='',
n_filter=64,
offset=(1, 0, 0),
size=(32, 32),
width=0,
caption='',
conn=True,
anchor='-east',
anchor_to='-west',
rtl=False):
"""Generate convolution layer with relu activation
Arguments:
name {string} -- layer name
Keyword Arguments:
prev {str} -- name of previous layer (default: {''})
z_label {str} -- label along the z axis of the layer (default: '')
n_filter {int} -- number of filters (default: {64})
offset {tuple} -- offset to previous layer (default: {(1,0,0)})
size {int|tuple} -- [description] (default: {(32,32)})
width {str} -- width of layers in graph (default: {'0'})
caption {str} -- layer caption (default: {''})
conn {bool} -- draw short connection from prev layer (default: {False})
anchor {str} -- position of anchor (default: {'-east'})
Returns:
layer {list} -- list of graph elements
"""
# if names are equal with incrementing numbers, assume name
if not prev:
prev_s = name.split('_')
prev = '{}_{}'.format(prev_s[0], str(int(prev_s[1]) - 1))
if not width:
width = log(n_filter, 4)
if not isinstance(size, tuple):
size = (size, size)
if rtl:
layer = tikz.rtl_conv_relu(name='{}'.format(name),
z_label=z_label,
n_filter=(n_filter),
offset=offset,
caption=caption,
to='{}{}'.format(prev, anchor),
width=width,
size=size)
else:
layer = tikz.conv_relu(name='{}'.format(name),
z_label=z_label,
n_filter=(n_filter),
offset=offset,
caption=caption,
to='{}{}'.format(prev, anchor),
width=width,
size=size)
if conn:
layer += tikz.short_connection('{}'.format(prev),
'{}'.format(name),
anchor_of=anchor,
anchor_to=anchor_to)
return layer
def multi_conv(num,
name,
prev,
layer_num=0,
z_label='',
n_filter=64,
scale=32,
name_start=0,
offset=(1, 0, 0),
width='0',
size=(32, 32),
opacity=0.5,
conn=True,
anchor='-east'):
"""
Generate a block of multiple convolution layers
Arguments:
num {[type]} -- [description]
name {[type]} -- [description]
prev {[type]} -- [description]
Keyword Arguments:
layer_num {int} -- [description] (default: {0})
z_label {str} -- [description] (default: {256})
n_filter {int} -- [description] (default: {64})
scale {int} -- [description] (default: {32})
name_start {int} -- [description] (default: {0})
offset {tuple} -- [description] (default: {(1, 0, 0)})
width {str} -- [description] (default: {'0'})
size {tuple} -- [description] (default: {(32, 32)})
opacity {float} -- [description] (default: {0.5})
conn {bool} -- [description] (default: {False})
anchor {str} -- [description] (default: {'-east'})
Returns:
[type] -- [description]
"""
layers = []
j = 0
layer_names = [
*[
'{}_{}'.format(name, i)
for i in range(name_start, num + name_start)
]
]
if not isinstance(n_filter, list):
n_filter = [n_filter] * num
if not isinstance(size, tuple):
size = (size, size)
# first layer
layer = [
tikz.conv(name='{}'.format(layer_names[0]),
caption=str(layer_num + j),
offset=offset,
to='{}{}'.format(prev, anchor),
n_filter=n_filter[j],
size=size,
width=log(n_filter[j], 4))
]
j += 1
layers = layer
if conn:
layers += tikz.short_connection(prev, layer_names[0])
prev = layer_names[0]
# middle layers
for l_name in layer_names[1:-1]:
layer = [
tikz.conv(name='{}'.format(l_name),
caption=str(layer_num + j),
offset='(0,0,0)',
to='{}{}'.format(prev, anchor),
n_filter=n_filter[j],
size=size,
width=log(n_filter[j], 4))
]
prev = l_name
layers += layer
j += 1
# last layer
layer = [
tikz.conv(name='{}'.format(layer_names[-1]),
caption=str(layer_num + j),
offset='(0,0,0)',
to='{}{}'.format(prev, anchor),
z_label=z_label,
n_filter=n_filter[j],
size=size,
width=log(n_filter[j], 4))
]
layers += layer
return layers
def create_architecture():
input = 40
base_width = 64
arch = []
arch += tikz.start()
arch += tikz.image(name='image_0',
file='\\input_image',
to=('-3,0,0'),
size=(10, 10))
arch += blocks.conv_relu(name='conv_0_0',
prev='0,0,0',
z_label='I',
size=(input, input),
n_filter=64,
anchor='',
conn=False)
arch += tikz.short_connection(of='image_0',
to='conv_0_0',
anchor_of='',
fill='')
arch += blocks.conv_relu(name='conv_0_1',
prev='conv_0_0',
z_label='I/2',
size=(input / 2, input / 2),
n_filter=64,
offset=(2, 0, 0),
conn=False)
arch += tikz.short_connection(of='conv_0_0', to='conv_0_1', fill='')
arch += tikz.resample('conv_0_0', 'conv_0_1')
arch += blocks.conv_relu(name='conv_1_0',
prev='conv_0_1',
z_label='I/4',
size=(input / 4, input / 4),
n_filter=64,
offset=(1, 0, 0),
conn=False)
arch += tikz.short_connection(of='conv_0_1', to='conv_1_0', fill='')
arch += tikz.resample('conv_0_1', 'conv_1_0')
arch += tikz.pool(name='pool_0',
width=2,
to='conv_1_0',
size=(input / 4, input / 4),
offset=(1, 0, 0))
arch += tikz.short_connection(of='conv_1_0', to='pool_0', fill='')
# arch += blocks.multi_conv_relu(num=3, name='conv_1', prev='conv_1_0', name_start=1,
# n_filter=[64, 64, 256], size=(input / 4, input / 4),
# offset=(1.5, 0, 0))
# arch += blocks.tikz.long_connection('conv_1_0', 'conv_1_3', pos=1.5, anchor_to='-northeast')
arch += blocks.bottleneck(3,
'bottleneck_1',
prev='pool_0',
size=(input / 4, input / 4),
n_filter=[64, 64, 256],
offset=(1.5, 0, 0),
layer_num=5)
arch += blocks.bottleneck(3,
'bottleneck_2',
prev='bottleneck_1_2',
size=(input / 4, input / 4),
n_filter=[64, 64, 256],
offset=(1.5, 0, 0),
layer_num=8)
arch += blocks.bottleneck(3,
'bottleneck_3',
prev='bottleneck_2_2',
size=(input / 4, input / 4),
n_filter=[64, 64, 256],
offset=(1.5, 0, 0),
layer_num=11)
arch += blocks.bottleneck(3,
'bottleneck_4',
prev='bottleneck_3_2',
size=(input / 8, input / 8),
n_filter=[128, 128, 512],
offset=(3, 0, 0),
layer_num=14)
arch += blocks.bottleneck(3,
'bottleneck_7',
prev='bottleneck_4_2',
size=(input / 8, input / 8),
n_filter=[128, 128, 512],
offset=(1.5, 0, 0),
conn=False,
ellipsis=True,
layer_num=24)
arch += blocks.bottleneck(3,
'bottleneck_8',
prev='bottleneck_7_2',
size=(input / 16, input / 16),
n_filter=[256, 256, 1024],
offset=(1.5, 0, 0),
pos=2,
layer_num=27)
arch += blocks.bottleneck(3,
'bottleneck_13',
prev='bottleneck_8_2',
size=(input / 16, input / 16),
n_filter=[256, 256, 1024],
offset=(1.5, 0, 0),
pos=2,
conn=False,
ellipsis=True,
layer_num=43)
arch += blocks.bottleneck(3,
'bottleneck_14',
prev='bottleneck_13_2',
size=(input / 32, input / 32),
n_filter=[512, 512, 2048],
offset=(1.5, 0, 0),
pos=3,
layer_num=46)
arch += blocks.bottleneck(3,
'bottleneck_16',
prev='bottleneck_14_2',
size=(input / 32, input / 32),
layer_num=53,
n_filter=[512, 512, 2048],
offset=(1.5, 0, 0),
pos=3,
conn=False,
ellipsis=True)
arch += tikz.coordinate('resnet_last_dummy',
of='bottleneck_16_2-east',
offset=(3, 0, 0))
arch += tikz.coordinate('resnet_connection_dummy',
of='resnet_last_dummy',
offset=(0, 0, 6))
arch += tikz.short_connection(of='bottleneck_16_2',
to='resnet_last_dummy',
anchor_to='')
arch += tikz.short_connection(to='resnet_connection_dummy',
of='resnet_last_dummy',
anchor_to='',
anchor_of='')
arch += tikz.pool(name='pool_1',
width=2,
to='bottleneck_16_2',
size=(input / 4, input / 4),
offset=(0, -5, 0),
anchor='-center',
caption='$1 \\times 1$')
arch += blocks.conv_relu(name='conv_pool_1',
prev='pool_1',
offset=(-2.5, 0, 0),
size=(input / 32, input / 32),
n_filter=512,
anchor='-west',
conn=False,
rtl=True)
arch += tikz.short_connection(of='pool_1',
to='conv_pool_1',
anchor_of='-west',
anchor_to='-east',
options='pos=0.75')
arch += tikz.pool(name='pool_2',
width=2,
to='pool_1',
size=(input / 4, input / 4),
offset=(0, 0, 6),
anchor='-center',
caption='$2 \\times 2$')
arch += tikz.grid(name='grid_2', at='pool_2', steps=2)
arch += blocks.conv_relu(name='conv_pool_2',
prev='pool_2',
offset=(-2.5, 0, 0),
size=(input / 32, input / 32),
n_filter=512,
anchor='-west',
conn=False,
rtl=True)
arch += tikz.short_connection(of='pool_2',
to='conv_pool_2',
anchor_of='-west',
anchor_to='-east',
options='pos=0.75')
arch += tikz.pool(name='pool_3',
width=2,
to='pool_2',
size=(input / 4, input / 4),
offset=(0, 0, 6),
anchor='-center',
caption='$4 \\times 4$')
arch += tikz.grid(name='grid_3', at='pool_3', steps=4)
arch += blocks.conv_relu(name='conv_pool_3',
prev='pool_3',
offset=(-2.5, 0, 0),
size=(input / 32, input / 32),
n_filter=512,
anchor='-west',
conn=False,
rtl=True)
arch += tikz.short_connection(of='pool_3',
to='conv_pool_3',
anchor_of='-west',
anchor_to='-east',
options='pos=0.75')
arch += tikz.pool(name='pool_4',
width=2,
to='pool_3',
size=(input / 4, input / 4),
offset=(0, 0, 6),
anchor='-center',
caption='$8 \\times 8$')
arch += tikz.grid(name='grid_4', at='pool_4', steps=8)
arch += blocks.conv_relu(name='conv_pool_4',
prev='pool_4',
offset=(-2.5, 0, 0),
size=(input / 32, input / 32),
n_filter=512,
anchor='-west',
conn=False,
rtl=True)
arch += tikz.short_connection(of='pool_4',
to='conv_pool_4',
anchor_of='-west',
anchor_to='-east',
options='pos=0.75')
arch += blocks.conc(name='conc_1',
prev='pool_2',
offset=(-5, 0, 2.5),
conn=False)
arch += tikz.coordinate('dummy_pool_1', 'pool_1-east', (5, 0, 0))
arch += tikz.coordinate('dummy_pool_2', 'pool_2-east', (5, 0, 0))
arch += tikz.coordinate('dummy_pool_3', 'pool_3-east', (5, 0, 0))
arch += tikz.coordinate('dummy_pool_4', 'pool_4-east', (5, 0, 0))
arch += tikz.short_connection('dummy_pool_1',
'pool_1',
anchor_of='',
anchor_to='-east')
arch += tikz.double_connection('dummy_pool_1',
'dummy_pool_2',
'pool_2',
anchor_of='',
anchor_to='-east')
arch += tikz.double_connection('dummy_pool_2',
'dummy_pool_3',
'pool_3',
anchor_of='',
anchor_to='-east')
arch += tikz.double_connection('dummy_pool_3',
'dummy_pool_4',
'pool_4',
anchor_of='',
anchor_to='-east')
arch += tikz.z_connection(of='resnet_last_dummy',
to='dummy_pool_1',
anchor_to='',
shift=(6, 0, 0),
anchor_of='')
# arch += tikz.z_connection(of='conv_5_0_1', to='pool_2', anchor_of='-anchor', anchor_to='-east', shift=(-1, -1.5, 2))
# arch += tikz.short_connection(of='conv_5_0_1', to='pool_3', anchor_of='-west', anchor_to='-south')
# arch += tikz.z_connection(of='conv_5_0_1', to='pool_4', anchor_of='-west', anchor_to='-north', shift=(0, 0, 0))
arch += tikz.z_connection('conv_pool_1',
'conc_1',
anchor_of='-west',
anchor_to='-northeast',
shift=(-2, 0, 0))
arch += tikz.z_connection('conv_pool_2',
'conc_1',
anchor_of='-west',
anchor_to='-east',
shift=(0, 0, 0))
arch += tikz.z_connection('conv_pool_3',
'conc_1',
anchor_of='-west',
anchor_to='-southeast',
shift=(-0, 0, 0))
arch += tikz.z_connection('conv_pool_4',
'conc_1',
anchor_of='-west',
anchor_to='-southwest',
shift=(-2, 0, 0))
arch += tikz.z_connection('resnet_connection_dummy',
'conc_1',
anchor_of='',
anchor_to='-northwest',
shift=(-4.5, 0, 0))
arch += blocks.conv_relu(name='conv_60',
prev='conc_1',
offset=(-2.5, 0, 0),
size=(input / 32, input / 32),
n_filter=512,
anchor='-west',
conn=False)
arch += tikz.short_connection(of='conc_1',
to='conv_60',
anchor_of='-west',
anchor_to='-east',
options='pos=0.75')
arch += blocks.conv_relu(name='conv_60',
prev='conc_1',
offset=(-2.5, 0, 0),
size=(input / 32, input / 32),
n_filter=512,
anchor='-west',
conn=False,
rtl=True)
arch += tikz.z_conv_relu(name='conv_61',
to='bottleneck_14_connection',
offset=(0, 0, 8),
size=(input / 16, input / 16),
n_filter=512)
arch += tikz.short_connection('bottleneck_14_connection',
'conv_61',
anchor_of='',
anchor_to='-far')
arch += blocks.sum(
name='sum_1',
prev='conv_60',
offset=(-3, 2, 0),
conn=False,
)
arch += tikz.short_connection('conv_61',
'sum_1',
anchor_of='-near',
anchor_to='-northeast')
arch += blocks.upsample(name='up_1',
prev='sum_1',
offset=(-2.5, 0, 0),
size=(input / 16, input / 16),
n_filter=512,
anchor='-west',
anchor_of='-west',
conn=True)
arch += blocks.conv_relu(name='conv_62',
prev='conv_60',
offset=(-5, 0, 9.4),
size=(input / 16, input / 16),
n_filter=512,
anchor='-west',
conn=False,
rtl=True)
arch += tikz.z_connection(of='conv_60',
to='sum_1',
anchor_of='-farwest',
anchor_to='-east',
shift=(-0.3, 0, -5))
arch += tikz.z_conv_relu(name='conv_63',
to='bottleneck_8_connection',
offset=(0, 0, 8),
size=(input / 8, input / 8),
n_filter=512)
arch += tikz.short_connection('bottleneck_8_connection',
'conv_63',
anchor_of='',
anchor_to='-far')
arch += blocks.sum(name='sum_2',
prev='up_1',
offset=(-3, 0, 0),
conn=False)
arch += tikz.short_connection('conv_63',
'sum_2',
anchor_of='-near',
anchor_to='-northeast')
arch += tikz.short_connection('up_1',
'sum_2',
anchor_of='-west',
anchor_to='-east')
arch += blocks.upsample(name='up_2',
prev='sum_2',
offset=(-2.5, 0, 0),
size=(input / 8, input / 8),
n_filter=512,
anchor='-west',
anchor_of='-west')
arch += tikz.z_conv_relu(name='conv_64',
to='up_1-south',
offset=(-0.2, 0, 5),
size=(input / 8, input / 8),
n_filter=512)
arch += tikz.short_connection(of='up_1',
to='conv_64',
anchor_of='-nearsouthwest',
anchor_to='-far')
arch += tikz.z_conv_relu(name='conv_65',
to='bottleneck_4_connection',
offset=(-0.25, 0, 10),
size=(input / 4, input / 4),
n_filter=512)
arch += tikz.short_connection('bottleneck_4_connection',
'conv_65',
anchor_of='',
anchor_to='-far',
options='pos=0.6')
arch += blocks.sum(name='sum_3',
prev='up_2',
offset=(-3, 0, 0),
conn=False)
arch += tikz.short_connection('conv_65',
'sum_3',
anchor_of='-near',
anchor_to='-northeast')
arch += tikz.short_connection('up_2',
'sum_3',
anchor_of='-west',
anchor_to='-east')
arch += tikz.z_conv_relu(name='conv_66',
to='up_2-nearsouthwest',
offset=(-0.65, 0, 3),
size=(input / 4, input / 4),
n_filter=512)
arch += tikz.short_connection(of='up_2',
to='conv_66',
anchor_of='-nearsouthwest',
anchor_to='-far',
fill='')
arch += tikz.z_conv_relu(name='up_3',
to='sum_3-southwest',
offset=(-0.75, 0, 6),
size=(input / 4, input / 4),
n_filter=512)
arch += tikz.short_connection(of='sum_3',
to='up_3',
anchor_of='-southwest',
anchor_to='-far',
fill='')
arch += blocks.conc(name='conc_2',
prev='conv_62',
offset=(-11, 0.5, 0),
conn=False)
arch += tikz.z_connection(of='conv_60',
to='conv_62',
anchor_of='-nearwest',
anchor_to='-east',
shift=(-1, -2, 4))
arch += tikz.z_connection(of='conv_64',
to='conc_2',
anchor_of='-near',
anchor_to='-east',
shift=(-1, -1.45, 2.75))
arch += tikz.short_connection(of='conv_62',
to='conc_2',
anchor_of='-east',
anchor_to='-south')
arch += tikz.z_connection(of='conv_66',
to='conc_2',
anchor_of='-near',
anchor_to='-northeast',
shift=(0, 0, 0))
arch += tikz.z_connection(of='up_3',
to='conc_2',
anchor_of='-near',
anchor_to='-west',
shift=(0, 0, 6))
arch += blocks.conv_relu(name='conv_67',
prev='conc_2',
n_filter=512,
size=(input / 4, input / 4),
rtl=True,
offset=(-4, 0, 8),
conn=False)
arch += tikz.z_connection(of='conc_2',
to='conv_67',
anchor_of='-southwest',
anchor_to='-east',
shift=(0, 0, 7.1))
arch += blocks.conv_relu(name='conv_68',
prev='conv_67',
n_filter='27',
width=2,
size=(input / 4, input / 4),
rtl=True,
offset=(-3.5, 0, 0),
anchor='-west',
anchor_to='-east')
arch += tikz.soft_max('soft_max',
offset=(-2, 0, 0),
to='conv_68',
size=(input / 4, input / 4),
n_filter=1,
anchor_to='-west')
arch += tikz.short_connection('conv_68',
'soft_max',
anchor_of='-west',
anchor_to='-east')
arch += tikz.results_upsampling()
arch += tikz.spatial_mask()
arch += tikz.legend()
# arch += tikz.resample('image_1', 'image_2')
# arch += tikz.short_connection(of='conv_61', to='sum_1', anchor_of='-east',
# anchor_to='-west')
# arch += tikz.resample('image_1', 'image_2')
# Close environment
arch += tikz.env_end()
return arch
