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Convert submodule PlotNeuralNet into a regular folder

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This commit is contained in:
Jan Kowalczyk
2025-08-13 14:13:00 +02:00
parent bb875cc08e
commit ef0ce7db89
42 changed files with 3856 additions and 0 deletions
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75
thesis/third_party/PlotNeuralNet/pycore/blocks.py vendored Normal file
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from .tikzeng import *
#define new block
def block_2ConvPool( name, botton, top, s_filer=256, n_filer=64, offset="(1,0,0)", size=(32,32,3.5), opacity=0.5 ):
return [
to_ConvConvRelu(
name="ccr_{}".format( name ),
s_filer=str(s_filer),
n_filer=(n_filer,n_filer),
offset=offset,
to="({}-east)".format( botton ),
width=(size[2],size[2]),
height=size[0],
depth=size[1],
),
to_Pool(
name="{}".format( top ),
offset="(0,0,0)",
to="(ccr_{}-east)".format( name ),
width=1,
height=size[0] - int(size[0]/4),
depth=size[1] - int(size[0]/4),
opacity=opacity, ),
to_connection(
"{}".format( botton ),
"ccr_{}".format( name )
)
]
def block_Unconv( name, botton, top, s_filer=256, n_filer=64, offset="(1,0,0)", size=(32,32,3.5), opacity=0.5 ):
return [
to_UnPool( name='unpool_{}'.format(name), offset=offset, to="({}-east)".format(botton), width=1, height=size[0], depth=size[1], opacity=opacity ),
to_ConvRes( name='ccr_res_{}'.format(name), offset="(0,0,0)", to="(unpool_{}-east)".format(name), s_filer=str(s_filer), n_filer=str(n_filer), width=size[2], height=size[0], depth=size[1], opacity=opacity ),
to_Conv( name='ccr_{}'.format(name), offset="(0,0,0)", to="(ccr_res_{}-east)".format(name), s_filer=str(s_filer), n_filer=str(n_filer), width=size[2], height=size[0], depth=size[1] ),
to_ConvRes( name='ccr_res_c_{}'.format(name), offset="(0,0,0)", to="(ccr_{}-east)".format(name), s_filer=str(s_filer), n_filer=str(n_filer), width=size[2], height=size[0], depth=size[1], opacity=opacity ),
to_Conv( name='{}'.format(top), offset="(0,0,0)", to="(ccr_res_c_{}-east)".format(name), s_filer=str(s_filer), n_filer=str(n_filer), width=size[2], height=size[0], depth=size[1] ),
to_connection(
"{}".format( botton ),
"unpool_{}".format( name )
)
]
def block_Res( num, name, botton, top, s_filer=256, n_filer=64, offset="(0,0,0)", size=(32,32,3.5), opacity=0.5 ):
lys = []
layers = [ *[ '{}_{}'.format(name,i) for i in range(num-1) ], top]
for name in layers:
ly = [ to_Conv(
name='{}'.format(name),
offset=offset,
to="({}-east)".format( botton ),
s_filer=str(s_filer),
n_filer=str(n_filer),
width=size[2],
height=size[0],
depth=size[1]
),
to_connection(
"{}".format( botton ),
"{}".format( name )
)
]
botton = name
lys+=ly
lys += [
to_skip( of=layers[1], to=layers[-2], pos=1.25),
]
return lys