130 lines
2.9 KiB
Python
130 lines
2.9 KiB
Python
# subter_lenet_arch.py
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# Requires running from inside the PlotNeuralNet repo, like: python3 ../subter_lenet_arch.py
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import sys, argparse
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sys.path.append("../") # import pycore from repo root
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from pycore.tikzeng import *
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parser = argparse.ArgumentParser()
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parser.add_argument("--rep_dim", type=int, default=1024, help="latent size for FC")
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args = parser.parse_args()
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REP = int(args.rep_dim)
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# Visual scales so the huge width doesn't dominate the figure
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H32, H16, H8 = 26, 18, 12
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D2048, D1024, D512 = 52, 36, 24
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W1, W4, W8 = 1, 2, 4
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arch = [
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to_head(".."),
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to_cor(),
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to_begin(),
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to_Conv(
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"latent",
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n_filer="",
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s_filer="latent dim",
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offset="(2,0,0)",
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to="(0,0,0)",
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height=H8 * 1.6,
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depth=1.3,
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width=W1,
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caption=f"Latent Space",
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),
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# to_connection("fc1", "latent"),
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# --------------------------- DECODER ---------------------------
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# FC back to 16384
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to_fc(
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"fc3",
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n_filer="{{4×512×8}}",
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zlabeloffset=0.35,
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offset="(2,-.5,0)",
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to="(latent-east)",
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height=1.3,
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depth=D512,
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width=W1,
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caption=f"FC",
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captionshift=20,
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),
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# to_connection("latent", "fc3"),
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# Reshape to 4×8×512
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to_UnPool(
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"up1",
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n_filer=4,
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offset="(2.5,0,0)",
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to="(fc3-east)",
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height=H16,
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depth=D1024,
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width=W4,
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caption="",
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),
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# Up ×2: 8×512 -> 16×1024 (we just draw a labeled box)
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# DeConv1 (5×5, same): 4->8, 16×1024
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to_Conv(
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"deconv1",
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s_filer="{{1024×16}}",
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zlabeloffset=0.2,
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n_filer=8,
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offset="(0,0,0)",
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to="(up1-east)",
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height=H16,
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depth=D1024,
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width=W8,
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caption="Deconv1",
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),
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# to_connection("fc3", "up1"),
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# Up ×2: 16×1024 -> 32×2048
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to_UnPool(
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"up2",
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offset="(2,0,0)",
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n_filer=8,
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to="(deconv1-east)",
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height=H32,
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depth=D2048,
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width=W8,
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caption="Deconv2",
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captionshift=10,
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),
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# to_connection("deconv1", "up2"),
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# DeConv2 (5×5, same): 8->1, 32×2048
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to_Conv(
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"deconv2",
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s_filer="{{2048×32}}",
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zlabeloffset=0.15,
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n_filer=1,
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offset="(0,0,0)",
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to="(up2-east)",
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height=H32,
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depth=D2048,
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width=W1,
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caption="",
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),
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# to_connection("up2", "deconv2"),
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# Output
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to_Conv(
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"out",
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s_filer="{{2048×32}}",
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zlabeloffset=0.15,
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n_filer=1,
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offset="(2,0,0)",
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to="(deconv2-east)",
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height=H32,
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depth=D2048,
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width=1.0,
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caption="Output",
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captionshift=5,
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),
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# to_connection("deconv2", "out"),
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to_end(),
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]
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def main():
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name = "subter_lenet_arch"
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to_generate(arch, name + ".tex")
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if __name__ == "__main__":
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main()
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