unignored pdfs, added network arch diagrams

thesis/third_party/PlotNeuralNet/deepsad/arch_ef_decoder.py

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+# subter_lenet_arch.py
+# Requires running from inside the PlotNeuralNet repo, like: python3 ../subter_lenet_arch.py
+import sys, argparse
+
+sys.path.append("../")  # import pycore from repo root
+
+from pycore.tikzeng import *
+
+parser = argparse.ArgumentParser()
+parser.add_argument("--rep_dim", type=int, default=1024, help="latent size for FC")
+args = parser.parse_args()
+REP = int(args.rep_dim)
+
+# Visual scales so the huge width doesn't dominate the figure
+H32, H16, H8, H1 = 26, 18, 12, 1
+D2048, D1024, D512, D256, D128, D1 = 52, 36, 24, 12, 6, 1
+W1, W4, W8, W16, W32 = 1, 2, 2, 4, 8
+
+
+arch = [
+    to_head(".."),
+    to_cor(),
+    to_begin(),
+    to_Conv(
+        "latent",
+        n_filer="",
+        s_filer="latent dim",
+        offset="(2,0,0)",
+        to="(0,0,0)",
+        height=H8 * 1.6,
+        depth=D1,
+        width=W1,
+        caption=f"Latent Space",
+    ),
+    # to_connection("fc1", "latent"),
+    # --------------------------- DECODER ---------------------------
+    # FC back to 16384
+    to_fc(
+        "fc3",
+        n_filer="{{8×128×8}}",
+        offset="(2,0,0)",
+        to="(latent-east)",
+        height=H1,
+        depth=D512,
+        width=W1,
+        caption=f"FC",
+    ),
+    to_Conv(
+        "unsqueeze",
+        s_filer="",
+        n_filer=32,
+        offset="(2,0,0)",
+        to="(fc3-east)",
+        height=H8,
+        depth=D128,
+        width=W32,
+        caption="unsqueeze",
+    ),
+    # to_connection("latent", "fc3"),
+    # Reshape to 4×8×512
+    to_UnPool(
+        "up1",
+        offset="(2,0,0)",
+        to="(unsqueeze-east)",
+        height=H16,
+        depth=D256,
+        width=W32,
+        caption="",
+    ),
+    to_Conv(
+        "dwdeconv1",
+        s_filer="",
+        n_filer=1,
+        offset="(0,0,0)",
+        to="(up1-east)",
+        height=H16,
+        depth=D256,
+        width=W1,
+        caption="deconv1",
+    ),
+    to_Conv(
+        "dwdeconv2",
+        s_filer="{{256×16}}",
+        n_filer=32,
+        offset="(0,0,0)",
+        to="(dwdeconv1-east)",
+        height=H16,
+        depth=D256,
+        width=W32,
+        caption="",
+    ),
+    to_UnPool(
+        "up2",
+        offset="(2,0,0)",
+        to="(dwdeconv2-east)",
+        height=H16,
+        depth=D1024,
+        width=W32,
+        caption="",
+    ),
+    to_Conv(
+        "dwdeconv3",
+        s_filer="",
+        n_filer=1,
+        offset="(0,0,0)",
+        to="(up2-east)",
+        height=H16,
+        depth=D1024,
+        width=W1,
+        caption="deconv2",
+    ),
+    to_Conv(
+        "dwdeconv4",
+        s_filer="{{1024×16}}",
+        n_filer=16,
+        offset="(0,0,0)",
+        to="(dwdeconv3-east)",
+        height=H16,
+        depth=D1024,
+        width=W16,
+        caption="",
+    ),
+    to_UnPool(
+        "up3",
+        offset="(2,0,0)",
+        to="(dwdeconv4-east)",
+        height=H32,
+        depth=D2048,
+        width=W16,
+        caption="",
+    ),
+    to_Conv(
+        "dwdeconv5",
+        s_filer="",
+        n_filer=1,
+        offset="(0,0,0)",
+        to="(up3-east)",
+        height=H32,
+        depth=D2048,
+        width=W1,
+        caption="deconv3",
+    ),
+    to_Conv(
+        "dwdeconv6",
+        s_filer="{{2048×32}}",
+        n_filer=8,
+        offset="(0,0,0)",
+        to="(dwdeconv5-east)",
+        height=H32,
+        depth=D2048,
+        width=W8,
+        caption="",
+    ),
+    to_Conv(
+        "outconv",
+        s_filer="{{2048×32}}",
+        n_filer=1,
+        offset="(2,0,0)",
+        to="(dwdeconv6-east)",
+        height=H32,
+        depth=D2048,
+        width=W1,
+        caption="deconv4",
+    ),
+    # to_connection("up2", "deconv2"),
+    # Output
+    to_Conv(
+        "out",
+        s_filer="{{2048×32}}",
+        n_filer=1,
+        offset="(2,0,0)",
+        to="(outconv-east)",
+        height=H32,
+        depth=D2048,
+        width=W1,
+        caption="output",
+    ),
+    # to_connection("deconv2", "out"),
+    to_end(),
+]
+
+
+def main():
+    name = "subter_lenet_arch"
+    to_generate(arch, name + ".tex")
+
+
+if __name__ == "__main__":
+    main()