reworked network arch diagrams

thesis/third_party/PlotNeuralNet/pycore/tikzeng.py

@@ -69,6 +69,7 @@ def to_Conv(
     s_filer=256,
     n_filer=64,
     offset="(0,0,0)",
+    zlabeloffset=0.3,
     to="(0,0,0)",
     width=1,
     height=40,
@@ -92,6 +93,9 @@ def to_Conv(
         xlabel={{"""
         + str(n_filer)
         + """, }},
+        zlabeloffset="""
+        + str(zlabeloffset)
+        + """,
         zlabel="""
         + str(s_filer)
         + """,
@@ -168,7 +172,10 @@ def to_ConvConvRelu(
 # Pool
 def to_Pool(
     name,
+    n_filer="",
+    s_filer="",
     offset="(0,0,0)",
+    zlabeloffset=0.3,
     to="(0,0,0)",
     width=1,
     height=32,
@@ -187,6 +194,15 @@ def to_Pool(
         name="""
         + name
         + """,
+        xlabel={{"""
+        + str(n_filer)
+        + """, }},
+        zlabeloffset="""
+        + str(zlabeloffset)
+        + """,
+        zlabel="""
+        + str(s_filer)
+        + """,
         caption="""
         + caption
         + r""",
@@ -212,6 +228,7 @@ def to_Pool(
 # unpool4,
 def to_UnPool(
     name,
+    n_filer="",
     offset="(0,0,0)",
     to="(0,0,0)",
     width=1,
@@ -238,6 +255,9 @@ def to_UnPool(
         opacity="""
         + str(opacity)
         + """,
+        xlabel={{"""
+        + str(n_filer)
+        + """, }},
         height="""
         + str(height)
         + """,
@@ -360,6 +380,7 @@ def to_SoftMax(
     depth=25,
     opacity=0.8,
     caption=" ",
+    z_label_offset=0,
 ):
     return (
         r"""
@@ -428,6 +449,7 @@ def to_fc(
     name,
     n_filer=120,
     offset="(0,0,0)",
+    zlabeloffset=0.3,
     to="(0,0,0)",
     width=2,
     height=2,
@@ -450,6 +472,9 @@ def to_fc(
         + caption
         + """,
         xlabel={{" ","dummy"}},
+        zlabeloffset="""
+        + str(zlabeloffset)
+        + """,
         zlabel="""
         + str(n_filer)
         + """,