From c5891ce25e26777c7fdb0e75b227c0b405ae1e15 Mon Sep 17 00:00:00 2001
From: Grant Sanderson <grantsanderson7@gmail.com>
Date: Fri, 20 Oct 2017 16:29:58 -0700
Subject: [PATCH] Tweaks to GradientNudging in nn/part2

---
 nn/part2.py | 40 ++++++++++++++++++++++++++++++++--------
 1 file changed, 32 insertions(+), 8 deletions(-)

diff --git a/nn/part2.py b/nn/part2.py
index 350675b7..c6f75105 100644
--- a/nn/part2.py
+++ b/nn/part2.py
@@ -77,6 +77,8 @@ def get_decimal_vector(nums, with_dots = True):
     result.brackets = brackets
     result.decimals = decimals
     result.contents = contents
+    if with_dots:
+        result.dots = dots
     return result
 
 
@@ -2606,7 +2608,8 @@ class TODOInsertEmphasizeComplexityOfCostFunctionCopy(TODOStub):
 
 class GradientNudging(PreviewLearning):
     CONFIG = {
-        "n_steps" : 10
+        "n_steps" : 10,
+        "n_decimals" : 8,
     }
     def construct(self):
         self.setup_network_mob()
@@ -2623,18 +2626,24 @@ class GradientNudging(PreviewLearning):
         lhs = TexMobject(
             "-", "\\nabla", "C(", "\\dots", ")", "="
         )
-        lhs.to_edge(LEFT)
         brace = Brace(lhs.get_part_by_tex("dots"), DOWN)
         words = brace.get_text("All weights \\\\ and biases")
         words.scale(0.8, about_point = words.get_top())
         np.random.seed(3)
-        nums = 4*(np.random.random(8)-0.5)
+        nums = 4*(np.random.random(self.n_decimals)-0.5)
         vect = get_decimal_vector(nums)
         vect.next_to(lhs, RIGHT)
+        group = VGroup(lhs, brace, words, vect)
+        group.to_corner(UP+LEFT)
 
-        self.add(lhs, brace, words, vect)
+        self.add(*group)
 
-        self.grad_vect = vect
+        self.set_variables_as_attrs(
+            grad_lhs = lhs,
+            grad_vect = vect,
+            grad_arg_words = words,
+            grad_arg_brace = brace
+        )
 
     def change_weights_repeatedly(self):
         network_mob = self.network_mob
@@ -2659,14 +2668,17 @@ class GradientNudging(PreviewLearning):
         ])
 
         mover = VGroup(*decimals.family_members_with_points()).copy()
-        mover.set_fill(opacity = 0)
-        mover.set_stroke(width = 1)
-        target = VGroup(*self.network_mob.edge_groups.family_members_with_points())
+        # mover.set_fill(opacity = 0)
+        mover.set_stroke(width = 0)
+        target = VGroup(*self.network_mob.edge_groups.family_members_with_points()).copy()
+        target.set_fill(opacity = 0)
+        ApplyMethod(target.set_stroke, YELLOW, 2).update(0.3)
         self.play(
             ReplacementTransform(mover, target),
             FadeIn(words),
             LaggedStart(GrowArrow, arrows, run_time = 1)
         )
+        self.play(FadeOut(target))
         self.play(self.get_edge_change_anim(edges))
         self.play(*self.get_decimal_change_anims(decimals))
         for x in range(self.n_steps):
@@ -2698,6 +2710,16 @@ class GradientNudging(PreviewLearning):
         )
 
     def get_decimal_change_anims(self, decimals):
+        words = TextMobject("Recompute \\\\ gradient")
+        words.next_to(decimals, DOWN, MED_LARGE_BUFF)
+        def wrf(t):
+            if t < 1./3:
+                return smooth(3*t)
+            elif t < 2./3:
+                return 1
+            else:
+                return smooth(3 - 3*t)
+
         changes = 0.2*(np.random.random(len(decimals))-0.5)
         def generate_change_func(x, dx):
             return lambda a : interpolate(x, x+dx, a)
@@ -2707,6 +2729,8 @@ class GradientNudging(PreviewLearning):
                 generate_change_func(decimal.number, change)
             )
             for decimal, change in zip(decimals, changes)
+        ] + [
+            FadeIn(words, rate_func = wrf, run_time = 1.5, remover = True)
         ]
 
 class BackPropWrapper(PiCreatureScene):