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Up to InterpretFirstWeightMatrixRows in NN part 2

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Grant Sanderson
2017-10-12 17:38:25 -07:00
parent fd59591000
commit d138ffd353
6 changed files with 1210 additions and 41 deletions
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20
nn/part1.py
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@ -196,19 +196,22 @@ class NetworkMobject(VGroup):
for l1, l2 in zip(self.layers[:-1], self.layers[1:]):
edge_group = VGroup()
for n1, n2 in it.product(l1.neurons, l2.neurons):
edge = Line(
n1.get_center(),
n2.get_center(),
buff = self.neuron_radius,
stroke_color = self.edge_color,
stroke_width = self.edge_stroke_width,
)
edge = self.get_edge(n1, n2)
edge_group.add(edge)
n1.edges_out.add(edge)
n2.edges_in.add(edge)
self.edge_groups.add(edge_group)
self.add_to_back(self.edge_groups)
def get_edge(self, neuron1, neuron2):
return Line(
neuron1.get_center(),
neuron2.get_center(),
buff = self.neuron_radius,
stroke_color = self.edge_color,
stroke_width = self.edge_stroke_width,
)
def get_active_layer(self, layer_index, activation_vector):
layer = self.layers[layer_index].deepcopy()
n_neurons = len(layer.neurons)
@ -2980,6 +2983,7 @@ class ContinualEdgeUpdate(ContinualAnimation):
"max_stroke_width" : 3,
"stroke_width_exp" : 7,
"n_cycles" : 5,
"colors" : [GREEN, GREEN, GREEN, RED],
}
def __init__(self, network_mob, **kwargs):
digest_config(self, kwargs)
@ -2988,7 +2992,7 @@ class ContinualEdgeUpdate(ContinualAnimation):
self.move_to_targets = []
for edge in edges:
edge.colors = [
random.choice([GREEN, GREEN, GREEN, RED])
random.choice(self.colors)
for x in range(n_cycles)
]
msw = self.max_stroke_width