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for arguments to be passed through to each neural network layer when running a neural network forward pass.
37 lines
1.1 KiB
Python
37 lines
1.1 KiB
Python
from manim import *
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import random
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from manim_ml.neural_network.layers.parent_layers import VGroupNeuralNetworkLayer
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class VectorLayer(VGroupNeuralNetworkLayer):
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"""Shows a vector"""
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def __init__(self, num_values, value_func=lambda: random.uniform(0, 1),
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**kwargs):
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super().__init__(**kwargs)
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self.num_values = num_values
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self.value_func = value_func
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# Make the vector
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self.vector_label = self.make_vector()
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self.add(self.vector_label)
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def make_vector(self):
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"""Makes the vector"""
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if False:
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# TODO install Latex
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values = np.array([self.value_func() for i in range(self.num_values)])
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values = values[None, :].T
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vector = Matrix(values)
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vector_label = Text(f"[{self.value_func():.2f}]")
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vector_label.scale(0.3)
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return vector_label
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def make_forward_pass_animation(self, layer_args={}, **kwargs):
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return AnimationGroup()
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@override_animation(Create)
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def _create_override(self):
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"""Create animation"""
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return Write(self.vector_label) |