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75 lines
2.1 KiB
Python
75 lines
2.1 KiB
Python
from manim import *
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from manim_ml.neural_network.layers.convolutional_2d import Convolutional2DLayer
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from manim_ml.neural_network.layers.feed_forward import FeedForwardLayer
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from manim_ml.neural_network.neural_network import NeuralNetwork
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from manim_ml.utils.testing.frames_comparison import frames_comparison
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__module_test__ = "padding"
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# Make the specific scene
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config.pixel_height = 1200
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config.pixel_width = 1900
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config.frame_height = 6.0
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config.frame_width = 6.0
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class CombinedScene(ThreeDScene):
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def construct(self):
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# Make nn
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nn = NeuralNetwork(
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[
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Convolutional2DLayer(
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num_feature_maps=1,
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feature_map_size=7,
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padding=1,
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padding_dashed=True,
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),
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Convolutional2DLayer(
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num_feature_maps=3,
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feature_map_size=7,
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filter_size=3,
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padding=0,
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padding_dashed=False,
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),
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FeedForwardLayer(3),
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],
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layer_spacing=0.25,
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)
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# Center the nn
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nn.move_to(ORIGIN)
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self.add(nn)
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# Play animation
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forward_pass = nn.make_forward_pass_animation()
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self.wait(1)
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self.play(forward_pass, run_time=30)
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@frames_comparison
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def test_ConvPadding(scene):
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# Make nn
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nn = NeuralNetwork(
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[
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Convolutional2DLayer(
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num_feature_maps=1, feature_map_size=7, padding=1, padding_dashed=True
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),
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Convolutional2DLayer(
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num_feature_maps=3,
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feature_map_size=7,
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filter_size=3,
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padding=1,
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filter_spacing=0.35,
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padding_dashed=False,
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),
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FeedForwardLayer(3),
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],
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layer_spacing=0.25,
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)
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# Center the nn
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nn.move_to(ORIGIN)
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scene.add(nn)
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# Play animation
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forward_pass = nn.make_forward_pass_animation()
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scene.play(forward_pass, run_time=30)
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