A usefull CNN/DenseNet visualization tool
Project description
neural-network-renderer
The code generating the image is writen in Python. This code generates .tex
and .sty
files that are directly compiled and deleted once the resulting PDF is available.
Example
Here is an example of the code to generate a simple convolutionnal-network representation:
from neural_network_renderer.architecture import Architecture
from neural_network_renderer.colors import Colors
from neural_network_renderer.layers import Conv, ConvConvRelu, Dense, DottedLines, Input, Pool, Softmax, Spacer
def main():
Colors.Dense("lightgray")
Colors.Softmax("lightgray")
arch = Architecture(4 / 32)
# first layer
arch.add(ConvConvRelu(s_filter=64, n_filter=[32, 32], to="(5,0,0)"))
arch.add(Pool([32, 32, 32]))
arch.add(Spacer(width=20))
# second layer
arch.add(ConvConvRelu(s_filter=32, n_filter=[64, 64]))
arch.add(Pool([16, 16, 64]))
arch.add(Spacer())
# third layer
arch.add(ConvConvRelu(s_filter=16, n_filter=[64, 64]))
arch.add(Pool([8, 8, 64], name="last_pool"))
arch.add(Spacer())
# GPA
arch.add(Conv(s_filter=8, n_filter=1, name="gpa", caption="GPA"))
# flatten
arch.add(Dense(64, name="flatten", offset="(4,0,0)", caption="Hidden Layer"))
arch.add(Softmax(5, 5, name="output", caption="Output", offset="(4,0,0)"))
arch.add(DottedLines("gpa", "flatten"))
arch.add(DottedLines("flatten", "output"))
arch.to_pdf("output_file")
if __name__ == "__main__":
main()
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