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fix: 🚑️ Refactor repo to allow proper pip install
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rhoadesScholar committed Apr 2, 2024
1 parent 820f19e commit 7a0bbe6
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Showing 16 changed files with 2 additions and 96 deletions.
4 changes: 2 additions & 2 deletions setup.cfg
Original file line number Diff line number Diff line change
Expand Up @@ -15,7 +15,7 @@ classifiers =

[options]
package_dir=
=leibnetz
=src
packages=find:
zip_safe = True
include_package_data = True
Expand All @@ -25,5 +25,5 @@ install_requires =
funlib.learn.torch @ git+https://github.com/funkelab/funlib.learn.torch.git

[options.packages.find]
where=leibnetz
where=src

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94 changes: 0 additions & 94 deletions tests/leibnet_test.py
Original file line number Diff line number Diff line change
Expand Up @@ -186,97 +186,3 @@ def test_leibnet_cpu():
if __name__ == "__main__":
test_leibnet_cpu()
test_leibnet_gpu()

# %% [markdown]
# ```mermaid
# graph LR
# node-in_conv_0([in_conv_0])
# node-downsample_0[\downsample_0/]
# node-in_conv_1([in_conv_1])
# node-downsample_1[\downsample_1/]
# node-bottleneck([bottleneck])
# node-upsample_1[/upsample_1\]
# node-out_conv_1([out_conv_1])
# node-upsample_0[/upsample_0\]
# node-out_conv_0([out_conv_0])
# node-output([output])
# out_conv_0[out_conv_0: 20x20x20]
# upsample_0[upsample_0: 28x28x28]
# in_conv_0[in_conv_0: 76x76x76]
# out_conv_1[out_conv_1: 14x14x14]
# upsample_1[upsample_1: 20x20x20]
# in_conv_1[in_conv_1: 32x32x32]
# bottleneck[bottleneck: 10x10x10]
# downsample_1[downsample_1: 16x16x16]
# downsample_0[downsample_0: 38x38x38]
# input[input: 82x82x82]
# subgraph 8nmx8nmx8nm
# input---node-in_conv_0
# end
# subgraph 8nmx8nmx8nm
# node-in_conv_0-->in_conv_0
# end
# subgraph 8nmx8nmx8nm
# in_conv_0-.-node-downsample_0
# end
# subgraph 16nmx16nmx16nm
# node-downsample_0-.->downsample_0
# end
# subgraph 16nmx16nmx16nm
# downsample_0---node-in_conv_1
# end
# subgraph 16nmx16nmx16nm
# node-in_conv_1-->in_conv_1
# end
# subgraph 16nmx16nmx16nm
# in_conv_1-.-node-downsample_1
# end
# subgraph 32nmx32nmx32nm
# node-downsample_1-.->downsample_1
# end
# subgraph 32nmx32nmx32nm
# downsample_1---node-bottleneck
# end
# subgraph 32nmx32nmx32nm
# node-bottleneck-->bottleneck
# end
# subgraph 32nmx32nmx32nm
# bottleneck===node-upsample_1
# end
# subgraph 16nmx16nmx16nm
# node-upsample_1==>upsample_1
# end
# subgraph 16nmx16nmx16nm
# upsample_1---node-out_conv_1
# end
# subgraph 16nmx16nmx16nm
# in_conv_1---node-out_conv_1
# end
# subgraph 16nmx16nmx16nm
# node-out_conv_1-->out_conv_1
# end
# subgraph 16nmx16nmx16nm
# out_conv_1===node-upsample_0
# end
# subgraph 8nmx8nmx8nm
# node-upsample_0==>upsample_0
# end
# subgraph 8nmx8nmx8nm
# upsample_0---node-out_conv_0
# end
# subgraph 8nmx8nmx8nm
# in_conv_0---node-out_conv_0
# end
# subgraph 8nmx8nmx8nm
# node-out_conv_0-->out_conv_0
# end
# subgraph 8nmx8nmx8nm
# out_conv_0---node-output
# end
# subgraph 8nmx8nmx8nm
# node-output-->output
# end
# ```


# %%

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