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Project.toml
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authors = ["jeremiedb <[email protected]>"]
name = "NeuroTreeModels"
uuid = "1db4e0a5-a364-4b0c-897c-2bd5a4a3a1f2"
version = "1.3.1"
[deps]
CUDA = "052768ef-5323-5732-b1bb-66c8b64840ba"
CategoricalArrays = "324d7699-5711-5eae-9e2f-1d82baa6b597"
ChainRulesCore = "d360d2e6-b24c-11e9-a2a3-2a2ae2dbcce4"
DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
Flux = "587475ba-b771-5e3f-ad9e-33799f191a9c"
MLJModelInterface = "e80e1ace-859a-464e-9ed9-23947d8ae3ea"
MLUtils = "f1d291b0-491e-4a28-83b9-f70985020b54"
Optimisers = "3bd65402-5787-11e9-1adc-39752487f4e2"
Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
StatsBase = "2913bbd2-ae8a-5f71-8c99-4fb6c76f3a91"
Tables = "bd369af6-aec1-5ad0-b16a-f7cc5008161c"
cuDNN = "02a925ec-e4fe-4b08-9a7e-0d78e3d38ccd"
[compat]
CUDA = "4, 5"
CategoricalArrays = "0.10"
ChainRulesCore = "1"
DataFrames = "1.3"
Flux = "0.13, 0.14"
MLJModelInterface = "1.0"
MLUtils = "0.4"
Optimisers = "0.3"
Random = "1"
Statistics = "1"
StatsBase = "0.34"
Tables = "1.9"
cuDNN = "1"
julia = "1.9"
[extras]
MLDatasets = "eb30cadb-4394-5ae3-aed4-317e484a6458"
MLJBase = "a7f614a8-145f-11e9-1d2a-a57a1082229d"
MLJTestInterface = "72560011-54dd-4dc2-94f3-c5de45b75ecd"
Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
[targets]
test = ["Test", "MLDatasets", "MLJTestInterface", "MLJBase"]