standalone: add runtime implementation for linalg functions
This commit is contained in:
parent
d6a4d0a634
commit
faf07527cb
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@ -73,6 +73,15 @@ dependencies = [
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"windows-sys",
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"windows-sys",
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]
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]
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[[package]]
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name = "approx"
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version = "0.5.1"
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source = "registry+https://github.com/rust-lang/crates.io-index"
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checksum = "cab112f0a86d568ea0e627cc1d6be74a1e9cd55214684db5561995f6dad897c6"
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dependencies = [
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"num-traits",
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]
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[[package]]
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[[package]]
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name = "ascii-canvas"
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name = "ascii-canvas"
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version = "3.0.0"
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version = "3.0.0"
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@ -247,6 +256,12 @@ version = "0.2.2"
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source = "registry+https://github.com/rust-lang/crates.io-index"
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source = "registry+https://github.com/rust-lang/crates.io-index"
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checksum = "7a81dae078cea95a014a339291cec439d2f232ebe854a9d672b796c6afafa9b7"
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checksum = "7a81dae078cea95a014a339291cec439d2f232ebe854a9d672b796c6afafa9b7"
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[[package]]
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name = "cslice"
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version = "0.3.0"
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source = "registry+https://github.com/rust-lang/crates.io-index"
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checksum = "0f8cb7306107e4b10e64994de6d3274bd08996a7c1322a27b86482392f96be0a"
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[[package]]
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[[package]]
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name = "dirs-next"
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name = "dirs-next"
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version = "2.0.0"
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version = "2.0.0"
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@ -521,6 +536,12 @@ dependencies = [
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"windows-targets",
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"windows-targets",
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]
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]
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[[package]]
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name = "libm"
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version = "0.2.8"
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source = "registry+https://github.com/rust-lang/crates.io-index"
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checksum = "4ec2a862134d2a7d32d7983ddcdd1c4923530833c9f2ea1a44fc5fa473989058"
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[[package]]
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[[package]]
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name = "libredox"
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name = "libredox"
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version = "0.1.3"
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version = "0.1.3"
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@ -531,6 +552,14 @@ dependencies = [
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"libc",
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"libc",
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]
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]
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[[package]]
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name = "linalg_externfns"
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version = "0.1.0"
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dependencies = [
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"cslice",
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"nalgebra",
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]
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[[package]]
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[[package]]
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name = "linked-hash-map"
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name = "linked-hash-map"
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version = "0.5.6"
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version = "0.5.6"
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@ -659,17 +688,70 @@ version = "0.1.0"
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dependencies = [
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dependencies = [
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"clap",
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"clap",
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"inkwell",
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"inkwell",
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"linalg_externfns",
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"nac3core",
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"nac3core",
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"nac3parser",
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"nac3parser",
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"parking_lot",
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"parking_lot",
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]
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]
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[[package]]
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name = "nalgebra"
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version = "0.32.6"
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source = "registry+https://github.com/rust-lang/crates.io-index"
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checksum = "7b5c17de023a86f59ed79891b2e5d5a94c705dbe904a5b5c9c952ea6221b03e4"
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dependencies = [
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"approx",
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"num-complex",
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"num-rational",
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"num-traits",
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"simba",
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"typenum",
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]
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[[package]]
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[[package]]
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name = "new_debug_unreachable"
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name = "new_debug_unreachable"
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version = "1.0.6"
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version = "1.0.6"
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source = "registry+https://github.com/rust-lang/crates.io-index"
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source = "registry+https://github.com/rust-lang/crates.io-index"
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checksum = "650eef8c711430f1a879fdd01d4745a7deea475becfb90269c06775983bbf086"
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checksum = "650eef8c711430f1a879fdd01d4745a7deea475becfb90269c06775983bbf086"
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[[package]]
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name = "num-complex"
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version = "0.4.6"
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source = "registry+https://github.com/rust-lang/crates.io-index"
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checksum = "73f88a1307638156682bada9d7604135552957b7818057dcef22705b4d509495"
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dependencies = [
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"num-traits",
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]
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[[package]]
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name = "num-integer"
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version = "0.1.46"
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source = "registry+https://github.com/rust-lang/crates.io-index"
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checksum = "7969661fd2958a5cb096e56c8e1ad0444ac2bbcd0061bd28660485a44879858f"
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dependencies = [
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"num-traits",
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]
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[[package]]
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name = "num-rational"
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version = "0.4.2"
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source = "registry+https://github.com/rust-lang/crates.io-index"
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checksum = "f83d14da390562dca69fc84082e73e548e1ad308d24accdedd2720017cb37824"
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dependencies = [
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"num-integer",
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"num-traits",
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]
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[[package]]
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name = "num-traits"
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version = "0.2.19"
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source = "registry+https://github.com/rust-lang/crates.io-index"
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checksum = "071dfc062690e90b734c0b2273ce72ad0ffa95f0c74596bc250dcfd960262841"
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dependencies = [
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"autocfg",
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"libm",
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]
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[[package]]
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[[package]]
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name = "once_cell"
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name = "once_cell"
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version = "1.19.0"
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version = "1.19.0"
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@ -699,6 +781,12 @@ dependencies = [
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"windows-targets",
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"windows-targets",
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]
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]
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[[package]]
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name = "paste"
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version = "1.0.15"
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source = "registry+https://github.com/rust-lang/crates.io-index"
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checksum = "57c0d7b74b563b49d38dae00a0c37d4d6de9b432382b2892f0574ddcae73fd0a"
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[[package]]
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[[package]]
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name = "petgraph"
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name = "petgraph"
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version = "0.6.5"
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version = "0.6.5"
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@ -1070,6 +1158,18 @@ dependencies = [
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"yaml-rust",
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"yaml-rust",
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]
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]
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[[package]]
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name = "simba"
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version = "0.8.1"
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source = "registry+https://github.com/rust-lang/crates.io-index"
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checksum = "061507c94fc6ab4ba1c9a0305018408e312e17c041eb63bef8aa726fa33aceae"
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dependencies = [
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"approx",
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"num-complex",
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"num-traits",
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"paste",
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]
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[[package]]
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[[package]]
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name = "similar"
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name = "similar"
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version = "2.6.0"
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version = "2.6.0"
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@ -1230,6 +1330,12 @@ dependencies = [
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"crunchy",
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"crunchy",
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]
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]
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[[package]]
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name = "typenum"
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version = "1.17.0"
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source = "registry+https://github.com/rust-lang/crates.io-index"
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checksum = "42ff0bf0c66b8238c6f3b578df37d0b7848e55df8577b3f74f92a69acceeb825"
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[[package]]
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[[package]]
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name = "unic-char-property"
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name = "unic-char-property"
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version = "0.9.0"
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version = "0.9.0"
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@ -4,6 +4,7 @@ members = [
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"nac3ast",
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"nac3ast",
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"nac3parser",
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"nac3parser",
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"nac3core",
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"nac3core",
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"nac3standalone/linalg_externfns",
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"nac3standalone",
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"nac3standalone",
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"nac3artiq",
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"nac3artiq",
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"runkernel",
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"runkernel",
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@ -8,6 +8,7 @@ edition = "2021"
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parking_lot = "0.12"
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parking_lot = "0.12"
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nac3parser = { path = "../nac3parser" }
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nac3parser = { path = "../nac3parser" }
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nac3core = { path = "../nac3core" }
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nac3core = { path = "../nac3core" }
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linalg_externfns = { path = "./linalg_externfns" }
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[dependencies.clap]
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[dependencies.clap]
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version = "4.5"
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version = "4.5"
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@ -0,0 +1,11 @@
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[package]
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name = "linalg_externfns"
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version = "0.1.0"
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edition = "2021"
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[lib]
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crate-type = ["staticlib"]
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[dependencies]
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nalgebra = {version = "0.32.6", default-features = false, features = ["libm", "alloc"]}
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cslice = "0.3.0"
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@ -0,0 +1,408 @@
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/// Uses `nalgebra` crate to invoke `np_linalg` and `sp_linalg` functions
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/// When converting between `nalgebra::Matrix` and `NDArray` following considerations are necessary
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///
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/// * Both `nalgebra::Matrix` and `NDArray` require their content to be stored in row-major order
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/// * `NDArray` data pointer can be directly read and converted to `nalgebra::Matrix` (row and column number must be known)
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/// * `nalgebra::Matrix::as_slice` returns the content of matrix in column-major order and initial data needs to be transposed before storing it in `NDArray` data pointer
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mod runtime_exception;
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use core::slice;
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use nalgebra::DMatrix;
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macro_rules! raise_exn {
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($name:expr, $fn_name:expr, $message:expr, $param0:expr, $param1:expr, $param2:expr) => {{
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use cslice::AsCSlice;
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let name_id = $crate::runtime_exception::get_exception_id($name);
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let exn = $crate::runtime_exception::Exception {
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id: name_id,
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file: file!().as_c_slice(),
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line: line!(),
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column: column!(),
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// https://github.com/rust-lang/rfcs/pull/1719
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function: $fn_name.as_c_slice(),
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message: $message.as_c_slice(),
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param: [$param0, $param1, $param2],
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};
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#[allow(unused_unsafe)]
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unsafe {
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$crate::runtime_exception::raise(&exn)
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}
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}};
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($name:expr, $fn_name:expr, $message:expr) => {{
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raise_exn!($name, $fn_name, $message, 0, 0, 0)
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}};
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}
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pub struct InputMatrix {
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pub ndims: usize,
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pub dims: *const usize,
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pub data: *mut f64,
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}
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impl InputMatrix {
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fn get_dims(&mut self) -> Vec<usize> {
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let dims = unsafe { slice::from_raw_parts(self.dims, self.ndims) };
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dims.to_vec()
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}
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}
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/// # Safety
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///
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/// `mat1` and `mat2` should point to a valid 1DArray of `f64` floats in row-major order
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#[no_mangle]
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pub unsafe extern "C" fn np_dot(mat1: *mut InputMatrix, mat2: *mut InputMatrix) -> f64 {
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let mat1 = mat1.as_mut().unwrap();
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let mat2 = mat2.as_mut().unwrap();
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if !(mat1.ndims == 1 && mat2.ndims == 1) {
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let err_msg = format!(
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"expected 1D Vector Input, but received {}D and {}D input",
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mat1.ndims, mat2.ndims
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);
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raise_exn!("ValueError", "np_dot", err_msg);
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}
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let dim1 = (*mat1).get_dims();
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let dim2 = (*mat2).get_dims();
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if dim1[0] != dim2[0] {
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let err_msg = format!("shapes ({},) and ({},) not aligned", dim1[0], dim2[0]);
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raise_exn!("ValueError", "np_dot", err_msg);
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}
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let data_slice1 = unsafe { slice::from_raw_parts_mut(mat1.data, dim1[0]) };
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let data_slice2 = unsafe { slice::from_raw_parts_mut(mat2.data, dim2[0]) };
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let matrix1 = DMatrix::from_row_slice(dim1[0], 1, data_slice1);
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let matrix2 = DMatrix::from_row_slice(dim2[0], 1, data_slice2);
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matrix1.dot(&matrix2)
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}
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/// # Safety
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///
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/// `mat1` and `mat2` should point to a valid 2DArray of `f64` floats in row-major order
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#[no_mangle]
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pub unsafe extern "C" fn np_linalg_matmul(
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mat1: *mut InputMatrix,
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mat2: *mut InputMatrix,
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out: *mut InputMatrix,
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) {
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let mat1 = mat1.as_mut().unwrap();
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let mat2 = mat2.as_mut().unwrap();
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let out = out.as_mut().unwrap();
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if !(mat1.ndims == 2 && mat2.ndims == 2) {
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let err_msg = format!(
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"expected 2D Vector Input, but received {}D and {}D input",
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mat1.ndims, mat2.ndims
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);
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raise_exn!("ValueError", "np_matmul", err_msg);
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}
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let dim1 = (*mat1).get_dims();
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let dim2 = (*mat2).get_dims();
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if dim1[1] != dim2[0] {
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let err_msg = format!(
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"shapes ({},{}) and ({},{}) not aligned: {} (dim 1) != {} (dim 0)",
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dim1[0], dim1[1], dim2[0], dim2[1], dim1[1], dim2[0]
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);
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raise_exn!("ValueError", "np_matmul", err_msg);
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}
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let outdim = out.get_dims();
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let out_slice = unsafe { slice::from_raw_parts_mut(out.data, outdim[0] * outdim[1]) };
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let data_slice1 = unsafe { slice::from_raw_parts_mut(mat1.data, dim1[0] * dim1[1]) };
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let data_slice2 = unsafe { slice::from_raw_parts_mut(mat2.data, dim2[0] * dim2[1]) };
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let matrix1 = DMatrix::from_row_slice(dim1[0], dim1[1], data_slice1);
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let matrix2 = DMatrix::from_row_slice(dim2[0], dim2[1], data_slice2);
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let mut result = DMatrix::<f64>::zeros(outdim[0], outdim[1]);
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matrix1.mul_to(&matrix2, &mut result);
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out_slice.copy_from_slice(result.transpose().as_slice());
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}
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/// # Safety
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///
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/// `mat1` should point to a valid 2DArray of `f64` floats in row-major order
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#[no_mangle]
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pub unsafe extern "C" fn np_linalg_cholesky(mat1: *mut InputMatrix, out: *mut InputMatrix) {
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||||||
|
let mat1 = mat1.as_mut().unwrap();
|
||||||
|
let out = out.as_mut().unwrap();
|
||||||
|
|
||||||
|
if mat1.ndims != 2 {
|
||||||
|
let err_msg = format!("expected 2D Vector Input, but received {}D input", mat1.ndims);
|
||||||
|
raise_exn!("ValueError", "np_linalg_cholesky", err_msg);
|
||||||
|
}
|
||||||
|
|
||||||
|
let dim1 = (*mat1).get_dims();
|
||||||
|
if dim1[0] != dim1[1] {
|
||||||
|
let err_msg =
|
||||||
|
format!("last 2 dimensions of the array must be square: {0} != {1}", dim1[0], dim1[1]);
|
||||||
|
raise_exn!("LinAlgError", "np_linalg_cholesky", err_msg);
|
||||||
|
}
|
||||||
|
|
||||||
|
let outdim = out.get_dims();
|
||||||
|
let out_slice = unsafe { slice::from_raw_parts_mut(out.data, outdim[0] * outdim[1]) };
|
||||||
|
let data_slice1 = unsafe { slice::from_raw_parts_mut(mat1.data, dim1[0] * dim1[1]) };
|
||||||
|
|
||||||
|
let matrix1 = DMatrix::from_row_slice(dim1[0], dim1[1], data_slice1);
|
||||||
|
let result = matrix1.cholesky();
|
||||||
|
match result {
|
||||||
|
Some(res) => {
|
||||||
|
out_slice.copy_from_slice(res.unpack().transpose().as_slice());
|
||||||
|
}
|
||||||
|
None => {
|
||||||
|
raise_exn!("LinAlgError", "np_linalg_cholesky", "Matrix is not positive definite");
|
||||||
|
}
|
||||||
|
};
|
||||||
|
}
|
||||||
|
|
||||||
|
/// # Safety
|
||||||
|
///
|
||||||
|
/// `mat1` should point to a valid 2DArray of `f64` floats in row-major order
|
||||||
|
#[no_mangle]
|
||||||
|
pub unsafe extern "C" fn np_linalg_qr(
|
||||||
|
mat1: *mut InputMatrix,
|
||||||
|
out_q: *mut InputMatrix,
|
||||||
|
out_r: *mut InputMatrix,
|
||||||
|
) {
|
||||||
|
let mat1 = mat1.as_mut().unwrap();
|
||||||
|
let out_q = out_q.as_mut().unwrap();
|
||||||
|
let out_r = out_r.as_mut().unwrap();
|
||||||
|
|
||||||
|
if mat1.ndims != 2 {
|
||||||
|
let err_msg = format!("expected 2D Vector Input, but received {}D input", mat1.ndims);
|
||||||
|
raise_exn!("ValueError", "np_linalg_cholesky", err_msg);
|
||||||
|
}
|
||||||
|
|
||||||
|
let dim1 = (*mat1).get_dims();
|
||||||
|
let outq_dim = (*out_q).get_dims();
|
||||||
|
let outr_dim = (*out_r).get_dims();
|
||||||
|
|
||||||
|
let data_slice1 = unsafe { slice::from_raw_parts_mut(mat1.data, dim1[0] * dim1[1]) };
|
||||||
|
let out_q_slice = unsafe { slice::from_raw_parts_mut(out_q.data, outq_dim[0] * outq_dim[1]) };
|
||||||
|
let out_r_slice = unsafe { slice::from_raw_parts_mut(out_r.data, outr_dim[0] * outr_dim[1]) };
|
||||||
|
|
||||||
|
// Refer to https://github.com/dimforge/nalgebra/issues/735
|
||||||
|
let matrix1 = DMatrix::from_row_slice(dim1[0], dim1[1], data_slice1);
|
||||||
|
|
||||||
|
let res = matrix1.qr();
|
||||||
|
let (q, r) = res.unpack();
|
||||||
|
|
||||||
|
// Uses different algo need to match numpy
|
||||||
|
out_q_slice.copy_from_slice(q.transpose().as_slice());
|
||||||
|
out_r_slice.copy_from_slice(r.transpose().as_slice());
|
||||||
|
}
|
||||||
|
|
||||||
|
/// # Safety
|
||||||
|
///
|
||||||
|
/// `mat1` should point to a valid 2DArray of `f64` floats in row-major order
|
||||||
|
#[no_mangle]
|
||||||
|
pub unsafe extern "C" fn np_linalg_svd(
|
||||||
|
mat1: *mut InputMatrix,
|
||||||
|
outu: *mut InputMatrix,
|
||||||
|
outs: *mut InputMatrix,
|
||||||
|
outvh: *mut InputMatrix,
|
||||||
|
) {
|
||||||
|
let mat1 = mat1.as_mut().unwrap();
|
||||||
|
let outu = outu.as_mut().unwrap();
|
||||||
|
let outs = outs.as_mut().unwrap();
|
||||||
|
let outvh = outvh.as_mut().unwrap();
|
||||||
|
|
||||||
|
if mat1.ndims != 2 {
|
||||||
|
let err_msg = format!("expected 2D Vector Input, but received {}D input", mat1.ndims);
|
||||||
|
raise_exn!("ValueError", "np_linalg_svd", err_msg);
|
||||||
|
}
|
||||||
|
|
||||||
|
let dim1 = (*mat1).get_dims();
|
||||||
|
let outu_dim = (*outu).get_dims();
|
||||||
|
let outs_dim = (*outs).get_dims();
|
||||||
|
let outvh_dim = (*outvh).get_dims();
|
||||||
|
|
||||||
|
let data_slice1 = unsafe { slice::from_raw_parts_mut(mat1.data, dim1[0] * dim1[1]) };
|
||||||
|
let out_u_slice = unsafe { slice::from_raw_parts_mut(outu.data, outu_dim[0] * outu_dim[1]) };
|
||||||
|
let out_s_slice = unsafe { slice::from_raw_parts_mut(outs.data, outs_dim[0]) };
|
||||||
|
let out_vh_slice =
|
||||||
|
unsafe { slice::from_raw_parts_mut(outvh.data, outvh_dim[0] * outvh_dim[1]) };
|
||||||
|
|
||||||
|
let matrix = DMatrix::from_row_slice(dim1[0], dim1[1], data_slice1);
|
||||||
|
let result = matrix.svd(true, true);
|
||||||
|
out_u_slice.copy_from_slice(result.u.unwrap().transpose().as_slice());
|
||||||
|
out_s_slice.copy_from_slice(result.singular_values.as_slice());
|
||||||
|
out_vh_slice.copy_from_slice(result.v_t.unwrap().transpose().as_slice());
|
||||||
|
}
|
||||||
|
|
||||||
|
/// # Safety
|
||||||
|
///
|
||||||
|
/// `mat1` should point to a valid 2DArray of `f64` floats in row-major order
|
||||||
|
#[no_mangle]
|
||||||
|
pub unsafe extern "C" fn np_linalg_inv(mat1: *mut InputMatrix, out: *mut InputMatrix) {
|
||||||
|
let mat1 = mat1.as_mut().unwrap();
|
||||||
|
let out = out.as_mut().unwrap();
|
||||||
|
|
||||||
|
if mat1.ndims != 2 {
|
||||||
|
let err_msg = format!("expected 2D Vector Input, but received {}D input", mat1.ndims);
|
||||||
|
raise_exn!("ValueError", "np_linalg_inv", err_msg);
|
||||||
|
}
|
||||||
|
let dim1 = (*mat1).get_dims();
|
||||||
|
|
||||||
|
if dim1[0] != dim1[1] {
|
||||||
|
let err_msg =
|
||||||
|
format!("last 2 dimensions of the array must be square: {0} != {1}", dim1[0], dim1[1]);
|
||||||
|
raise_exn!("LinAlgError", "np_linalg_inv", err_msg);
|
||||||
|
}
|
||||||
|
|
||||||
|
let outdim = out.get_dims();
|
||||||
|
let out_slice = unsafe { slice::from_raw_parts_mut(out.data, outdim[0] * outdim[1]) };
|
||||||
|
let data_slice1 = unsafe { slice::from_raw_parts_mut(mat1.data, dim1[0] * dim1[1]) };
|
||||||
|
|
||||||
|
let matrix = DMatrix::from_row_slice(dim1[0], dim1[1], data_slice1);
|
||||||
|
if !matrix.is_invertible() {
|
||||||
|
raise_exn!("LinAlgError", "np_linalg_inv", "no inverse for Singular Matrix");
|
||||||
|
}
|
||||||
|
let inv = matrix.try_inverse().unwrap();
|
||||||
|
out_slice.copy_from_slice(inv.transpose().as_slice());
|
||||||
|
}
|
||||||
|
|
||||||
|
/// # Safety
|
||||||
|
///
|
||||||
|
/// `mat1` should point to a valid 2DArray of `f64` floats in row-major order
|
||||||
|
#[no_mangle]
|
||||||
|
pub unsafe extern "C" fn np_linalg_pinv(mat1: *mut InputMatrix, out: *mut InputMatrix) {
|
||||||
|
let mat1 = mat1.as_mut().unwrap();
|
||||||
|
let out = out.as_mut().unwrap();
|
||||||
|
|
||||||
|
if mat1.ndims != 2 {
|
||||||
|
let err_msg = format!("expected 2D Vector Input, but received {}D input", mat1.ndims);
|
||||||
|
raise_exn!("ValueError", "np_linalg_pinv", err_msg);
|
||||||
|
}
|
||||||
|
let dim1 = (*mat1).get_dims();
|
||||||
|
let outdim = out.get_dims();
|
||||||
|
let out_slice = unsafe { slice::from_raw_parts_mut(out.data, outdim[0] * outdim[1]) };
|
||||||
|
let data_slice1 = unsafe { slice::from_raw_parts_mut(mat1.data, dim1[0] * dim1[1]) };
|
||||||
|
|
||||||
|
let matrix = DMatrix::from_row_slice(dim1[0], dim1[1], data_slice1);
|
||||||
|
let svd = matrix.svd(true, true);
|
||||||
|
let inv = svd.pseudo_inverse(1e-15);
|
||||||
|
|
||||||
|
match inv {
|
||||||
|
Ok(m) => {
|
||||||
|
out_slice.copy_from_slice(m.transpose().as_slice());
|
||||||
|
}
|
||||||
|
Err(e) => {
|
||||||
|
raise_exn!("LinAlgError", "np_linalg_pinv", e);
|
||||||
|
}
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
/// # Safety
|
||||||
|
///
|
||||||
|
/// `mat1` should point to a valid 2DArray of `f64` floats in row-major order
|
||||||
|
#[no_mangle]
|
||||||
|
pub unsafe extern "C" fn sp_linalg_lu(
|
||||||
|
mat1: *mut InputMatrix,
|
||||||
|
out_l: *mut InputMatrix,
|
||||||
|
out_u: *mut InputMatrix,
|
||||||
|
) {
|
||||||
|
let mat1 = mat1.as_mut().unwrap();
|
||||||
|
let out_l = out_l.as_mut().unwrap();
|
||||||
|
let out_u = out_u.as_mut().unwrap();
|
||||||
|
|
||||||
|
if mat1.ndims != 2 {
|
||||||
|
let err_msg = format!("expected 2D Vector Input, but received {}D input", mat1.ndims);
|
||||||
|
raise_exn!("ValueError", "sp_linalg_lu", err_msg);
|
||||||
|
}
|
||||||
|
|
||||||
|
let dim1 = (*mat1).get_dims();
|
||||||
|
let outl_dim = (*out_l).get_dims();
|
||||||
|
let outu_dim = (*out_u).get_dims();
|
||||||
|
|
||||||
|
let data_slice1 = unsafe { slice::from_raw_parts_mut(mat1.data, dim1[0] * dim1[1]) };
|
||||||
|
let out_l_slice = unsafe { slice::from_raw_parts_mut(out_l.data, outl_dim[0] * outl_dim[1]) };
|
||||||
|
let out_u_slice = unsafe { slice::from_raw_parts_mut(out_u.data, outu_dim[0] * outu_dim[1]) };
|
||||||
|
|
||||||
|
let matrix = DMatrix::from_row_slice(dim1[0], dim1[1], data_slice1);
|
||||||
|
let (_, l, u) = matrix.lu().unpack();
|
||||||
|
|
||||||
|
out_l_slice.copy_from_slice(l.transpose().as_slice());
|
||||||
|
out_u_slice.copy_from_slice(u.transpose().as_slice());
|
||||||
|
}
|
||||||
|
|
||||||
|
/// # Safety
|
||||||
|
///
|
||||||
|
/// `mat1` should point to a valid 2DArray of `f64` floats in row-major order
|
||||||
|
#[no_mangle]
|
||||||
|
pub unsafe extern "C" fn sp_linalg_schur(
|
||||||
|
mat1: *mut InputMatrix,
|
||||||
|
out_t: *mut InputMatrix,
|
||||||
|
out_z: *mut InputMatrix,
|
||||||
|
) {
|
||||||
|
let mat1 = mat1.as_mut().unwrap();
|
||||||
|
let out_t = out_t.as_mut().unwrap();
|
||||||
|
let out_z = out_z.as_mut().unwrap();
|
||||||
|
|
||||||
|
if mat1.ndims != 2 {
|
||||||
|
let err_msg = format!("expected 2D Vector Input, but received {}D input", mat1.ndims);
|
||||||
|
raise_exn!("ValueError", "sp_linalg_schur", err_msg);
|
||||||
|
}
|
||||||
|
|
||||||
|
let dim1 = (*mat1).get_dims();
|
||||||
|
|
||||||
|
if dim1[0] != dim1[1] {
|
||||||
|
let err_msg =
|
||||||
|
format!("last 2 dimensions of the array must be square: {0} != {1}", dim1[0], dim1[1]);
|
||||||
|
raise_exn!("LinAlgError", "np_linalg_schur", err_msg);
|
||||||
|
}
|
||||||
|
|
||||||
|
let out_t_dim = (*out_t).get_dims();
|
||||||
|
let out_z_dim = (*out_z).get_dims();
|
||||||
|
|
||||||
|
let data_slice1 = unsafe { slice::from_raw_parts_mut(mat1.data, dim1[0] * dim1[1]) };
|
||||||
|
let out_t_slice = unsafe { slice::from_raw_parts_mut(out_t.data, out_t_dim[0] * out_t_dim[1]) };
|
||||||
|
let out_z_slice = unsafe { slice::from_raw_parts_mut(out_z.data, out_z_dim[0] * out_z_dim[1]) };
|
||||||
|
|
||||||
|
let matrix = DMatrix::from_row_slice(dim1[0], dim1[1], data_slice1);
|
||||||
|
let (z, t) = matrix.schur().unpack();
|
||||||
|
|
||||||
|
out_t_slice.copy_from_slice(t.transpose().as_slice());
|
||||||
|
out_z_slice.copy_from_slice(z.transpose().as_slice());
|
||||||
|
}
|
||||||
|
|
||||||
|
/// # Safety
|
||||||
|
///
|
||||||
|
/// `mat1` should point to a valid 2DArray of `f64` floats in row-major order
|
||||||
|
#[no_mangle]
|
||||||
|
pub unsafe extern "C" fn sp_linalg_hessenberg(
|
||||||
|
mat1: *mut InputMatrix,
|
||||||
|
out_h: *mut InputMatrix,
|
||||||
|
out_q: *mut InputMatrix,
|
||||||
|
) {
|
||||||
|
let mat1 = mat1.as_mut().unwrap();
|
||||||
|
let out_h = out_h.as_mut().unwrap();
|
||||||
|
let out_q = out_q.as_mut().unwrap();
|
||||||
|
|
||||||
|
if mat1.ndims != 2 {
|
||||||
|
let err_msg = format!("expected 2D Vector Input, but received {}D input", mat1.ndims);
|
||||||
|
raise_exn!("ValueError", "sp_linalg_hessenberg", err_msg);
|
||||||
|
}
|
||||||
|
|
||||||
|
let dim1 = (*mat1).get_dims();
|
||||||
|
|
||||||
|
if dim1[0] != dim1[1] {
|
||||||
|
let err_msg =
|
||||||
|
format!("last 2 dimensions of the array must be square: {} != {}", dim1[0], dim1[1]);
|
||||||
|
raise_exn!("LinAlgError", "sp_linalg_hessenberg", err_msg);
|
||||||
|
}
|
||||||
|
|
||||||
|
let out_h_dim = (*out_h).get_dims();
|
||||||
|
let out_q_dim = (*out_q).get_dims();
|
||||||
|
|
||||||
|
let data_slice1 = unsafe { slice::from_raw_parts_mut(mat1.data, dim1[0] * dim1[1]) };
|
||||||
|
let out_h_slice = unsafe { slice::from_raw_parts_mut(out_h.data, out_h_dim[0] * out_h_dim[1]) };
|
||||||
|
let out_q_slice = unsafe { slice::from_raw_parts_mut(out_q.data, out_q_dim[0] * out_q_dim[1]) };
|
||||||
|
|
||||||
|
let matrix = DMatrix::from_row_slice(dim1[0], dim1[1], data_slice1);
|
||||||
|
let (q, h) = matrix.hessenberg().unpack();
|
||||||
|
|
||||||
|
out_h_slice.copy_from_slice(h.transpose().as_slice());
|
||||||
|
out_q_slice.copy_from_slice(q.transpose().as_slice());
|
||||||
|
}
|
||||||
|
|
@ -0,0 +1,66 @@
|
||||||
|
#![allow(non_camel_case_types)]
|
||||||
|
#![allow(unused)]
|
||||||
|
|
||||||
|
// ARTIQ Exception struct declaration
|
||||||
|
use cslice::CSlice;
|
||||||
|
|
||||||
|
// Note: CSlice within an exception may not be actual cslice, they may be strings that exist only
|
||||||
|
// in the host. If the length == usize:MAX, the pointer is actually a string key in the host.
|
||||||
|
#[repr(C)]
|
||||||
|
#[derive(Clone)]
|
||||||
|
pub struct Exception<'a> {
|
||||||
|
pub id: u32,
|
||||||
|
pub file: CSlice<'a, u8>,
|
||||||
|
pub line: u32,
|
||||||
|
pub column: u32,
|
||||||
|
pub function: CSlice<'a, u8>,
|
||||||
|
pub message: CSlice<'a, u8>,
|
||||||
|
pub param: [i64; 3],
|
||||||
|
}
|
||||||
|
|
||||||
|
fn str_err(_: core::str::Utf8Error) -> core::fmt::Error {
|
||||||
|
core::fmt::Error
|
||||||
|
}
|
||||||
|
|
||||||
|
fn exception_str<'a>(s: &'a CSlice<'a, u8>) -> Result<&'a str, core::str::Utf8Error> {
|
||||||
|
if s.len() == usize::MAX {
|
||||||
|
Ok("<host string>")
|
||||||
|
} else {
|
||||||
|
core::str::from_utf8(s.as_ref())
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
pub unsafe fn raise(exception: *const Exception) -> ! {
|
||||||
|
let e = &*exception;
|
||||||
|
let f1 = exception_str(&e.function).map_err(str_err).unwrap();
|
||||||
|
let f2 = exception_str(&e.file).map_err(str_err).unwrap();
|
||||||
|
let f3 = exception_str(&e.message).map_err(str_err).unwrap();
|
||||||
|
|
||||||
|
panic!("Exception {} from {} in {}:{}:{}, message: {}", e.id, f1, f2, e.line, e.column, f3);
|
||||||
|
}
|
||||||
|
|
||||||
|
static EXCEPTION_ID_LOOKUP: [(&str, u32); 14] = [
|
||||||
|
("RuntimeError", 0),
|
||||||
|
("RTIOUnderflow", 1),
|
||||||
|
("RTIOOverflow", 2),
|
||||||
|
("RTIODestinationUnreachable", 3),
|
||||||
|
("DMAError", 4),
|
||||||
|
("I2CError", 5),
|
||||||
|
("CacheError", 6),
|
||||||
|
("SPIError", 7),
|
||||||
|
("ZeroDivisionError", 8),
|
||||||
|
("IndexError", 9),
|
||||||
|
("UnwrapNoneError", 10),
|
||||||
|
("Value", 11),
|
||||||
|
("ValueError", 12),
|
||||||
|
("LinAlgError", 13),
|
||||||
|
];
|
||||||
|
|
||||||
|
pub fn get_exception_id(name: &str) -> u32 {
|
||||||
|
for (n, id) in EXCEPTION_ID_LOOKUP.iter() {
|
||||||
|
if *n == name {
|
||||||
|
return *id;
|
||||||
|
}
|
||||||
|
}
|
||||||
|
unimplemented!("unallocated internal exception id")
|
||||||
|
}
|
||||||
Loading…
Reference in New Issue