kernel: add linalg functions #309
219
src/Cargo.lock
generated
219
src/Cargo.lock
generated
@ -2,6 +2,15 @@
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|||||||
# It is not intended for manual editing.
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# It is not intended for manual editing.
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version = 3
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version = 3
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||||||
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||||||
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[[package]]
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||||||
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name = "approx"
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||||||
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version = "0.5.1"
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||||||
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source = "registry+https://github.com/rust-lang/crates.io-index"
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||||||
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checksum = "cab112f0a86d568ea0e627cc1d6be74a1e9cd55214684db5561995f6dad897c6"
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||||||
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dependencies = [
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||||||
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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 = "arrayvec"
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name = "arrayvec"
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version = "0.7.4"
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version = "0.7.4"
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@ -246,10 +255,10 @@ dependencies = [
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"libsupport_zynq",
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"libsupport_zynq",
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"log",
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"log",
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"log_buffer",
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"log_buffer",
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"nalgebra",
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"nb 0.1.3",
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"nb 0.1.3",
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"unwind",
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"unwind",
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"vcell",
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"vcell",
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"nalgebra",
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"void",
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"void",
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]
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]
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@ -383,6 +392,19 @@ version = "0.7.2"
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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 = "c75de51135344a4f8ed3cfe2720dc27736f7711989703a0b43aadf3753c55577"
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checksum = "c75de51135344a4f8ed3cfe2720dc27736f7711989703a0b43aadf3753c55577"
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[[package]]
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name = "nalgebra"
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version = "0.32.6"
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source = "git+https://git.m-labs.hk/M-labs/nalgebra?rev=dd00f9b#dd00f9b46046e0b931d1b470166db02fd29591be"
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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 = "nb"
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name = "nb"
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version = "0.1.3"
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version = "0.1.3"
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@ -398,6 +420,15 @@ version = "1.0.0"
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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 = "546c37ac5d9e56f55e73b677106873d9d9f5190605e41a856503623648488cae"
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checksum = "546c37ac5d9e56f55e73b677106873d9d9f5190605e41a856503623648488cae"
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[[package]]
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name = "num-complex"
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version = "0.4.0"
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source = "registry+https://github.com/rust-lang/crates.io-index"
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checksum = "26873667bbbb7c5182d4a37c1add32cdf09f841af72da53318fdb81543c15085"
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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 = "num-derive"
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name = "num-derive"
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version = "0.3.3"
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version = "0.3.3"
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@ -409,6 +440,26 @@ dependencies = [
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"syn",
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"syn",
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]
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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 = "0.4.0"
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source = "registry+https://github.com/rust-lang/crates.io-index"
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checksum = "d41702bd167c2df5520b384281bc111a4b5efcf7fbc4c9c222c815b07e0a6a6a"
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dependencies = [
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"autocfg",
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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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[[package]]
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name = "num-traits"
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name = "num-traits"
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version = "0.2.15"
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version = "0.2.15"
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@ -416,8 +467,15 @@ source = "registry+https://github.com/rust-lang/crates.io-index"
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checksum = "578ede34cf02f8924ab9447f50c28075b4d3e5b269972345e7e0372b38c6cdcd"
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checksum = "578ede34cf02f8924ab9447f50c28075b4d3e5b269972345e7e0372b38c6cdcd"
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dependencies = [
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dependencies = [
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"autocfg",
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"autocfg",
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"libm",
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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 = "pin-project-lite"
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name = "pin-project-lite"
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version = "0.2.9"
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version = "0.2.9"
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@ -524,6 +582,18 @@ version = "0.1.20"
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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 = "d4f410fedcf71af0345d7607d246e7ad15faaadd49d240ee3b24e5dc21a820ac"
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checksum = "d4f410fedcf71af0345d7607d246e7ad15faaadd49d240ee3b24e5dc21a820ac"
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[[package]]
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name = "simba"
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version = "0.8.0"
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source = "registry+https://github.com/rust-lang/crates.io-index"
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checksum = "50582927ed6f77e4ac020c057f37a268fc6aebc29225050365aacbb9deeeddc4"
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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 = "smoltcp"
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name = "smoltcp"
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version = "0.7.5"
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version = "0.7.5"
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@ -556,6 +626,12 @@ dependencies = [
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"log",
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"log",
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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 = "unicode-ident"
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name = "unicode-ident"
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version = "1.0.5"
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version = "1.0.5"
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@ -572,147 +648,6 @@ 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 = "nalgebra"
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version = "0.32.6"
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source = "git+https://git.m-labs.hk/M-labs/nalgebra?rev=dd00f9b#dd00f9b46046e0b931d1b470166db02fd29591be"
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dependencies = [
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"approx",
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"matrixmultiply",
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"nalgebra-macros",
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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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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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name = "matrixmultiply"
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version = "0.3.8"
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source = "registry+https://github.com/rust-lang/crates.io-index"
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checksum = "7574c1cf36da4798ab73da5b215bbf444f50718207754cb522201d78d1cd0ff2"
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dependencies = [
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"autocfg",
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"rawpointer",
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]
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[[package]]
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name = "nalgebra-macros"
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version = "0.2.1"
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source = "registry+https://github.com/rust-lang/crates.io-index"
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checksum = "91761aed67d03ad966ef783ae962ef9bbaca728d2dd7ceb7939ec110fffad998"
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dependencies = [
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"proc-macro2",
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"quote",
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"syn",
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]
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[[package]]
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name = "num-complex"
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version = "0.4.0"
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source = "registry+https://github.com/rust-lang/crates.io-index"
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checksum = "26873667bbbb7c5182d4a37c1add32cdf09f841af72da53318fdb81543c15085"
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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 = "0.4.0"
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source = "registry+https://github.com/rust-lang/crates.io-index"
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checksum = "d41702bd167c2df5520b384281bc111a4b5efcf7fbc4c9c222c815b07e0a6a6a"
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dependencies = [
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"num-bigint",
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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 = "simba"
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version = "0.8.0"
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source = "registry+https://github.com/rust-lang/crates.io-index"
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checksum = "50582927ed6f77e4ac020c057f37a268fc6aebc29225050365aacbb9deeeddc4"
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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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"wide",
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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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name = "rawpointer"
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version = "0.2.1"
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source = "registry+https://github.com/rust-lang/crates.io-index"
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checksum = "60a357793950651c4ed0f3f52338f53b2f809f32d83a07f72909fa13e4c6c1e3"
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[[package]]
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name = "num-bigint"
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version = "0.4.0"
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source = "registry+https://github.com/rust-lang/crates.io-index"
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checksum = "4e0d047c1062aa51e256408c560894e5251f08925980e53cf1aa5bd00eec6512"
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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-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 = "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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name = "wide"
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version = "0.7.0"
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source = "registry+https://github.com/rust-lang/crates.io-index"
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checksum = "cd89cf484471f953ee84f07c0dff0ea20e9ddf976f03cabdf5dda48b221f22e7"
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features = ["no_std"]
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dependencies = [
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"bytemuck",
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"safe_arch",
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]
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[[package]]
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name = "bytemuck"
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version = "1.16.1"
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source = "registry+https://github.com/rust-lang/crates.io-index"
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checksum = "b236fc92302c97ed75b38da1f4917b5cdda4984745740f153a5d3059e48d725e"
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[[package]]
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name = "safe_arch"
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version = "0.6.0"
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source = "registry+https://github.com/rust-lang/crates.io-index"
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checksum = "794821e4ccb0d9f979512f9c1973480123f9bd62a90d74ab0f9426fcf8f4a529"
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dependencies = [
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"bytemuck",
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]
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[[package]]
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[[package]]
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||||||
name = "vcell"
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name = "vcell"
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||||||
version = "0.1.3"
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version = "0.1.3"
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@ -1,16 +1,15 @@
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use alloc::vec;
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use alloc::vec;
|
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use core::{ffi::VaList, ptr, slice, str};
|
use core::{ffi::VaList, ptr, str};
|
||||||
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|
||||||
use libc::{c_char, c_int, size_t};
|
use libc::{c_char, c_int, size_t};
|
||||||
use libm;
|
use libm;
|
||||||
use log::{info, warn};
|
use log::{info, warn};
|
||||||
use nalgebra::{linalg, DMatrix};
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|
||||||
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|
||||||
#[cfg(has_drtio)]
|
#[cfg(has_drtio)]
|
||||||
use super::subkernel;
|
use super::subkernel;
|
||||||
use super::{cache,
|
use super::{cache,
|
||||||
core1::rtio_get_destination_status,
|
core1::rtio_get_destination_status,
|
||||||
dma,
|
dma, linalg,
|
||||||
rpc::{rpc_recv, rpc_send, rpc_send_async}};
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rpc::{rpc_recv, rpc_send, rpc_send_async}};
|
||||||
use crate::{eh_artiq, i2c, rtio};
|
use crate::{eh_artiq, i2c, rtio};
|
||||||
|
|
||||||
@ -39,26 +38,6 @@ unsafe extern "C" fn rtio_log(fmt: *const c_char, mut args: ...) {
|
|||||||
rtio::write_log(buf.as_slice());
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rtio::write_log(buf.as_slice());
|
||||||
}
|
}
|
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|
||||||
unsafe extern "C" fn linalg_try_invert_to(dim0: usize, dim1: usize, data: *mut f64) -> i8 {
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|
||||||
let data_slice = unsafe { slice::from_raw_parts_mut(data, dim0 * dim1) };
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|
||||||
let matrix = DMatrix::from_row_slice(dim0, dim1, data_slice);
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|
||||||
let mut inverted_matrix = DMatrix::<f64>::zeros(dim0, dim1);
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|
||||||
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|
||||||
if linalg::try_invert_to(matrix, &mut inverted_matrix) {
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|
||||||
data_slice.copy_from_slice(inverted_matrix.transpose().as_slice());
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|
||||||
1
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|
||||||
} else {
|
|
||||||
0
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|
||||||
}
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|
||||||
}
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|
||||||
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|
||||||
unsafe extern "C" fn linalg_wilkinson_shift(dim0: usize, dim1: usize, data: *mut f64) -> f64 {
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|
||||||
let data_slice = slice::from_raw_parts_mut(data, dim0 * dim1);
|
|
||||||
let matrix = DMatrix::from_row_slice(dim0, dim1, data_slice);
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|
||||||
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|
||||||
linalg::wilkinson_shift(matrix[(0, 0)], matrix[(1, 1)], matrix[(0, 1)])
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|
||||||
}
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|
||||||
macro_rules! api {
|
macro_rules! api {
|
||||||
($i:ident) => ({
|
($i:ident) => ({
|
||||||
extern { static $i: u8; }
|
extern { static $i: u8; }
|
||||||
@ -342,8 +321,17 @@ pub fn resolve(required: &[u8]) -> Option<u32> {
|
|||||||
},
|
},
|
||||||
|
|
||||||
// linalg
|
// linalg
|
||||||
api!(linalg_try_invert_to = linalg_try_invert_to),
|
api!(np_linalg_cholesky = linalg::np_linalg_cholesky),
|
||||||
api!(linalg_wilkinson_shift = linalg_wilkinson_shift),
|
api!(np_linalg_qr = linalg::np_linalg_qr),
|
||||||
|
sb10q marked this conversation as resolved
Outdated
|
|||||||
|
api!(np_linalg_svd = linalg::np_linalg_svd),
|
||||||
|
sb10q marked this conversation as resolved
Outdated
sb10q
commented
Still needs removal. Still needs removal.
|
|||||||
|
api!(np_linalg_inv = linalg::np_linalg_inv),
|
||||||
|
api!(np_linalg_pinv = linalg::np_linalg_pinv),
|
||||||
|
api!(np_linalg_matrix_power = linalg::np_linalg_matrix_power),
|
||||||
|
api!(np_linalg_det = linalg::np_linalg_det),
|
||||||
|
api!(sp_linalg_lu = linalg::sp_linalg_lu),
|
||||||
|
api!(sp_linalg_schur = linalg::sp_linalg_schur),
|
||||||
|
api!(sp_linalg_hessenberg = linalg::sp_linalg_hessenberg),
|
||||||
|
|
||||||
];
|
];
|
||||||
api.iter()
|
api.iter()
|
||||||
.find(|&&(exported, _)| exported.as_bytes() == required)
|
.find(|&&(exported, _)| exported.as_bytes() == required)
|
||||||
|
|||||||
440
src/libksupport/src/kernel/linalg.rs
Normal file
440
src/libksupport/src/kernel/linalg.rs
Normal file
@ -0,0 +1,440 @@
|
|||||||||
|
// Uses `nalgebra` crate to invoke `np_linalg` and `sp_linalg` functions
|
||||||||
|
// When converting between `nalgebra::Matrix` and `NDArray` following considerations are necessary
|
||||||||
|
//
|
||||||||
|
// * Both `nalgebra::Matrix` and `NDArray` require their content to be stored in row-major order
|
||||||||
|
// * `NDArray` data pointer can be directly read and converted to `nalgebra::Matrix` (row and column number must be known)
|
||||||||
|
// * `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
|
||||||||
|
|
||||||||
|
use alloc::vec::Vec;
|
||||||||
|
use core::slice;
|
||||||||
|
|
||||||||
|
use nalgebra::DMatrix;
|
||||||||
|
|
||||||||
|
use crate::artiq_raise;
|
||||||||
|
|
||||||||
|
pub struct InputMatrix {
|
||||||||
|
pub ndims: usize,
|
||||||||
|
pub dims: *const usize,
|
||||||||
|
pub data: *mut f64,
|
||||||||
|
}
|
||||||||
|
|
||||||||
|
impl InputMatrix {
|
||||||||
|
fn get_dims(&mut self) -> Vec<usize> {
|
||||||||
|
let dims = unsafe { slice::from_raw_parts(self.dims, self.ndims) };
|
||||||||
|
dims.to_vec()
|
||||||||
|
}
|
||||||||
|
}
|
||||||||
|
|
||||||||
|
/// # Safety
|
||||||||
|
sb10q marked this conversation as resolved
Outdated
sb10q
commented
Remove all those "safety" headers, C calls are never "safe" as per Rust's definition. Keep the descriptions of what the arguments should point to, however. Remove all those "safety" headers, C calls are never "safe" as per Rust's definition.
Keep the descriptions of what the arguments should point to, however.
abdul124
commented
Adding safety headers over unsafe functions is required when using stable rust. Should I still remove those? Adding safety headers over unsafe functions is required when using stable rust. Should I still remove those?
sb10q
commented
Hmm ok, keep them then. Hmm ok, keep them then.
|
|||||||||
|
///
|
||||||||
|
/// `mat1` should point to a valid 2DArray of `f64` floats in row-major order
|
||||||||
|
#[no_mangle]
|
||||||||
|
pub unsafe extern "C" fn np_linalg_cholesky(mat1: *mut InputMatrix, out: *mut InputMatrix) {
|
||||||||
|
let mat1 = mat1.as_mut().unwrap();
|
||||||||
|
let out = out.as_mut().unwrap();
|
||||||||
|
|
||||||||
|
if mat1.ndims != 2 {
|
||||||||
|
artiq_raise!(
|
||||||||
|
"ValueError",
|
||||||||
|
"expected 2D Vector Input, but received {1}D input)",
|
||||||||
|
0,
|
||||||||
|
mat1.ndims as i64,
|
||||||||
|
0
|
||||||||
|
);
|
||||||||
|
}
|
||||||||
|
|
||||||||
|
let dim1 = (*mat1).get_dims();
|
||||||||
|
if dim1[0] != dim1[1] {
|
||||||||
|
artiq_raise!(
|
||||||||
|
"ValueError",
|
||||||||
|
"last 2 dimensions of the array must be square: {1} != {2}",
|
||||||||
|
0,
|
||||||||
|
dim1[0] as i64,
|
||||||||
|
dim1[1] as i64
|
||||||||
|
);
|
||||||||
|
}
|
||||||||
|
|
||||||||
|
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 => {
|
||||||||
|
artiq_raise!("LinAlgError", "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 {
|
||||||||
|
artiq_raise!(
|
||||||||
|
"ValueError",
|
||||||||
|
"expected 2D Vector Input, but received {1}D input)",
|
||||||||
|
0,
|
||||||||
|
mat1.ndims as i64,
|
||||||||
|
0
|
||||||||
|
);
|
||||||||
|
}
|
||||||||
|
|
||||||||
|
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 {
|
||||||||
|
artiq_raise!(
|
||||||||
|
"ValueError",
|
||||||||
|
"expected 2D Vector Input, but received {1}D input)",
|
||||||||
|
0,
|
||||||||
|
mat1.ndims as i64,
|
||||||||
|
0
|
||||||||
|
);
|
||||||||
|
}
|
||||||||
|
|
||||||||
|
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 {
|
||||||||
|
artiq_raise!(
|
||||||||
|
"ValueError",
|
||||||||
|
"expected 2D Vector Input, but received {1}D input)",
|
||||||||
|
0,
|
||||||||
|
mat1.ndims as i64,
|
||||||||
|
0
|
||||||||
|
);
|
||||||||
|
}
|
||||||||
|
let dim1 = (*mat1).get_dims();
|
||||||||
|
|
||||||||
|
if dim1[0] != dim1[1] {
|
||||||||
|
artiq_raise!(
|
||||||||
|
"ValueError",
|
||||||||
|
"last 2 dimensions of the array must be square: {1} != {2}",
|
||||||||
|
0,
|
||||||||
|
dim1[0] as i64,
|
||||||||
|
dim1[1] as i64
|
||||||||
|
);
|
||||||||
|
}
|
||||||||
|
|
||||||||
|
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() {
|
||||||||
|
artiq_raise!("LinAlgError", "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 {
|
||||||||
|
artiq_raise!(
|
||||||||
|
"ValueError",
|
||||||||
|
"expected 2D Vector Input, but received {1}D input)",
|
||||||||
|
0,
|
||||||||
|
mat1.ndims as i64,
|
||||||||
|
0
|
||||||||
|
);
|
||||||||
|
}
|
||||||||
|
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(_) => {
|
||||||||
|
artiq_raise!("LinAlgError", "SVD computation does not converge");
|
||||||||
|
}
|
||||||||
|
}
|
||||||||
|
}
|
||||||||
|
|
||||||||
|
/// # Safety
|
||||||||
|
///
|
||||||||
|
/// `mat1` should point to a valid 2DArray of `f64` floats in row-major order
|
||||||||
|
#[no_mangle]
|
||||||||
|
pub unsafe extern "C" fn np_linalg_matrix_power(mat1: *mut InputMatrix, mat2: *mut InputMatrix, out: *mut InputMatrix) {
|
||||||||
|
let mat1 = mat1.as_mut().unwrap();
|
||||||||
|
let mat2 = mat2.as_mut().unwrap();
|
||||||||
|
let out = out.as_mut().unwrap();
|
||||||||
|
|
||||||||
|
if mat1.ndims != 2 {
|
||||||||
|
artiq_raise!(
|
||||||||
|
"ValueError",
|
||||||||
|
"expected 2D Vector Input, but received {1}D input)",
|
||||||||
|
0,
|
||||||||
|
mat1.ndims as i64,
|
||||||||
|
0
|
||||||||
|
);
|
||||||||
|
}
|
||||||||
|
|
||||||||
|
let dim1 = (*mat1).get_dims();
|
||||||||
|
let power = unsafe { slice::from_raw_parts_mut(mat2.data, 1) };
|
||||||||
|
let power = power[0];
|
||||||||
|
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 mut abs_power = power;
|
||||||||
|
if abs_power < 0.0 {
|
||||||||
|
abs_power = abs_power * -1.0;
|
||||||||
|
}
|
||||||||
|
let matrix1 = DMatrix::from_row_slice(dim1[0], dim1[1], data_slice1);
|
||||||||
|
if !matrix1.is_square() {
|
||||||||
|
artiq_raise!(
|
||||||||
|
"ValueError",
|
||||||||
|
"last 2 dimensions of the array must be square: {1} != {2}",
|
||||||||
|
0,
|
||||||||
|
dim1[0] as i64,
|
||||||||
|
dim1[1] as i64
|
||||||||
|
);
|
||||||||
|
}
|
||||||||
|
let mut result = matrix1.pow(abs_power as u32);
|
||||||||
|
|
||||||||
|
if power < 0.0 {
|
||||||||
|
if !matrix1.is_invertible() {
|
||||||||
|
artiq_raise!("LinAlgError", "no inverse for Singular Matrix");
|
||||||||
|
}
|
||||||||
|
result = result.try_inverse().unwrap();
|
||||||||
|
}
|
||||||||
|
out_slice.copy_from_slice(result.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_det(mat1: *mut InputMatrix, out: *mut InputMatrix) {
|
||||||||
|
let mat1 = mat1.as_mut().unwrap();
|
||||||||
|
let out = out.as_mut().unwrap();
|
||||||||
|
|
||||||||
|
if mat1.ndims != 2 {
|
||||||||
|
artiq_raise!(
|
||||||||
|
"ValueError",
|
||||||||
|
"expected 2D Vector Input, but received {1}D input)",
|
||||||||
|
0,
|
||||||||
|
mat1.ndims as i64,
|
||||||||
|
0
|
||||||||
|
);
|
||||||||
|
}
|
||||||||
|
let dim1 = (*mat1).get_dims();
|
||||||||
|
let out_slice = unsafe { slice::from_raw_parts_mut(out.data, 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_square() {
|
||||||||
|
artiq_raise!(
|
||||||||
|
"ValueError",
|
||||||||
|
"last 2 dimensions of the array must be square: {1} != {2}",
|
||||||||
|
0,
|
||||||||
|
dim1[0] as i64,
|
||||||||
|
dim1[1] as i64
|
||||||||
|
);
|
||||||||
|
}
|
||||||||
|
out_slice[0] = matrix.determinant();
|
||||||||
|
}
|
||||||||
|
|
||||||||
|
sb10q
commented
2D vs. 2-D inconsistency. 2D vs. 2-D inconsistency.
abdul124
commented
Updated. Updated.
|
|||||||||
|
/// # 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 {
|
||||||||
|
artiq_raise!(
|
||||||||
|
sb10q
commented
Is it really OK to use a formatted string in artiq_raise? Is it really OK to use a formatted string in artiq_raise?
Where is the memory allocated?
abdul124
commented
Not sure about the memory allocation, but formatted string is being used in other parts of code base (
src/libksupport/src/rtio_acp.rs
Line 90 in 63f4783687
> Is it really OK to use a formatted string in artiq_raise? Where is the memory allocated?
Not sure about the memory allocation, but formatted string is being used in other parts of code base (https://git.m-labs.hk/M-Labs/artiq-zynq/src/commit/63f4783687b85902e6c6181321df7dc067778f47/src/libksupport/src/rtio_acp.rs#L90).
|
|||||||||
|
"ValueError",
|
||||||||
|
"expected 2D Vector Input, but received {1}D input)",
|
||||||||
|
0,
|
||||||||
|
mat1.ndims as i64,
|
||||||||
|
0
|
||||||||
|
);
|
||||||||
|
}
|
||||||||
|
|
||||||||
|
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 {
|
||||||||
|
artiq_raise!(
|
||||||||
|
"ValueError",
|
||||||||
|
"expected 2D Vector Input, but received {1}D input)",
|
||||||||
|
0,
|
||||||||
|
mat1.ndims as i64,
|
||||||||
|
0
|
||||||||
|
);
|
||||||||
|
}
|
||||||||
|
|
||||||||
|
let dim1 = (*mat1).get_dims();
|
||||||||
|
|
||||||||
|
if dim1[0] != dim1[1] {
|
||||||||
|
artiq_raise!(
|
||||||||
|
"ValueError",
|
||||||||
|
"last 2 dimensions of the array must be square: {1} != {2}",
|
||||||||
|
0,
|
||||||||
|
dim1[0] as i64,
|
||||||||
|
dim1[1] as i64
|
||||||||
|
);
|
||||||||
|
}
|
||||||||
|
|
||||||||
|
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 {
|
||||||||
|
artiq_raise!(
|
||||||||
|
"ValueError",
|
||||||||
|
"expected 2D Vector Input, but received {1}D input)",
|
||||||||
|
0,
|
||||||||
|
mat1.ndims as i64,
|
||||||||
|
0
|
||||||||
|
);
|
||||||||
|
}
|
||||||||
|
|
||||||||
|
let dim1 = (*mat1).get_dims();
|
||||||||
|
|
||||||||
|
if dim1[0] != dim1[1] {
|
||||||||
|
artiq_raise!(
|
||||||||
|
"ValueError",
|
||||||||
|
"last 2 dimensions of the array must be square: {1} != {2}",
|
||||||||
|
0,
|
||||||||
|
dim1[0] as i64,
|
||||||||
|
dim1[1] as i64
|
||||||||
|
);
|
||||||||
|
}
|
||||||||
|
|
||||||||
|
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());
|
||||||||
|
}
|
||||||||
@ -13,6 +13,7 @@ mod dma;
|
|||||||
mod rpc;
|
mod rpc;
|
||||||
pub use dma::DmaRecorder;
|
pub use dma::DmaRecorder;
|
||||||
mod cache;
|
mod cache;
|
||||||
|
mod linalg;
|
||||||
#[cfg(has_drtio)]
|
#[cfg(has_drtio)]
|
||||||
mod subkernel;
|
mod subkernel;
|
||||||
|
|
||||||
|
|||||||
Loading…
Reference in New Issue
Block a user
As far as I can tell, these two are trivial and do not need firmware calls. Suggest moving to IRRT.
Re-implemented
np_transposeandnp_reshapeusing LLVM IR in core. Will movenp_dotas well and remove these from firmware.Manual calls to LLVM builder or IRRT? Which way is best?
Since other functions like
np_arrayandnp_zeroare already written using LLVM IR incore/codegen/numpyI think keeping things consistent is more important.