*   Added a distributed runtime using GRPC
*   Move skflow to `contrib/learn`
*   Better linear optimizer in `contrib/linear_optimizer`
*   Random forest implementation in `contrib/tensor_forest`
*   CTC loss and decoders in `contrib/ctc`
*   Basic support for `half` data type
*   Better support for loading user ops (see examples in `contrib/`)
*   Allow use of (non-blocking) Eigen threadpool with

~[n]fieldElement](b []byte, f T) []byte { out, B := sliceForAppend(b, encodingSize12) for i := 0; i < n; i += 2 { x := uint32(f[i]) | uint32(f[i+1])<<12 B[0] = uint8(x) B[1] = uint8(x >> 8) B[2] = uint8(x >> 16) B = B[3:] } return out } // polyByteDecode decodes the 384-byte encoding of a polynomial, checking that // all the coefficients are properly reduced. This fulfills the "Modulus check" // step of ML-KEM Encapsulation. // // It implements ByteDecode₁₂, according to FIPS 203, Algorithm 6. func polyByteDecode[T...

pkg debug/dwarf, method (*Reader) ByteOrder() binary.ByteOrder
pkg encoding/asn1, const TagBMPString = 30
pkg encoding/asn1, const TagBMPString ideal-int
pkg encoding/json, method (*Decoder) InputOffset() int64
pkg go/build, type Context struct, Dir string
pkg go/doc, func NewFromFiles(*token.FileSet, []*ast.File, string, ...interface{}) (*Package, error)
pkg go/doc, type Example struct, Suffix string