1use poulpy_hal::{
  2    layouts::{Data, DataMut, DataRef, FillUniform, ReaderFrom, WriterTo},
  3    source::Source,
  4};
  5
  6use crate::layouts::{
  7    Base2K, Degree, Dnum, Dsize, GGLWE, GGLWEInfos, GGLWEToMut, GGLWEToRef, GLWEInfos, LWEInfos, Rank, TorusPrecision,
  8};
  9use byteorder::{LittleEndian, ReadBytesExt, WriteBytesExt};
 10
 11use std::fmt;
 12
 13#[derive(PartialEq, Eq, Copy, Clone, Debug)]
 14pub struct TensorKeyLayout {
 15    pub n: Degree,
 16    pub base2k: Base2K,
 17    pub k: TorusPrecision,
 18    pub rank: Rank,
 19    pub dnum: Dnum,
 20    pub dsize: Dsize,
 21}
 22
 23#[derive(PartialEq, Eq, Clone)]
 24pub struct TensorKey<D: Data> {
 25    pub(crate) keys: Vec<GGLWE<D>>,
 26}
 27
 28impl<D: Data> LWEInfos for TensorKey<D> {
 29    fn n(&self) -> Degree {
 30        self.keys[0].n()
 31    }
 32
 33    fn base2k(&self) -> Base2K {
 34        self.keys[0].base2k()
 35    }
 36
 37    fn k(&self) -> TorusPrecision {
 38        self.keys[0].k()
 39    }
 40
 41    fn size(&self) -> usize {
 42        self.keys[0].size()
 43    }
 44}
 45
 46impl<D: Data> GLWEInfos for TensorKey<D> {
 47    fn rank(&self) -> Rank {
 48        self.keys[0].rank_out()
 49    }
 50}
 51
 52impl<D: Data> GGLWEInfos for TensorKey<D> {
 53    fn rank_in(&self) -> Rank {
 54        self.rank_out()
 55    }
 56
 57    fn rank_out(&self) -> Rank {
 58        self.keys[0].rank_out()
 59    }
 60
 61    fn dsize(&self) -> Dsize {
 62        self.keys[0].dsize()
 63    }
 64
 65    fn dnum(&self) -> Dnum {
 66        self.keys[0].dnum()
 67    }
 68}
 69
 70impl LWEInfos for TensorKeyLayout {
 71    fn n(&self) -> Degree {
 72        self.n
 73    }
 74
 75    fn base2k(&self) -> Base2K {
 76        self.base2k
 77    }
 78
 79    fn k(&self) -> TorusPrecision {
 80        self.k
 81    }
 82}
 83
 84impl GLWEInfos for TensorKeyLayout {
 85    fn rank(&self) -> Rank {
 86        self.rank_out()
 87    }
 88}
 89
 90impl GGLWEInfos for TensorKeyLayout {
 91    fn rank_in(&self) -> Rank {
 92        self.rank
 93    }
 94
 95    fn dsize(&self) -> Dsize {
 96        self.dsize
 97    }
 98
 99    fn rank_out(&self) -> Rank {
100        self.rank
101    }
102
103    fn dnum(&self) -> Dnum {
104        self.dnum
105    }
106}
107
108impl<D: DataRef> fmt::Debug for TensorKey<D> {
109    fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
110        write!(f, "{self}")
111    }
112}
113
114impl<D: DataMut> FillUniform for TensorKey<D> {
115    fn fill_uniform(&mut self, log_bound: usize, source: &mut Source) {
116        self.keys
117            .iter_mut()
118            .for_each(|key: &mut GGLWE<D>| key.fill_uniform(log_bound, source))
119    }
120}
121
122impl<D: DataRef> fmt::Display for TensorKey<D> {
123    fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
124        writeln!(f, "(GLWETensorKey)",)?;
125        for (i, key) in self.keys.iter().enumerate() {
126            write!(f, "{i}: {key}")?;
127        }
128        Ok(())
129    }
130}
131
132impl TensorKey<Vec<u8>> {
133    pub fn alloc_from_infos<A>(infos: &A) -> Self
134    where
135        A: GGLWEInfos,
136    {
137        assert_eq!(
138            infos.rank_in(),
139            infos.rank_out(),
140            "rank_in != rank_out is not supported for GGLWETensorKey"
141        );
142        Self::alloc(
143            infos.n(),
144            infos.base2k(),
145            infos.k(),
146            infos.rank(),
147            infos.dnum(),
148            infos.dsize(),
149        )
150    }
151
152    pub fn alloc(n: Degree, base2k: Base2K, k: TorusPrecision, rank: Rank, dnum: Dnum, dsize: Dsize) -> Self {
153        let pairs: u32 = (((rank.0 + 1) * rank.0) >> 1).max(1);
154        TensorKey {
155            keys: (0..pairs)
156                .map(|_| GGLWE::alloc(n, base2k, k, Rank(1), rank, dnum, dsize))
157                .collect(),
158        }
159    }
160
161    pub fn bytes_of_from_infos<A>(infos: &A) -> usize
162    where
163        A: GGLWEInfos,
164    {
165        assert_eq!(
166            infos.rank_in(),
167            infos.rank_out(),
168            "rank_in != rank_out is not supported for GGLWETensorKey"
169        );
170        Self::bytes_of(
171            infos.n(),
172            infos.base2k(),
173            infos.k(),
174            infos.rank(),
175            infos.dnum(),
176            infos.dsize(),
177        )
178    }
179
180    pub fn bytes_of(n: Degree, base2k: Base2K, k: TorusPrecision, rank: Rank, dnum: Dnum, dsize: Dsize) -> usize {
181        let pairs: usize = (((rank.0 + 1) * rank.0) >> 1).max(1) as usize;
182        pairs * GGLWE::bytes_of(n, base2k, k, Rank(1), rank, dnum, dsize)
183    }
184}
185
186impl<D: DataMut> TensorKey<D> {
187    // Returns a mutable reference to GGLWE_{s}(s[i] * s[j])
188    pub fn at_mut(&mut self, mut i: usize, mut j: usize) -> &mut GGLWE<D> {
189        if i > j {
190            std::mem::swap(&mut i, &mut j);
191        };
192        let rank: usize = self.rank_out().into();
193        &mut self.keys[i * rank + j - (i * (i + 1) / 2)]
194    }
195}
196
197impl<D: DataRef> TensorKey<D> {
198    // Returns a reference to GGLWE_{s}(s[i] * s[j])
199    pub fn at(&self, mut i: usize, mut j: usize) -> &GGLWE<D> {
200        if i > j {
201            std::mem::swap(&mut i, &mut j);
202        };
203        let rank: usize = self.rank_out().into();
204        &self.keys[i * rank + j - (i * (i + 1) / 2)]
205    }
206}
207
208impl<D: DataMut> ReaderFrom for TensorKey<D> {
209    fn read_from<R: std::io::Read>(&mut self, reader: &mut R) -> std::io::Result<()> {
210        let len: usize = reader.read_u64::<LittleEndian>()? as usize;
211        if self.keys.len() != len {
212            return Err(std::io::Error::new(
213                std::io::ErrorKind::InvalidData,
214                format!("self.keys.len()={} != read len={}", self.keys.len(), len),
215            ));
216        }
217        for key in &mut self.keys {
218            key.read_from(reader)?;
219        }
220        Ok(())
221    }
222}
223
224impl<D: DataRef> WriterTo for TensorKey<D> {
225    fn write_to<W: std::io::Write>(&self, writer: &mut W) -> std::io::Result<()> {
226        writer.write_u64::<LittleEndian>(self.keys.len() as u64)?;
227        for key in &self.keys {
228            key.write_to(writer)?;
229        }
230        Ok(())
231    }
232}
233
234pub trait TensorKeyToRef {
235    fn to_ref(&self) -> TensorKey<&[u8]>;
236}
237
238impl<D: DataRef> TensorKeyToRef for TensorKey<D>
239where
240    GGLWE<D>: GGLWEToRef,
241{
242    fn to_ref(&self) -> TensorKey<&[u8]> {
243        TensorKey {
244            keys: self.keys.iter().map(|c| c.to_ref()).collect(),
245        }
246    }
247}
248
249pub trait TensorKeyToMut {
250    fn to_mut(&mut self) -> TensorKey<&mut [u8]>;
251}
252
253impl<D: DataMut> TensorKeyToMut for TensorKey<D>
254where
255    GGLWE<D>: GGLWEToMut,
256{
257    fn to_mut(&mut self) -> TensorKey<&mut [u8]> {
258        TensorKey {
259            keys: self.keys.iter_mut().map(|c| c.to_mut()).collect(),
260        }
261    }
262}