1use poulpy_hal::{
  2    layouts::{Data, DataMut, DataRef, FillUniform, ReaderFrom, WriterTo},
  3    source::Source,
  4};
  5
  6use crate::layouts::{
  7    Base2K, Degree, Dnum, Dsize, GGLWEInfos, GLWEInfos, GLWESwitchingKey, GLWESwitchingKeyToMut, GLWESwitchingKeyToRef, LWEInfos,
  8    Rank, TorusPrecision,
  9};
 10use byteorder::{LittleEndian, ReadBytesExt, WriteBytesExt};
 11
 12use std::fmt;
 13
 14#[derive(PartialEq, Eq, Copy, Clone, Debug)]
 15pub struct TensorKeyLayout {
 16    pub n: Degree,
 17    pub base2k: Base2K,
 18    pub k: TorusPrecision,
 19    pub rank: Rank,
 20    pub dnum: Dnum,
 21    pub dsize: Dsize,
 22}
 23
 24#[derive(PartialEq, Eq, Clone)]
 25pub struct TensorKey<D: Data> {
 26    pub(crate) keys: Vec<GLWESwitchingKey<D>>,
 27}
 28
 29impl<D: Data> LWEInfos for TensorKey<D> {
 30    fn n(&self) -> Degree {
 31        self.keys[0].n()
 32    }
 33
 34    fn base2k(&self) -> Base2K {
 35        self.keys[0].base2k()
 36    }
 37
 38    fn k(&self) -> TorusPrecision {
 39        self.keys[0].k()
 40    }
 41
 42    fn size(&self) -> usize {
 43        self.keys[0].size()
 44    }
 45}
 46
 47impl<D: Data> GLWEInfos for TensorKey<D> {
 48    fn rank(&self) -> Rank {
 49        self.keys[0].rank_out()
 50    }
 51}
 52
 53impl<D: Data> GGLWEInfos for TensorKey<D> {
 54    fn rank_in(&self) -> Rank {
 55        self.rank_out()
 56    }
 57
 58    fn rank_out(&self) -> Rank {
 59        self.keys[0].rank_out()
 60    }
 61
 62    fn dsize(&self) -> Dsize {
 63        self.keys[0].dsize()
 64    }
 65
 66    fn dnum(&self) -> Dnum {
 67        self.keys[0].dnum()
 68    }
 69}
 70
 71impl LWEInfos for TensorKeyLayout {
 72    fn n(&self) -> Degree {
 73        self.n
 74    }
 75
 76    fn base2k(&self) -> Base2K {
 77        self.base2k
 78    }
 79
 80    fn k(&self) -> TorusPrecision {
 81        self.k
 82    }
 83}
 84
 85impl GLWEInfos for TensorKeyLayout {
 86    fn rank(&self) -> Rank {
 87        self.rank_out()
 88    }
 89}
 90
 91impl GGLWEInfos for TensorKeyLayout {
 92    fn rank_in(&self) -> Rank {
 93        self.rank
 94    }
 95
 96    fn dsize(&self) -> Dsize {
 97        self.dsize
 98    }
 99
100    fn rank_out(&self) -> Rank {
101        self.rank
102    }
103
104    fn dnum(&self) -> Dnum {
105        self.dnum
106    }
107}
108
109impl<D: DataRef> fmt::Debug for TensorKey<D> {
110    fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
111        write!(f, "{self}")
112    }
113}
114
115impl<D: DataMut> FillUniform for TensorKey<D> {
116    fn fill_uniform(&mut self, log_bound: usize, source: &mut Source) {
117        self.keys
118            .iter_mut()
119            .for_each(|key: &mut GLWESwitchingKey<D>| key.fill_uniform(log_bound, source))
120    }
121}
122
123impl<D: DataRef> fmt::Display for TensorKey<D> {
124    fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
125        writeln!(f, "(GLWETensorKey)",)?;
126        for (i, key) in self.keys.iter().enumerate() {
127            write!(f, "{i}: {key}")?;
128        }
129        Ok(())
130    }
131}
132
133impl TensorKey<Vec<u8>> {
134    pub fn alloc_from_infos<A>(infos: &A) -> Self
135    where
136        A: GGLWEInfos,
137    {
138        assert_eq!(
139            infos.rank_in(),
140            infos.rank_out(),
141            "rank_in != rank_out is not supported for GGLWETensorKey"
142        );
143        Self::alloc(
144            infos.n(),
145            infos.base2k(),
146            infos.k(),
147            infos.rank(),
148            infos.dnum(),
149            infos.dsize(),
150        )
151    }
152
153    pub fn alloc(n: Degree, base2k: Base2K, k: TorusPrecision, rank: Rank, dnum: Dnum, dsize: Dsize) -> Self {
154        let pairs: u32 = (((rank.0 + 1) * rank.0) >> 1).max(1);
155        TensorKey {
156            keys: (0..pairs)
157                .map(|_| GLWESwitchingKey::alloc(n, base2k, k, Rank(1), rank, dnum, dsize))
158                .collect(),
159        }
160    }
161
162    pub fn bytes_of_from_infos<A>(infos: &A) -> usize
163    where
164        A: GGLWEInfos,
165    {
166        assert_eq!(
167            infos.rank_in(),
168            infos.rank_out(),
169            "rank_in != rank_out is not supported for GGLWETensorKey"
170        );
171        Self::bytes_of(
172            infos.n(),
173            infos.base2k(),
174            infos.k(),
175            infos.rank(),
176            infos.dnum(),
177            infos.dsize(),
178        )
179    }
180
181    pub fn bytes_of(n: Degree, base2k: Base2K, k: TorusPrecision, rank: Rank, dnum: Dnum, dsize: Dsize) -> usize {
182        let pairs: usize = (((rank.0 + 1) * rank.0) >> 1).max(1) as usize;
183        pairs * GLWESwitchingKey::bytes_of(n, base2k, k, Rank(1), rank, dnum, dsize)
184    }
185}
186
187impl<D: DataMut> TensorKey<D> {
188    // Returns a mutable reference to GLWESwitchingKey_{s}(s[i] * s[j])
189    pub fn at_mut(&mut self, mut i: usize, mut j: usize) -> &mut GLWESwitchingKey<D> {
190        if i > j {
191            std::mem::swap(&mut i, &mut j);
192        };
193        let rank: usize = self.rank_out().into();
194        &mut self.keys[i * rank + j - (i * (i + 1) / 2)]
195    }
196}
197
198impl<D: DataRef> TensorKey<D> {
199    // Returns a reference to GLWESwitchingKey_{s}(s[i] * s[j])
200    pub fn at(&self, mut i: usize, mut j: usize) -> &GLWESwitchingKey<D> {
201        if i > j {
202            std::mem::swap(&mut i, &mut j);
203        };
204        let rank: usize = self.rank_out().into();
205        &self.keys[i * rank + j - (i * (i + 1) / 2)]
206    }
207}
208
209impl<D: DataMut> ReaderFrom for TensorKey<D> {
210    fn read_from<R: std::io::Read>(&mut self, reader: &mut R) -> std::io::Result<()> {
211        let len: usize = reader.read_u64::<LittleEndian>()? as usize;
212        if self.keys.len() != len {
213            return Err(std::io::Error::new(
214                std::io::ErrorKind::InvalidData,
215                format!("self.keys.len()={} != read len={}", self.keys.len(), len),
216            ));
217        }
218        for key in &mut self.keys {
219            key.read_from(reader)?;
220        }
221        Ok(())
222    }
223}
224
225impl<D: DataRef> WriterTo for TensorKey<D> {
226    fn write_to<W: std::io::Write>(&self, writer: &mut W) -> std::io::Result<()> {
227        writer.write_u64::<LittleEndian>(self.keys.len() as u64)?;
228        for key in &self.keys {
229            key.write_to(writer)?;
230        }
231        Ok(())
232    }
233}
234
235pub trait TensorKeyToRef {
236    fn to_ref(&self) -> TensorKey<&[u8]>;
237}
238
239impl<D: DataRef> TensorKeyToRef for TensorKey<D>
240where
241    GLWESwitchingKey<D>: GLWESwitchingKeyToRef,
242{
243    fn to_ref(&self) -> TensorKey<&[u8]> {
244        TensorKey {
245            keys: self.keys.iter().map(|c| c.to_ref()).collect(),
246        }
247    }
248}
249
250pub trait TensorKeyToMut {
251    fn to_mut(&mut self) -> TensorKey<&mut [u8]>;
252}
253
254impl<D: DataMut> TensorKeyToMut for TensorKey<D>
255where
256    GLWESwitchingKey<D>: GLWESwitchingKeyToMut,
257{
258    fn to_mut(&mut self) -> TensorKey<&mut [u8]> {
259        TensorKey {
260            keys: self.keys.iter_mut().map(|c| c.to_mut()).collect(),
261        }
262    }
263}