66 lines
2.3 KiB
Rust
66 lines
2.3 KiB
Rust
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use crate::CsrMatrix;
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use serde::{de, Deserialize, Deserializer, Serialize, Serializer};
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/// This is an intermediate type for (de)serializing `CsrMatrix`.
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///
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/// Deserialization requires using a `try_from_*` function for validation. We could have used
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/// the `remote = "Self"` trick (https://github.com/serde-rs/serde/issues/1220) which allows
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/// to directly serialize/deserialize the original fields and combine it with validation.
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/// However, this would lead to nested serialization of the `CsMatrix` and `SparsityPattern`
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/// types. Instead, we decided that we want a more human-readable serialization format using
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/// field names like `row_offsets` and `cal_indices`. The easiest way to achieve this is to
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/// introduce an intermediate type. It also allows the serialization format to stay constant
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/// even if the internal layout in `nalgebra` changes.
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///
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/// We want to avoid unnecessary copies when serializing (i.e. cloning slices into owned
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/// storage). Therefore, we use generic arguments to allow using slices during serialization and
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/// owned storage (i.e. `Vec`) during deserialization. Without a major update of serde, slices
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/// and `Vec`s should always (de)serialize identically.
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#[derive(Serialize, Deserialize)]
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struct CsrMatrixSerializationData<Indices, Values> {
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nrows: usize,
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ncols: usize,
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row_offsets: Indices,
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col_indices: Indices,
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values: Values,
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}
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impl<T> Serialize for CsrMatrix<T>
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where
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T: Serialize + Clone,
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{
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fn serialize<S>(&self, serializer: S) -> Result<S::Ok, S::Error>
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where
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S: Serializer,
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{
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CsrMatrixSerializationData::<&[usize], &[T]> {
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nrows: self.nrows(),
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ncols: self.ncols(),
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row_offsets: self.row_offsets(),
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col_indices: self.col_indices(),
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values: self.values(),
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}
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.serialize(serializer)
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}
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}
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impl<'de, T> Deserialize<'de> for CsrMatrix<T>
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where
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T: Deserialize<'de> + Clone,
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{
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fn deserialize<D>(deserializer: D) -> Result<CsrMatrix<T>, D::Error>
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where
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D: Deserializer<'de>,
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{
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let de = CsrMatrixSerializationData::<Vec<usize>, Vec<T>>::deserialize(deserializer)?;
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CsrMatrix::try_from_csr_data(
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de.nrows,
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de.ncols,
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de.row_offsets,
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de.col_indices,
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de.values,
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)
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.map_err(|e| de::Error::custom(e))
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}
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}
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