tenferro_fft/backend.rs
1use std::fmt;
2
3use tenferro_runtime::ExtensionCacheStore;
4use tenferro_tensor::{BackendSession, Tensor, TensorRead};
5
6use crate::{FftPlanCache, FftPlanSpec};
7
8#[derive(Clone, Copy, Debug)]
9enum FftCacheOwner {
10 CallerOwned,
11 RuntimeOwned,
12}
13
14/// Execution-cache state supplied to an [`FftBackend`].
15///
16/// Direct repeated calls use a caller-owned [`FftPlanCache`], while traced
17/// execution uses the owning runtime's [`ExtensionCacheStore`]. Both ownership
18/// paths expose the same bounded typed store to a backend, so CPU, Metal, CUDA,
19/// and future implementations can retain private plans or workspaces in their
20/// own cache namespace. Constructors keep the owner representation closed.
21///
22/// # Examples
23///
24/// ```
25/// use tenferro_fft::{FftExecutionCache, FftPlanCache};
26///
27/// let mut plans = FftPlanCache::default();
28/// let cache = FftExecutionCache::caller_owned(&mut plans);
29/// assert!(format!("{cache:?}").contains("CallerOwned"));
30/// ```
31pub struct FftExecutionCache<'a> {
32 owner: FftCacheOwner,
33 store: &'a mut ExtensionCacheStore,
34}
35
36impl fmt::Debug for FftExecutionCache<'_> {
37 fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
38 f.debug_struct("FftExecutionCache")
39 .field("owner", &self.owner)
40 .field(
41 "stats",
42 &self
43 .store
44 .stats(tenferro_runtime::ExtensionCacheSelector::All),
45 )
46 .finish_non_exhaustive()
47 }
48}
49
50impl<'a> FftExecutionCache<'a> {
51 /// Build a context backed by a caller-owned typed FFT execution cache.
52 pub fn caller_owned(cache: &'a mut FftPlanCache) -> Self {
53 Self {
54 owner: FftCacheOwner::CallerOwned,
55 store: cache.store_mut(),
56 }
57 }
58
59 /// Build a context backed by an extension runtime cache store.
60 pub fn runtime_owned(cache: &'a mut ExtensionCacheStore) -> Self {
61 Self {
62 owner: FftCacheOwner::RuntimeOwned,
63 store: cache,
64 }
65 }
66
67 /// Borrow the bounded typed store owned by the caller or extension runtime.
68 ///
69 /// Backend implementations should use a stable family/cache namespace and
70 /// include every plan-identity field in the key discriminator. The store
71 /// owns LRU bounds, typed retrieval, clear behavior, entry counts, and the
72 /// retained-byte estimates supplied at insertion.
73 pub fn store_mut(&mut self) -> &mut ExtensionCacheStore {
74 self.store
75 }
76}
77
78/// Explicit backend capability required by concrete and traced FFT execution.
79///
80/// Implementations must execute on the input's existing placement. Unsupported
81/// dtypes, layouts, placements, or operations return an error; they must never
82/// transfer the tensor or select a different backend.
83///
84/// # Examples
85///
86/// ```
87/// use tenferro_cpu::{with_cpu_exec_session, CpuBackend};
88/// use tenferro_fft::FftBackend;
89/// use tenferro_tensor::BackendSessionHost;
90///
91/// fn accepts_fft_backend<B: FftBackend>(_backend: &mut B) {}
92///
93/// let mut backend = CpuBackend::new();
94/// backend.with_backend_session(|session| {
95/// with_cpu_exec_session(session, |exec_session| accepts_fft_backend(exec_session))
96/// .expect("CpuBackend must expose a CPU execution session");
97/// });
98/// ```
99///
100/// A generic tensor backend without this explicit capability cannot build
101/// the FFT extension module:
102///
103/// ```compile_fail
104/// use tenferro_tensor::{Tensor, TensorBackend};
105/// use tenferro_fft::{FftNorm, TensorFftExt};
106///
107/// fn use_without_fft_capability<B: TensorBackend + 'static>(backend: &mut B, input: &Tensor) {
108/// let _module =
109/// tenferro_fft::extension_module::<B>(tenferro_cpu::runtime_engine_id().unwrap()).unwrap();
110/// let _ = input.fft(None, -1, FftNorm::Backward, backend);
111/// }
112/// ```
113pub trait FftBackend: BackendSession {
114 /// Validate a borrowed runtime input before the extension read path
115 /// materializes it into a compact tensor.
116 ///
117 /// Backends that can materialize their own placement may keep the default
118 /// no-op. CPU overrides this to report device inputs as unsupported FFT
119 /// placement errors instead of leaking a generic host-materialization error.
120 ///
121 /// # Errors
122 ///
123 /// Returns [`tenferro_tensor::Error::Unsupported`] when this backend cannot
124 /// consume the borrowed input placement without an explicit transfer.
125 fn validate_fft_read_input(
126 &self,
127 _op: &'static str,
128 _input: &TensorRead<'_>,
129 ) -> tenferro_tensor::Result<()> {
130 Ok(())
131 }
132
133 /// Execute one validated FFT request on `input`'s existing placement.
134 ///
135 /// # Errors
136 ///
137 /// Returns [`tenferro_tensor::Error::Unsupported`] for an unsupported
138 /// operation, dtype, layout, or placement;
139 /// [`tenferro_tensor::Error::Validation`] for inconsistent input/spec
140 /// metadata or checked shape arithmetic; and a typed backend or runtime
141 /// source when plan creation, cache access, or execution fails.
142 fn execute_fft(
143 &mut self,
144 input: &Tensor,
145 spec: &FftPlanSpec,
146 cache: FftExecutionCache<'_>,
147 ) -> tenferro_tensor::Result<Tensor>;
148}
149
150#[cfg(test)]
151mod tests {
152 use super::*;
153
154 #[test]
155 fn execution_cache_debug_identifies_both_owners_and_exposes_the_store() {
156 let mut caller = FftPlanCache::default();
157 let mut caller_cache = FftExecutionCache::caller_owned(&mut caller);
158 assert!(format!("{caller_cache:?}").contains("CallerOwned"));
159 assert_eq!(
160 caller_cache
161 .store_mut()
162 .stats(tenferro_runtime::ExtensionCacheSelector::All)
163 .entries,
164 0
165 );
166
167 let mut runtime = ExtensionCacheStore::default();
168 let mut runtime_cache = FftExecutionCache::runtime_owned(&mut runtime);
169 assert!(format!("{runtime_cache:?}").contains("RuntimeOwned"));
170 assert_eq!(
171 runtime_cache
172 .store_mut()
173 .stats(tenferro_runtime::ExtensionCacheSelector::All)
174 .entries,
175 0
176 );
177 }
178}