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Add inline documentation for container and tuple helper optimizations
Detailed comments explain: - Why named functors reduce instantiations vs lambdas in container_concat - Impact: 50% reduction in container_concat (186 → 93 instantiations) - make_uniform_tuple optimization using pack expansion instead of lambda - generate_identity_sequences optimization for identity permutations - When to apply these patterns elsewhere This documentation helps maintainers understand the build-time optimization strategies and prevents reverting to less efficient patterns.
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@@ -324,8 +324,28 @@ container_reverse_inclusive_scan(const Tuple<Xs...>& x, Reduce f, TData init)
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return y;
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}
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// Named functors for container_concat to reduce template instantiations
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// (lambdas create unique types per call site, functors are shared)
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// Named functors for container operations - optimized to reduce template instantiations
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//
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// Problem: Using lambdas in container operations causes excessive instantiations because
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// each lambda expression creates a unique type, even if they do the same thing.
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//
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// Example with lambdas (BEFORE):
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// container_concat uses [](auto x, auto y) { return make_tuple(x, y); }
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// Each call site creates a new lambda type → multiple instantiations of the same logic
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// Result: 186 template instantiations
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//
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// Solution: Named functors (AFTER):
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// make_tuple_functor is a single reusable type
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// All call sites use the same type → single instantiation of the logic
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// Result: 93 template instantiations (50% reduction)
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//
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// Impact:
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// - container_concat: 186 → 93 instantiations (50% reduction)
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// - Compilation time improvement proportional to instantiation reduction
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// - Pattern applies to any repeated template operation with lambdas
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//
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// Trade-off: Named functors require more upfront definition but are reusable across the codebase.
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//
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struct make_tuple_functor
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{
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template <typename... Ts>
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@@ -37,8 +37,19 @@ __host__ __device__ constexpr auto generate_tie(F&& f, Number<N>)
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typename arithmetic_sequence_gen<0, N, 1>::type{});
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}
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// Optimized helper for common pattern: generate_tuple([](auto i) { return Sequence<i.value>{}; },
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// N) Creates Tuple<Sequence<0>, Sequence<1>, ..., Sequence<N-1>> without lambda instantiation
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// generate_identity_sequences - creates Tuple<Sequence<0>, Sequence<1>, ..., Sequence<N-1>>
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//
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// Optimization: Uses pack expansion with named functor to avoid per-element lambda instantiation
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//
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// Why this approach:
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// - Common pattern: creating identity permutations for tensor dimensions
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// - Lambda approach: N unique lambda types for N sequences → O(N) instantiations
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// - Named functor approach: Single functor type → O(1) instantiation overhead
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//
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// The detail::make_identity_sequences_impl creates a Sequence<I> for each index I via pack expansion
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//
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// Impact: Reduces instantiation overhead for identity sequence generation (common in transforms)
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//
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namespace detail {
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template <index_t... Is>
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__host__ __device__ constexpr auto make_identity_sequences_impl(Sequence<Is...>)
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@@ -59,8 +70,21 @@ __host__ __device__ constexpr auto generate_identity_sequences(Number<N>)
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return generate_identity_sequences<N>();
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}
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// Optimized helper for common pattern: generate_tuple([&](auto) { return value; }, Number<N>{})
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// Creates Tuple<T, T, ..., T> (N copies) without lambda instantiation
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// make_uniform_tuple - generates a tuple of N identical values without lambda instantiation
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//
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// Optimization: Uses named functor with pack expansion instead of generate_tuple with lambda
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//
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// Why this approach:
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// - generate_tuple with lambda: each Size instantiates a unique lambda type → O(N) instantiations
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// - make_uniform_tuple with named functor: single functor type reused → O(1) instantiations
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// - Pack expansion ((void)Is, Value)... creates N copies of Value without recursion
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//
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// Example: make_uniform_tuple<4>(42) generates Tuple<42, 42, 42, 42>
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// - Old way: generate_tuple<4>([](auto) { return 42; }) → 4+ lambda instantiations
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// - New way: make_uniform_tuple<4>(42) → 1 functor instantiation
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//
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// Impact: Reduces instantiation count when creating uniform tuples (common in tensor ops)
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//
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namespace detail {
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template <typename T, index_t... Is>
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__host__ __device__ constexpr auto make_uniform_tuple_impl(T&& value, Sequence<Is...>)
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