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SymIntify randint and randperm #98968

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88a51c3
SymIntify randint and randperm
ezyang Apr 12, 2023
9cf93a7
Update on "SymIntify randint and randperm"
ezyang Apr 12, 2023
458071d
Update on "SymIntify randint and randperm"
ezyang Apr 12, 2023
d68c4a9
Update on "SymIntify randint and randperm"
ezyang Apr 12, 2023
9b0fe57
Update on "SymIntify randint and randperm"
ezyang Apr 12, 2023
e2e6522
Update on "SymIntify randint and randperm"
ezyang Apr 14, 2023
ddd27b1
Update on "SymIntify randint and randperm"
ezyang Apr 14, 2023
872534b
Update on "SymIntify randint and randperm"
ezyang Apr 15, 2023
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10 changes: 5 additions & 5 deletions aten/src/ATen/functorch/BatchRulesRandomness.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -279,8 +279,8 @@ struct RandomBatchRuleHelper<F, Func, typelist<T1, T...>> {
};

template <typename F, F Func, typename... T>
Tensor rand_int_wrapper(SymIntArrayRef shape, int64_t high, T... extra_args) {
return Func(high, shape, std::forward<T>(extra_args)...);
Tensor rand_int_wrapper(SymIntArrayRef shape, c10::SymInt high, T... extra_args) {
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nit: probably ok w/o c10 namespace

return Func(high, std::move(shape), std::forward<T>(extra_args)...);
}

template <typename A, A a, typename C>
Expand All @@ -298,10 +298,10 @@ struct RandIntBatchRuleHelper;

template <typename F, F Func, typename T1, typename T2, typename... T>
struct RandIntBatchRuleHelper<F, Func, typelist<T1, T2, T...>> {
static Tensor apply(int64_t high, SymIntArrayRef shape, T... extra_args) {
static Tensor apply(c10::SymInt high, SymIntArrayRef shape, T... extra_args) {
return random_batching_rule<decltype(&rand_int_wrapper<F, Func, T...>),
&rand_int_wrapper<F, Func, T...>,
int64_t, T...>(shape, high, std::forward<T>(extra_args)...);
c10::SymInt, T...>(shape, std::move(high), std::forward<T>(extra_args)...);
}
};

Expand All @@ -318,7 +318,7 @@ struct RandTwoLeadingScalarsBatchRuleHelper<F, Func, typelist<T0, T1, T2, T...>>
static Tensor apply(T0 scalar0, T1 scalar1, SymIntArrayRef shape, T... extra_args) {
return random_batching_rule<decltype(&rand_int_low_wrapper<F, Func, T0, T1, T...>),
&rand_int_low_wrapper<F, Func, T0, T1, T...>,
int64_t, int64_t, T...>(shape, scalar0, scalar1, std::forward<T>(extra_args)...);
T0, T1, T...>(shape, scalar0, scalar1, std::forward<T>(extra_args)...);
}
};

Expand Down
28 changes: 14 additions & 14 deletions aten/src/ATen/native/native_functions.yaml
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Original file line number Diff line number Diff line change
Expand Up @@ -4361,55 +4361,55 @@
CompositeExplicitAutograd: rand_like
autogen: rand_like.out

- func: randint(int high, SymInt[] size, *, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor
- func: randint(SymInt high, SymInt[] size, *, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor
tags: nondeterministic_seeded
dispatch:
CompositeExplicitAutograd: randint

- func: randint.generator(int high, SymInt[] size, *, Generator? generator, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor
- func: randint.generator(SymInt high, SymInt[] size, *, Generator? generator, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor
tags: nondeterministic_seeded
dispatch:
CompositeExplicitAutograd: randint

- func: randint.low(int low, int high, SymInt[] size, *, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor
- func: randint.low(SymInt low, SymInt high, SymInt[] size, *, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor
tags: nondeterministic_seeded
dispatch:
CompositeExplicitAutograd: randint

- func: randint.low_generator(int low, int high, SymInt[] size, *, Generator? generator, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor
- func: randint.low_generator(SymInt low, SymInt high, SymInt[] size, *, Generator? generator, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor
tags: nondeterministic_seeded
dispatch:
CompositeExplicitAutograd: randint

- func: randint.out(int high, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!)
- func: randint.out(SymInt high, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!)
tags: nondeterministic_seeded
dispatch:
CompositeExplicitAutograd: randint_out

- func: randint.generator_out(int high, SymInt[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!)
- func: randint.generator_out(SymInt high, SymInt[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!)
tags: nondeterministic_seeded
dispatch:
CompositeExplicitAutograd: randint_out

- func: randint.low_out(int low, int high, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!)
- func: randint.low_out(SymInt low, SymInt high, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!)
tags: nondeterministic_seeded
dispatch:
CompositeExplicitAutograd: randint_out

- func: randint.low_generator_out(int low, int high, SymInt[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!)
- func: randint.low_generator_out(SymInt low, SymInt high, SymInt[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!)
tags: nondeterministic_seeded
dispatch:
CompositeExplicitAutograd: randint_out

- func: randint_like(Tensor self, int high, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor
- func: randint_like(Tensor self, SymInt high, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor
tags: nondeterministic_seeded
dispatch:
# NB: Although this composite mutates on the inside, it is
# non-differentiable so NonFunctional doesn't apply
CompositeExplicitAutograd: randint_like
autogen: randint_like.out

- func: randint_like.low_dtype(Tensor self, int low, int high, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor
- func: randint_like.low_dtype(Tensor self, SymInt low, SymInt high, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor
tags: nondeterministic_seeded
dispatch:
# NB: Although this composite mutates on the inside, it is
Expand Down Expand Up @@ -4457,22 +4457,22 @@
CompositeExplicitAutograd, CompositeImplicitAutogradNestedTensor: randn_like
autogen: randn_like.out

- func: randperm(int n, *, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor
- func: randperm(SymInt n, *, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor
tags: nondeterministic_seeded
dispatch:
CompositeExplicitAutograd: randperm

- func: randperm.generator(int n, *, Generator? generator, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor
- func: randperm.generator(SymInt n, *, Generator? generator, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor
tags: nondeterministic_seeded
dispatch:
CompositeExplicitAutograd: randperm

- func: randperm.out(int n, *, Tensor(a!) out) -> Tensor(a!)
- func: randperm.out(SymInt n, *, Tensor(a!) out) -> Tensor(a!)
tags: nondeterministic_seeded
dispatch:
CompositeExplicitAutograd: randperm_out

- func: randperm.generator_out(int n, *, Generator? generator, Tensor(a!) out) -> Tensor(a!)
- func: randperm.generator_out(SymInt n, *, Generator? generator, Tensor(a!) out) -> Tensor(a!)
tags: nondeterministic_seeded
dispatch:
CPU: randperm_out_cpu
Expand Down