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#pragma once
#include <cstdint>
#include <c10/core/ScalarType.h>
#include <ATen/cuda/CUDAConfig.h>
// NOTE: These templates are intentionally not defined in this header,
// which aviods re-compiling them for each translation unit. If you get
// a link error, you need to add an explicit instantiation for your
// types in cub.cu
namespace at::cuda::cub {
inline int get_num_bits(uint64_t max_key) {
int num_bits = 1;
while (max_key > 1) {
max_key >>= 1;
num_bits++;
}
return num_bits;
}
namespace detail {
// radix_sort_pairs doesn't interact with value_t other than to copy
// the data, so we can save template instantiations by reinterpreting
// it as an opaque type.
template <int N> struct alignas(N) OpaqueType { char data[N]; };
template<typename key_t, int value_size>
void radix_sort_pairs_impl(
const key_t *keys_in, key_t *keys_out,
const OpaqueType<value_size> *values_in, OpaqueType<value_size> *values_out,
int64_t n, bool descending, int64_t begin_bit, int64_t end_bit);
} // namespace detail
template<typename key_t, typename value_t>
void radix_sort_pairs(
const key_t *keys_in, key_t *keys_out,
const value_t *values_in, value_t *values_out,
int64_t n, bool descending=false, int64_t begin_bit=0, int64_t end_bit=sizeof(key_t)*8) {
static_assert(std::is_trivially_copyable<value_t>::value ||
AT_ROCM_ENABLED(), // ROCm incorrectly fails this check for vector types
"radix_sort_pairs value type must be trivially copyable");
// Make value type opaque, so all inputs of a certain size use the same template instantiation
using opaque_t = detail::OpaqueType<sizeof(value_t)>;
static_assert(sizeof(value_t) <= 8 && (sizeof(value_t) & (sizeof(value_t) - 1)) == 0,
"This size of value_t is not instantiated. Please instantiate it in cub.cu"
" and modify this check.");
static_assert(sizeof(value_t) == alignof(value_t), "Expected value_t to be size-aligned");
detail::radix_sort_pairs_impl(
keys_in, keys_out,
reinterpret_cast<const opaque_t*>(values_in),
reinterpret_cast<opaque_t*>(values_out),
n, descending, begin_bit, end_bit);
}
template<typename key_t>
void radix_sort_keys(
const key_t *keys_in, key_t *keys_out,
int64_t n, bool descending=false, int64_t begin_bit=0, int64_t end_bit=sizeof(key_t)*8);
// NOTE: Intermediate sums will be truncated to input_t precision
template <typename input_t, typename output_t>
void inclusive_sum_truncating(const input_t *input, output_t *output, int64_t n);
template <typename scalar_t>
void inclusive_sum(const scalar_t *input, scalar_t *output, int64_t n) {
return inclusive_sum_truncating(input, output, n);
}
// NOTE: Sums are done is common_type<input_t, output_t>
template <typename input_t, typename output_t>
void exclusive_sum_in_common_type(const input_t *input, output_t *output, int64_t n);
template <typename scalar_t>
void exclusive_sum(const scalar_t *input, scalar_t *output, int64_t n) {
return exclusive_sum_in_common_type(input, output, n);
}
void mask_exclusive_sum(const uint8_t *mask, int64_t *output_idx, int64_t n);
inline void mask_exclusive_sum(const bool *mask, int64_t *output_idx, int64_t n) {
return mask_exclusive_sum(
reinterpret_cast<const uint8_t*>(mask), output_idx, n);
}
} // namespace at::cuda::cub
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