#pragma once

#if defined(__AVX512F__) && defined(__AVX512BF16__) && defined(__AMX_BF16__)
#define CPU_CAPABILITY_AVX512
#endif

#include <ATen/cpu/vec/functional.h>
#include <ATen/cpu/vec/vec.h>

namespace {

using namespace at::vec;

template <typename scalar_t, typename std::enable_if_t<is_reduced_floating_point_v<scalar_t>, int> = 0>
inline Vectorized<scalar_t> convert_from_float_ext(const Vectorized<float>& a, const Vectorized<float>& b) {
  return at::vec::convert_from_float<scalar_t>(a, b);
}

#if defined(CPU_CAPABILITY_AVX512)

// `at::vec::convert_from_float<>` from PyTorch doesn't have avx512-bf16 intrinsics
// use native instruction for bfloat16->float32 conversion
template <>
inline Vectorized<at::BFloat16>
convert_from_float_ext<at::BFloat16>(const Vectorized<float>& a, const Vectorized<float>& b) {
  return (__m512i)(_mm512_cvtne2ps_pbh(__m512(b), __m512(a)));
}

#define CVT_BF16_TO_FP32(a) _mm512_castsi512_ps(_mm512_slli_epi32(_mm512_cvtepu16_epi32(a), 16))

#define CVT_FP16_TO_FP32(a) _mm512_cvtps_ph(a, (_MM_FROUND_TO_NEAREST_INT | _MM_FROUND_NO_EXC))

#endif

// vector to scalar reduction
#if defined(CPU_CAPABILITY_AVX512) && 0
inline float vec_reduce_sum(const Vectorized<float>& a) {
  return _mm512_reduce_add_ps(__m512(a));
}

inline float vec_reduce_max(const Vectorized<float>& a) {
  return _mm512_reduce_max_ps(__m512(a));
}
#else
inline float vec_reduce_sum(const Vectorized<float>& a) {
  return vec_reduce_all([](Vectorized<float>& x, Vectorized<float>& y) { return x + y; }, a);
}

inline float vec_reduce_max(const Vectorized<float>& a) {
  return vec_reduce_all([](Vectorized<float>& x, Vectorized<float>& y) { return maximum(x, y); }, a);
}
#endif

// https://github.com/InternLM/lmdeploy/blob/086481ed84b59bee3b8e4274e5fc69620040c048/lmdeploy/pytorch/kernels/cuda/w8a8_triton_kernels.py#L282
template <typename scalar_t>
inline void
quantize_row_int8(uint8_t* __restrict__ Aq, float& As, const scalar_t* __restrict__ A, int64_t K, float eps = 1e-7) {
  float amax = 0.f;  // absolute max
  for (int64_t k = 0; k < K; ++k) {
    const float val = static_cast<float>(A[k]);
    amax = std::max(amax, std::abs(val));
  }

  amax = std::max(amax, eps);
  const float scale = amax / 127;
  const float inv_scale = 127 / amax;

  for (int64_t k = 0; k < K; ++k) {
    const float val = static_cast<float>(A[k]) * inv_scale;
    Aq[k] = (uint8_t)(std::round(val)) + 128;
  }
  As = scale;
}

#if defined(CPU_CAPABILITY_AVX512)
template <>
inline void quantize_row_int8<at::BFloat16>(
    uint8_t* __restrict__ Aq, float& As, const at::BFloat16* __restrict__ A, int64_t K, float eps) {
  const __m512 signBit = _mm512_set1_ps(-0.0f);
  const __m512i off = _mm512_set1_epi32(128);

  // K is 32x, no remainder
  float amax = 0.f;
  __m512 vamax0 = _mm512_set1_ps(0.f);
  __m512 vamax1 = _mm512_set1_ps(0.f);
  for (int64_t k = 0; k < K; k += 32) {
    __m512i va = _mm512_loadu_si512((void*)(A + k));
    __m512 va0 = CVT_BF16_TO_FP32(_mm512_extracti32x8_epi32(va, 0));
    __m512 va1 = CVT_BF16_TO_FP32(_mm512_extracti32x8_epi32(va, 1));
    vamax0 = _mm512_max_ps(vamax0, _mm512_andnot_ps(signBit, va0));
    vamax1 = _mm512_max_ps(vamax1, _mm512_andnot_ps(signBit, va1));
  }
  amax = _mm512_reduce_max_ps(_mm512_max_ps(vamax0, vamax1));
  amax = std::max(amax, eps);
  const float scale = amax / 127;
  const float inv_scale = 127 / amax;
  const __m512 vd = _mm512_set1_ps(inv_scale);

  for (int64_t k = 0; k < K; k += 32) {
    __m512i va = _mm512_loadu_si512((void*)(A + k));
    __m512 va0 = CVT_BF16_TO_FP32(_mm512_extracti32x8_epi32(va, 0));
    __m512 va1 = CVT_BF16_TO_FP32(_mm512_extracti32x8_epi32(va, 1));
    va0 = _mm512_mul_ps(va0, vd);
    va1 = _mm512_mul_ps(va1, vd);
    va0 = _mm512_roundscale_ps(va0, (_MM_FROUND_TO_NEAREST_INT | _MM_FROUND_NO_EXC));
    va1 = _mm512_roundscale_ps(va1, (_MM_FROUND_TO_NEAREST_INT | _MM_FROUND_NO_EXC));
    __m128i i0 = _mm512_cvtepi32_epi8(_mm512_add_epi32(_mm512_cvtps_epi32(va0), off));
    __m128i i1 = _mm512_cvtepi32_epi8(_mm512_add_epi32(_mm512_cvtps_epi32(va1), off));
    _mm256_storeu_si256(reinterpret_cast<__m256i*>(Aq + k), _mm256_set_m128i(i1, i0));
  }
  As = scale;
}
#endif

}  // anonymous namespace