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/******************************************************************************
* Copyright (c) 2024, Tri Dao.
******************************************************************************/
#pragma once
#include "philox.cuh"
#include "utils.h"
namespace flash {
struct Dropout {
const unsigned long long seed, offset;
const uint8_t p_dropout_in_uint8_t;
__forceinline__ __device__ Dropout(const unsigned long long seed, const unsigned long long offset,
const uint8_t p_dropout_in_uint8_t,
const int bid, const int hid, const int tid, const int nheads)
: seed(seed)
, offset(offset + (bid * nheads + hid) * 32 + tid % 32)
, p_dropout_in_uint8_t(p_dropout_in_uint8_t) {
}
template <bool encode_dropout_in_sign_bit=false, typename Engine, typename Layout>
__forceinline__ __device__ void apply_dropout(Tensor<Engine, Layout> &tensor_,
int block_row_start, int block_col_start, int block_row_stride) {
// convert shape from (4, MMA_M, MMA_N) to (8, MMA_M, MMA_N / 2)
Tensor tensor = make_tensor(tensor_.data(), flash::convert_layout_acc_dropout(tensor_.layout()));
using T = typename Engine::value_type;
auto encode_dropout = [](bool keep, T val) {
return keep ? val : (encode_dropout_in_sign_bit ? -val : T(0));
};
static_assert(decltype(size<2>(tensor))::value % 2 == 0);
const uint16_t p_dropout_8bit_in_uint16_t = uint16_t(p_dropout_in_uint8_t);
const uint32_t p_dropout_8bit_in_uint32_t = (uint32_t(p_dropout_8bit_in_uint16_t) << 16) | uint32_t(p_dropout_8bit_in_uint16_t);
// if (cute::thread0()) { printf("threshold2 = 0x%x\n", p_dropout_8bit_in_uint32_t); }
#pragma unroll
for (int m = 0; m < size<1>(tensor); ++m, block_row_start += block_row_stride) {
uint2 rowcol = make_uint2(block_row_start, block_col_start);
#pragma unroll
for (int n = 0; n < size<2>(tensor) / 2; ++n, ++rowcol.y) {
// if (cute::thread(32, 0)) { printf("m = %d, n = %d, row = %d, col = %d\n", m, n, int(rowcol.x), int(rowcol.y));}
uint4 random_uint4 = flash::philox(seed, reinterpret_cast<unsigned long long&>(rowcol), offset);
// if (cute::thread0()) { printf("philox = %u, %d, %d, %d\n", random_uint4.x, random_uint4.y, random_uint4.z, random_uint4.w);}
uint8_t (&rnd_8)[16] = reinterpret_cast<uint8_t (&)[16]>(random_uint4);
// Special implementation for 16-bit types: we duplicate the threshold to the
// low and high 16 bits of a 32-bit value, then use the f16x2 comparison instruction
// to get a mask. The low 16 bits of the mask will be either 0xffff or 0x0000,
// and the high 16 bits will be either 0xffff or 0x0000, depending on whether
// the random value is less than the threshold.
// We then do a bit-wise AND between the mask and the original value (in 32-bit).
// We're exploiting the fact that floating point comparison is equivalent to integer
// comparison, since we're comparing unsigned integers whose top 8-bits are zero.
if (!encode_dropout_in_sign_bit
&& (std::is_same<T, cutlass::half_t>::value || std::is_same<T, cutlass::bfloat16_t>::value)) {
uint16_t rnd_16[16];
#pragma unroll
for (int i = 0; i < 16; i++) { rnd_16[i] = uint16_t(rnd_8[i]); }
uint32_t (&rnd_32)[8] = reinterpret_cast<uint32_t (&)[8]>(rnd_16);
#pragma unroll
for (int j = 0; j < 2; j++) {
Tensor tensor_uint32 = recast<uint32_t>(tensor(_, m, n * 2 + j));
// if (cute::thread0()) { printf("random = 0x%x, 0x%x, 0x%x, 0x%x\n", rnd_32[j * 4 + 0], rnd_32[j * 4 + 1], rnd_32[j * 4 + 2], rnd_32[j * 4 + 3]); }
// if (cute::thread0()) { printf("tensor_uint32 = 0x%x, 0x%x, 0x%x, 0x%x\n", tensor_uint32(0), tensor_uint32(1), tensor_uint32(2), tensor_uint32(3)); }
#pragma unroll
for (int i = 0; i < 4; i++) {
uint32_t mask;
asm volatile("set.le.u32.f16x2 %0, %1, %2;\n" : "=r"(mask) : "r"(rnd_32[j * 4 + i]), "r"(p_dropout_8bit_in_uint32_t));
tensor_uint32(i) &= mask;
}
// if (cute::thread0()) { printf("tensor_uint32 = 0x%x, 0x%x, 0x%x, 0x%x\n", tensor_uint32(0), tensor_uint32(1), tensor_uint32(2), tensor_uint32(3)); }
}
} else {
#pragma unroll
for (int j = 0; j < 2; j++) {
#pragma unroll
for (int i = 0; i < 8; i++) {
tensor(i, m, n * 2 + j) = encode_dropout(rnd_8[j * 8 + i] <= p_dropout_in_uint8_t, tensor(i, m, n * 2 + j));
}
Tensor tensor_uint32 = recast<uint32_t>(tensor(_, m, n * 2 + j));
// if (cute::thread0()) { printf("tensor_uint32 = 0x%x, 0x%x, 0x%x, 0x%x\n", tensor_uint32(0), tensor_uint32(1), tensor_uint32(2), tensor_uint32(3)); }
}
}
// // if ((threadIdx.x == 0) && (blockIdx.x == 0) && (blockIdx.y == 0)) {
// // printf("n = %d, ph Philox: %u, %u, %u, %u\n", n, rnd_8.x, rnd_8.y, rnd_8.z, rnd_8.w);
// // }
}
}
}
};
} // namespace flash
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