#include #include #include "ATen/ATen.h" #define MIN_VALUE (-1e38) typedef at::BFloat16 bf16; __global__ void kernel_forward(const int B, const int T, const int C, const float *__restrict__ const _w, const bf16 *__restrict__ const _u, const bf16 *__restrict__ const _k, const bf16 *__restrict__ const _v, bf16 *__restrict__ const _y) { const int idx = blockIdx.x * blockDim.x + threadIdx.x; const int _b = idx / C; const int _c = idx % C; const int _offset = _b * T * C + _c; float u = float(_u[_c]); float w = _w[_c]; const bf16 *__restrict__ const k = _k + _offset; const bf16 *__restrict__ const v = _v + _offset; bf16 *__restrict__ const y = _y + _offset; // aa and bb are running sums divided by exp(pp) (to avoid overflow) float aa = 0, bb = 0, pp = MIN_VALUE; for (int i = 0; i < T; i++) { const int ii = i * C; const float kk = float(k[ii]); const float vv = float(v[ii]); float ww = u + kk; float p = max(pp, ww); float e1 = exp(pp - p); float e2 = exp(ww - p); y[ii] = bf16((e1 * aa + e2 * vv) / (e1 * bb + e2)); ww = w + pp; p = max(ww, kk); e1 = exp(ww - p); e2 = exp(kk - p); aa = e1 * aa + e2 * vv; bb = e1 * bb + e2; pp = p; } } __global__ void kernel_backward(const int B, const int T, const int C, const float *__restrict__ const _w, const bf16 *__restrict__ const _u, const bf16 *__restrict__ const _k, const bf16 *__restrict__ const _v, const bf16 *__restrict__ const _y, const bf16 *__restrict__ const _gy, bf16 *__restrict__ const _gw, bf16 *__restrict__ const _gu, bf16 *__restrict__ const _gk, bf16 *__restrict__ const _gv) { const int idx = blockIdx.x * blockDim.x + threadIdx.x; const int _b = idx / C; const int _c = idx % C; const int _offset = _b * T * C + _c; float u = float(_u[_c]); float w = _w[_c]; const bf16 *__restrict__ const k = _k + _offset; const bf16 *__restrict__ const v = _v + _offset; const bf16 *__restrict__ const y = _y + _offset; const bf16 *__restrict__ const gy = _gy + _offset; bf16 *__restrict__ const gk = _gk + _offset; bf16 *__restrict__ const gv = _gv + _offset; float q[Tmax], r[Tmax]; float gw = 0, gu = 0, aa = 0, bb = 0, ga = 0, gb = 0, pp = MIN_VALUE; for (int i = 0; i < T; i++) { const int ii = i * C; const float kk = float(k[ii]); const float vv = float(v[ii]); const float yy = float(y[ii]); float ww = u + kk; float p = max(pp, ww); float e1 = exp(pp - p); float e2 = exp(ww - p); const float qq = float(gy[ii]) / (e1 * bb + e2); gw += (ga - gb * yy) * e1 * qq; gu += (vv - yy) * e2 * qq; q[i] = qq; r[i] = ww - p; ww = w + pp; p = max(ww, kk); e1 = exp(ww - p); e2 = exp(kk - p); ga = e1 * (aa + ga); gb = e1 * (bb + gb); aa = e1 * aa + e2 * vv; bb = e1 * bb + e2; pp = p; } const int _offsetBC = _b * C + _c; _gw[_offsetBC] = bf16(gw * _w[_c]); // multiply by w because of w -> -exp(w) in python forward() _gu[_offsetBC] = bf16(gu); aa = 0, bb = 0, pp = MIN_VALUE; for (int i = T - 1; i >= 0; i--) { const int ii = i * C; const float kk = float(k[ii]); const float vv = float(v[ii]); const float yy = float(y[ii]); const float qq = q[i]; const float rr = r[i]; float e1 = qq * exp(rr); float e2 = exp(kk + pp); gk[ii] = bf16(e1 * (vv - yy) + e2 * (aa * vv + bb)); gv[ii] = bf16(e1 + e2 * aa); const float ww = w + pp; const float www = rr - u - kk; const float p = max(ww, www); e1 = exp(ww - p); e2 = qq * exp(www - p); aa = e1 * aa + e2; bb = e1 * bb - e2 * yy; pp = p; } } void cuda_forward(int B, int T, int C, float *w, bf16 *u, bf16 *k, bf16 *v, bf16 *y) { dim3 threadsPerBlock( min(C, 32) ); // requires --maxrregcount 60 for optimal performance assert(B * C % threadsPerBlock.x == 0); dim3 numBlocks(B * C / threadsPerBlock.x); kernel_forward<<>>(B, T, C, w, u, k, v, y); } void cuda_backward(int B, int T, int C, float *w, bf16 *u, bf16 *k, bf16 *v, bf16 *y, bf16 *gy, bf16 *gw, bf16 *gu, bf16 *gk, bf16 *gv) { dim3 threadsPerBlock( min(C, 32) ); // requires --maxrregcount 60 for optimal performance assert(B * C % threadsPerBlock.x == 0); dim3 numBlocks(B * C / threadsPerBlock.x); kernel_backward<<>>(B, T, C, w, u, k, v, y, gy, gw, gu, gk, gv); }