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#include "opt-step-adamw.cuh"
#include <cstdint>
static __global__ void opt_step_adamw_f32(
float * __restrict__ x, const float * __restrict__ g, float * __restrict__ g_m, float * __restrict__ g_v, const int64_t k,
const float alpha, const float beta1, const float beta2, const float eps, const float wd,
const float beta1h, const float beta2h) {
const int64_t i = (int64_t) blockIdx.x*blockDim.x + threadIdx.x;
if (i >= k) {
return;
}
const float gi = g[i];
const float gmi = g_m[i]*beta1 + gi*(1.0f - beta1);
const float gvi = g_v[i]*beta2 + gi*gi*(1.0f - beta2);
g_m[i] = gmi;
g_v[i] = gvi;
const float mh = gmi*beta1h;
const float vh = sqrtf(gvi*beta2h) + eps;
x[i] = x[i]*(1.0f - alpha*wd) - mh/vh;
}
static void opt_step_adamw_f32_cuda(
float * x, const float * g, float * g_m, float * g_v, const int64_t k,
const float alpha, const float beta1, const float beta2, const float eps, const float wd,
const float beta1h, const float beta2h, cudaStream_t stream) {
const dim3 block_dims(CUDA_OPT_STEP_ADAMW_BLOCK_SIZE, 1, 1);
const dim3 block_nums((k + CUDA_OPT_STEP_ADAMW_BLOCK_SIZE - 1) / CUDA_OPT_STEP_ADAMW_BLOCK_SIZE, 1, 1);
opt_step_adamw_f32<<<block_nums, block_dims, 0, stream>>>(x, g, g_m, g_v, k, alpha, beta1, beta2, eps, wd, beta1h, beta2h);
}
void ggml_cuda_opt_step_adamw(ggml_backend_cuda_context & ctx, ggml_tensor * dst) {
const ggml_tensor * src0 = dst->src[0];
const ggml_tensor * src0_grad = dst->src[1];
const ggml_tensor * src0_grad_m = dst->src[2];
const ggml_tensor * src0_grad_v = dst->src[3];
GGML_ASSERT(src0->type == GGML_TYPE_F32);
GGML_ASSERT(src0_grad->type == GGML_TYPE_F32);
GGML_ASSERT(src0_grad_m->type == GGML_TYPE_F32);
GGML_ASSERT(src0_grad_v->type == GGML_TYPE_F32);
GGML_ASSERT(ggml_is_contiguous(src0));
GGML_ASSERT(ggml_is_contiguous(src0_grad));
GGML_ASSERT(ggml_is_contiguous(src0_grad_m));
GGML_ASSERT(ggml_is_contiguous(src0_grad_v));
GGML_ASSERT(ggml_are_same_shape(src0, src0_grad));
GGML_ASSERT(ggml_are_same_shape(src0, src0_grad_m));
GGML_ASSERT(ggml_are_same_shape(src0, src0_grad_v));
float * src0_d = (float *) src0->data;
const float * src0_grad_d = (const float *) src0_grad->data;
float * src0_grad_m_d = (float *) src0_grad_m->data;
float * src0_grad_v_d = (float *) src0_grad_v->data;
cudaStream_t stream = ctx.stream();
const int64_t ne = ggml_nelements(src0);
int64_t iter; memcpy(&iter, &dst->op_params[0], sizeof(int64_t));
float alpha; memcpy(&alpha, &dst->op_params[2], sizeof(float));
float beta1; memcpy(&beta1, &dst->op_params[3], sizeof(float));
float beta2; memcpy(&beta2, &dst->op_params[4], sizeof(float));
float eps; memcpy(&eps, &dst->op_params[5], sizeof(float));
float wd; memcpy(&wd, &dst->op_params[6], sizeof(float));
const float beta1h = alpha/(1.0f - powf(beta1, iter));
const float beta2h = 1.0f/(1.0f - powf(beta2, iter));
opt_step_adamw_f32_cuda(src0_d, src0_grad_d, src0_grad_m_d, src0_grad_v_d, ne, alpha, beta1, beta2, eps, wd, beta1h, beta2h, stream);
iter++;
memcpy(&dst->op_params[0], &iter, sizeof(int64_t));
}
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