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* Adding Ling/Ring (a.k.a., Bailing-MoE2) * Add expert group selection (not working, so turned off) * BailingMoE2 conversion * WIP * Bits and pieces --------- Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>
36 lines
1.5 KiB
Plaintext
36 lines
1.5 KiB
Plaintext
#include "scale.cuh"
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#define MAX_GRIDDIM_X 0x7FFFFFFF
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static __global__ void scale_f32(const float * x, float * dst, const float scale, const float bias, const int64_t nelements) {
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int64_t tid = (int64_t)blockIdx.x * (int64_t)blockDim.x + (int64_t)threadIdx.x;
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int64_t stride = (int64_t)blockDim.x * (int64_t)gridDim.x;
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for (int64_t i = tid; i < nelements; i += stride) {
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dst[i] = scale * x[i] + bias;
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}
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}
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static void scale_f32_cuda(const float * x, float * dst, const float scale, const float bias, const int64_t nelements, cudaStream_t stream) {
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const int64_t num_blocks = (nelements + CUDA_SCALE_BLOCK_SIZE - 1) / CUDA_SCALE_BLOCK_SIZE;
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// Whehn will we be scaling tensors with more than 2^39 elements?
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//scale_f32<<<MIN(MAX_GRIDDIM_X, num_blocks), CUDA_SCALE_BLOCK_SIZE, 0, stream>>>(x, dst, scale, bias, nelements);
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scale_f32<<<num_blocks, CUDA_SCALE_BLOCK_SIZE, 0, stream>>>(x, dst, scale, bias, nelements); }
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void ggml_cuda_op_scale(ggml_backend_cuda_context & ctx, ggml_tensor * dst) {
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const ggml_tensor * src0 = dst->src[0];
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const float * src0_d = (const float *)src0->data;
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float * dst_d = (float *)dst->data;
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cudaStream_t stream = ctx.stream();
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GGML_ASSERT(src0->type == GGML_TYPE_F32);
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GGML_ASSERT( dst->type == GGML_TYPE_F32);
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float scale;
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float bias;
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memcpy(&scale, (float *) dst->op_params + 0, sizeof(float));
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memcpy(&bias, (float *) dst->op_params + 1, sizeof(float));
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scale_f32_cuda(src0_d, dst_d, scale, bias, ggml_nelements(src0), stream);
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}
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