mirror of
https://github.com/ggerganov/whisper.cpp.git
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2948c740a2
* sync : update scripts * sync : ggml * talk-llama : sync llama.cpp * make : WHISPER_CUBLAS -> WHISPER_CUDA * ci : try to fix sycl build * talk-llama : fix make build
64 lines
2.2 KiB
Plaintext
64 lines
2.2 KiB
Plaintext
#include "alibi.cuh"
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static __global__ void alibi_f32(const float * x, float * dst, const int ncols, const int k_rows,
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const int n_heads_log2_floor, const float m0, const float m1) {
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const int col = blockDim.x*blockIdx.x + threadIdx.x;
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if (col >= ncols) {
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return;
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}
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const int row = blockDim.y*blockIdx.y + threadIdx.y;
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const int i = row*ncols + col;
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const int k = row/k_rows;
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float m_k;
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if (k < n_heads_log2_floor) {
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m_k = powf(m0, k + 1);
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} else {
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m_k = powf(m1, 2 * (k - n_heads_log2_floor) + 1);
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}
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dst[i] = col * m_k + x[i];
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}
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static void alibi_f32_cuda(const float * x, float * dst, const int ncols, const int nrows,
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const int k_rows, const int n_heads_log2_floor, const float m0,
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const float m1, cudaStream_t stream) {
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const dim3 block_dims(CUDA_ALIBI_BLOCK_SIZE, 1, 1);
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const int num_blocks_x = (ncols + CUDA_ALIBI_BLOCK_SIZE - 1) / (CUDA_ALIBI_BLOCK_SIZE);
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const dim3 block_nums(num_blocks_x, nrows, 1);
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alibi_f32<<<block_nums, block_dims, 0, stream>>>(x, dst, ncols, k_rows, n_heads_log2_floor, m0, m1);
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}
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void ggml_cuda_op_alibi(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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const int64_t ne00 = src0->ne[0];
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const int64_t ne01 = src0->ne[1];
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const int64_t ne02 = src0->ne[2];
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const int64_t nrows = ggml_nrows(src0);
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//const int n_past = ((int32_t *) dst->op_params)[0];
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const int n_head = ((int32_t *) dst->op_params)[1];
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float max_bias;
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memcpy(&max_bias, (int32_t *) dst->op_params + 2, sizeof(float));
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//GGML_ASSERT(ne01 + n_past == ne00);
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GGML_ASSERT(n_head == ne02);
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const int n_heads_log2_floor = 1 << (int) floor(log2(n_head));
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const float m0 = powf(2.0f, -(max_bias) / n_heads_log2_floor);
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const float m1 = powf(2.0f, -(max_bias / 2.0f) / n_heads_log2_floor);
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alibi_f32_cuda(src0_d, dst_d, ne00, nrows, ne01, n_heads_log2_floor, m0, m1, stream);
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}
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