extern/whisper.cpp
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ggml : add ggml_gelu_erf() CUDA kernel (llama/13719)

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* ggml : add ggml_gelu_erf() CUDA kernel

* missing semicolon
This commit is contained in:
Xuan-Son Nguyen 2025-05-24 13:06:47 +02:00 committed by Georgi Gerganov
parent f1576b2659
commit 2d6c6862f7
3 changed files with 16 additions and 0 deletions
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4
ggml/src/ggml-cuda/ggml-cuda.cu
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@ -2192,6 +2192,9 @@ static bool ggml_cuda_compute_forward(ggml_backend_cuda_context & ctx, struct gg
case GGML_UNARY_OP_SILU:
ggml_cuda_op_silu(ctx, dst);
break;
case GGML_UNARY_OP_GELU_ERF:
ggml_cuda_op_gelu_erf(ctx, dst);
break;
case GGML_UNARY_OP_GELU_QUICK:
ggml_cuda_op_gelu_quick(ctx, dst);
break;
@ -2977,6 +2980,7 @@ static bool ggml_backend_cuda_device_supports_op(ggml_backend_dev_t dev, const g
case GGML_UNARY_OP_SIGMOID:
case GGML_UNARY_OP_HARDSIGMOID:
case GGML_UNARY_OP_HARDSWISH:
case GGML_UNARY_OP_GELU_ERF:
case GGML_UNARY_OP_GELU_QUICK:
case GGML_UNARY_OP_TANH:
case GGML_UNARY_OP_EXP:

10
ggml/src/ggml-cuda/unary.cu
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@ -23,6 +23,12 @@ static __device__ __forceinline__ float op_gelu(float x) {
return 0.5f*x*(1.0f + tanhf(SQRT_2_OVER_PI*x*(1.0f + GELU_COEF_A*x*x)));
}
static __device__ __forceinline__ float op_gelu_erf(float x) {
const float SQRT_2_INV = 0.70710678118654752440084436210484f;
return 0.5f*x*(1.0f + erff(x*SQRT_2_INV));
}
static __device__ __forceinline__ float op_gelu_quick(float x) {
const float GELU_QUICK_COEF = -1.702f;
@ -134,6 +140,10 @@ void ggml_cuda_op_gelu(ggml_backend_cuda_context & ctx, ggml_tensor * dst) {
ggml_cuda_op_unary<op_gelu>(ctx, dst);
}
void ggml_cuda_op_gelu_erf(ggml_backend_cuda_context & ctx, ggml_tensor * dst) {
ggml_cuda_op_unary<op_gelu_erf>(ctx, dst);
}
void ggml_cuda_op_gelu_quick(ggml_backend_cuda_context & ctx, ggml_tensor * dst) {
ggml_cuda_op_unary<op_gelu_quick>(ctx, dst);
}

2
ggml/src/ggml-cuda/unary.cuh
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@ -30,6 +30,8 @@ void ggml_cuda_op_silu(ggml_backend_cuda_context & ctx, ggml_tensor * dst);
void ggml_cuda_op_silu_back(ggml_backend_cuda_context & ctx, ggml_tensor * dst);
void ggml_cuda_op_gelu_erf(ggml_backend_cuda_context & ctx, ggml_tensor * dst);
void ggml_cuda_op_gelu_quick(ggml_backend_cuda_context & ctx, ggml_tensor * dst);
void ggml_cuda_op_tanh(ggml_backend_cuda_context & ctx, ggml_tensor * dst);