add GELU_ERF (#14455)
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@ -431,6 +431,7 @@ struct vk_device_struct {
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// [src/dst 0=fp32,1=fp16]
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vk_pipeline pipeline_gelu[2];
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vk_pipeline pipeline_gelu_erf[2];
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vk_pipeline pipeline_gelu_quick[2];
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vk_pipeline pipeline_silu[2];
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vk_pipeline pipeline_relu[2];
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@ -2761,6 +2762,7 @@ static void ggml_vk_load_shaders(vk_device& device) {
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ggml_vk_create_pipeline(device, device->pipeline_ ## name [1], #name "_f16", name ## _f16_len, name ## _f16_data, "main", 2, sizeof(vk_op_push_constants), {512, 1, 1}, {}, 1);
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CREATE_UNARY(gelu)
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CREATE_UNARY(gelu_erf)
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CREATE_UNARY(gelu_quick)
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CREATE_UNARY(silu)
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CREATE_UNARY(relu)
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@ -6481,6 +6483,8 @@ static vk_pipeline ggml_vk_op_get_pipeline(ggml_backend_vk_context * ctx, const
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return ctx->device->pipeline_silu[dst->type == GGML_TYPE_F16];
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case GGML_UNARY_OP_GELU:
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return ctx->device->pipeline_gelu[dst->type == GGML_TYPE_F16];
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case GGML_UNARY_OP_GELU_ERF:
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return ctx->device->pipeline_gelu_erf[dst->type == GGML_TYPE_F16];
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case GGML_UNARY_OP_GELU_QUICK:
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return ctx->device->pipeline_gelu_quick[dst->type == GGML_TYPE_F16];
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case GGML_UNARY_OP_RELU:
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@ -8827,6 +8831,7 @@ static bool ggml_vk_build_graph(ggml_backend_vk_context * ctx, ggml_cgraph * cgr
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switch (ggml_get_unary_op(node)) {
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case GGML_UNARY_OP_SILU:
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case GGML_UNARY_OP_GELU:
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case GGML_UNARY_OP_GELU_ERF:
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case GGML_UNARY_OP_GELU_QUICK:
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case GGML_UNARY_OP_RELU:
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case GGML_UNARY_OP_TANH:
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@ -9072,6 +9077,7 @@ static bool ggml_vk_build_graph(ggml_backend_vk_context * ctx, ggml_cgraph * cgr
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switch (ggml_get_unary_op(node)) {
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case GGML_UNARY_OP_SILU:
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case GGML_UNARY_OP_GELU:
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case GGML_UNARY_OP_GELU_ERF:
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case GGML_UNARY_OP_GELU_QUICK:
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case GGML_UNARY_OP_RELU:
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case GGML_UNARY_OP_TANH:
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@ -9289,6 +9295,7 @@ static bool ggml_vk_compute_forward(ggml_backend_vk_context * ctx, ggml_tensor *
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switch (ggml_get_unary_op(tensor)) {
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case GGML_UNARY_OP_SILU:
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case GGML_UNARY_OP_GELU:
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case GGML_UNARY_OP_GELU_ERF:
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case GGML_UNARY_OP_GELU_QUICK:
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case GGML_UNARY_OP_RELU:
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case GGML_UNARY_OP_TANH:
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@ -10095,6 +10102,7 @@ static bool ggml_backend_vk_device_supports_op(ggml_backend_dev_t dev, const ggm
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case GGML_OP_UNARY:
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switch (ggml_get_unary_op(op)) {
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case GGML_UNARY_OP_GELU:
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case GGML_UNARY_OP_GELU_ERF:
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case GGML_UNARY_OP_GELU_QUICK:
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case GGML_UNARY_OP_SILU:
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case GGML_UNARY_OP_RELU:
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@ -10835,6 +10843,9 @@ static void ggml_vk_check_results_0(ggml_tensor * tensor) {
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case GGML_UNARY_OP_GELU:
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tensor_clone = ggml_gelu(ggml_ctx, src_clone[0]);
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break;
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case GGML_UNARY_OP_GELU_ERF:
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tensor_clone = ggml_gelu_erf(ggml_ctx, src_clone[0]);
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break;
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case GGML_UNARY_OP_GELU_QUICK:
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tensor_clone = ggml_gelu_quick(ggml_ctx, src_clone[0]);
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break;
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@ -0,0 +1,39 @@
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#version 450
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#include "generic_head.comp"
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#include "types.comp"
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#extension GL_EXT_control_flow_attributes : enable
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layout(local_size_x = 512, local_size_y = 1, local_size_z = 1) in;
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layout (binding = 0) readonly buffer X {A_TYPE data_a[];};
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layout (binding = 1) writeonly buffer D {D_TYPE data_d[];};
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void main() {
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// based on Abramowitz and Stegun formula 7.1.26 or similar Hastings' approximation
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// ref: https://www.johndcook.com/blog/python_erf/
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const float p_erf = 0.3275911f;
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const float a1_erf = 0.254829592f;
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const float a2_erf = -0.284496736f;
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const float a3_erf = 1.421413741f;
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const float a4_erf = -1.453152027f;
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const float a5_erf = 1.061405429f;
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const float SQRT_2_INV = 0.70710678118654752440084436210484f;
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const uint i = gl_GlobalInvocationID.z * 262144 + gl_GlobalInvocationID.y * 512 + gl_GlobalInvocationID.x;
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if (i >= p.KX) {
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return;
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}
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const float a = float(data_a[i]);
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const float a_div_sqr2 = a * SQRT_2_INV;
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const float sign_x = sign(a_div_sqr2);
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const float x = abs(a_div_sqr2);
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const float t = 1.0f / (1.0f + p_erf * x);
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const float y = 1.0f - (((((a5_erf * t + a4_erf) * t) + a3_erf) * t + a2_erf) * t + a1_erf) * t * exp(-x * x);
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const float erf_approx = sign_x * y;
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data_d[i] = D_TYPE(0.5f * a * (1.0f + erf_approx));
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}
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@ -574,6 +574,8 @@ void process_shaders() {
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string_to_spv("gelu_f16", "gelu.comp", {{"A_TYPE", "float16_t"}, {"D_TYPE", "float16_t"}});
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string_to_spv("gelu_f32", "gelu.comp", {{"A_TYPE", "float"}, {"D_TYPE", "float"}});
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string_to_spv("gelu_erf_f16", "gelu_erf.comp", {{"A_TYPE", "float16_t"}, {"D_TYPE", "float16_t"}});
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string_to_spv("gelu_erf_f32", "gelu_erf.comp", {{"A_TYPE", "float"}, {"D_TYPE", "float"}});
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string_to_spv("gelu_quick_f16", "gelu_quick.comp", {{"A_TYPE", "float16_t"}, {"D_TYPE", "float16_t"}});
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string_to_spv("gelu_quick_f32", "gelu_quick.comp", {{"A_TYPE", "float"}, {"D_TYPE", "float"}});
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string_to_spv("silu_f16", "silu.comp", {{"A_TYPE", "float16_t"}, {"D_TYPE", "float16_t"}});
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