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vulkan: implement more backpropagation operators (#11914)

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* vulkan: implement GGML_OP_ROPE_BACK

* vulkan: implement GGML_OP_RMS_NORM_BACK

* vulkan: implement GGML_OP_SILU_BACK

* vulkan: implement GGML_OP_SOFTMAX_BACK
This commit is contained in:
Rémy O
2025-02-25 12:04:45 +01:00
committed by GitHub
parent 0b52745649
commit 61d4f39dfe
6 changed files with 233 additions and 7 deletions
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101
ggml/src/ggml-vulkan/ggml-vulkan.cpp
View File

@@ -241,15 +241,18 @@ struct vk_device_struct {
vk_pipeline pipeline_norm_f32;
vk_pipeline pipeline_group_norm_f32;
vk_pipeline pipeline_rms_norm_f32;
vk_pipeline pipeline_rms_norm_back_f32;
vk_pipeline pipeline_gelu_f32;
vk_pipeline pipeline_gelu_quick_f32;
vk_pipeline pipeline_silu_f32;
vk_pipeline pipeline_silu_back_f32;
vk_pipeline pipeline_relu_f32;
vk_pipeline pipeline_leaky_relu_f32;
vk_pipeline pipeline_tanh_f32;
vk_pipeline pipeline_diag_mask_inf_f32;
vk_pipeline pipeline_soft_max_f32, pipeline_soft_max_f32_f16;
vk_pipeline pipeline_soft_max_f32_wg512, pipeline_soft_max_f32_f16_wg512;
vk_pipeline pipeline_soft_max_back_f32;
vk_pipeline pipeline_rope_norm_f32, pipeline_rope_norm_f16;
vk_pipeline pipeline_rope_neox_f32, pipeline_rope_neox_f16;
vk_pipeline pipeline_rope_multi_f32, pipeline_rope_multi_f16;
@@ -504,6 +507,7 @@ struct vk_op_rope_push_constants {
uint32_t s1;
uint32_t s2;
int32_t sections[4];
uint32_t is_back;
};
struct vk_op_soft_max_push_constants {
@@ -2121,6 +2125,7 @@ static void ggml_vk_load_shaders(vk_device& device) {
ggml_vk_create_pipeline(device, device->pipeline_norm_f32, "norm_f32", norm_f32_len, norm_f32_data, "main", 2, sizeof(vk_op_push_constants), {1, 1, 1}, {}, 1);
ggml_vk_create_pipeline(device, device->pipeline_group_norm_f32, "group_norm_f32", group_norm_f32_len, group_norm_f32_data, "main", 2, sizeof(vk_op_push_constants), {1, 1, 1}, {}, 1);
ggml_vk_create_pipeline(device, device->pipeline_rms_norm_f32, "rms_norm_f32", rms_norm_f32_len, rms_norm_f32_data, "main", 2, sizeof(vk_op_push_constants), {1, 1, 1}, {}, 1);
ggml_vk_create_pipeline(device, device->pipeline_rms_norm_back_f32, "rms_norm_back_f32", rms_norm_back_f32_len, rms_norm_back_f32_data, "main", 3, sizeof(vk_op_push_constants), {1, 1, 1}, {}, 1);
ggml_vk_create_pipeline(device, device->pipeline_cpy_f32_f32, "cpy_f32_f32", cpy_f32_f32_len, cpy_f32_f32_data, "main", 2, sizeof(vk_op_unary_push_constants), {512, 1, 1}, {}, 1);
ggml_vk_create_pipeline(device, device->pipeline_cpy_f32_f16, "cpy_f32_f16", cpy_f32_f16_len, cpy_f32_f16_data, "main", 2, sizeof(vk_op_unary_push_constants), {512, 1, 1}, {}, 1);
@@ -2180,6 +2185,7 @@ static void ggml_vk_load_shaders(vk_device& device) {
ggml_vk_create_pipeline(device, device->pipeline_gelu_f32, "gelu_f32", gelu_f32_len, gelu_f32_data, "main", 2, sizeof(vk_op_push_constants), {512, 1, 1}, {}, 1);
ggml_vk_create_pipeline(device, device->pipeline_gelu_quick_f32, "gelu_quick_f32", gelu_quick_f32_len, gelu_quick_f32_data, "main", 2, sizeof(vk_op_push_constants), {512, 1, 1}, {}, 1);
ggml_vk_create_pipeline(device, device->pipeline_silu_f32, "silu_f32", silu_f32_len, silu_f32_data, "main", 2, sizeof(vk_op_push_constants), {512, 1, 1}, {}, 1);
ggml_vk_create_pipeline(device, device->pipeline_silu_back_f32, "silu_back_f32", silu_back_f32_len, silu_back_f32_data, "main", 3, sizeof(vk_op_push_constants), {512, 1, 1}, {}, 1);
ggml_vk_create_pipeline(device, device->pipeline_relu_f32, "relu_f32", relu_f32_len, relu_f32_data, "main", 2, sizeof(vk_op_push_constants), {512, 1, 1}, {}, 1);
ggml_vk_create_pipeline(device, device->pipeline_leaky_relu_f32, "leaky_relu_f32", leaky_relu_f32_len, leaky_relu_f32_data, "main", 2, sizeof(vk_op_push_constants), {512, 1, 1}, {}, 1);
ggml_vk_create_pipeline(device, device->pipeline_tanh_f32, "tanh_f32", tanh_f32_len, tanh_f32_data, "main", 2, sizeof(vk_op_push_constants), {512, 1, 1}, {}, 1);
@@ -2190,6 +2196,7 @@ static void ggml_vk_load_shaders(vk_device& device) {
ggml_vk_create_pipeline(device, device->pipeline_soft_max_f32_wg512, "soft_max_f32_wg512", soft_max_f32_len, soft_max_f32_data, "main", 3, sizeof(vk_op_soft_max_push_constants), {1, 1, 1}, { 512 }, 1);
ggml_vk_create_pipeline(device, device->pipeline_soft_max_f32_f16, "soft_max_f32_f16", soft_max_f32_f16_len, soft_max_f32_f16_data, "main", 3, sizeof(vk_op_soft_max_push_constants), {1, 1, 1}, { device->subgroup_size }, 1);
ggml_vk_create_pipeline(device, device->pipeline_soft_max_f32_f16_wg512, "soft_max_f32_f16_wg512", soft_max_f32_f16_len, soft_max_f32_f16_data, "main", 3, sizeof(vk_op_soft_max_push_constants), {1, 1, 1}, { 512 }, 1);
ggml_vk_create_pipeline(device, device->pipeline_soft_max_back_f32, "soft_max_back_f32", soft_max_back_f32_len, soft_max_back_f32_data, "main", 3, sizeof(vk_op_push_constants), {1, 1, 1}, { device->subgroup_size }, 1);
ggml_vk_create_pipeline(device, device->pipeline_rope_norm_f32, "rope_norm_f32", rope_norm_f32_len, rope_norm_f32_data, "main", 4, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
ggml_vk_create_pipeline(device, device->pipeline_rope_neox_f32, "rope_neox_f32", rope_neox_f32_len, rope_neox_f32_data, "main", 4, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
@@ -5283,6 +5290,11 @@ static vk_pipeline ggml_vk_op_get_pipeline(ggml_backend_vk_context * ctx, const
case GGML_OP_CONT:
case GGML_OP_DUP:
return ggml_vk_get_cpy_pipeline(ctx, src0, dst, dst->type);
case GGML_OP_SILU_BACK:
if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_F32 && dst->type == GGML_TYPE_F32) {
return ctx->device->pipeline_silu_back_f32;
}
return nullptr;
case GGML_OP_NORM:
if (src0->type == GGML_TYPE_F32 && dst->type == GGML_TYPE_F32) {
return ctx->device->pipeline_norm_f32;
@@ -5298,6 +5310,11 @@ static vk_pipeline ggml_vk_op_get_pipeline(ggml_backend_vk_context * ctx, const
return ctx->device->pipeline_rms_norm_f32;
}
return nullptr;
case GGML_OP_RMS_NORM_BACK:
if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_F32 && dst->type == GGML_TYPE_F32) {
return ctx->device->pipeline_rms_norm_back_f32;
}
return nullptr;
case GGML_OP_UNARY:
switch (ggml_get_unary_op(dst)) {
case GGML_UNARY_OP_SILU:
@@ -5344,7 +5361,13 @@ static vk_pipeline ggml_vk_op_get_pipeline(ggml_backend_vk_context * ctx, const
return src0->ne[0] > 1024 ? ctx->device->pipeline_soft_max_f32_f16_wg512 : ctx->device->pipeline_soft_max_f32_f16;
}
return nullptr;
case GGML_OP_SOFT_MAX_BACK:
if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_F32 && dst->type == GGML_TYPE_F32) {
return ctx->device->pipeline_soft_max_back_f32;
}
return nullptr;
case GGML_OP_ROPE:
case GGML_OP_ROPE_BACK:
{
const int mode = ((const int32_t *) dst->op_params)[2];
const bool is_neox = mode & GGML_ROPE_TYPE_NEOX;
@@ -5672,7 +5695,9 @@ static void ggml_vk_op_f32(ggml_backend_vk_context * ctx, vk_context& subctx, co
switch (op) {
case GGML_OP_NORM:
case GGML_OP_RMS_NORM:
case GGML_OP_RMS_NORM_BACK:
case GGML_OP_SOFT_MAX:
case GGML_OP_SOFT_MAX_BACK:
case GGML_OP_SUM_ROWS:
case GGML_OP_ARGMAX:
{
@@ -5696,6 +5721,7 @@ static void ggml_vk_op_f32(ggml_backend_vk_context * ctx, vk_context& subctx, co
} break;
case GGML_OP_DIAG_MASK_INF:
case GGML_OP_ROPE:
case GGML_OP_ROPE_BACK:
elements = { (uint32_t)ggml_nrows(src0), (uint32_t)ne00, 1 };
break;
case GGML_OP_GET_ROWS:
@@ -5791,7 +5817,7 @@ static void ggml_vk_op_f32(ggml_backend_vk_context * ctx, vk_context& subctx, co
ggml_vk_sync_buffers(subctx);
ggml_vk_dispatch_pipeline(ctx, subctx, pipeline, { vk_subbuffer{ d_X, x_buf_offset, x_sz }, subbuf_y, vk_subbuffer{ d_D, d_buf_offset, d_sz } }, sizeof(PC), &pc, elements);
} else if (op == GGML_OP_ROPE) {
} else if (op == GGML_OP_ROPE || op == GGML_OP_ROPE_BACK) {
// Empty src2 is possible in rope, but the shader needs a buffer
vk_subbuffer subbuf_z;
if (use_src2) {
@@ -6313,6 +6339,10 @@ static void ggml_vk_cpy(ggml_backend_vk_context * ctx, vk_context& subctx, const
}, dryrun);
}
static void ggml_vk_silu_back(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst, bool dryrun = false) {
ggml_vk_op_f32<vk_op_push_constants>(ctx, subctx, src0, src1, nullptr, dst, GGML_OP_SILU_BACK, { (uint32_t)ggml_nelements(src0), 0, 0.0f, 0.0f }, dryrun);
}
static void ggml_vk_norm(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst, bool dryrun = false) {
float * op_params = (float *)dst->op_params;
@@ -6335,6 +6365,11 @@ static void ggml_vk_rms_norm(ggml_backend_vk_context * ctx, vk_context& subctx,
ggml_vk_op_f32<vk_op_push_constants>(ctx, subctx, src0, nullptr, nullptr, dst, GGML_OP_RMS_NORM, { (uint32_t)src0->ne[0], (uint32_t)src0->ne[1], op_params[0], 0.0f }, dryrun);
}
static void ggml_vk_rms_norm_back(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst, bool dryrun = false) {
float * op_params = (float *)dst->op_params;
ggml_vk_op_f32<vk_op_push_constants>(ctx, subctx, src0, src1, nullptr, dst, GGML_OP_RMS_NORM_BACK, { (uint32_t)src0->ne[0], (uint32_t)src0->ne[1], op_params[0], 0.0f }, dryrun);
}
static void ggml_vk_unary(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst, bool dryrun = false) {
ggml_vk_op_f32<vk_op_push_constants>(ctx, subctx, src0, nullptr, nullptr, dst, GGML_OP_UNARY, { (uint32_t)ggml_nelements(src0), 0, 0.0f, 0.0f }, dryrun);
}
@@ -6370,7 +6405,12 @@ static void ggml_vk_soft_max(ggml_backend_vk_context * ctx, vk_context& subctx,
}, dryrun);
}
static void ggml_vk_rope(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, const ggml_tensor * src1, const ggml_tensor * src2, ggml_tensor * dst, bool dryrun = false) {
static void ggml_vk_soft_max_back(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst, bool dryrun = false) {
float * op_params = (float *)dst->op_params;
ggml_vk_op_f32<vk_op_push_constants>(ctx, subctx, src0, src1, nullptr, dst, GGML_OP_SOFT_MAX_BACK, { (uint32_t)src0->ne[0], (uint32_t)src0->ne[1], op_params[0], op_params[1] }, dryrun);
}
static void ggml_vk_rope(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, const ggml_tensor * src1, const ggml_tensor * src2, ggml_tensor * dst, bool backprop, bool dryrun = false) {
const int n_dims = ((int32_t *) dst->op_params)[1];
const int mode = ((int32_t *) dst->op_params)[2];
// const int n_ctx = ((int32_t *) dst->op_params)[3];
@@ -6398,7 +6438,7 @@ static void ggml_vk_rope(ggml_backend_vk_context * ctx, vk_context& subctx, cons
(uint32_t)src0->ne[0], (uint32_t)n_dims, freq_scale, (uint32_t)src0->ne[1],
freq_base, ext_factor, attn_factor, {corr_dims[0], corr_dims[1]}, theta_scale,
src2 != nullptr, (uint32_t)src0->ne[2], s1, s2,
sections[0], sections[1], sections[2], sections[3],
sections[0], sections[1], sections[2], sections[3], backprop
}, dryrun);
}
@@ -7319,12 +7359,16 @@ static bool ggml_vk_build_graph(ggml_backend_vk_context * ctx, ggml_tensor * nod
case GGML_OP_CPY:
case GGML_OP_CONT:
case GGML_OP_DUP:
case GGML_OP_SILU_BACK:
case GGML_OP_NORM:
case GGML_OP_GROUP_NORM:
case GGML_OP_RMS_NORM:
case GGML_OP_RMS_NORM_BACK:
case GGML_OP_DIAG_MASK_INF:
case GGML_OP_SOFT_MAX:
case GGML_OP_SOFT_MAX_BACK:
case GGML_OP_ROPE:
case GGML_OP_ROPE_BACK:
case GGML_OP_MUL_MAT:
case GGML_OP_MUL_MAT_ID:
case GGML_OP_ARGSORT:
@@ -7377,13 +7421,17 @@ static bool ggml_vk_build_graph(ggml_backend_vk_context * ctx, ggml_tensor * nod
case GGML_OP_CPY:
case GGML_OP_CONT:
case GGML_OP_DUP:
case GGML_OP_SILU_BACK:
case GGML_OP_NORM:
case GGML_OP_GROUP_NORM:
case GGML_OP_RMS_NORM:
case GGML_OP_RMS_NORM_BACK:
case GGML_OP_UNARY:
case GGML_OP_DIAG_MASK_INF:
case GGML_OP_SOFT_MAX:
case GGML_OP_SOFT_MAX_BACK:
case GGML_OP_ROPE:
case GGML_OP_ROPE_BACK:
case GGML_OP_ARGSORT:
case GGML_OP_SUM:
case GGML_OP_SUM_ROWS:
@@ -7475,6 +7523,10 @@ static bool ggml_vk_build_graph(ggml_backend_vk_context * ctx, ggml_tensor * nod
case GGML_OP_DUP:
ggml_vk_cpy(ctx, compute_ctx, src0, node, dryrun);
break;
case GGML_OP_SILU_BACK:
ggml_vk_silu_back(ctx, compute_ctx, src0, src1, node, dryrun);
break;
case GGML_OP_NORM:
ggml_vk_norm(ctx, compute_ctx, src0, node, dryrun);
@@ -7487,6 +7539,10 @@ static bool ggml_vk_build_graph(ggml_backend_vk_context * ctx, ggml_tensor * nod
case GGML_OP_RMS_NORM:
ggml_vk_rms_norm(ctx, compute_ctx, src0, node, dryrun);
break;
case GGML_OP_RMS_NORM_BACK:
ggml_vk_rms_norm_back(ctx, compute_ctx, src0, src1, node, dryrun);
break;
case GGML_OP_UNARY:
switch (ggml_get_unary_op(node)) {
@@ -7508,9 +7564,17 @@ static bool ggml_vk_build_graph(ggml_backend_vk_context * ctx, ggml_tensor * nod
case GGML_OP_SOFT_MAX:
ggml_vk_soft_max(ctx, compute_ctx, src0, src1, node, dryrun);
break;
case GGML_OP_SOFT_MAX_BACK:
ggml_vk_soft_max_back(ctx, compute_ctx, src0, src1, node, dryrun);
break;
case GGML_OP_ROPE:
ggml_vk_rope(ctx, compute_ctx, src0, src1, src2, node, dryrun);
ggml_vk_rope(ctx, compute_ctx, src0, src1, src2, node, false, dryrun);
break;
case GGML_OP_ROPE_BACK:
ggml_vk_rope(ctx, compute_ctx, src0, src1, src2, node, true, dryrun);
break;
case GGML_OP_ARGSORT:
@@ -7636,12 +7700,16 @@ static bool ggml_vk_compute_forward(ggml_backend_vk_context * ctx, ggml_tensor *
case GGML_OP_CPY:
case GGML_OP_CONT:
case GGML_OP_DUP:
case GGML_OP_SILU_BACK:
case GGML_OP_NORM:
case GGML_OP_GROUP_NORM:
case GGML_OP_RMS_NORM:
case GGML_OP_RMS_NORM_BACK:
case GGML_OP_DIAG_MASK_INF:
case GGML_OP_SOFT_MAX:
case GGML_OP_SOFT_MAX_BACK:
case GGML_OP_ROPE:
case GGML_OP_ROPE_BACK:
case GGML_OP_RESHAPE:
case GGML_OP_VIEW:
case GGML_OP_PERMUTE:
@@ -8560,6 +8628,7 @@ static bool ggml_backend_vk_device_supports_op(ggml_backend_dev_t dev, const ggm
case GGML_OP_REPEAT_BACK:
return op->type == GGML_TYPE_F32 && op->src[0]->type == GGML_TYPE_F32;
case GGML_OP_ROPE:
case GGML_OP_ROPE_BACK:
case GGML_OP_NONE:
case GGML_OP_RESHAPE:
case GGML_OP_VIEW:
@@ -8576,6 +8645,8 @@ static bool ggml_backend_vk_device_supports_op(ggml_backend_dev_t dev, const ggm
case GGML_OP_MUL:
case GGML_OP_DIV:
case GGML_OP_CONCAT:
case GGML_OP_SILU_BACK:
case GGML_OP_RMS_NORM_BACK:
case GGML_OP_UPSCALE:
case GGML_OP_SCALE:
case GGML_OP_SQR:
@@ -8585,6 +8656,7 @@ static bool ggml_backend_vk_device_supports_op(ggml_backend_dev_t dev, const ggm
case GGML_OP_PAD:
case GGML_OP_DIAG_MASK_INF:
case GGML_OP_SOFT_MAX:
case GGML_OP_SOFT_MAX_BACK:
case GGML_OP_ARGSORT:
case GGML_OP_SUM:
case GGML_OP_SUM_ROWS:
@@ -8976,15 +9048,22 @@ static void ggml_vk_check_results_0(ggml_tensor * tensor) {
tensor_clone = ggml_group_norm(ggml_ctx, src_clone[0], *(int *)tensor->op_params, ((float *)tensor->op_params)[1]);
} else if (tensor->op == GGML_OP_RMS_NORM) {
tensor_clone = ggml_rms_norm(ggml_ctx, src_clone[0], *(float *)tensor->op_params);
} else if (tensor->op == GGML_OP_RMS_NORM_BACK) {
const float eps = ((float *) tensor->op_params)[0];
tensor_clone = ggml_rms_norm_back(ggml_ctx, src_clone[0], src_clone[1], eps);
} else if (tensor->op == GGML_OP_SILU_BACK) {
tensor_clone = ggml_silu_back(ggml_ctx, src_clone[0], src_clone[1]);
} else if (tensor->op == GGML_OP_SOFT_MAX) {
if (src1 != nullptr) {
tensor_clone = ggml_soft_max_ext(ggml_ctx, src_clone[0], src_clone[1], ((float *)tensor->op_params)[0], ((float *)tensor->op_params)[1]);
} else {
tensor_clone = ggml_soft_max(ggml_ctx, src_clone[0]);
}
} else if (tensor->op == GGML_OP_SOFT_MAX_BACK) {
tensor_clone = ggml_soft_max_ext_back(ggml_ctx, src_clone[0], src_clone[1], ((float *)tensor->op_params)[0], ((float *)tensor->op_params)[1]);
} else if (tensor->op == GGML_OP_DIAG_MASK_INF) {
tensor_clone = ggml_diag_mask_inf(ggml_ctx, src_clone[0], *(int *)tensor->op_params);
} else if (tensor->op == GGML_OP_ROPE) {
} else if (tensor->op == GGML_OP_ROPE || tensor->op == GGML_OP_ROPE_BACK) {
const int n_dims = ((int32_t *) tensor->op_params)[1];
const int mode = ((int32_t *) tensor->op_params)[2];
//const int n_ctx_ggml = ((int32_t *) tensor->op_params)[3];
@@ -8997,9 +9076,17 @@ static void ggml_vk_check_results_0(ggml_tensor * tensor) {
const float beta_slow = ((float *) tensor->op_params)[10];
if (mode & GGML_ROPE_TYPE_MROPE) {
int32_t *sections = ((int32_t *) tensor->op_params) + 11;
tensor_clone = ggml_rope_multi(ggml_ctx, src_clone[0], src_clone[1], src_clone[2], n_dims, sections, mode, n_ctx_orig_ggml, freq_base, freq_scale, ext_factor, attn_factor, beta_fast, beta_slow);
if (tensor->op == GGML_OP_ROPE) {
tensor_clone = ggml_rope_multi(ggml_ctx, src_clone[0], src_clone[1], src_clone[2], n_dims, sections, mode, n_ctx_orig_ggml, freq_base, freq_scale, ext_factor, attn_factor, beta_fast, beta_slow);
} else {
tensor_clone = ggml_rope_multi_back(ggml_ctx, src_clone[0], src_clone[1], src_clone[2], n_dims, sections, mode, n_ctx_orig_ggml, freq_base, freq_scale, ext_factor, attn_factor, beta_fast, beta_slow);
}
} else {
tensor_clone = ggml_rope_ext(ggml_ctx, src_clone[0], src_clone[1], src_clone[2], n_dims, mode, n_ctx_orig_ggml, freq_base, freq_scale, ext_factor, attn_factor, beta_fast, beta_slow);
if (tensor->op == GGML_OP_ROPE) {
tensor_clone = ggml_rope_ext(ggml_ctx, src_clone[0], src_clone[1], src_clone[2], n_dims, mode, n_ctx_orig_ggml, freq_base, freq_scale, ext_factor, attn_factor, beta_fast, beta_slow);
} else {
tensor_clone = ggml_rope_ext_back(ggml_ctx, src_clone[0], src_clone[1], src_clone[2], n_dims, mode, n_ctx_orig_ggml, freq_base, freq_scale, ext_factor, attn_factor, beta_fast, beta_slow);
}
}
} else if (tensor->op == GGML_OP_UNARY) {
switch (ggml_get_unary_op(tensor)) {

55
ggml/src/ggml-vulkan/vulkan-shaders/rms_norm_back.comp Normal file
View File

@@ -0,0 +1,55 @@
#version 450
#include "generic_head.comp"
#include "types.comp"
#extension GL_EXT_control_flow_attributes : enable
#define BLOCK_SIZE 512
layout(local_size_x = BLOCK_SIZE, local_size_y = 1, local_size_z = 1) in;
layout (binding = 0) readonly buffer G {A_TYPE data_a[];};
layout (binding = 1) readonly buffer X {B_TYPE data_b[];};
layout (binding = 2) writeonly buffer D {D_TYPE data_d[];};
shared FLOAT_TYPE sum_xx[BLOCK_SIZE];
shared FLOAT_TYPE sum_xg[BLOCK_SIZE];
void main() {
const uint row = gl_WorkGroupID.z * 262144 + gl_WorkGroupID.y * 512 + gl_WorkGroupID.x;
const uint tid = gl_LocalInvocationID.x;
// Compute derivative of x[i]/norm(x) = g[i]/norm(x) - x[i] dot(x,g)/KX / norm(x)^1.5
// partial sums for thread in warp
sum_xx[tid] = FLOAT_TYPE(0.0f);
sum_xg[tid] = FLOAT_TYPE(0.0f);
[[unroll]] for (uint col = tid; col < p.KX; col += BLOCK_SIZE) {
const FLOAT_TYPE gi = FLOAT_TYPE(data_a[row*p.KX + col]);
const FLOAT_TYPE xi = FLOAT_TYPE(data_b[row*p.KX + col]);
sum_xx[tid] += xi * xi;
sum_xg[tid] += xi * gi;
}
// sum up partial sums and write back result
barrier();
[[unroll]] for (int s = BLOCK_SIZE / 2; s > 0; s >>= 1) {
if (tid < s) {
sum_xx[tid] += sum_xx[tid + s];
sum_xg[tid] += sum_xg[tid + s];
}
barrier();
}
const FLOAT_TYPE eps = FLOAT_TYPE(p.param1);
const FLOAT_TYPE mean = sum_xx[0] / FLOAT_TYPE(p.KX);
const FLOAT_TYPE scale_g = inversesqrt(mean + eps);
const FLOAT_TYPE scale_x = -scale_g * sum_xg[0] / (sum_xx[0] + FLOAT_TYPE(p.KX) * eps);
[[unroll]] for (uint col = tid; col < p.KX; col += BLOCK_SIZE) {
data_d[row*p.KX + col] = D_TYPE(
scale_g * FLOAT_TYPE(data_a[row*p.KX + col]) +
scale_x * FLOAT_TYPE(data_b[row*p.KX + col]));
}
}

5
ggml/src/ggml-vulkan/vulkan-shaders/rope_head.comp
View File

@@ -29,6 +29,7 @@ layout (push_constant) uniform parameter {
uint s1;
uint s2;
int sections[4];
uint is_back;
} p;
float rope_yarn_ramp(const float low, const float high, const uint i0) {
@@ -48,6 +49,10 @@ void rope_yarn(const float theta_extrap, const uint i0, out float cos_theta, out
// Get n-d magnitude scaling corrected for interpolation
mscale *= 1.0f + 0.1f * log(1.0f / p.freq_scale);
}
// Backprogagation uses inverted rotation
if (p.is_back != 0) {
theta = -theta;
}
cos_theta = cos(theta) * mscale;
sin_theta = sin(theta) * mscale;
}

26
ggml/src/ggml-vulkan/vulkan-shaders/silu_back.comp Normal file
View File

@@ -0,0 +1,26 @@
#version 450
#include "generic_head.comp"
#include "types.comp"
#extension GL_EXT_control_flow_attributes : enable
layout(local_size_x = 512, local_size_y = 1, local_size_z = 1) in;
layout (binding = 0) readonly buffer G {A_TYPE data_g[];};
layout (binding = 1) readonly buffer X {B_TYPE data_x[];};
layout (binding = 2) writeonly buffer D {D_TYPE data_d[];};
void main() {
const uint i = gl_GlobalInvocationID.z * 262144 + gl_GlobalInvocationID.y * 512 + gl_GlobalInvocationID.x;
if (i >= p.KX) {
return;
}
// Compute derivative of SiLU(x): 1/(1+exp(-x)) - x*exp(-x)/(1+exp(-x))^2
const float xi = float(data_x[i]);
const float s = 1.0f / (1.0f + exp(-xi));
data_d[i] = D_TYPE(data_g[i] * (s + xi * s * (1 - s)));
}

50
ggml/src/ggml-vulkan/vulkan-shaders/soft_max_back.comp Normal file
View File

@@ -0,0 +1,50 @@
#version 450
#extension GL_EXT_control_flow_attributes : enable
#include "generic_head.comp"
#include "types.comp"
layout(constant_id = 0) const uint BLOCK_SIZE = 32;
layout(local_size_x_id = 0, local_size_y = 1, local_size_z = 1) in;
// In this shader Y = softmax(X) and X is not provided as input.
layout (binding = 0) readonly buffer G {A_TYPE data_g[];};
layout (binding = 1) readonly buffer Y {B_TYPE data_y[];};
layout (binding = 2) buffer D {D_TYPE data_d[];};
shared FLOAT_TYPE sum_yg[BLOCK_SIZE];
void main() {
const uint row = gl_WorkGroupID.z * 262144 + gl_WorkGroupID.y * 512 + gl_WorkGroupID.x;
const uint tid = gl_LocalInvocationID.x;
FLOAT_TYPE scale = p.param1;
// partial sums for thread in warp
sum_yg[tid] = FLOAT_TYPE(0.0f);
[[unroll]] for (uint col = tid; col < p.KX; col += BLOCK_SIZE) {
const FLOAT_TYPE gi = FLOAT_TYPE(data_g[row*p.KX + col]);
const FLOAT_TYPE yi = FLOAT_TYPE(data_y[row*p.KX + col]);
sum_yg[tid] += yi * gi;
}
// sum up partial sums and write back result
barrier();
[[unroll]] for (uint s = BLOCK_SIZE / 2; s > 0; s >>= 1) {
if (tid < s) {
sum_yg[tid] += sum_yg[tid + s];
}
barrier();
}
const FLOAT_TYPE dot_yg = sum_yg[0];
[[unroll]] for (uint col = tid; col < p.KX; col += BLOCK_SIZE) {
data_d[row*p.KX + col] = D_TYPE(scale
* (FLOAT_TYPE(data_g[row*p.KX + col]) - dot_yg)
* FLOAT_TYPE(data_y[row*p.KX + col]));
}
}

3
ggml/src/ggml-vulkan/vulkan-shaders/vulkan-shaders-gen.cpp
View File

@@ -427,6 +427,7 @@ void process_shaders() {
string_to_spv("norm_f32", "norm.comp", merge_maps(base_dict, {{"A_TYPE", "float"}, {"D_TYPE", "float"}}));
string_to_spv("group_norm_f32", "group_norm.comp", merge_maps(base_dict, {{"A_TYPE", "float"}, {"D_TYPE", "float"}}));
string_to_spv("rms_norm_f32", "rms_norm.comp", merge_maps(base_dict, {{"A_TYPE", "float"}, {"D_TYPE", "float"}}));
string_to_spv("rms_norm_back_f32", "rms_norm_back.comp", merge_maps(base_dict, {{"A_TYPE", "float"}, {"B_TYPE", "float"}, {"D_TYPE", "float"}}));
string_to_spv("cpy_f32_f32", "copy.comp", {{"A_TYPE", "float"}, {"D_TYPE", "float"}});
string_to_spv("cpy_f32_f16", "copy.comp", {{"A_TYPE", "float"}, {"D_TYPE", "float16_t"}});
@@ -477,6 +478,7 @@ void process_shaders() {
string_to_spv("gelu_f32", "gelu.comp", {{"A_TYPE", "float"}, {"D_TYPE", "float"}});
string_to_spv("gelu_quick_f32", "gelu_quick.comp", {{"A_TYPE", "float"}, {"D_TYPE", "float"}});
string_to_spv("silu_f32", "silu.comp", {{"A_TYPE", "float"}, {"D_TYPE", "float"}});
string_to_spv("silu_back_f32", "silu_back.comp", {{"A_TYPE", "float"}, {"B_TYPE", "float"}, {"D_TYPE", "float"}});
string_to_spv("relu_f32", "relu.comp", {{"A_TYPE", "float"}, {"D_TYPE", "float"}});
string_to_spv("leaky_relu_f32", "leaky_relu.comp", {{"A_TYPE", "float"}, {"D_TYPE", "float"}});
string_to_spv("tanh_f32", "tanh.comp", {{"A_TYPE", "float"}, {"D_TYPE", "float"}});
@@ -485,6 +487,7 @@ void process_shaders() {
string_to_spv("soft_max_f32", "soft_max.comp", merge_maps(base_dict, {{"A_TYPE", "float"}, {"B_TYPE", "float"}, {"D_TYPE", "float"}}));
string_to_spv("soft_max_f32_f16", "soft_max.comp", merge_maps(base_dict, {{"A_TYPE", "float"}, {"B_TYPE", "float16_t"}, {"D_TYPE", "float"}}));
string_to_spv("soft_max_back_f32", "soft_max_back.comp", merge_maps(base_dict, {{"A_TYPE", "float"}, {"B_TYPE", "float"}, {"D_TYPE", "float"}}));
string_to_spv("rope_norm_f32", "rope_norm.comp", {{"A_TYPE", "float"}, {"D_TYPE", "float"}});
string_to_spv("rope_norm_f16", "rope_norm.comp", {{"A_TYPE", "float16_t"}, {"D_TYPE", "float16_t"}});