#pragma once
#include "ggml-vulkan-push-constants.h"
extern ggml_backend_buffer_type_i ggml_backend_vk_buffer_type_interface;
extern bool vk_memory_logger_enabled;
extern bool vk_perf_logger_enabled;
extern bool vk_perf_logger_concurrent;
extern bool vk_enable_sync_logger;
extern uint32_t vk_perf_logger_frequency;
extern std::string vk_pipeline_stats_filter;
extern void * const vk_ptr_base;
extern vk_instance_t vk_instance;
extern ggml_backend_buffer_i ggml_backend_vk_buffer_interface;
vk_device ggml_vk_get_device(size_t idx);
DispatchLoaderDynamic & ggml_vk_default_dispatcher();
void ggml_vk_instance_init();
void ggml_vk_init(ggml_backend_vk_context * ctx, size_t idx);
int ggml_vk_get_device_count();
void ggml_vk_get_device_description(int device, char * description, size_t description_size);
bool ggml_vk_instance_layer_settings_available();
bool ggml_vk_instance_portability_enumeration_ext_available(const std::vector<vk::ExtensionProperties>& instance_extensions);
bool ggml_vk_instance_debug_utils_ext_available(const std::vector<vk::ExtensionProperties> & instance_extensions);
bool ggml_vk_device_is_supported(const vk::PhysicalDevice & vkdev);
bool ggml_vk_khr_cooperative_matrix_support(const vk::PhysicalDeviceProperties& props, const vk::PhysicalDeviceDriverProperties& driver_props, vk_device_architecture arch);
uint32_t ggml_vk_intel_shader_core_count(const vk::PhysicalDevice& vkdev);
bool ggml_vk_intel_windows_driver_in_range(uint32_t driver_version, uint32_t lower_major, uint32_t lower_minor, uint32_t upper_major, uint32_t upper_minor);
void ggml_vk_destroy_pipeline(vk::Device& device, vk_pipeline& pipeline);
vk_fa_tuning_params get_fa_tuning_params(const vk_device& device, uint32_t hsk, uint32_t hsv, uint32_t n_rows, uint32_t n_kv, ggml_type k_type, ggml_type v_type, bool f32acc);
vk_fa_pipeline_state get_fa_pipeline_state(const vk_device& device, const vk_fa_tuning_params& params, uint32_t hsk, uint32_t hsv, bool aligned, bool f32acc, bool use_mask, bool use_mask_opt, bool use_logit_softcap, bool use_sparse, ggml_type k_type, ggml_type v_type);
uint32_t get_subgroup_size(const std::string &pipeline_name, const vk_device_architecture &arch);
void ggml_vk_load_shaders(vk_device& device, vk_pipeline requested = nullptr);
bool ggml_vk_flash_attn_scalar_shmem_support(const vk_device& device, const vk_fa_tuning_params& params, uint32_t hsk, uint32_t hsv, bool f32acc, ggml_type k_type, ggml_type v_type);
bool ggml_vk_flash_attn_coopmat_shmem_support(const vk_device& device, const vk_fa_tuning_params& params, uint32_t hsk, uint32_t hsv, bool f32acc, ggml_type k_type = GGML_TYPE_F16, ggml_type v_type = GGML_TYPE_F16);
vk_buffer ggml_vk_create_buffer_check(vk_device& device, size_t size, vk::MemoryPropertyFlags req_flags, vk::MemoryPropertyFlags fallback_flags = vk::MemoryPropertyFlags(0));
vk_buffer ggml_vk_create_buffer_device(vk_device& device, size_t size);
void ggml_vk_destroy_buffer(vk_buffer& buf);
void * ggml_vk_host_malloc(vk_device& device, size_t size);
void ggml_vk_host_free(vk_device& device, void* ptr);
void ggml_vk_host_get(const vk_device& device, const void * ptr, vk_buffer& buf, size_t& buf_offset);
void ggml_vk_ensure_sync_staging_buffer(vk_device& device, size_t size);
void ggml_vk_ensure_sync_staging_buffer(ggml_backend_vk_context * ctx, size_t size);
bool ggml_vk_buffer_write_2d_async(vk_context subctx, vk_buffer& dst, size_t offset, const void * src, size_t spitch, size_t dpitch, size_t width, size_t height, bool sync_staging = false);
bool ggml_vk_buffer_write_async(vk_context subctx, vk_buffer& dst, size_t offset, const void * src, size_t size, bool sync_staging = false);
void ggml_vk_buffer_write_2d(vk_buffer& dst, size_t offset, const void * src, size_t spitch, size_t dpitch, size_t width, size_t height);
void ggml_vk_buffer_write(vk_buffer& dst, size_t offset, const void * src, size_t size);
bool ggml_vk_buffer_read_2d_async(vk_context subctx, vk_buffer& src, size_t offset, void * dst, size_t spitch, size_t dpitch, size_t width, size_t height, bool sync_staging = false);
void ggml_vk_buffer_read_2d(vk_buffer& src, size_t offset, void * dst, size_t spitch, size_t dpitch, size_t width, size_t height);
void ggml_vk_buffer_read(vk_buffer& src, size_t offset, void * dst, size_t size);
void ggml_vk_buffer_copy_async(vk_context& ctx, vk_buffer& dst, size_t dst_offset, vk_buffer& src, size_t src_offset, size_t size);
void ggml_vk_buffer_copy(vk_buffer& dst, size_t dst_offset, vk_buffer& src, size_t src_offset, size_t size);
void ggml_vk_buffer_memset_async(vk_context& ctx, vk_buffer& dst, size_t offset, uint32_t c, size_t size);
void ggml_vk_buffer_memset(vk_buffer& dst, size_t offset, uint32_t c, size_t size);
vk_buffer ggml_vk_buffer_from_host_ptr(vk_device & device, void * ptr, size_t size);
uint64_t vk_tensor_offset(const ggml_tensor * tensor);
uint32_t get_misalign_bytes(const ggml_backend_vk_context * ctx, const ggml_tensor * t);
void ggml_vk_wait_for_fence(ggml_backend_vk_context * ctx);
void ggml_pipeline_request_descriptor_sets(ggml_backend_vk_context *ctx, vk_pipeline& pipeline, uint32_t n);
void ggml_pipeline_allocate_descriptor_sets(ggml_backend_vk_context * ctx);
void ggml_vk_submit(vk_context& ctx, vk::Fence fence);
uint32_t ggml_vk_find_queue_family_index(std::vector<vk::QueueFamilyProperties>& queue_family_props, const vk::QueueFlags& required, const vk::QueueFlags& avoid, int32_t compute_index, uint32_t min_num_queues);
std::unique_ptr<vk_queue> ggml_vk_create_queue(vk_device& device, uint32_t queue_family_index, uint32_t queue_index, vk::PipelineStageFlags&& stage_flags, bool transfer_only);
std::unique_ptr<vk_queue> ggml_vk_create_aliased_queue(vk_device& device, const std::unique_ptr<vk_queue>& source);
vk_context ggml_vk_create_context(ggml_backend_vk_context * ctx, vk_command_pool& p);
vk_context ggml_vk_create_temporary_context(vk_command_pool& p);
void ggml_vk_command_pool_cleanup(vk_device& device, vk_command_pool& p);
void ggml_vk_queue_command_pools_cleanup(vk_device& device);
vk_subbuffer ggml_vk_subbuffer(const ggml_backend_vk_context* ctx, const vk_buffer& buf, size_t offset = 0);
void ggml_vk_sync_buffers(ggml_backend_vk_context* ctx, vk_context& subctx);
void ggml_vk_set_event(vk_context& ctx, vk::Event& event);
void ggml_vk_wait_events(vk_context& ctx, std::vector<vk::Event>&& events);
vk_subbuffer ggml_vk_tensor_subbuffer(const ggml_backend_vk_context * ctx, const ggml_tensor * tensor, bool allow_misalign = false);
void ggml_vk_cmd_label_begin(vk::CommandBuffer buf, const char * name);
void ggml_vk_ctx_end(vk_context& ctx);
void ggml_vk_ctx_begin(vk_device& device, vk_context& subctx);
vk_context ggml_vk_get_compute_ctx(ggml_backend_vk_context * ctx);
vk_context ggml_vk_get_transfer_ctx(ggml_backend_vk_context * ctx);
bool ggml_vk_submit_transfer_ctx(ggml_backend_vk_context * ctx);
size_t ggml_vk_align_size(size_t width, size_t align);
void deferred_memcpy(void * dst, const void * src, size_t size, std::vector<vk_staging_memcpy>* memcpys = nullptr);
void deferred_memset(void * dst, uint32_t val, size_t size, std::vector<vk_staging_memset>* memsets = nullptr);
vk_pipeline ggml_vk_get_to_fp16(ggml_backend_vk_context * ctx, ggml_type type);
void ggml_vk_matmul(ggml_backend_vk_context * ctx, vk_context& subctx, vk_pipeline& pipeline, vk_subbuffer&& a, vk_subbuffer&& b, vk_subbuffer&& d, vk_subbuffer&& split_k_buffer, uint32_t m, uint32_t n, uint32_t k, uint32_t stride_a, uint32_t stride_b, uint32_t stride_d, uint32_t batch_stride_a, uint32_t batch_stride_b, uint32_t batch_stride_d, uint32_t split_k, uint32_t batch, uint32_t ne02, uint32_t ne12, uint32_t broadcast2, uint32_t broadcast3, uint32_t padded_n);
bool ggml_vk_dim01_contiguous(const ggml_tensor * tensor);
vk_pipeline ggml_vk_get_cpy_pipeline(ggml_backend_vk_context * ctx, const ggml_tensor * src, const ggml_tensor * dst, ggml_type to);
vk_pipeline ggml_vk_get_quantize_pipeline(ggml_backend_vk_context * ctx, ggml_type type);
void ggml_vk_quantize_q8_1(ggml_backend_vk_context * ctx, vk_context& subctx, const vk_subbuffer & in, const vk_subbuffer & out, uint32_t ne);
void ggml_vk_dsv4_hc_comb(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * mixes, const ggml_tensor * scale, const ggml_tensor * base, ggml_tensor * dst);
void ggml_vk_dsv4_hc_pre(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * x, const ggml_tensor * weights, ggml_tensor * dst);
void ggml_vk_dsv4_hc_post(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * x, const ggml_tensor * residual, const ggml_tensor * post, const ggml_tensor * comb, ggml_tensor * dst);
void ggml_vk_mul_mat(ggml_backend_vk_context * ctx, vk_context& subctx, const struct ggml_cgraph * cgraph, int node_idx);
bool ggml_vk_use_mul_mat_vec_id(const struct ggml_cgraph * cgraph, int node_idx);
void ggml_vk_mul_mat_id(ggml_backend_vk_context * ctx, vk_context& subctx, const struct ggml_cgraph * cgraph, int node_idx);
void ggml_vk_flash_attn(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * q, const ggml_tensor * k, const ggml_tensor * v, const ggml_tensor * mask, const ggml_tensor * sinks, ggml_tensor * dst);
void ggml_vk_cpy_to_contiguous(ggml_backend_vk_context * ctx, vk_context& subctx, vk_pipeline pipeline, const ggml_tensor * tensor, const vk_subbuffer & in, const vk_subbuffer & out);
bool ggml_vk_can_use_fwht(const ggml_backend_vk_context * ctx, const ggml_tensor * src1, const ggml_tensor * dst);
void ggml_vk_fwht(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src, ggml_tensor * dst);
void ggml_vk_get_rows(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst);
void ggml_vk_get_rows_back(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst);
void ggml_vk_acc(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst);
void ggml_vk_multi_add(ggml_backend_vk_context * ctx, vk_context& subctx, ggml_cgraph * cgraph, int node_idx);
void ggml_vk_add(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst);
void ggml_vk_out_prod(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst);
void ggml_vk_sub(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst);
void ggml_vk_mul(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst);
int ggml_vk_unary_mul_op_index(ggml_unary_op op);
void ggml_vk_unary_mul(ggml_backend_vk_context * ctx, vk_context& subctx, const struct ggml_cgraph * cgraph, int node_idx);
void ggml_vk_div(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst);
void ggml_vk_add_id(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, const ggml_tensor * src1, const ggml_tensor * src2, ggml_tensor * dst);
void ggml_vk_rwkv_wkv6(ggml_backend_vk_context * ctx, vk_context& subctx, ggml_tensor * dst);
void ggml_vk_rwkv_wkv7(ggml_backend_vk_context * ctx, vk_context& subctx, ggml_tensor * dst);
void ggml_vk_gated_linear_attn(ggml_backend_vk_context * ctx, vk_context& subctx, ggml_tensor * dst);
void ggml_vk_lightning_indexer(ggml_backend_vk_context * ctx, vk_context& subctx, ggml_tensor * dst);
void ggml_vk_gated_delta_net(ggml_backend_vk_context * ctx, vk_context& subctx, ggml_tensor * dst);
void ggml_vk_ssm_scan(ggml_backend_vk_context * ctx, vk_context& subctx, ggml_tensor * dst);
void ggml_vk_ssm_conv(ggml_backend_vk_context * ctx, vk_context& subctx, const struct ggml_cgraph * cgraph, int node_idx);
void ggml_vk_opt_step_adamw(ggml_backend_vk_context * ctx, vk_context& subctx, ggml_tensor * dst);
void ggml_vk_opt_step_sgd(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, const ggml_tensor * src1, const ggml_tensor * src2, ggml_tensor * dst);
void ggml_vk_concat(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst);
void ggml_vk_upscale(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst);
void ggml_vk_scale(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst);
void ggml_vk_sqr(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst);
void ggml_vk_sqrt(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst);
void ggml_vk_add1(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst);
void ggml_vk_arange(ggml_backend_vk_context * ctx, vk_context& subctx, ggml_tensor * dst);
void ggml_vk_fill(ggml_backend_vk_context * ctx, vk_context& subctx, ggml_tensor * dst);
void ggml_vk_sin(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst);
void ggml_vk_cos(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst);
void ggml_vk_log(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst);
void ggml_vk_tri(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst);
void ggml_vk_diag(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst);
void ggml_vk_clamp(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst);
void ggml_vk_pad(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst);
void ggml_vk_pad_reflect_1d(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst);
void ggml_vk_roll(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst);
void ggml_vk_repeat(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst);
void ggml_vk_repeat_back(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst);
void ggml_vk_cpy(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst);
void ggml_vk_set_rows(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst);
void ggml_vk_silu_back(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst);
void ggml_vk_norm(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst);
void ggml_vk_group_norm(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst);
uint32_t ggml_vk_rms_partials_size(ggml_backend_vk_context * ctx, const ggml_tensor *node);
void ggml_vk_rms_norm(ggml_backend_vk_context * ctx, vk_context& subctx, const struct ggml_cgraph * cgraph, int node_idx, float * op_params);
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);
void ggml_vk_l2_norm(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst);
void ggml_vk_unary(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst);
void ggml_vk_xielu(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst);
void ggml_vk_glu(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst);
void ggml_vk_diag_mask_inf(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst);
void ggml_vk_soft_max(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, const ggml_tensor * src1, const ggml_tensor * src2, ggml_tensor * dst);
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);
void ggml_vk_topk_moe(ggml_backend_vk_context * ctx, vk_context& subctx, ggml_cgraph * cgraph, int node_idx);
void ggml_vk_rope(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_cgraph * cgraph, int node_idx, bool backprop);
void ggml_vk_argsort(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst);
void ggml_vk_topk(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst);
void ggml_vk_topk_qsa(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_cgraph * cgraph, int node_idx);
void ggml_vk_sum(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst);
void ggml_vk_sum_rows(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst);
void ggml_vk_mean(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst);
void ggml_vk_cumsum(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst);
void ggml_vk_cross_entropy_loss(ggml_backend_vk_context * ctx, vk_context& subctx, ggml_tensor * dst);
void ggml_vk_cross_entropy_loss_back(ggml_backend_vk_context * ctx, vk_context& subctx, ggml_tensor * dst);
void ggml_vk_argmax(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst);
void ggml_vk_count_equal(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst);
void ggml_vk_solve_tri(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst);
void ggml_vk_im2col(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst);
void ggml_vk_im2col_3d(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst);
void ggml_vk_timestep_embedding(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst);
void ggml_vk_conv_transpose_1d(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst);
void ggml_vk_col2im_1d(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst);
void ggml_vk_snake_dispatch_fused(ggml_backend_vk_context * ctx, vk_context& subctx, ggml_cgraph * cgraph, int node_idx);
void ggml_vk_pool_1d(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst);
void ggml_vk_pool_2d(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst);
void ggml_vk_conv_2d(ggml_backend_vk_context * ctx, vk_context & subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst);
void ggml_vk_conv_3d(ggml_backend_vk_context * ctx, vk_context & subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst);
void ggml_vk_conv_2d_dw(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst);
void ggml_vk_leaky_relu(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst);
void ggml_vk_preallocate_buffers(ggml_backend_vk_context * ctx, vk_context subctx);
bool ggml_vk_build_graph(ggml_backend_vk_context * ctx, ggml_cgraph * cgraph, int node_idx, ggml_tensor *node_begin, int node_idx_begin, bool last_node, bool almost_ready, bool submit);
void ggml_vk_compute_forward(ggml_backend_vk_context* ctx, ggml_cgraph * cgraph, ggml_tensor* tensor, int tensor_idx, bool almost_ready);
void ggml_vk_graph_cleanup(ggml_backend_vk_context * ctx);
void ggml_vk_cleanup(ggml_backend_vk_context * ctx);
void ggml_vk_synchronize(ggml_backend_vk_context * ctx);
bool ggml_vk_is_empty(ggml_tensor * node);
bool ggml_vk_can_fuse(const ggml_backend_vk_context * ctx, const struct ggml_cgraph * cgraph, int node_idx, std::initializer_list<enum ggml_op> ops);
bool ggml_vk_can_fuse_ssm_conv(const ggml_backend_vk_context * ctx, const struct ggml_cgraph * cgraph, int node_idx, int num_extra);
bool ggml_vk_can_fuse_topk_moe(ggml_backend_vk_context * ctx, const struct ggml_cgraph * cgraph, int node_idx, topk_moe_mode mode);
bool ggml_vk_can_fuse_topk_qsa(ggml_backend_vk_context * ctx, const struct ggml_cgraph * cgraph, int node_idx);
bool ggml_vk_can_fuse_rope_set_rows(ggml_backend_vk_context * ctx, const struct ggml_cgraph * cgraph, int node_idx);
bool ggml_vk_can_fuse_rms_norm_set_rows(ggml_backend_vk_context * ctx, const struct ggml_cgraph * cgraph, int node_idx);
bool ggml_vk_can_fuse_snake(ggml_backend_vk_context * ctx, const struct ggml_cgraph * cgraph, int node_idx);
bool ggml_vk_tensors_overlap(const ggml_tensor * a, const ggml_tensor * b, bool elementwise);
bool ggml_vk_can_fuse_rms_norm_mul_rope(ggml_backend_vk_context * ctx, const struct ggml_cgraph * cgraph, int node_idx);
uint32_t ggml_vk_fuse_multi_add(ggml_backend_vk_context * ctx, const struct ggml_cgraph * cgraph, int node_idx);
void ggml_vk_graph_optimize(ggml_backend_t backend, struct ggml_cgraph * graph, struct ggml_backend_graph_optimize_params * params);
bool ggml_backend_buffer_is_vk(ggml_backend_buffer_t buffer);
void ggml_backend_vk_buffer_free_buffer(ggml_backend_buffer_t buffer);
void * ggml_backend_vk_buffer_get_base(ggml_backend_buffer_t buffer);
enum ggml_status ggml_backend_vk_buffer_init_tensor(ggml_backend_buffer_t buffer, ggml_tensor * tensor);
void ggml_backend_vk_buffer_memset_tensor(ggml_backend_buffer_t buffer, ggml_tensor * tensor, uint8_t value, size_t offset, size_t size);
void ggml_backend_vk_buffer_set_tensor(ggml_backend_buffer_t buffer, ggml_tensor * tensor, const void * data, size_t offset, size_t size);
void ggml_backend_vk_buffer_set_tensor_2d(ggml_backend_buffer_t buffer, ggml_tensor * tensor, const void * data, size_t offset, size_t size, size_t n_copies, size_t stride_tensor, size_t stride_data);
void ggml_backend_vk_buffer_get_tensor(ggml_backend_buffer_t buffer, const ggml_tensor * tensor, void * data, size_t offset, size_t size);
void ggml_backend_vk_buffer_get_tensor_2d(ggml_backend_buffer_t buffer, const ggml_tensor * tensor, void * data, size_t offset, size_t size, size_t n_copies, size_t stride_tensor, size_t stride_data);
bool ggml_backend_vk_buffer_cpy_tensor(ggml_backend_buffer_t buffer, const ggml_tensor * src, ggml_tensor * dst);
void ggml_backend_vk_buffer_clear(ggml_backend_buffer_t buffer, uint8_t value);
const char * ggml_backend_vk_buffer_type_name(ggml_backend_buffer_type_t buft);
ggml_backend_buffer_t ggml_backend_vk_buffer_type_alloc_buffer(ggml_backend_buffer_type_t buft, size_t size);
size_t ggml_backend_vk_buffer_type_get_alignment(ggml_backend_buffer_type_t buft);
size_t ggml_backend_vk_buffer_type_get_max_size(ggml_backend_buffer_type_t buft);
size_t ggml_backend_vk_buffer_type_get_alloc_size(ggml_backend_buffer_type_t buft, const ggml_tensor * tensor);
void ggml_backend_vk_free(ggml_backend_t backend);
ggml_backend_reg_t ggml_backend_vk_reg();
int64_t ggml_vk_get_op_batch_size(const ggml_tensor * op);
bool ggml_vk_lightning_indexer_k_type_supported(ggml_type type);
void ggml_vk_print_device_fault_info(const vk_device& device);
uint64_t ggml_vk_get_node_flops(const ggml_tensor * node);
void ggml_vk_print_node_list(const ggml_cgraph * cgraph, int start, int end);
void ggml_vk_print_device_lost_info(const vk_device& device);
size_t ggml_vk_tensor_buffer_offset(const ggml_backend_vk_context * ctx, const ggml_tensor * t);
size_t ggml_vk_descriptor_offset(size_t tensor_offset, size_t alignment, size_t type_size);
uint32_t ggml_vk_concat_unit_size(ggml_type type);
bool ggml_vk_concat_supported(const ggml_tensor * src0, const ggml_tensor * src1, const ggml_tensor * dst);
template <typename T>
inline void ggml_vk_dispatch_pipeline(ggml_backend_vk_context* ctx, vk_context& subctx, vk_pipeline& pipeline, std::initializer_list<vk::DescriptorBufferInfo> const& descriptor_buffer_infos, const T &push_constants, std::array<uint32_t, 3> elements) {
const uint32_t wg0 = CEIL_DIV(elements[0], pipeline->wg_denoms[0]);
const uint32_t wg1 = CEIL_DIV(elements[1], pipeline->wg_denoms[1]);
const uint32_t wg2 = CEIL_DIV(elements[2], pipeline->wg_denoms[2]);
VK_LOG_DEBUG("ggml_vk_dispatch_pipeline(" << pipeline->name << ", {";
for (auto& buffer : descriptor_buffer_infos) {
std::cerr << "(" << buffer.buffer << ", " << buffer.offset << ", " << buffer.range << "), ";
}
std::cerr << "}, (" << wg0 << "," << wg1 << "," << wg2 << "))");
GGML_ASSERT(wg0 <= ctx->device->properties.limits.maxComputeWorkGroupCount[0] &&
wg1 <= ctx->device->properties.limits.maxComputeWorkGroupCount[1] &&
wg2 <= ctx->device->properties.limits.maxComputeWorkGroupCount[2]);
GGML_ASSERT(ctx->descriptor_set_idx < ctx->descriptor_sets.size());
GGML_ASSERT(descriptor_buffer_infos.size() <= MAX_PARAMETER_COUNT);
GGML_ASSERT(pipeline->parameter_count == descriptor_buffer_infos.size());
GGML_ASSERT(pipeline->push_constant_size == push_constant_size(push_constants));
vk::DescriptorSet& descriptor_set = ctx->descriptor_sets[ctx->descriptor_set_idx++];
vk::WriteDescriptorSet write_descriptor_set{ descriptor_set, 0, 0, pipeline->parameter_count, vk::DescriptorType::eStorageBuffer, nullptr, descriptor_buffer_infos.begin() };
ctx->device->device.updateDescriptorSets({ write_descriptor_set }, {});
subctx->s->buffer->buf.pushConstants(pipeline->layout, vk::ShaderStageFlagBits::eCompute, 0, push_constant_size(push_constants), push_constant_data(push_constants));
subctx->s->buffer->buf.bindPipeline(vk::PipelineBindPoint::eCompute, pipeline->pipeline);
subctx->s->buffer->buf.bindDescriptorSets(vk::PipelineBindPoint::eCompute,
pipeline->layout,
0,
{ descriptor_set },
{});
{
ggml_vk_debug_label dbg(subctx, pipeline->name, wg0, wg1, wg2);
subctx->s->buffer->buf.dispatch(wg0, wg1, wg2);
}
}