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metal : add CONV_TRANSPOSE_2D (#16542)

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* initial: headers and metal-device.cpp updates

* adding conv_transpose_2d

* fix type

* fix type: int32->int64

* Update ggml/src/ggml-metal/ggml-metal.metal

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

* Update ggml/src/ggml-metal/ggml-metal.metal

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

* Update ggml/src/ggml-metal/ggml-metal.metal

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

* add checks for src[0] and src[1]; add type checks

* Update ggml-metal.metal

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

* add more tests, add optimization to threading

* add dynamic memory allocation in metal

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
This commit is contained in:
Ilia Ilmer
2025-10-17 09:33:58 +03:00
committed by GitHub
co-authored by Georgi Gerganov
parent 79967ec596
commit 9ad4f1931e
8 changed files with 198 additions and 0 deletions
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ggml/src/ggml-metal/ggml-metal.metal
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@@ -4179,6 +4179,97 @@ kernel void kernel_conv_transpose_1d<half>(
uint3 tgpig[[threadgroup_position_in_grid]],
uint3 tgpg[[threadgroups_per_grid]]);
typedef void (conv_transpose_2d_t)(
constant ggml_metal_kargs_conv_transpose_2d & args,
device const float * src0,
device const float * src1,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
uint3 tgpg[[threadgroups_per_grid]]);
template <typename T>
kernel void kernel_conv_transpose_2d(
constant ggml_metal_kargs_conv_transpose_2d & args,
device const T * src0,
device const float * src1,
device char * dst,
threadgroup float * shared_sum [[threadgroup(0)]],
uint3 tgpig[[threadgroup_position_in_grid]],
uint3 tpitg[[thread_position_in_threadgroup]],
uint3 ntg[[threads_per_threadgroup]]) {
const int64_t out_x = tgpig[0];
const int64_t out_y = tgpig[1];
const int64_t out_c = tgpig[2];
const int64_t kw = tpitg[0];
const int64_t kh = tpitg[1];
float v = 0.0f;
for (int64_t in_c = 0; in_c < args.IC; in_c++) {
int64_t in_y = out_y - kh;
if (in_y < 0 || in_y % args.s0) continue;
in_y /= args.s0;
if (in_y >= args.IH) continue;
int64_t in_x = out_x - kw;
if (in_x < 0 || in_x % args.s0) continue;
in_x /= args.s0;
if (in_x >= args.IW) continue;
const int64_t input_idx = (args.IW * args.IH) * in_c + (args.IW) * in_y + in_x;
const int64_t kernel_idx = (args.KH * args.KW * args.OC) * in_c + (args.KH * args.KW) * out_c + (args.KW) * kh + kw;
v += (float)src0[kernel_idx] * src1[input_idx];
}
const uint tid = tpitg.y * ntg.x + tpitg.x;
shared_sum[tid] = v;
threadgroup_barrier(mem_flags::mem_threadgroup);
if (tid == 0) {
float total = 0.0f;
const uint num_threads = ntg.x * ntg.y;
for (uint i = 0; i < num_threads; i++) {
total += shared_sum[i];
}
device float * dst_ptr = (device float *) (dst + out_x*args.nb0 + out_y * args.nb1 + out_c*args.nb2);
dst_ptr[0] = total;
}
}
template [[host_name("kernel_conv_transpose_2d_f32_f32")]]
kernel void kernel_conv_transpose_2d<float>(
constant ggml_metal_kargs_conv_transpose_2d & args,
device const float * src0,
device const float * src1,
device char * dst,
threadgroup float * shared_sum [[threadgroup(0)]],
uint3 tgpig[[threadgroup_position_in_grid]],
uint3 tpitg[[thread_position_in_threadgroup]],
uint3 ntg[[threads_per_threadgroup]]);
template [[host_name("kernel_conv_transpose_2d_f16_f32")]]
kernel void kernel_conv_transpose_2d<half>(
constant ggml_metal_kargs_conv_transpose_2d & args,
device const half * src0,
device const float * src1,
device char * dst,
threadgroup float * shared_sum [[threadgroup(0)]],
uint3 tgpig[[threadgroup_position_in_grid]],
uint3 tpitg[[thread_position_in_threadgroup]],
uint3 ntg[[threads_per_threadgroup]]);
kernel void kernel_upscale_f32(
constant ggml_metal_kargs_upscale & args,
device const char * src0,