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metal: add col2im_1d op (f32/f16/bf16) (llama/25176)

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* metal: add col2im_1d op (f32/f16/bf16)

Gather kernel mirroring the CPU/CUDA path: each output (t_out, oc)
reads its ceil(K/s0) source columns with an F32 accumulator, a single
write and no atomics. One thread per output element, 256 per
threadgroup.

* metal: check dst contiguity and type match in supports_op for COL2IM_1D

Align the GGML_OP_COL2IM_1D predicate with the CPU, CUDA, and Vulkan
backends: the kernel writes dst with linear indexing and assumes the
same type as src0, so supports_op must also require a contiguous dst
and op->type == op->src[0]->type.

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

Co-authored-by: YiChen Lv <63285796+forforever73@users.noreply.github.com>

---------

Co-authored-by: YiChen Lv <63285796+forforever73@users.noreply.github.com>
This commit is contained in:
Pascal
2026-07-06 20:47:36 +02:00
committed by Georgi Gerganov
parent 3f05208e5c
commit 91ca310157
7 changed files with 125 additions and 0 deletions
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20
ggml/src/ggml-metal/ggml-metal-device.cpp
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@@ -1800,6 +1800,26 @@ ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_conv_transpose_1
return res;
}
ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_col2im_1d(ggml_metal_library_t lib, const ggml_tensor * op) {
assert(op->op == GGML_OP_COL2IM_1D);
GGML_ASSERT(ggml_is_contiguous(op->src[0]));
GGML_ASSERT(op->src[0]->type == GGML_TYPE_F32 || op->src[0]->type == GGML_TYPE_F16 || op->src[0]->type == GGML_TYPE_BF16);
char base[256];
char name[256];
snprintf(base, 256, "kernel_col2im_1d_%s", ggml_type_name(op->src[0]->type));
snprintf(name, 256, "%s", base);
ggml_metal_pipeline_with_params res = ggml_metal_library_get_pipeline(lib, name);
if (!res.pipeline) {
res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr);
}
return res;
}
ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_conv_transpose_2d(ggml_metal_library_t lib, const ggml_tensor * op) {
assert(op->op == GGML_OP_CONV_TRANSPOSE_2D);

1
ggml/src/ggml-metal/ggml-metal-device.h
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@@ -150,6 +150,7 @@ struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_rope
struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_im2col (ggml_metal_library_t lib, const struct ggml_tensor * op);
struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_conv_transpose_1d (ggml_metal_library_t lib, const struct ggml_tensor * op);
struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_conv_transpose_2d (ggml_metal_library_t lib, const struct ggml_tensor * op);
struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_col2im_1d (ggml_metal_library_t lib, const struct ggml_tensor * op);
struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_conv_2d (ggml_metal_library_t lib, const struct ggml_tensor * op);
struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_conv_3d (ggml_metal_library_t lib, const struct ggml_tensor * op);
struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_upscale (ggml_metal_library_t lib, const struct ggml_tensor * op);

5
ggml/src/ggml-metal/ggml-metal-device.m
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@@ -1157,6 +1157,11 @@ bool ggml_metal_device_supports_op(ggml_metal_device_t dev, const struct ggml_te
(op->src[0]->type == GGML_TYPE_F16 || op->src[0]->type == GGML_TYPE_F32) &&
op->src[1]->type == GGML_TYPE_F32 &&
op->type == GGML_TYPE_F32;
case GGML_OP_COL2IM_1D:
return (op->src[0]->type == GGML_TYPE_F32 || op->src[0]->type == GGML_TYPE_F16 || op->src[0]->type == GGML_TYPE_BF16) &&
op->type == op->src[0]->type &&
ggml_is_contiguous(op->src[0]) &&
ggml_is_contiguous(op);
case GGML_OP_CONV_3D:
return ggml_is_contiguous(op->src[0]) &&
ggml_is_contiguous(op->src[1]) &&

10
ggml/src/ggml-metal/ggml-metal-impl.h
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@@ -603,6 +603,16 @@ typedef struct {
uint64_t nb1;
} ggml_metal_kargs_conv_transpose_1d;
typedef struct {
int32_t T_in;
int32_t T_out;
int32_t OC;
int32_t K;
int32_t K_OC;
int32_t s0;
int32_t p0;
} ggml_metal_kargs_col2im_1d;
typedef struct {
int32_t IC;
int32_t IH;

45
ggml/src/ggml-metal/ggml-metal-ops.cpp
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@@ -395,6 +395,10 @@ static int ggml_metal_op_encode_impl(ggml_metal_op_t ctx, int idx) {
{
n_fuse = ggml_metal_op_conv_transpose_2d(ctx, idx);
} break;
case GGML_OP_COL2IM_1D:
{
n_fuse = ggml_metal_op_col2im_1d(ctx, idx);
} break;
case GGML_OP_CONV_3D:
{
n_fuse = ggml_metal_op_conv_3d(ctx, idx);
@@ -3854,6 +3858,47 @@ int ggml_metal_op_conv_transpose_1d(ggml_metal_op_t ctx, int idx) {
return 1;
}
int ggml_metal_op_col2im_1d(ggml_metal_op_t ctx, int idx) {
ggml_tensor * op = ctx->node(idx);
ggml_metal_library_t lib = ctx->lib;
ggml_metal_encoder_t enc = ctx->enc;
const int32_t s0 = ((const int32_t *)(op->op_params))[0];
const int32_t OC = ((const int32_t *)(op->op_params))[1];
const int32_t p0 = ((const int32_t *)(op->op_params))[2];
const int32_t K_OC = (int32_t) op->src[0]->ne[0];
const int32_t T_in = (int32_t) op->src[0]->ne[1];
const int32_t K = K_OC / OC;
const int32_t T_out = (int32_t) op->ne[0];
ggml_metal_kargs_col2im_1d args = {
/*.T_in =*/ T_in,
/*.T_out =*/ T_out,
/*.OC =*/ OC,
/*.K =*/ K,
/*.K_OC =*/ K_OC,
/*.s0 =*/ s0,
/*.p0 =*/ p0,
};
auto pipeline = ggml_metal_library_get_pipeline_col2im_1d(lib, op);
const int total = T_out * OC;
const int nth = 256;
const int ntg = (total + nth - 1) / nth;
ggml_metal_encoder_set_pipeline(enc, pipeline);
ggml_metal_encoder_set_bytes (enc, &args, sizeof(args), 0);
ggml_metal_encoder_set_buffer (enc, ggml_metal_get_buffer_id(op->src[0]), 1);
ggml_metal_encoder_set_buffer (enc, ggml_metal_get_buffer_id(op), 2);
ggml_metal_encoder_dispatch_threadgroups(enc, ntg, 1, 1, nth, 1, 1);
return 1;
}
int ggml_metal_op_conv_transpose_2d(ggml_metal_op_t ctx, int idx) {
ggml_tensor * op = ctx->node(idx);

1
ggml/src/ggml-metal/ggml-metal-ops.h
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@@ -78,6 +78,7 @@ int ggml_metal_op_conv_2d (ggml_metal_op_t ctx, int idx);
int ggml_metal_op_conv_3d (ggml_metal_op_t ctx, int idx);
int ggml_metal_op_conv_transpose_1d (ggml_metal_op_t ctx, int idx);
int ggml_metal_op_conv_transpose_2d (ggml_metal_op_t ctx, int idx);
int ggml_metal_op_col2im_1d (ggml_metal_op_t ctx, int idx);
int ggml_metal_op_upscale (ggml_metal_op_t ctx, int idx);
int ggml_metal_op_pad (ggml_metal_op_t ctx, int idx);
int ggml_metal_op_pad_reflect_1d (ggml_metal_op_t ctx, int idx);

43
ggml/src/ggml-metal/ggml-metal.metal
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@@ -4977,6 +4977,49 @@ kernel void kernel_conv_transpose_1d<half>(
uint3 tgpg[[threadgroups_per_grid]]);
template <typename T>
kernel void kernel_col2im_1d(
constant ggml_metal_kargs_col2im_1d & args,
device const T * col,
device T * dst,
uint tgpig [[threadgroup_position_in_grid]],
uint tpitg [[thread_position_in_threadgroup]],
uint ntg [[threads_per_threadgroup]]) {
const int idx = tgpig * ntg + tpitg;
if (idx >= args.T_out * args.OC) {
return;
}
const int t_out = idx % args.T_out;
const int oc = idx / args.T_out;
const int t_abs = t_out + args.p0; // absolute position in uncropped signal
int t_in_min = (t_abs - args.K + args.s0) / args.s0; // ceil((t_abs - K + 1) / s0)
if (t_in_min < 0) {
t_in_min = 0;
}
int t_in_max = t_abs / args.s0;
if (t_in_max >= args.T_in) {
t_in_max = args.T_in - 1;
}
float sum = 0.0f;
for (int t_in = t_in_min; t_in <= t_in_max; t_in++) {
const int k = t_abs - t_in * args.s0;
sum += float(col[(oc * args.K + k) + t_in * args.K_OC]);
}
dst[t_out + oc * args.T_out] = T(sum);
}
template [[host_name("kernel_col2im_1d_f32")]] kernel void kernel_col2im_1d<float>(constant ggml_metal_kargs_col2im_1d &, device const float *, device float *, uint, uint, uint);
template [[host_name("kernel_col2im_1d_f16")]] kernel void kernel_col2im_1d<half>(constant ggml_metal_kargs_col2im_1d &, device const half *, device half *, uint, uint, uint);
#if defined(GGML_METAL_HAS_BF16)
template [[host_name("kernel_col2im_1d_bf16")]] kernel void kernel_col2im_1d<bfloat>(constant ggml_metal_kargs_col2im_1d &, device const bfloat *, device bfloat *, uint, uint, uint);
#endif
typedef void (conv_transpose_2d_t)(
constant ggml_metal_kargs_conv_transpose_2d & args,
device const float * src0,