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b9101 ... b9103

Author SHA1 Message Date
Alessandro de Oliveira Faria (A.K.A.CABELO)
838374375c vendor : update cpp-httplib to 0.44.0 (#22919) 2026-05-11 08:47:13 +02:00
Neo Zhang
7d442abf5c [SYCL] Add OP im2col_3d (#22903)
* add im2col_3d

* format code

* update the ops.md
2026-05-11 08:01:47 +03:00
8 changed files with 2605 additions and 2164 deletions

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@@ -61,13 +61,14 @@ Legend:
| HARDSIGMOID | ❌ | ✅ | ✅ | 🟡 | ✅ | ❌ | ✅ | 🟡 | ✅ | ❌ | ❌ |
| HARDSWISH | ❌ | ✅ | ✅ | 🟡 | ✅ | ❌ | ✅ | 🟡 | ✅ | ❌ | ❌ |
| IM2COL | ❌ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❌ | ❌ |
| IM2COL_3D | ❌ | ❌ | ✅ | ✅ | ❌ | ❌ | | ✅ | ❌ | ❌ | ❌ |
| IM2COL_3D | ❌ | ❌ | ✅ | ✅ | ❌ | ❌ | | ✅ | ❌ | ❌ | ❌ |
| L2_NORM | ❌ | ✅ | ✅ | ✅ | ✅ | ❌ | ✅ | ✅ | ✅ | ❌ | ❌ |
| LEAKY_RELU | ❌ | ✅ | ✅ | ✅ | 🟡 | ❌ | ✅ | 🟡 | ❌ | ❌ | ❌ |
| LOG | ❌ | ✅ | ✅ | ✅ | ✅ | ❌ | 🟡 | ✅ | ✅ | ❌ | ❌ |
| MEAN | ❌ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❌ | ❌ | ❌ |
| MUL | ❌ | ✅ | ✅ | ✅ | 🟡 | ✅ | ✅ | ✅ | ✅ | ❌ | ❌ |
| MUL_MAT | 🟡 | 🟡 | 🟡 | 🟡 | 🟡 | 🟡 | 🟡 | 🟡 | 🟡 | 🟡 | 🟡 |
| MUL_MAT_HADAMARD | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ | ❌ |
| MUL_MAT_ID | ❌ | 🟡 | ✅ | ✅ | 🟡 | 🟡 | 🟡 | ✅ | 🟡 | 🟡 | ❌ |
| NEG | ❌ | ✅ | ✅ | 🟡 | ✅ | ❌ | ✅ | 🟡 | ✅ | ❌ | ❌ |
| NORM | ❌ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | 🟡 | ❌ | ❌ | ❌ |

File diff suppressed because it is too large Load Diff

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@@ -4159,6 +4159,11 @@ static void ggml_sycl_im2col(ggml_backend_sycl_context & ctx, ggml_tensor * dst)
ggml_sycl_op_im2col(ctx, dst);
}
static void ggml_sycl_im2col_3d(ggml_backend_sycl_context & ctx, ggml_tensor * dst) {
scope_op_debug_print scope_dbg_print(__func__, dst, /*num_src=*/2);
ggml_sycl_op_im2col_3d(ctx, dst);
}
static void ggml_sycl_sum(ggml_backend_sycl_context & ctx, ggml_tensor * dst) {
scope_op_debug_print scope_dbg_print(__func__, dst, /*num_src=*/1);
GGML_ASSERT(ggml_is_contiguous(dst->src[0]));
@@ -4456,6 +4461,9 @@ static bool ggml_sycl_compute_forward(ggml_backend_sycl_context & ctx, struct gg
case GGML_OP_IM2COL:
ggml_sycl_im2col(ctx, dst);
break;
case GGML_OP_IM2COL_3D:
ggml_sycl_im2col_3d(ctx, dst);
break;
case GGML_OP_POOL_2D:
ggml_sycl_pool2d(ctx, dst);
break;
@@ -5175,6 +5183,7 @@ static bool ggml_backend_sycl_device_supports_op(ggml_backend_dev_t dev, const g
case GGML_OP_ROPE:
case GGML_OP_ROPE_BACK:
case GGML_OP_IM2COL:
case GGML_OP_IM2COL_3D:
case GGML_OP_UPSCALE:
return true;
case GGML_OP_SUM:

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@@ -1,6 +1,6 @@
//
// MIT license
// Copyright (C) 2024 Intel Corporation
// Copyright (C) 2026 Intel Corporation
// SPDX-License-Identifier: MIT
//
@@ -12,125 +12,389 @@
#include "im2col.hpp"
#include <sycl/sycl.hpp>
#include <type_traits> // For std::is_same_v
#include "ggml.h"
#define MAX_GRIDDIM_Z 65535
template <typename T>
static void im2col_kernel(const float * x, T * dst, int64_t batch_offset, int64_t offset_delta, int64_t IC, int64_t IW,
int64_t IH, int64_t OH, int64_t OW, int64_t KW, int64_t KH, int64_t pelements, int64_t CHW,
int s0, int s1, int p0, int p1, int d0, int d1, const sycl::nd_item<3> & item_ct1) {
const int64_t work_group_size = item_ct1.get_local_range(2);
const int64_t global_id = item_ct1.get_local_id(2) + (work_group_size * item_ct1.get_group(2));
static void im2col_kernel(
const float * x, T * dst,
int64_t IC, int64_t IW, int64_t IH, int64_t OH, int64_t OW, int64_t KW, int64_t KH,
int64_t IC_IH_IW, int64_t IH_IW, int64_t N_OH, int64_t KH_KW, int64_t IC_KH_KW,
int s0, int s1, int p0, int p1, int d0, int d1) {
auto item_ct1 = sycl::ext::oneapi::this_work_item::get_nd_item<3>();
const int64_t i = item_ct1.get_local_id(2) + item_ct1.get_group(2) * item_ct1.get_local_range(2);
if (i >= IC_KH_KW) {
return;
}
// make each work-item deal with more elements since sycl global range can not exceed max int
for (int64_t i = global_id; i < pelements; i += (work_group_size * item_ct1.get_group_range(2))) {
const int64_t ksize = OW * KH;
const int64_t kx = i / ksize;
const int64_t kd = kx * ksize;
const int64_t ky = (i - kd) / OW;
const int64_t ix = i % OW;
const int64_t iic = i / (KH_KW);
const int64_t rem = i - iic * KH_KW;
const int64_t ikh = rem / KW;
const int64_t ikw = rem - ikh * KW;
const int64_t oh = item_ct1.get_group(1);
const int64_t batch = item_ct1.get_group(0) / IC;
const int64_t ic = item_ct1.get_group(0) % IC;
const int64_t iow = item_ct1.get_group(1);
for (int64_t iz = item_ct1.get_group(0); iz < N_OH; iz += MAX_GRIDDIM_Z) {
const int64_t in = iz / OH;
const int64_t ioh = iz - in * OH;
const int64_t iiw = (ix * s0) + (kx * d0) - p0;
const int64_t iih = (oh * s1) + (ky * d1) - p1;
const int64_t iiw = iow * s0 + ikw * d0 - p0;
const int64_t iih = ioh * s1 + ikh * d1 - p1;
const int64_t offset_dst = (((batch * OH + oh) * OW + ix) * CHW) + (ic * (KW * KH) + ky * KW + kx);
const int64_t offset_dst =
((in * OH + ioh) * OW + iow) * IC_KH_KW + iic * KH_KW + ikh * KW + ikw;
const int64_t offset_src_base = (ic * offset_delta) + (batch * batch_offset);
const int64_t offset_src = offset_src_base + (iih * IW) + iiw;
const bool out_of_bounds = (iih < 0 || iih >= IH || iiw < 0 || iiw >= IW);
const float src_val = out_of_bounds ? 0.0f : x[offset_src];
if constexpr (std::is_same_v<T, sycl::half>) {
dst[offset_dst] = sycl::half(src_val);
} else if constexpr (std::is_same_v<T, float>) {
dst[offset_dst] = src_val;
if (iih < 0 || iih >= IH || iiw < 0 || iiw >= IW) {
dst[offset_dst] = 0.0f;
} else {
const int64_t offset_src = iic * IC_IH_IW + in * IH_IW;
dst[offset_dst] = x[offset_src + iih * IW + iiw];
}
}
GGML_UNUSED(IC);
GGML_UNUSED(KH);
}
// im2col: [N, IC, IH, IW] => [N, OH, OW, IC*KH*KW]
template <typename T>
static void im2col_sycl_internal(const float * x, T * dst, int64_t IW, int64_t IH, int64_t OW, int64_t OH, int64_t KW,
int64_t KH, int64_t IC, int64_t batch, int64_t batch_offset, int64_t offset_delta,
int s0, int s1, int p0, int p1, int d0, int d1, queue_ptr stream) {
const int64_t parallel_elements = OW * KW * KH;
const int64_t num_blocks = (parallel_elements + SYCL_IM2COL_BLOCK_SIZE - 1) / SYCL_IM2COL_BLOCK_SIZE;
// decrease global range when it exceeds the max int
int64_t local_size = downsample_sycl_global_range(batch * IC * OH * num_blocks, SYCL_IM2COL_BLOCK_SIZE);
sycl::range<3> block_nums(batch * IC, OH, num_blocks);
sycl::range<3> local_range(1, 1, local_size);
const int64_t CHW = IC * KH * KW;
stream->parallel_for(sycl::nd_range<3>(block_nums * local_range, local_range), [=](sycl::nd_item<3> item_ct1) {
im2col_kernel<T>(x, dst, batch_offset, offset_delta, IC, IW, IH, OH, OW, KW, KH, parallel_elements, CHW, s0, s1,
p0, p1, d0, d1, item_ct1);
});
static void im2col_sycl(const float * x,
T * dst,
int64_t IW,
int64_t IH,
int64_t OW,
int64_t OH,
int64_t KW,
int64_t KH,
int64_t IC,
int64_t N,
int64_t IC_IH_IW,
int64_t IH_IW,
int s0,
int s1,
int p0,
int p1,
int d0,
int d1,
dpct::queue_ptr stream) {
const int64_t IC_KH_KW = IC * KH * KW;
const int64_t num_blocks = (IC_KH_KW + SYCL_IM2COL_BLOCK_SIZE - 1) / SYCL_IM2COL_BLOCK_SIZE;
const int64_t N_OH = N * OH;
const int64_t KH_KW = KW*KH;
dpct::dim3 block_nums(num_blocks, OW, MIN(N_OH, MAX_GRIDDIM_Z));
/*
DPCT1049:73: The work-group size passed to the SYCL kernel may exceed the limit. To get the device limit, query info::device::max_work_group_size. Adjust the work-group size if needed.
*/
stream->parallel_for(sycl::nd_range<3>(block_nums * sycl::range<3>(1, 1, MIN(IC_KH_KW, SYCL_IM2COL_BLOCK_SIZE)),
sycl::range<3>(1, 1, MIN(IC_KH_KW, SYCL_IM2COL_BLOCK_SIZE))),
[=](sycl::nd_item<3> item_ct1) {
im2col_kernel(x, dst, IC, IW, IH, OH, OW, KW, KH, IC_IH_IW, IH_IW, N_OH, KH_KW, IC_KH_KW,
s0, s1, p0, p1, d0, d1);
});
}
static void im2col_sycl_f16(const float * x, sycl::half * dst, int64_t IW, int64_t IH, int64_t OW, int64_t OH,
int64_t KW, int64_t KH, int64_t IC, int64_t batch, int64_t batch_offset,
int64_t offset_delta, int s0, int s1, int p0, int p1, int d0, int d1, queue_ptr stream) {
if (!stream->get_device().has(sycl::aspect::fp16)) {
throw sycl::exception(sycl::make_error_code(sycl::errc::kernel_not_supported),
"Device does not support half precision (fp16) operations!");
}
im2col_sycl_internal<sycl::half>(x, dst, IW, IH, OW, OH, KW, KH, IC, batch, batch_offset, offset_delta, s0, s1, p0,
p1, d0, d1, stream);
static void im2col_sycl_f16(const float * x,
sycl::half * dst,
int64_t IW,
int64_t IH,
int64_t OW,
int64_t OH,
int64_t KW,
int64_t KH,
int64_t IC,
int64_t N,
int64_t IC_IH_IW,
int64_t IH_IW,
int s0,
int s1,
int p0,
int p1,
int d0,
int d1,
dpct::queue_ptr stream) {
im2col_sycl<sycl::half>(x, dst, IW, IH, OW, OH, KW, KH, IC, N, IC_IH_IW, IH_IW, s0, s1, p0, p1, d0, d1, stream);
}
static void im2col_sycl_f32(const float * x, float * dst, int64_t IW, int64_t IH, int64_t OW, int64_t OH, int64_t KW,
int64_t KH, int64_t IC, int64_t batch, int64_t batch_offset, int64_t offset_delta, int s0,
int s1, int p0, int p1, int d0, int d1, queue_ptr stream) {
im2col_sycl_internal<float>(x, dst, IW, IH, OW, OH, KW, KH, IC, batch, batch_offset, offset_delta, s0, s1, p0, p1,
d0, d1, stream);
static void im2col_sycl_f32(const float * x,
float * dst,
int64_t IW,
int64_t IH,
int64_t OW,
int64_t OH,
int64_t KW,
int64_t KH,
int64_t IC,
int64_t N,
int64_t IC_IH_IW,
int64_t IH_IW,
int s0,
int s1,
int p0,
int p1,
int d0,
int d1,
dpct::queue_ptr stream) {
im2col_sycl<float>(x, dst, IW, IH, OW, OH, KW, KH, IC, N, IC_IH_IW, IH_IW, s0, s1, p0, p1, d0, d1, stream);
}
void ggml_sycl_op_im2col(ggml_backend_sycl_context & ctx, ggml_tensor * dst) {
const ggml_tensor * src0 = dst->src[0];
const ggml_tensor * src1 = dst->src[1];
const float * src1_d = (const float *)src1->data;
float * dst_d = (float *)dst->data;
dpct::queue_ptr stream = ctx.stream();
GGML_ASSERT(src1->type == GGML_TYPE_F32);
GGML_ASSERT(dst->type == GGML_TYPE_F16 || dst->type == GGML_TYPE_F32);
GGML_ASSERT( dst->type == GGML_TYPE_F16 || dst->type == GGML_TYPE_F32);
const int32_t s0 = ((const int32_t *) (dst->op_params))[0];
const int32_t s1 = ((const int32_t *) (dst->op_params))[1];
const int32_t p0 = ((const int32_t *) (dst->op_params))[2];
const int32_t p1 = ((const int32_t *) (dst->op_params))[3];
const int32_t d0 = ((const int32_t *) (dst->op_params))[4];
const int32_t d1 = ((const int32_t *) (dst->op_params))[5];
const int32_t s0 = ((const int32_t*)(dst->op_params))[0];
const int32_t s1 = ((const int32_t*)(dst->op_params))[1];
const int32_t p0 = ((const int32_t*)(dst->op_params))[2];
const int32_t p1 = ((const int32_t*)(dst->op_params))[3];
const int32_t d0 = ((const int32_t*)(dst->op_params))[4];
const int32_t d1 = ((const int32_t*)(dst->op_params))[5];
const bool is_2D = ((const int32_t *) (dst->op_params))[6] == 1;
const bool is_2D = ((const int32_t*)(dst->op_params))[6] == 1;
const int64_t IC = src1->ne[is_2D ? 2 : 1];
const int64_t IH = is_2D ? src1->ne[1] : 1;
const int64_t IW = src1->ne[0];
const int64_t IW = src1->ne[0];
const int64_t KH = is_2D ? src0->ne[1] : 1;
const int64_t KW = src0->ne[0];
const int64_t KW = src0->ne[0];
const int64_t OH = is_2D ? dst->ne[2] : 1;
const int64_t OW = dst->ne[1];
const int64_t OW = dst->ne[1];
const size_t delta_offset = src1->nb[is_2D ? 2 : 1] / sizeof(float);
const int64_t batch = src1->ne[is_2D ? 3 : 2];
const size_t batch_offset = src1->nb[is_2D ? 3 : 2] / sizeof(float);
const int64_t IC_IH_IW = src1->nb[is_2D ? 2 : 1] / 4; // nb is byte offset, src is type float32
const int64_t N = src1->ne[is_2D ? 3 : 2];
const int64_t IH_IW = src1->nb[is_2D ? 3 : 2] / 4; // nb is byte offset, src is type float32
queue_ptr stream = ctx.stream();
if (dst->type == GGML_TYPE_F16) {
im2col_sycl_f16((const float *) src1->data, (sycl::half *) dst->data, IW, IH, OW, OH, KW, KH, IC, batch,
batch_offset, delta_offset, s0, s1, p0, p1, d0, d1, stream);
if(dst->type == GGML_TYPE_F16) {
im2col_sycl_f16(src1_d, (sycl::half *) dst_d, IW, IH, OW, OH, KW, KH, IC, N, IC_IH_IW, IH_IW, s0, s1, p0, p1,
d0, d1, stream);
} else {
im2col_sycl_f32((const float *) src1->data, (float *) dst->data, IW, IH, OW, OH, KW, KH, IC, batch,
batch_offset, delta_offset, s0, s1, p0, p1, d0, d1, stream);
im2col_sycl_f32(src1_d, (float *) dst_d, IW, IH, OW, OH, KW, KH, IC, N, IC_IH_IW, IH_IW, s0, s1, p0, p1, d0, d1, stream);
}
}
// [N*IC, ID, IH, IW] => [N*OD, OH, OW, IC * KD * KH * KW]
template <typename T>
static void im2col_3d_kernel(
const float * src, T * dst,
int64_t N, int64_t IC, int64_t ID, int64_t IH, int64_t IW, int64_t OC,
int64_t KD, int64_t KH, int64_t KW, int64_t OD, int64_t OH, int64_t OW,
int64_t OH_OW, int64_t KD_KH_KW, int64_t ID_IH_IW, int64_t KH_KW, int64_t IH_IW, int64_t IC_ID_IH_IW,
int64_t IC_KD_KH_KW, int64_t OW_KD_KH_KW, int64_t OD_OH_OW_IC_KD_KH_KW, int64_t OH_OW_IC_KD_KH_KW,
int64_t OW_IC_KD_KH_KW, int64_t N_OD_OH, int64_t OD_OH,
int64_t stride_q, int64_t stride_z, int64_t stride_y, int64_t stride_x,
int s0, int s1, int s2, int p0, int p1, int p2, int d0, int d1, int d2) {
auto item_ct1 = sycl::ext::oneapi::this_work_item::get_nd_item<3>();
const int64_t i = item_ct1.get_local_id(2) + item_ct1.get_group(2) * item_ct1.get_local_range(2);
if (i >= IC_KD_KH_KW) {
return;
}
GGML_UNUSED(N); GGML_UNUSED(OC); GGML_UNUSED(OH_OW); GGML_UNUSED(OD); GGML_UNUSED(OW); GGML_UNUSED(KD); GGML_UNUSED(KH);
GGML_UNUSED(ID_IH_IW); GGML_UNUSED(IH_IW); GGML_UNUSED(IC_ID_IH_IW); GGML_UNUSED(OW_KD_KH_KW);
const int64_t iic = i / KD_KH_KW;
const int64_t ikd = (i - iic * KD_KH_KW) / KH_KW;
const int64_t ikh = (i - iic * KD_KH_KW - ikd * KH_KW) / KW;
const int64_t ikw = i % KW;
const int64_t iow = item_ct1.get_group(1);
for (int64_t iz = item_ct1.get_group(0); iz < N_OD_OH; iz += MAX_GRIDDIM_Z) {
const int64_t in = iz / OD_OH;
const int64_t iod = (iz - in*OD_OH) / OH;
const int64_t ioh = iz % OH;
const int64_t iiw = iow * s0 + ikw * d0 - p0;
const int64_t iih = ioh * s1 + ikh * d1 - p1;
const int64_t iid = iod * s2 + ikd * d2 - p2;
const int64_t offset_dst = in*OD_OH_OW_IC_KD_KH_KW + iod*OH_OW_IC_KD_KH_KW + ioh*OW_IC_KD_KH_KW + iow*IC_KD_KH_KW + iic*KD_KH_KW + ikd * KH_KW + ikh*KW + ikw;
if (iih < 0 || iih >= IH || iiw < 0 || iiw >= IW || iid < 0 || iid >= ID) {
dst[offset_dst] = 0.0f;
} else {
const int64_t offset_src = ((in * IC + iic) * stride_q) + (iid * stride_z) + (iih * stride_y) + (iiw * stride_x);
dst[offset_dst] = src[offset_src];
}
}
}
// [N*IC, ID, IH, IW] => [N*OD, OH, OW, IC * KD * KH * KW]
template <typename T>
static void im2col_3d_sycl(const float * src,
T * dst,
int64_t N,
int64_t IC,
int64_t ID,
int64_t IH,
int64_t IW,
int64_t OC,
int64_t KD,
int64_t KH,
int64_t KW,
int64_t OD,
int64_t OH,
int64_t OW,
int64_t stride_q,
int64_t stride_z,
int64_t stride_y,
int64_t stride_x,
int s0,
int s1,
int s2,
int p0,
int p1,
int p2,
int d0,
int d1,
int d2,
dpct::queue_ptr stream) {
const int64_t OH_OW = OH*OW;
const int64_t KD_KH_KW = KD*KH*KW;
const int64_t ID_IH_IW = ID*IH*IW;
const int64_t KH_KW = KH*KW;
const int64_t IH_IW = IH*IW;
const int64_t IC_KD_KH_KW = IC*KD*KH*KW;
const int64_t OW_KD_KH_KW = OW*KD*KH*KW;
const int64_t N_OD_OH = N*OD*OH;
const int64_t OD_OH = OD*OH;
const int64_t IC_ID_IH_IW = IC*ID*IH*IW;
const int64_t OD_OH_OW_IC_KD_KH_KW = OD*OH*OW*IC*KD*KH*KW;
const int64_t OH_OW_IC_KD_KH_KW = OH*OW*IC*KD*KH*KW;
const int64_t OW_IC_KD_KH_KW = OW*IC*KD*KH*KW;
const int64_t num_blocks = (IC_KD_KH_KW + SYCL_IM2COL_BLOCK_SIZE - 1) / SYCL_IM2COL_BLOCK_SIZE;
dpct::dim3 block_nums(num_blocks, OW, MIN(N_OD_OH, MAX_GRIDDIM_Z));
/*
DPCT1049:74: The work-group size passed to the SYCL kernel may exceed the limit. To get the device limit, query info::device::max_work_group_size. Adjust the work-group size if needed.
*/
stream->parallel_for(sycl::nd_range<3>(block_nums * sycl::range<3>(1, 1, MIN(IC_KD_KH_KW, SYCL_IM2COL_BLOCK_SIZE)),
sycl::range<3>(1, 1, MIN(IC_KD_KH_KW, SYCL_IM2COL_BLOCK_SIZE))),
[=](sycl::nd_item<3> item_ct1) {
im2col_3d_kernel(src, dst, N, IC, ID, IH, IW, OC, KD, KH, KW, OD, OH, OW, OH_OW, KD_KH_KW,
ID_IH_IW, KH_KW, IH_IW, IC_ID_IH_IW, IC_KD_KH_KW, OW_KD_KH_KW,
OD_OH_OW_IC_KD_KH_KW, OH_OW_IC_KD_KH_KW, OW_IC_KD_KH_KW, N_OD_OH, OD_OH,
stride_q, stride_z, stride_y, stride_x, s0, s1, s2, p0, p1, p2, d0, d1,
d2);
});
}
static void im2col_3d_sycl_f16(const float * src,
sycl::half * dst,
int64_t N,
int64_t IC,
int64_t ID,
int64_t IH,
int64_t IW,
int64_t OC,
int64_t KD,
int64_t KH,
int64_t KW,
int64_t OD,
int64_t OH,
int64_t OW,
int64_t stride_q,
int64_t stride_z,
int64_t stride_y,
int64_t stride_x,
int s0,
int s1,
int s2,
int p0,
int p1,
int p2,
int d0,
int d1,
int d2,
dpct::queue_ptr stream) {
im2col_3d_sycl<sycl::half>(src, dst, N, IC, ID, IH, IW, OC, KD, KH, KW, OD, OH, OW, stride_q, stride_z, stride_y,
stride_x, s0, s1, s2, p0, p1, p2, d0, d1, d2, stream);
}
static void im2col_3d_sycl_f32(const float * src,
float * dst,
int64_t N,
int64_t IC,
int64_t ID,
int64_t IH,
int64_t IW,
int64_t OC,
int64_t KD,
int64_t KH,
int64_t KW,
int64_t OD,
int64_t OH,
int64_t OW,
int64_t stride_q,
int64_t stride_z,
int64_t stride_y,
int64_t stride_x,
int s0,
int s1,
int s2,
int p0,
int p1,
int p2,
int d0,
int d1,
int d2,
dpct::queue_ptr stream) {
im2col_3d_sycl<float>(src, dst, N, IC, ID, IH, IW, OC, KD, KH, KW, OD, OH, OW,
stride_q, stride_z, stride_y, stride_x,
s0, s1, s2, p0, p1, p2, d0, d1, d2, stream);
}
void ggml_sycl_op_im2col_3d(ggml_backend_sycl_context & ctx, ggml_tensor * dst) {
const ggml_tensor * src0 = dst->src[0];
const ggml_tensor * src1 = dst->src[1];
const float * src1_d = (const float *)src1->data;
float * dst_d = (float *)dst->data;
dpct::queue_ptr stream = ctx.stream();
GGML_ASSERT(src1->type == GGML_TYPE_F32);
GGML_ASSERT( dst->type == GGML_TYPE_F16 || dst->type == GGML_TYPE_F32);
GGML_TENSOR_BINARY_OP_LOCALS
const int32_t s0 = ((const int32_t *)(dst->op_params))[0];
const int32_t s1 = ((const int32_t *)(dst->op_params))[1];
const int32_t s2 = ((const int32_t *)(dst->op_params))[2];
const int32_t p0 = ((const int32_t *)(dst->op_params))[3];
const int32_t p1 = ((const int32_t *)(dst->op_params))[4];
const int32_t p2 = ((const int32_t *)(dst->op_params))[5];
const int32_t d0 = ((const int32_t *)(dst->op_params))[6];
const int32_t d1 = ((const int32_t *)(dst->op_params))[7];
const int32_t d2 = ((const int32_t *)(dst->op_params))[8];
const int32_t IC = ((const int32_t *)(dst->op_params))[9];
const int64_t N = ne13 / IC;
const int64_t ID = ne12;
const int64_t IH = ne11;
const int64_t IW = ne10;
const int64_t OC = ne03 / IC;
const int64_t KD = ne02;
const int64_t KH = ne01;
const int64_t KW = ne00;
const int64_t OD = ne3 / N;
const int64_t OH = ne2;
const int64_t OW = ne1;
const size_t es = ggml_element_size(src1);
const int64_t stride_x = src1->nb[0] / es;
const int64_t stride_y = src1->nb[1] / es;
const int64_t stride_z = src1->nb[2] / es;
const int64_t stride_q = src1->nb[3] / es;
if(dst->type == GGML_TYPE_F16) {
im2col_3d_sycl_f16(src1_d, (sycl::half *) dst_d, N, IC, ID, IH, IW, OC, KD, KH, KW, OD, OH, OW,
stride_q, stride_z, stride_y, stride_x,
s0, s1, s2, p0, p1, p2, d0, d1, d2, stream);
} else {
im2col_3d_sycl_f32(src1_d, (float *) dst_d, N, IC, ID, IH, IW, OC, KD, KH, KW, OD, OH, OW,
stride_q, stride_z, stride_y, stride_x,
s0, s1, s2, p0, p1, p2, d0, d1, d2, stream);
}
}

View File

@@ -1,6 +1,6 @@
//
// MIT license
// Copyright (C) 2024 Intel Corporation
// Copyright (C) 2026 Intel Corporation
// SPDX-License-Identifier: MIT
//
@@ -15,7 +15,9 @@
#include "common.hpp"
void ggml_sycl_op_im2col(
ggml_backend_sycl_context & ctx, ggml_tensor *dst);
#define SYCL_IM2COL_BLOCK_SIZE 256
void ggml_sycl_op_im2col(ggml_backend_sycl_context & ctx, ggml_tensor * dst);
void ggml_sycl_op_im2col_3d(ggml_backend_sycl_context & ctx, ggml_tensor * dst);
#endif // GGML_SYCL_IM2COL_HPP

View File

@@ -5,7 +5,7 @@ import os
import sys
import subprocess
HTTPLIB_VERSION = "refs/tags/v0.43.4"
HTTPLIB_VERSION = "refs/tags/v0.44.0"
vendor = {
"https://github.com/nlohmann/json/releases/latest/download/json.hpp": "vendor/nlohmann/json.hpp",

View File

@@ -1161,12 +1161,11 @@ bool parse_header(const char *beg, const char *end, T fn) {
if (!detail::fields::is_field_value(val)) { return false; }
if (case_ignore::equal(key, "Location") ||
case_ignore::equal(key, "Referer")) {
fn(key, val);
} else {
fn(key, decode_path_component(val));
}
// RFC 9110 §5.5: header field values are opaque octets and MUST NOT be
// percent-decoded by the recipient. Applications that need to interpret a
// value as a URI component should call httplib::decode_uri_component()
// (or decode_path_component()) explicitly.
fn(key, val);
return true;
}
@@ -6192,9 +6191,29 @@ ThreadPool::ThreadPool(size_t n, size_t max_n, size_t mqr)
#endif
max_thread_count_ = max_n == 0 ? n : max_n;
threads_.reserve(base_thread_count_);
for (size_t i = 0; i < base_thread_count_; i++) {
threads_.emplace_back(std::thread([this]() { worker(false); }));
#ifndef CPPHTTPLIB_NO_EXCEPTIONS
try {
#endif
for (size_t i = 0; i < base_thread_count_; i++) {
threads_.emplace_back(std::thread([this]() { worker(false); }));
}
#ifndef CPPHTTPLIB_NO_EXCEPTIONS
} catch (...) {
// If thread creation fails partway (e.g., pthread_create returns EAGAIN),
// signal the workers we already spawned to exit and join them so the
// vector destructor does not see joinable threads (which would call
// std::terminate). Then rethrow so the caller learns of the failure.
{
std::unique_lock<std::mutex> lock(mutex_);
shutdown_ = true;
}
cond_.notify_all();
for (auto &t : threads_) {
if (t.joinable()) { t.join(); }
}
throw;
}
#endif
}
bool ThreadPool::enqueue(std::function<void()> fn) {

View File

@@ -8,8 +8,8 @@
#ifndef CPPHTTPLIB_HTTPLIB_H
#define CPPHTTPLIB_HTTPLIB_H
#define CPPHTTPLIB_VERSION "0.43.4"
#define CPPHTTPLIB_VERSION_NUM "0x002b04"
#define CPPHTTPLIB_VERSION "0.44.0"
#define CPPHTTPLIB_VERSION_NUM "0x002c00"
#ifdef _WIN32
#if defined(_WIN32_WINNT) && _WIN32_WINNT < 0x0A00