CS348Project/llama.cpp
5
0
Fork 0
mirror of https://github.com/ggml-org/llama.cpp.git synced 2025-10-31 08:51:55 +00:00
Code Issues Packages Projects Releases Wiki Activity

metal : add GGML_OP_CONV_TRANSPOSE_1D kernels (ggml/1026)

Browse Source 
* wip

* wip implementation f32

* kernel conv transpose 1d f32 working

* initial commit
This commit is contained in:
PAB
2024-11-28 09:25:06 +01:00
committed by Georgi Gerganov
parent 3b4f2e33e2
commit 667d70d170
2 changed files with 121 additions and 0 deletions
Download Patch File Download Diff File Expand all files Collapse all files

48
ggml/src/ggml-metal/ggml-metal.m
View File

@@ -306,6 +306,8 @@ enum ggml_metal_kernel_type {
GGML_METAL_KERNEL_TYPE_IM2COL_F32,
GGML_METAL_KERNEL_TYPE_IM2COL_EXT_F16,
GGML_METAL_KERNEL_TYPE_IM2COL_EXT_F32,
GGML_METAL_KERNEL_TYPE_CONV_TRANSPOSE_1D_F32_F32,
GGML_METAL_KERNEL_TYPE_CONV_TRANSPOSE_1D_F16_F32,
GGML_METAL_KERNEL_TYPE_UPSCALE_F32,
GGML_METAL_KERNEL_TYPE_PAD_F32,
GGML_METAL_KERNEL_TYPE_ARANGE_F32,
@@ -870,6 +872,8 @@ static struct ggml_backend_metal_context * ggml_metal_init(ggml_backend_dev_t de
GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_IM2COL_F32, im2col_f32, true);
GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_IM2COL_EXT_F16, im2col_ext_f16, true);
GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_IM2COL_EXT_F32, im2col_ext_f32, true);
GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_CONV_TRANSPOSE_1D_F32_F32, conv_transpose_1d_f32_f32, true);
GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_CONV_TRANSPOSE_1D_F16_F32, conv_transpose_1d_f16_f32, true);
GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_UPSCALE_F32, upscale_f32, true);
GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_PAD_F32, pad_f32, true);
GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_TIMESTEP_EMBEDDING_F32, timestep_embedding_f32, true);
@@ -1069,6 +1073,7 @@ static bool ggml_metal_supports_op(const struct ggml_backend_metal_device_contex
case GGML_OP_REPEAT:
case GGML_OP_SCALE:
case GGML_OP_CLAMP:
case GGML_OP_CONV_TRANSPOSE_1D:
return true;
case GGML_OP_SQR:
case GGML_OP_SQRT:
@@ -3138,6 +3143,49 @@ static void ggml_metal_encode_node(
[encoder dispatchThreadgroups:MTLSizeMake(IC, OH, OW) threadsPerThreadgroup:MTLSizeMake(N, KH, KW)];
}
} break;
case GGML_OP_CONV_TRANSPOSE_1D:
{
GGML_ASSERT(ggml_is_contiguous(src0));
GGML_ASSERT(ggml_is_contiguous(src1));
GGML_ASSERT(src0->type == GGML_TYPE_F16 || src0->type == GGML_TYPE_F32);
GGML_ASSERT(src1->type == GGML_TYPE_F32);
GGML_ASSERT( dst->type == GGML_TYPE_F32);
const int32_t s0 = ((const int32_t *)(dst->op_params))[0];
const int32_t IC = src1->ne[1];
const int32_t IL = src1->ne[0];
const int32_t K = src0->ne[0];
const int32_t OL = dst->ne[0];
const int32_t OC = dst->ne[1];
id<MTLComputePipelineState> pipeline;
switch (src0->type) {
case GGML_TYPE_F32: {
pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_CONV_TRANSPOSE_1D_F32_F32].pipeline;
} break;
case GGML_TYPE_F16: {
pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_CONV_TRANSPOSE_1D_F16_F32].pipeline;
} break;
default: GGML_ABORT("fatal error");
};
[encoder setComputePipelineState:pipeline];
[encoder setBuffer:id_src0 offset:offs_src0 atIndex:0];
[encoder setBuffer:id_src1 offset:offs_src1 atIndex:1];
[encoder setBuffer:id_dst offset:offs_dst atIndex:2];
[encoder setBytes:&IC length:sizeof( int32_t) atIndex:3];
[encoder setBytes:&IL length:sizeof( int32_t) atIndex:4];
[encoder setBytes:&K length:sizeof( int32_t) atIndex:5];
[encoder setBytes:&s0 length:sizeof( int32_t) atIndex:6];
[encoder setBytes:&nb0 length:sizeof(uint64_t) atIndex:7];
[encoder setBytes:&nb1 length:sizeof(uint64_t) atIndex:8];
[encoder dispatchThreadgroups:MTLSizeMake(OL, OC, 1) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)];
} break;
case GGML_OP_UPSCALE:
{
GGML_ASSERT(src0->type == GGML_TYPE_F32);

73
ggml/src/ggml-metal/ggml-metal.metal
View File

@@ -2671,6 +2671,79 @@ kernel void kernel_im2col_ext(
template [[host_name("kernel_im2col_ext_f32")]] kernel im2col_ext_t kernel_im2col_ext<float>;
template [[host_name("kernel_im2col_ext_f16")]] kernel im2col_ext_t kernel_im2col_ext<half>;
typedef void (conv_transpose_1d_t)(
device const float * src0,
device const float * src1,
device char * dst,
constant int32_t & IC,
constant int32_t & IL,
constant int32_t & K,
constant int32_t & s0,
constant uint64_t & nb0,
constant uint64_t & nb1,
uint3 tgpig[[threadgroup_position_in_grid]],
uint3 tgpg[[threadgroups_per_grid]]);
template <typename T>
kernel void kernel_conv_transpose_1d(
device const T * src0,
device const float * src1,
device char * dst,
constant int32_t & IC,
constant int32_t & IL,
constant int32_t & K,
constant int32_t & s0,
constant uint64_t & nb0,
constant uint64_t & nb1,
uint3 tgpig[[threadgroup_position_in_grid]],
uint3 tgpg[[threadgroups_per_grid]]) {
float v = 0.0f;
for (int64_t c = 0; c < IC; c++) {
const int32_t kernel_offset = c * tgpg[1] * K + K * tgpig[1];
const int32_t input_offset = c * IL;
for (int64_t i = 0; i < IL; i++) {
if (tgpig[0] >= i * s0 && tgpig[0] < i * s0 + K) {
v += src0[kernel_offset + tgpig[0] - i * s0] * src1[input_offset + i];
}
}
}
device float * dst_ptr = (device float *) (dst + tgpig[0] * nb0 + tgpig[1] * nb1);
dst_ptr[0] = v;
}
template [[host_name("kernel_conv_transpose_1d_f32_f32")]]
kernel void kernel_conv_transpose_1d<float>(
device const float * src0,
device const float * src1,
device char * dst,
constant int32_t & IC,
constant int32_t & IL,
constant int32_t & K,
constant int32_t & s0,
constant uint64_t & nb0,
constant uint64_t & nb1,
uint3 tgpig[[threadgroup_position_in_grid]],
uint3 tgpg[[threadgroups_per_grid]]);
template [[host_name("kernel_conv_transpose_1d_f16_f32")]]
kernel void kernel_conv_transpose_1d<half>(
device const half * src0,
device const float * src1,
device char * dst,
constant int32_t & IC,
constant int32_t & IL,
constant int32_t & K,
constant int32_t & s0,
constant uint64_t & nb0,
constant uint64_t & nb1,
uint3 tgpig[[threadgroup_position_in_grid]],
uint3 tgpg[[threadgroups_per_grid]]);
kernel void kernel_upscale_f32(
device const char * src0,
device char * dst,