vbatts/llama.cpp
1
0
Fork 0
Code Issues Pull requests Projects Releases Packages Wiki Activity Actions

Implemented GGML_OP_NORM

Browse source
This commit is contained in:
niansa 2023-06-30 15:18:10 +02:00
parent 8fa60134b1
commit d1f84db4b6
1 changed files with 105 additions and 4 deletions
Download patch file Download diff file Expand all files Collapse all files

109
ggml-vulkan.cpp
View file

@ -482,7 +482,7 @@ layout(push_constant) uniform PushConstants {
} pcs;
layout(local_size_x = 1) in;
layout(binding = 0) buffer restrict readonly tensorInA { float in_[]; };
layout(binding = 0) buffer restrict readonly tensorIn { float in_[]; };
layout(binding = 1) buffer restrict writeonly tensorOut { float out_[]; };
void main() {
@ -509,7 +509,7 @@ layout(push_constant) uniform PushConstants {
} pcs;
layout(local_size_x = 1) in;
layout(binding = 0) buffer restrict readonly tensorInA { float in_[]; };
layout(binding = 0) buffer restrict readonly tensorIn { float in_[]; };
layout(binding = 1) buffer restrict writeonly tensorOut { float out_[]; };
void main() {
@ -535,7 +535,7 @@ layout(push_constant) uniform PushConstants {
} pcs;
layout(local_size_x = 1) in;
layout(binding = 0) buffer restrict readonly tensorInA { float in_[]; };
layout(binding = 0) buffer restrict readonly tensorIn { float in_[]; };
layout(binding = 1) buffer restrict writeonly tensorOut { float out_[]; };
void main() {
@ -565,7 +565,7 @@ layout(push_constant) uniform PushConstants {
} pcs;
layout(local_size_x = nth) in;
layout(binding = 0) buffer restrict readonly tensorInA { float in_[]; };
layout(binding = 0) buffer restrict readonly tensorIn { float in_[]; };
layout(binding = 1) buffer restrict writeonly tensorOut { float out_[]; };
shared float buf[nth];
@ -657,6 +657,104 @@ void ggml_vk_soft_max(kp::Sequence& seq,
}
static const std::string program_norm =
MULTILINE_QUOTE(
layout(push_constant) uniform PushConstants {
uint64_t ne00;
uint64_t nb01;
float eps;
uint inOff;
uint outOff;
} pcs;
layout(local_size_x = 1) in;
layout(binding = 0) buffer restrict readonly tensorIn { float in_[]; };
layout(binding = 1) buffer restrict tensorOut { float out_[]; };
shared float sum[nth];
void main() {
const uint x = gl_GlobalInvocationID.x; // Based from in_
// MEAN
// parallel sum
sum[gl_GlobalInvocationID.y] = 0.0;
for (uint i00 = gl_GlobalInvocationID.y; i00 < pcs.ne00; i00 += nth) {
sum[gl_GlobalInvocationID.y] += in_[x+i00];
}
// reduce
barrier();
memoryBarrierShared();
for (uint i = nth/2; i > 0; i /= 2) {
if (gl_GlobalInvocationID.y < i) {
sum[gl_GlobalInvocationID.y] += sum[gl_GlobalInvocationID.y + i];
}
barrier();
memoryBarrierShared();
}
// broadcast
if (gl_GlobalInvocationID.y == 0) {
sum[0] /= float(pcs.ne00);
}
barrier();
memoryBarrierShared();
const float mean = sum[0];
// recenter
const uint y = gl_GlobalInvocationID.x; // Based from out_
for (uint i00 = gl_GlobalInvocationID.y; i00 < pcs.ne00; i00 += nth) {
out_[y+i00] = in_[x+i00] - mean;
}
// VARIANCE
// parallel sum
sum[gl_GlobalInvocationID.y] = 0.0;
for (uint i00 = gl_GlobalInvocationID.y; i00 < pcs.ne00; i00 += nth) {
sum[gl_GlobalInvocationID.y] += out_[y+i00] * out_[y+i00];
}
// reduce
barrier();
memoryBarrierShared();
for (uint i = nth/2; i > 0; i /= 2) {
if (gl_GlobalInvocationID.y < i) {
sum[gl_GlobalInvocationID.y] += sum[gl_GlobalInvocationID.y + i];
}
barrier();
memoryBarrierShared();
}
// broadcast
if (gl_GlobalInvocationID.y == 0) {
sum[0] /= float(pcs.ne00);
}
barrier();
memoryBarrierShared();
const float variance = sum[0];
const float scale = 1.0/sqrt(variance + pcs.eps);
for (uint i00 = gl_GlobalInvocationID.y; i00 < pcs.ne00; i00 += nth) {
out_[y+i00] *= scale;
}
}
);
void ggml_vk_norm(kp::Sequence& seq,
const std::shared_ptr<kp::Tensor>& in, uint32_t inOff,
const std::shared_ptr<kp::Tensor>& out, uint32_t outOff,
int64_t ne00, int64_t ne01,
int64_t nrows) {
const static unsigned nth = 256;
const static auto spirv = glsl_compile_source(program_source_head+"#define nth "+std::to_string(nth)+"\n"+program_norm, __func__);
struct PushConstants {
uint64_t ne00, nb01;
float eps;
uint32_t inOff, outOff;
} pushConsts {
(uint64_t)ne00, (uint64_t)ne01, 1e-5f, inOff, outOff
};
seq.record<kp::OpAlgoDispatch>(mgr.algorithm<float, PushConstants>({in, out}, spirv, {(uint32_t)nrows, nth}, {}, {pushConsts}));
}
static const std::string program_diag_mask_inf =
MULTILINE_QUOTE(
layout(push_constant) uniform PushConstants {
@ -1100,6 +1198,9 @@ void ggml_vk_graph_compute(struct ggml_kompute_context * ctx, struct ggml_cgraph
break;
}
}
case GGML_OP_NORM: {
ggml_vk_norm(seq, id_src0, offs_src0, id_dst, offs_dst, ne00, ne01, ggml_nrows(src0));
} break;
default:
fprintf(stderr, "%s: node %3d, op = %8s not implemented\n", __func__, i, ggml_op_name(dst->op));
//GGML_ASSERT(false);