kompute : support mask parameter of softmax
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8bd38fe32d
commit
df687b10ab
2 changed files with 24 additions and 14 deletions
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@ -764,9 +764,10 @@ static void ggml_vk_gelu(Args&&... args) {
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static void ggml_vk_soft_max(
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kp::Sequence& seq,
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const std::shared_ptr<kp::Tensor>& in,
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const std::shared_ptr<kp::Tensor>& inA,
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const std::shared_ptr<kp::Tensor>& inB,
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const std::shared_ptr<kp::Tensor>& out,
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uint32_t inOff, uint32_t outOff,
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uint32_t inAOff, uint32_t inBOff, uint32_t outOff,
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int32_t ne00, int32_t ne01, int32_t ne02, uint32_t ne03,
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float scale
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) {
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@ -774,22 +775,27 @@ static void ggml_vk_soft_max(
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kp::shader_data::op_softmax_comp_spv_len);
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struct PushConstants {
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uint32_t inOff, outOff;
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uint32_t inAOff, inBOff, outOff;
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int32_t ne00, ne01, ne02;
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float scale;
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int32_t mask;
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} pushConsts {
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safe_divide(inOff, 4), safe_divide(outOff, 4),
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ne00, ne01, ne02, scale
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safe_divide(inAOff, 4), safe_divide(inBOff, 4), safe_divide(outOff, 4),
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ne00, ne01, ne02,
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scale,
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bool(inB)
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};
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auto & inB_ = inB ? inB : inA;
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std::shared_ptr<kp::Algorithm> s_algo = nullptr;
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if (!komputeManager()->hasAlgorithm(__func__)) {
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// FIXME: The softmax kernel needs to be fixed to use the subgroupsize which can vary by device
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const uint32_t local_x = 32;
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s_algo = komputeManager()->algorithm<uint32_t, PushConstants>(__func__, s_kompute_context->pool.get(), {in, out}, spirv, {unsigned(ne01), unsigned(ne02), unsigned(ne03)}, {local_x}, {pushConsts});
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s_algo = komputeManager()->algorithm<uint32_t, PushConstants>(__func__, s_kompute_context->pool.get(), {inA, inB_, out}, spirv, {unsigned(ne01), unsigned(ne02), unsigned(ne03)}, {local_x}, {pushConsts});
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} else {
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s_algo = komputeManager()->getAlgorithm(__func__);
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s_algo->setTensors({in, out});
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s_algo->setTensors({inA, inB_, out});
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s_algo->setWorkgroup({unsigned(ne01), unsigned(ne02), unsigned(ne03)});
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s_algo->setPushConstants<PushConstants>({pushConsts});
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s_algo->updateDescriptors(s_kompute_context->pool.get());
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@ -1552,7 +1558,7 @@ void ggml_vk_graph_compute(struct ggml_kompute_context * ctx, struct ggml_cgraph
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case GGML_OP_SOFT_MAX:
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{
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const float scale = ((float *) dst->op_params)[0];
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ggml_vk_soft_max(seq, id_src0, id_dst, off_src0, off_dst, ne00, ne01, ne02, ne03, scale);
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ggml_vk_soft_max(seq, id_src0, id_src1, id_dst, off_src0, off_src1, off_dst, ne00, ne01, ne02, ne03, scale);
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} break;
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case GGML_OP_DIAG_MASK_INF:
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{
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@ -6,16 +6,19 @@
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layout(local_size_x_id = 0) in;
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layout(binding = 0) buffer restrict readonly tensorIn { float in_[]; };
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layout(binding = 1) buffer restrict writeonly tensorOut { float out_[]; };
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layout(binding = 0) buffer restrict readonly tensorInA { float inA[]; };
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layout(binding = 1) buffer restrict readonly tensorInB { float inB[]; };
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layout(binding = 2) buffer restrict writeonly tensorOut { float out_[]; };
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layout(push_constant) uniform PushConstants {
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uint inOff;
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uint inAOff;
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uint inBOff;
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uint outOff;
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int ne00;
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int ne01;
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int ne02;
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float scale;
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int mask;
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} pcs;
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void main() {
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@ -27,20 +30,21 @@ void main() {
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const uint i01 = gl_WorkGroupID.x;
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const uint extra_off = i03*pcs.ne02*pcs.ne01*pcs.ne00 + i02*pcs.ne01*pcs.ne00 + i01*pcs.ne00;
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const uint psrc0 = extra_off + pcs.inOff; // Based from in_
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const uint psrc0 = extra_off + pcs.inAOff; // Based from inA
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const uint pmask = i01*pcs.ne00 + pcs.inBOff; // Based from inB
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const uint pdst = extra_off + pcs.outOff; // Based from out_
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// parallel max
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float localMax = uintBitsToFloat(0xFF800000);
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for (uint i00 = gl_SubgroupInvocationID.x; i00 < pcs.ne00; i00 += 32) {
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localMax = max(localMax, in_[psrc0 + i00]*pcs.scale);
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localMax = max(localMax, inA[psrc0 + i00]*pcs.scale + (pcs.mask!=0 ? inB[pmask + i00] : 0.0f));
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}
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float max_ = subgroupMax(localMax);
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// parallel sum
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float localSum = 0.0f;
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for (uint i00 = gl_SubgroupInvocationID.x; i00 < pcs.ne00; i00 += 32) {
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const float exp_psrc0 = exp(in_[psrc0 + i00]*pcs.scale - max_);
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const float exp_psrc0 = exp(inA[psrc0 + i00]*pcs.scale + (pcs.mask!=0 ? inB[pmask + i00] : 0.0f) - max_);
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localSum += exp_psrc0;
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out_[pdst + i00] = exp_psrc0;
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}
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