Implemented GGML_OP_NORM

ggml-vulkan.cpp

@@ -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);