ggml : add ggml_set_rows (#14274)

* ggml : add ggml_set_rows

Add ggml_set_rows(a, b, c) which copies rows from 'b' into 'a' using
indices from 'c'.

ref: #8366

* use I64 for indices

* ggml : add repeat impl for i64

* ggml : add ggml_is_contiguous_rows

* ggml : ggml_set_rows support broadcast

* ggml : ggml_set_rows support quantized dst

ggml-ci

* ggml : support GGML_TYPE_F32 ".from_float" trait

* ggml : ggml_set_rows update comment + better index name

* tests : add ggml_set_rows

* metal : add ggml_set_rows implementation

ggml-ci

* ggml : simplify forward_dup_f32

* ggml : fix supports_op

* tests : add comment to set_rows

* ggml : leave the repeat_i64 for a separate PR

ggml-ci

* ggml : set_rows use std::min instead of MIN

* ggml : better error message for set_rows unsupported type

* metal : perform op->type check only once

* tests : more consistent implementation + more tests

ggml-ci

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

ggml/src/ggml-cpu/ops.cpp

@@ -696,24 +696,8 @@ static void ggml_compute_forward_dup_f32(
     if (ggml_is_contiguous(dst)) {
         // TODO: simplify
         if (nb00 == sizeof(float)) {
-            if (dst->type == GGML_TYPE_F32) {
-                size_t id = 0;
-                const size_t rs = ne00 * nb00;
-                char * dst_ptr = (char *) dst->data;
-
-                for (int i03 = 0; i03 < ne03; i03++) {
-                    for (int i02 = 0; i02 < ne02; i02++) {
-                        id += rs * ir0;
-                        for (int i01 = ir0; i01 < ir1; i01++) {
-                            const char * src0_ptr = (char *) src0->data + i01*nb01 + i02*nb02 + i03*nb03;
-                            memcpy(dst_ptr + id, src0_ptr, rs);
-                            id += rs;
-                        }
-                        id += rs * (ne01 - ir1);
-                    }
-                }
-            } else if (ggml_get_type_traits_cpu(dst->type)->from_float) {
-                ggml_from_float_t const quantize_row_q = ggml_get_type_traits_cpu(dst->type)->from_float;
+            if (ggml_get_type_traits_cpu(dst->type)->from_float) {
+                ggml_from_float_t const from_float = ggml_get_type_traits_cpu(dst->type)->from_float;
 
                 size_t id = 0;
                 size_t rs = nb0 * (ne00 / ggml_blck_size(dst->type));
@@ -724,7 +708,7 @@ static void ggml_compute_forward_dup_f32(
                         id += rs * ir0;
                         for (int i01 = ir0; i01 < ir1; i01++) {
                             const float * src0_ptr = (float *) ((char *) src0->data + i01*nb01 + i02*nb02 + i03*nb03);
-                            quantize_row_q(src0_ptr, dst_ptr + id, ne00);
+                            from_float(src0_ptr, dst_ptr + id, ne00);
                             id += rs;
                         }
                         id += rs * (ne01 - ir1);
@@ -2300,6 +2284,12 @@ void ggml_compute_forward_repeat(
             {
                 ggml_compute_forward_repeat_f32(params, dst);
             } break;
+        // TODO: templateify the implemenation and support for I64
+        //       ref https://github.com/ggml-org/llama.cpp/pull/14274#discussion_r2169492225
+        //case GGML_TYPE_I64:
+        //    {
+        //        ggml_compute_forward_repeat_i64(params, dst);
+        //    } break;
         default:
             {
                 GGML_ABORT("fatal error");
@@ -4470,6 +4460,74 @@ void ggml_compute_forward_get_rows(
     //}
 }
 
+static void ggml_compute_forward_set_rows_f32(
+        const ggml_compute_params * params,
+              ggml_tensor * dst) {
+
+    const ggml_tensor * src0 = dst->src[0];
+    const ggml_tensor * src1 = dst->src[1];
+
+    GGML_TENSOR_BINARY_OP_LOCALS
+
+    const int64_t nc = ne00;
+    const int64_t nr = ne01;
+
+    assert(ne0  == nc);
+    assert(ne2  == ne02);
+    assert(ne3  == ne03);
+    assert(src0->type == GGML_TYPE_F32);
+    assert(ne02 % ne11 == 0);
+    assert(ne03 % ne12 == 0);
+
+    const int ith = params->ith;
+    const int nth = params->nth;
+
+    // rows per thread
+    const int64_t dr = (nr + nth - 1)/nth;
+
+    // row range for this thread
+    const int64_t ir0 = dr*ith;
+    const int64_t ir1 = std::min(ir0 + dr, nr);
+
+    ggml_from_float_t const from_float = ggml_get_type_traits_cpu(dst->type)->from_float;
+
+    for (int64_t i03 = 0; i03 < ne03; ++i03) {
+        for (int64_t i02 = 0; i02 < ne02; ++i02) {
+            for (int64_t i = ir0; i < ir1; ++i) {
+                const int64_t i12 = i03%ne12;
+                const int64_t i11 = i02%ne11;
+                const int64_t i10 = i;
+
+                const int64_t i1 = *(int64_t *) ((char *) src1->data + i10*nb10 + i11*nb11 + i12*nb12);
+
+                GGML_ASSERT(i1 >= 0 && i1 < ne1);
+
+                from_float(
+                        (const float *) ((char *) src0->data +  i*nb01 + i02*nb02 + i03*nb03),
+                                        ((char *)  dst->data + i1*nb1  + i02*nb2  + i03*nb3), nc);
+            }
+        }
+    }
+}
+
+void ggml_compute_forward_set_rows(
+        const ggml_compute_params * params,
+        ggml_tensor * dst) {
+
+    const ggml_tensor * src0 = dst->src[0];
+
+    switch (src0->type) {
+        case GGML_TYPE_F32:
+            {
+                ggml_compute_forward_set_rows_f32(params, dst);
+            } break;
+        default:
+            {
+                GGML_ABORT("src0->type = %d (%s) not supported", src0->type, ggml_type_name(src0->type));
+            }
+    }
+}
+
 // ggml_compute_forward_get_rows_back
 
 static void ggml_compute_forward_get_rows_back_f32_f16(