add ggml_log operation necessary for cross entropy loss

ggml.c

@@ -3734,6 +3734,7 @@ inline static void ggml_vec_scale_f32(const int n, float * y, const float   v) {
 inline static void ggml_vec_norm_f32 (const int n, float * s, const float * x) { ggml_vec_dot_f32(n, s, x, x); *s = sqrtf(*s);   }
 inline static void ggml_vec_sqr_f32  (const int n, float * y, const float * x) { for (int i = 0; i < n; ++i) y[i] = x[i]*x[i];   }
 inline static void ggml_vec_sqrt_f32 (const int n, float * y, const float * x) { for (int i = 0; i < n; ++i) y[i] = sqrtf(x[i]); }
+inline static void ggml_vec_log_f32  (const int n, float * y, const float * x) { for (int i = 0; i < n; ++i) y[i] = log(x[i]);   }
 inline static void ggml_vec_abs_f32  (const int n, float * y, const float * x) { for (int i = 0; i < n; ++i) y[i] = fabsf(x[i]); }
 inline static void ggml_vec_sgn_f32  (const int n, float * y, const float * x) { for (int i = 0; i < n; ++i) y[i] = (x[i] > 0.f) ? 1.f : ((x[i] < 0.f) ? -1.f : 0.f); }
 inline static void ggml_vec_step_f32 (const int n, float * y, const float * x) { for (int i = 0; i < n; ++i) y[i] = (x[i] > 0.f) ? 1.f : 0.f; }
@@ -3965,6 +3966,7 @@ static const char * GGML_OP_LABEL[GGML_OP_COUNT] = {
     "DIV",
     "SQR",
     "SQRT",
+    "LOG",
     "SUM",
     "SUM_ROWS",
     "MEAN",
@@ -4009,7 +4011,7 @@ static const char * GGML_OP_LABEL[GGML_OP_COUNT] = {
     "MAP_BINARY",
 };
 
-static_assert(GGML_OP_COUNT == 47, "GGML_OP_COUNT != 47");
+static_assert(GGML_OP_COUNT == 48, "GGML_OP_COUNT != 48");
 
 static const char * GGML_OP_SYMBOL[GGML_OP_COUNT] = {
     "none",
@@ -4023,6 +4025,7 @@ static const char * GGML_OP_SYMBOL[GGML_OP_COUNT] = {
     "x/y",
     "x^2",
     "√x",
+    "log(x)",
     "Σx",
     "Σx_k",
     "Σx/n",
@@ -4067,7 +4070,7 @@ static const char * GGML_OP_SYMBOL[GGML_OP_COUNT] = {
     "f(x,y)",
 };
 
-static_assert(GGML_OP_COUNT == 47, "GGML_OP_COUNT != 47");
+static_assert(GGML_OP_COUNT == 48, "GGML_OP_COUNT != 48");
 
 static_assert(sizeof(struct ggml_object)%GGML_MEM_ALIGN == 0, "ggml_object size must be a multiple of GGML_MEM_ALIGN");
 static_assert(sizeof(struct ggml_tensor)%GGML_MEM_ALIGN == 0, "ggml_tensor size must be a multiple of GGML_MEM_ALIGN");
@@ -5303,6 +5306,41 @@ struct ggml_tensor * ggml_sqrt_inplace(
     return ggml_sqrt_impl(ctx, a, true);
 }
 
+
+// ggml_log
+
+struct ggml_tensor * ggml_log_impl(
+        struct ggml_context * ctx,
+        struct ggml_tensor  * a,
+        bool inplace) {
+    bool is_node = false;
+
+    if (!inplace && (a->grad)) {
+        is_node = true;
+    }
+
+    struct ggml_tensor * result = inplace ? ggml_view_tensor(ctx, a) : ggml_dup_tensor(ctx, a);
+
+    result->op   = GGML_OP_LOG;
+    result->grad = is_node ? ggml_dup_tensor(ctx, result) : NULL;
+    result->src0 = a;
+    result->src1 = NULL;
+
+    return result;
+}
+
+struct ggml_tensor * ggml_log(
+        struct ggml_context * ctx,
+        struct ggml_tensor  * a) {
+    return ggml_log_impl(ctx, a, false);
+}
+
+struct ggml_tensor * ggml_log_inplace(
+        struct ggml_context * ctx,
+        struct ggml_tensor  * a) {
+    return ggml_log_impl(ctx, a, true);
+}
+
 // ggml_sum
 
 struct ggml_tensor * ggml_sum(
@@ -8572,6 +8610,49 @@ static void ggml_compute_forward_sqrt(
     }
 }
 
+
+// ggml_compute_forward_log
+
+static void ggml_compute_forward_log_f32(
+        const struct ggml_compute_params * params,
+        const struct ggml_tensor * src0,
+        struct ggml_tensor * dst) {
+    GGML_ASSERT(params->ith == 0);
+    GGML_ASSERT(ggml_are_same_shape(src0, dst));
+
+    if (params->type == GGML_TASK_INIT || params->type == GGML_TASK_FINALIZE) {
+        return;
+    }
+
+    const int n  = ggml_nrows(src0);
+    const int nc = src0->ne[0];
+
+    GGML_ASSERT( dst->nb[0] == sizeof(float));
+    GGML_ASSERT(src0->nb[0] == sizeof(float));
+
+    for (int i = 0; i < n; i++) {
+        ggml_vec_log_f32(nc,
+                (float *) ((char *) dst->data  + i*( dst->nb[1])),
+                (float *) ((char *) src0->data + i*(src0->nb[1])));
+    }
+}
+
+static void ggml_compute_forward_log(
+        const struct ggml_compute_params * params,
+        const struct ggml_tensor * src0,
+        struct ggml_tensor * dst) {
+    switch (src0->type) {
+        case GGML_TYPE_F32:
+            {
+                ggml_compute_forward_log_f32(params, src0, dst);
+            } break;
+        default:
+            {
+                GGML_ASSERT(false);
+            } break;
+    }
+}
+
 // ggml_compute_forward_sum
 
 static void ggml_compute_forward_sum_f32(
@@ -12871,6 +12952,10 @@ static void ggml_compute_forward(struct ggml_compute_params * params, struct ggm
             {
                 ggml_compute_forward_sqrt(params, tensor->src0, tensor);
             } break;
+        case GGML_OP_LOG:
+            {
+                ggml_compute_forward_log(params, tensor->src0, tensor);
+            } break;
         case GGML_OP_SUM:
             {
                 ggml_compute_forward_sum(params, tensor->src0, tensor);
@@ -13168,6 +13253,21 @@ static void ggml_compute_backward(struct ggml_context * ctx, struct ggml_tensor
                                 inplace);
                 }
             } break;
+        case GGML_OP_LOG:
+            {
+                if (src0->grad) {
+                    src0->grad =
+                        ggml_add_impl(ctx,
+                                src0->grad,
+                                ggml_div(ctx,
+                                    tensor->grad,
+                                    src0),
+                                inplace);
+                }
+                if (src1->grad) {
+                    // not supported
+                }
+            } break;
         case GGML_OP_SUM:
             {
                 if (src0->grad) {
@@ -14006,6 +14106,7 @@ void ggml_graph_compute(struct ggml_context * ctx, struct ggml_cgraph * cgraph)
                 case GGML_OP_DIV:
                 case GGML_OP_SQR:
                 case GGML_OP_SQRT:
+                case GGML_OP_LOG:
                 case GGML_OP_SUM:
                 case GGML_OP_SUM_ROWS:
                 case GGML_OP_MEAN:

ggml.h

@@ -259,6 +259,7 @@ extern "C" {
         GGML_OP_DIV,
         GGML_OP_SQR,
         GGML_OP_SQRT,
+        GGML_OP_LOG,
         GGML_OP_SUM,
         GGML_OP_SUM_ROWS,
         GGML_OP_MEAN,
@@ -535,6 +536,14 @@ extern "C" {
             struct ggml_context * ctx,
             struct ggml_tensor  * a);
 
+    GGML_API struct ggml_tensor * ggml_log(
+            struct ggml_context * ctx,
+            struct ggml_tensor  * a);
+
+    GGML_API struct ggml_tensor * ggml_log_inplace(
+            struct ggml_context * ctx,
+            struct ggml_tensor  * a);
+
     // return scalar
     GGML_API struct ggml_tensor * ggml_sum(
             struct ggml_context * ctx,