From cfb820b3436b9ddaead16a21a3a9bda7fad0c150 Mon Sep 17 00:00:00 2001
From: Pierrick HYMBERT <pierrick.hymbert@gmail.com>
Date: Wed, 10 Apr 2024 23:23:22 +0200
Subject: [PATCH] ggml-debug: better tensor type support

---
 examples/ggml-debug/ggml-debug.cpp | 29 ++++++++++++++++++++++-------
 1 file changed, 22 insertions(+), 7 deletions(-)

diff --git a/examples/ggml-debug/ggml-debug.cpp b/examples/ggml-debug/ggml-debug.cpp
index aa2df8c64..43be46ef0 100644
--- a/examples/ggml-debug/ggml-debug.cpp
+++ b/examples/ggml-debug/ggml-debug.cpp
@@ -13,7 +13,7 @@
  * Later on we can for example add operation or tensor name filter from the CLI arg, or a file descriptor to dump the tensor.
  */
 struct callback_data {
-    std::vector<int8_t> data;
+    std::vector<uint8_t> data;
 };
 
 static std::string ggml_ne_string(const ggml_tensor * t) {
@@ -27,7 +27,9 @@ static std::string ggml_ne_string(const ggml_tensor * t) {
     return str;
 }
 
-static void ggml_print_tensor(int8_t * data, const int64_t * ne, const size_t * nb, int64_t n) {
+static void ggml_print_tensor(uint8_t * data, ggml_type type, const int64_t * ne, const size_t * nb, int64_t n) {
+    size_t bs = ggml_blck_size(type);
+
     for (int64_t i3 = 0; i3 < ne[3]; i3++) {
         printf("                                     [\n");
         for (int64_t i2 = 0; i2 < ne[2] && i2 < n; i2++) {
@@ -35,8 +37,21 @@ static void ggml_print_tensor(int8_t * data, const int64_t * ne, const size_t *
             for (int64_t i1 = 0; i1 < ne[1] && i1 < n; i1++) {
                 printf("                                       [");
                 for (int64_t i0 = 0; i0 < ne[0] && i0 < n; i0++) {
-                    size_t i = i3 * nb[3] + i2 * nb[2] + i1 * nb[1] + i0 * nb[0];
-                    float v = *(float *)(data + i);
+                    size_t i = i3 * nb[3] + i2 * nb[2] + i1 * nb[1] + i0 / bs * nb[0];
+                    float v;
+                    if (type == GGML_TYPE_F16) {
+                        v = ggml_fp16_to_fp32(*(ggml_fp16_t *) data + i);
+                    } else if (type == GGML_TYPE_F32) {
+                        v = *(float *) data + i;
+                    } else if (type == GGML_TYPE_I32) {
+                        v = (float) *(int32_t *) data + i;
+                    } else if (type == GGML_TYPE_I16) {
+                        v = (float) *(int16_t *) data + i;
+                    } else if (type == GGML_TYPE_I8) {
+                        v = (float) *(int8_t *) data + i;
+                    } else {
+                        GGML_ASSERT(false);
+                    }
                     printf("%8.4f", v);
                     if (i0 < ne[0] - 1 && i0 < n - 1) printf(", ");
                 }
@@ -92,9 +107,9 @@ static bool ggml_debug(struct ggml_tensor * t, bool ask, void * user_data) {
         ggml_backend_tensor_get(t, cb_data->data.data(), 0, n_bytes);
     }
 
-    if (t->type == GGML_TYPE_F32 || t->type == GGML_TYPE_F16) {
-        int8_t * data = is_host ? (int8_t *) t->data : cb_data->data.data();
-        ggml_print_tensor(data, t->ne, t->nb, 3);
+    if (!ggml_is_quantized(t->type)) {
+        uint8_t * data = is_host ? (uint8_t *) t->data : cb_data->data.data();
+        ggml_print_tensor(data, t->type, t->ne, t->nb, 3);
     }
 
     return true;