Skip to content

fix: Compute the full sum in llama-eval-callback #15637

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 1 commit into from
Aug 28, 2025
Merged

fix: Compute the full sum in llama-eval-callback #15637

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
50 changes: 32 additions & 18 deletions examples/eval-callback/eval-callback.cpp
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -28,9 +28,40 @@ static std::string ggml_ne_string(const ggml_tensor * t) {
return str;
}

static float ggml_get_float_value(uint8_t * data, ggml_type type, const size_t * nb, size_t i0, size_t i1, size_t i2, size_t i3) {
size_t i = i3 * nb[3] + i2 * nb[2] + i1 * nb[1] + i0 * 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_I64) {
v = (float) *(int64_t *) &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_ABORT("fatal error");
}
return v;
}

static void ggml_print_tensor(uint8_t * data, ggml_type type, const int64_t * ne, const size_t * nb, int64_t n) {
GGML_ASSERT(n > 0);
float sum = 0;
for (int64_t i3 = 0; i3 < ne[3]; i3++) {
for (int64_t i2 = 0; i2 < ne[2]; i2++) {
for (int64_t i1 = 0; i1 < ne[1]; i1++) {
for (int64_t i0 = 0; i0 < ne[0]; i0++) {
const float v = ggml_get_float_value(data, type, nb, i0, i1, i2, i3);
sum += v;
}
}
}
}
for (int64_t i3 = 0; i3 < ne[3]; i3++) {
LOG(" [\n");
for (int64_t i2 = 0; i2 < ne[2]; i2++) {
Expand All @@ -50,25 +81,8 @@ static void ggml_print_tensor(uint8_t * data, ggml_type type, const int64_t * ne
LOG("..., ");
i0 = ne[0] - n;
}
size_t i = i3 * nb[3] + i2 * nb[2] + i1 * nb[1] + i0 * 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_I64) {
v = (float) *(int64_t *) &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_ABORT("fatal error");
}
const float v = ggml_get_float_value(data, type, nb, i0, i1, i2, i3);
LOG("%12.4f", v);
sum += v;
if (i0 < ne[0] - 1) LOG(", ");
}
LOG("],\n");
Expand Down
Loading