ggml-hexagon: respect input size when getting/setting tensor data (#16836)

* respect input size when getting/setting tensor data

allows partial repacking/copying when get tensor size is smaller than the actual tensor

* Removed duplicate repack_mxfp4_mxfp4x4x2 function
This commit is contained in:
l3utterfly
2025-10-31 12:46:31 +08:00
committed by GitHub
parent 6eb208d17e
commit 13002a0896

View File

@@ -676,6 +676,15 @@ static void repack_q4_0_q4x4x2(ggml_tensor * t, const void * data, size_t size)
size_t row_size_pd = ggml_row_size(t->type, hex_round_up(t->ne[0], QK_Q4_0x4x2)); // extra elements for the pad size_t row_size_pd = ggml_row_size(t->type, hex_round_up(t->ne[0], QK_Q4_0x4x2)); // extra elements for the pad
size_t row_size_rp = row_size * 2; // extra space for tmp pad (if any) size_t row_size_rp = row_size * 2; // extra space for tmp pad (if any)
// Ensure we don't try to read more data than is available in the source buffer 'data'
// or write more than the tensor can hold.
const size_t total_tensor_size = (size_t)nrows * row_size;
const size_t n_bytes_to_copy = size < total_tensor_size ? size : total_tensor_size;
// Calculate how many full rows and how many remaining bytes we need to process.
const int64_t n_full_rows = n_bytes_to_copy / row_size;
const size_t n_rem_bytes = n_bytes_to_copy % row_size;
void * buf_pd = ggml_aligned_malloc(row_size_pd); void * buf_pd = ggml_aligned_malloc(row_size_pd);
GGML_ASSERT(buf_pd != NULL); GGML_ASSERT(buf_pd != NULL);
@@ -687,7 +696,8 @@ static void repack_q4_0_q4x4x2(ggml_tensor * t, const void * data, size_t size)
init_row_q4x4x2((block_q4_0 *) buf_pd, t->ne[0]); // init padded buffer to make sure the tail is all zeros init_row_q4x4x2((block_q4_0 *) buf_pd, t->ne[0]); // init padded buffer to make sure the tail is all zeros
for (int64_t i = 0; i < nrows; i++) { // 1. Process all the full rows
for (int64_t i = 0; i < n_full_rows; i++) {
const uint8_t * src = (const uint8_t *) data + (i * row_size); const uint8_t * src = (const uint8_t *) data + (i * row_size);
uint8_t * dst = (uint8_t *) t->data + (i * row_size); uint8_t * dst = (uint8_t *) t->data + (i * row_size);
@@ -696,6 +706,25 @@ static void repack_q4_0_q4x4x2(ggml_tensor * t, const void * data, size_t size)
memcpy(dst, buf_rp, row_size); memcpy(dst, buf_rp, row_size);
} }
// 2. Process the final, potentially partial, row
if (n_rem_bytes > 0) {
const int64_t i = n_full_rows;
const uint8_t * src = (const uint8_t *) data + (i * row_size);
uint8_t * dst = (uint8_t *) t->data + (i * row_size);
// re-init the row because we are potentially copying a partial row
init_row_q4x4x2((block_q4_0 *) buf_pd, t->ne[0]);
// Copy only the remaining bytes from the source.
memcpy(buf_pd, src, n_rem_bytes);
// Repack the entire buffer
repack_row_q4x4x2((uint8_t *) buf_rp, (const block_q4_0 *) buf_pd, t->ne[0]);
// Write only the corresponding remaining bytes to the destination tensor.
memcpy(dst, buf_rp, n_rem_bytes);
}
ggml_aligned_free(buf_pd, row_size_pd); ggml_aligned_free(buf_pd, row_size_pd);
ggml_aligned_free(buf_rp, row_size_rp); ggml_aligned_free(buf_rp, row_size_rp);
} }
@@ -708,6 +737,14 @@ static void repack_q4x4x2_q4_0(void * data, const ggml_tensor * t, size_t size)
size_t row_size_pd = ggml_row_size(t->type, hex_round_up(t->ne[0], QK_Q4_0x4x2)); // extra elements for the pad size_t row_size_pd = ggml_row_size(t->type, hex_round_up(t->ne[0], QK_Q4_0x4x2)); // extra elements for the pad
size_t row_size_rp = row_size * 2; // extra space for tmp pad (if any) size_t row_size_rp = row_size * 2; // extra space for tmp pad (if any)
// Ensure we don't try to copy more data than the tensor actually contains.
const size_t total_tensor_size = (size_t)nrows * row_size;
const size_t n_bytes_to_copy = size < total_tensor_size ? size : total_tensor_size;
// Calculate how many full rows and how many remaining bytes we need to process.
const int64_t n_full_rows = n_bytes_to_copy / row_size;
const size_t n_rem_bytes = n_bytes_to_copy % row_size;
void * buf_pd = ggml_aligned_malloc(row_size_pd); void * buf_pd = ggml_aligned_malloc(row_size_pd);
GGML_ASSERT(buf_pd != NULL); GGML_ASSERT(buf_pd != NULL);
@@ -719,7 +756,8 @@ static void repack_q4x4x2_q4_0(void * data, const ggml_tensor * t, size_t size)
memset(buf_pd, 0, row_size_pd); // clear-out padded buffer to make sure the tail is all zeros memset(buf_pd, 0, row_size_pd); // clear-out padded buffer to make sure the tail is all zeros
for (int64_t i = 0; i < nrows; i++) { // 1. Process all the full rows
for (int64_t i = 0; i < n_full_rows; i++) {
const uint8_t * src = (const uint8_t *) t->data + (i * row_size); const uint8_t * src = (const uint8_t *) t->data + (i * row_size);
uint8_t * dst = (uint8_t *) data + (i * row_size); uint8_t * dst = (uint8_t *) data + (i * row_size);
@@ -728,6 +766,20 @@ static void repack_q4x4x2_q4_0(void * data, const ggml_tensor * t, size_t size)
memcpy(dst, buf_rp, row_size); memcpy(dst, buf_rp, row_size);
} }
// 2. Process the final, potentially partial, row
if (n_rem_bytes > 0) {
const int64_t i = n_full_rows;
const uint8_t * src = (const uint8_t *) t->data + (i * row_size);
uint8_t * dst = (uint8_t *) data + (i * row_size);
// We still need to read and unpack the entire source row because quantization is block-based.
memcpy(buf_pd, src, row_size);
unpack_row_q4x4x2((block_q4_0 *) buf_rp, (const uint8_t *) buf_pd, t->ne[0]);
// But we only copy the remaining number of bytes to the destination.
memcpy(dst, buf_rp, n_rem_bytes);
}
ggml_aligned_free(buf_pd, row_size_pd); ggml_aligned_free(buf_pd, row_size_pd);
ggml_aligned_free(buf_rp, row_size_rp); ggml_aligned_free(buf_rp, row_size_rp);
} }
@@ -950,6 +1002,15 @@ static void repack_q8_0_q8x4x2(ggml_tensor * t, const void * data, size_t size)
size_t row_size_pd = ggml_row_size(t->type, hex_round_up(t->ne[0], QK_Q8_0x4x2)); // extra elements for the pad size_t row_size_pd = ggml_row_size(t->type, hex_round_up(t->ne[0], QK_Q8_0x4x2)); // extra elements for the pad
size_t row_size_rp = row_size * 2; // extra space for tmp pad (if any) size_t row_size_rp = row_size * 2; // extra space for tmp pad (if any)
// Ensure we don't try to read more data than is available in the source buffer 'data'
// or write more than the tensor can hold.
const size_t total_tensor_size = (size_t)nrows * row_size;
const size_t n_bytes_to_copy = size < total_tensor_size ? size : total_tensor_size;
// Calculate how many full rows and how many remaining bytes we need to process.
const int64_t n_full_rows = n_bytes_to_copy / row_size;
const size_t n_rem_bytes = n_bytes_to_copy % row_size;
void * buf_pd = ggml_aligned_malloc(row_size_pd); void * buf_pd = ggml_aligned_malloc(row_size_pd);
GGML_ASSERT(buf_pd != NULL); GGML_ASSERT(buf_pd != NULL);
@@ -961,7 +1022,8 @@ static void repack_q8_0_q8x4x2(ggml_tensor * t, const void * data, size_t size)
init_row_q8x4x2((block_q8_0 *) buf_pd, t->ne[0]); // init padded buffer to make sure the tail is all zeros init_row_q8x4x2((block_q8_0 *) buf_pd, t->ne[0]); // init padded buffer to make sure the tail is all zeros
for (int64_t i = 0; i < nrows; i++) { // 1. Process all the full rows
for (int64_t i = 0; i < n_full_rows; i++) {
const uint8_t * src = (const uint8_t *) data + (i * row_size); const uint8_t * src = (const uint8_t *) data + (i * row_size);
uint8_t * dst = (uint8_t *) t->data + (i * row_size); uint8_t * dst = (uint8_t *) t->data + (i * row_size);
@@ -970,6 +1032,25 @@ static void repack_q8_0_q8x4x2(ggml_tensor * t, const void * data, size_t size)
memcpy(dst, buf_rp, row_size); memcpy(dst, buf_rp, row_size);
} }
// 2. Process the final, potentially partial, row
if (n_rem_bytes > 0) {
const int64_t i = n_full_rows;
const uint8_t * src = (const uint8_t *) data + (i * row_size);
uint8_t * dst = (uint8_t *) t->data + (i * row_size);
// re-init the row because we are potentially copying a partial row
init_row_q8x4x2((block_q8_0 *) buf_pd, t->ne[0]);
// Copy only the remaining bytes from the source.
memcpy(buf_pd, src, n_rem_bytes);
// Repack the entire buffer
repack_row_q8x4x2((uint8_t *) buf_rp, (const block_q8_0 *) buf_pd, t->ne[0]);
// Write only the corresponding remaining bytes to the destination tensor.
memcpy(dst, buf_rp, n_rem_bytes);
}
ggml_aligned_free(buf_pd, row_size_pd); ggml_aligned_free(buf_pd, row_size_pd);
ggml_aligned_free(buf_rp, row_size_rp); ggml_aligned_free(buf_rp, row_size_rp);
} }
@@ -982,6 +1063,14 @@ static void repack_q8x4x2_q8_0(void * data, const ggml_tensor * t, size_t size)
size_t row_size_pd = ggml_row_size(t->type, hex_round_up(t->ne[0], QK_Q8_0x4x2)); // extra elements for the pad size_t row_size_pd = ggml_row_size(t->type, hex_round_up(t->ne[0], QK_Q8_0x4x2)); // extra elements for the pad
size_t row_size_rp = row_size * 2; // extra space for tmp pad (if any) size_t row_size_rp = row_size * 2; // extra space for tmp pad (if any)
// Ensure we don't try to copy more data than the tensor actually contains.
const size_t total_tensor_size = (size_t)nrows * row_size;
const size_t n_bytes_to_copy = size < total_tensor_size ? size : total_tensor_size;
// Calculate how many full rows and how many remaining bytes we need to process.
const int64_t n_full_rows = n_bytes_to_copy / row_size;
const size_t n_rem_bytes = n_bytes_to_copy % row_size;
void * buf_pd = ggml_aligned_malloc(row_size_pd); void * buf_pd = ggml_aligned_malloc(row_size_pd);
GGML_ASSERT(buf_pd != NULL); GGML_ASSERT(buf_pd != NULL);
@@ -993,7 +1082,8 @@ static void repack_q8x4x2_q8_0(void * data, const ggml_tensor * t, size_t size)
memset(buf_pd, 0, row_size_pd); // clear-out padded buffer to make sure the tail is all zeros memset(buf_pd, 0, row_size_pd); // clear-out padded buffer to make sure the tail is all zeros
for (int64_t i = 0; i < nrows; i++) { // 1. Process all the full rows
for (int64_t i = 0; i < n_full_rows; i++) {
const uint8_t * src = (const uint8_t *) t->data + (i * row_size); const uint8_t * src = (const uint8_t *) t->data + (i * row_size);
uint8_t * dst = (uint8_t *) data + (i * row_size); uint8_t * dst = (uint8_t *) data + (i * row_size);
@@ -1002,6 +1092,20 @@ static void repack_q8x4x2_q8_0(void * data, const ggml_tensor * t, size_t size)
memcpy(dst, buf_rp, row_size); memcpy(dst, buf_rp, row_size);
} }
// 2. Process the final, potentially partial, row
if (n_rem_bytes > 0) {
const int64_t i = n_full_rows;
const uint8_t * src = (const uint8_t *) t->data + (i * row_size);
uint8_t * dst = (uint8_t *) data + (i * row_size);
// We still need to read and unpack the entire source row because quantization is block-based.
memcpy(buf_pd, src, row_size);
unpack_row_q8x4x2((block_q8_0 *) buf_rp, (const uint8_t *) buf_pd, t->ne[0]);
// But we only copy the remaining number of bytes to the destination.
memcpy(dst, buf_rp, n_rem_bytes);
}
ggml_aligned_free(buf_pd, row_size_pd); ggml_aligned_free(buf_pd, row_size_pd);
ggml_aligned_free(buf_rp, row_size_rp); ggml_aligned_free(buf_rp, row_size_rp);
} }
@@ -1249,6 +1353,15 @@ static void repack_mxfp4_mxfp4x4x2(ggml_tensor * t, const void * data, size_t si
size_t row_size_pd = ggml_row_size(t->type, hex_round_up(t->ne[0], QK_MXFP4x4x2)); // extra elements for the pad size_t row_size_pd = ggml_row_size(t->type, hex_round_up(t->ne[0], QK_MXFP4x4x2)); // extra elements for the pad
size_t row_size_rp = row_size * 2; // extra space for tmp pad (if any) size_t row_size_rp = row_size * 2; // extra space for tmp pad (if any)
// Ensure we don't try to read more data than is available in the source buffer 'data'
// or write more than the tensor can hold.
const size_t total_tensor_size = (size_t)nrows * row_size;
const size_t n_bytes_to_copy = size < total_tensor_size ? size : total_tensor_size;
// Calculate how many full rows and how many remaining bytes we need to process.
const int64_t n_full_rows = n_bytes_to_copy / row_size;
const size_t n_rem_bytes = n_bytes_to_copy % row_size;
void * buf_pd = ggml_aligned_malloc(row_size_pd); void * buf_pd = ggml_aligned_malloc(row_size_pd);
GGML_ASSERT(buf_pd != NULL); GGML_ASSERT(buf_pd != NULL);
@@ -1260,7 +1373,8 @@ static void repack_mxfp4_mxfp4x4x2(ggml_tensor * t, const void * data, size_t si
init_row_mxfp4x4x2((block_mxfp4 *) buf_pd, t->ne[0]); // init padded buffer to make sure the tail is all zeros init_row_mxfp4x4x2((block_mxfp4 *) buf_pd, t->ne[0]); // init padded buffer to make sure the tail is all zeros
for (int64_t i = 0; i < nrows; i++) { // 1. Process all the full rows
for (int64_t i = 0; i < n_full_rows; i++) {
const uint8_t * src = (const uint8_t *) data + (i * row_size); const uint8_t * src = (const uint8_t *) data + (i * row_size);
uint8_t * dst = (uint8_t *) t->data + (i * row_size); uint8_t * dst = (uint8_t *) t->data + (i * row_size);
@@ -1269,6 +1383,25 @@ static void repack_mxfp4_mxfp4x4x2(ggml_tensor * t, const void * data, size_t si
memcpy(dst, buf_rp, row_size); memcpy(dst, buf_rp, row_size);
} }
// 2. Process the final, potentially partial, row
if (n_rem_bytes > 0) {
const int64_t i = n_full_rows;
const uint8_t * src = (const uint8_t *) data + (i * row_size);
uint8_t * dst = (uint8_t *) t->data + (i * row_size);
// re-init the row because we are potentially copying a partial row
init_row_mxfp4x4x2((block_mxfp4 *) buf_pd, t->ne[0]);
// Copy only the remaining bytes from the source.
memcpy(buf_pd, src, n_rem_bytes);
// Repack the entire buffer (partial data + zero padding).
repack_row_mxfp4x4x2((uint8_t *) buf_rp, (const block_mxfp4 *) buf_pd, t->ne[0]);
// Write only the corresponding remaining bytes to the destination tensor.
memcpy(dst, buf_rp, n_rem_bytes);
}
ggml_aligned_free(buf_pd, row_size_pd); ggml_aligned_free(buf_pd, row_size_pd);
ggml_aligned_free(buf_rp, row_size_rp); ggml_aligned_free(buf_rp, row_size_rp);
} }
@@ -1281,6 +1414,14 @@ static void repack_mxfp4x4x2_mxfp4(void * data, const ggml_tensor * t, size_t si
size_t row_size_pd = ggml_row_size(t->type, hex_round_up(t->ne[0], QK_MXFP4x4x2)); // extra elements for the pad size_t row_size_pd = ggml_row_size(t->type, hex_round_up(t->ne[0], QK_MXFP4x4x2)); // extra elements for the pad
size_t row_size_rp = row_size * 2; // extra space for tmp pad (if any) size_t row_size_rp = row_size * 2; // extra space for tmp pad (if any)
// Ensure we don't try to copy more data than the tensor actually contains.
const size_t total_tensor_size = (size_t)nrows * row_size;
const size_t n_bytes_to_copy = size < total_tensor_size ? size : total_tensor_size;
// Calculate how many full rows and how many remaining bytes we need to process.
const int64_t n_full_rows = n_bytes_to_copy / row_size;
const size_t n_rem_bytes = n_bytes_to_copy % row_size;
void * buf_pd = ggml_aligned_malloc(row_size_pd); void * buf_pd = ggml_aligned_malloc(row_size_pd);
GGML_ASSERT(buf_pd != NULL); GGML_ASSERT(buf_pd != NULL);
@@ -1292,7 +1433,8 @@ static void repack_mxfp4x4x2_mxfp4(void * data, const ggml_tensor * t, size_t si
memset(buf_pd, 0, row_size_pd); // clear-out padded buffer to make sure the tail is all zeros memset(buf_pd, 0, row_size_pd); // clear-out padded buffer to make sure the tail is all zeros
for (int64_t i = 0; i < nrows; i++) { // 1. Process all the full rows
for (int64_t i = 0; i < n_full_rows; i++) {
const uint8_t * src = (const uint8_t *) t->data + (i * row_size); const uint8_t * src = (const uint8_t *) t->data + (i * row_size);
uint8_t * dst = (uint8_t *) data + (i * row_size); uint8_t * dst = (uint8_t *) data + (i * row_size);
@@ -1301,6 +1443,20 @@ static void repack_mxfp4x4x2_mxfp4(void * data, const ggml_tensor * t, size_t si
memcpy(dst, buf_rp, row_size); memcpy(dst, buf_rp, row_size);
} }
// 2. Process the final, potentially partial, row
if (n_rem_bytes > 0) {
const int64_t i = n_full_rows;
const uint8_t * src = (const uint8_t *) t->data + (i * row_size);
uint8_t * dst = (uint8_t *) data + (i * row_size);
// We still need to read and unpack the entire source row because the format is block-based.
memcpy(buf_pd, src, row_size);
unpack_row_mxfp4x4x2((block_mxfp4 *) buf_rp, (const uint8_t *) buf_pd, t->ne[0]);
// But we only copy the remaining number of bytes to the destination to respect the size limit.
memcpy(dst, buf_rp, n_rem_bytes);
}
ggml_aligned_free(buf_pd, row_size_pd); ggml_aligned_free(buf_pd, row_size_pd);
ggml_aligned_free(buf_rp, row_size_rp); ggml_aligned_free(buf_rp, row_size_rp);
} }
@@ -1319,19 +1475,19 @@ static void ggml_backend_hexagon_buffer_set_tensor(ggml_backend_buffer_t buffer,
switch (tensor->type) { switch (tensor->type) {
case GGML_TYPE_Q4_0: case GGML_TYPE_Q4_0:
GGML_ASSERT(offset == 0); GGML_ASSERT(offset == 0);
GGML_ASSERT(size == ggml_nbytes(tensor)); GGML_ASSERT(offset + size <= ggml_nbytes(tensor));
repack_q4_0_q4x4x2(tensor, data, size); repack_q4_0_q4x4x2(tensor, data, size);
break; break;
case GGML_TYPE_Q8_0: case GGML_TYPE_Q8_0:
GGML_ASSERT(offset == 0); GGML_ASSERT(offset == 0);
GGML_ASSERT(size == ggml_nbytes(tensor)); GGML_ASSERT(offset + size <= ggml_nbytes(tensor));
repack_q8_0_q8x4x2(tensor, data, size); repack_q8_0_q8x4x2(tensor, data, size);
break; break;
case GGML_TYPE_MXFP4: case GGML_TYPE_MXFP4:
GGML_ASSERT(offset == 0); GGML_ASSERT(offset == 0);
GGML_ASSERT(size == ggml_nbytes(tensor)); GGML_ASSERT(offset + size <= ggml_nbytes(tensor));
repack_mxfp4_mxfp4x4x2(tensor, data, size); repack_mxfp4_mxfp4x4x2(tensor, data, size);
break; break;
@@ -1355,19 +1511,19 @@ static void ggml_backend_hexagon_buffer_get_tensor(ggml_backend_buffer_t buffer,
switch (tensor->type) { switch (tensor->type) {
case GGML_TYPE_Q4_0: case GGML_TYPE_Q4_0:
GGML_ASSERT(offset == 0); GGML_ASSERT(offset == 0);
GGML_ASSERT(size == ggml_nbytes(tensor)); GGML_ASSERT(offset + size <= ggml_nbytes(tensor));
repack_q4x4x2_q4_0(data, tensor, size); repack_q4x4x2_q4_0(data, tensor, size);
break; break;
case GGML_TYPE_Q8_0: case GGML_TYPE_Q8_0:
GGML_ASSERT(offset == 0); GGML_ASSERT(offset == 0);
GGML_ASSERT(size == ggml_nbytes(tensor)); GGML_ASSERT(offset + size <= ggml_nbytes(tensor));
repack_q8x4x2_q8_0(data, tensor, size); repack_q8x4x2_q8_0(data, tensor, size);
break; break;
case GGML_TYPE_MXFP4: case GGML_TYPE_MXFP4:
GGML_ASSERT(offset == 0); GGML_ASSERT(offset == 0);
GGML_ASSERT(size == ggml_nbytes(tensor)); GGML_ASSERT(offset + size <= ggml_nbytes(tensor));
repack_mxfp4x4x2_mxfp4(data, tensor, size); repack_mxfp4x4x2_mxfp4(data, tensor, size);
break; break;