Skip to content

[CodeClean] handle error case #18

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
jaeyun-jung merged 1 commit into from
Aug 5, 2025
Merged

[CodeClean] handle error case #18

Show file tree
Hide file tree
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
61 changes: 42 additions & 19 deletions src/hal-backend-ml-snpe.cc
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -32,28 +32,20 @@ typedef struct _snpe_handle_s {
std::vector<Snpe_IUserBuffer_Handle_t> user_buffers;
} snpe_handle_s;

static int
ml_snpe_init (void **backend_private)
/** @brief Initialize handle. */
static void
_init_snpe_handle (snpe_handle_s *snpe)
{
snpe_handle_s *snpe = g_new0 (snpe_handle_s, 1);
memset (snpe, 0, sizeof (snpe_handle_s));

gst_tensors_info_init (&snpe->inputInfo);
gst_tensors_info_init (&snpe->outputInfo);

*backend_private = snpe;
return HAL_ML_ERROR_NONE;
}

static int
ml_snpe_deinit (void *backend_private)
/** @brief Close model and clear internal data in handle. */
static void
_clear_snpe_handle (snpe_handle_s *snpe)
{
snpe_handle_s *snpe = (snpe_handle_s *) backend_private;

if (!snpe) {
g_critical ("[snpe backend] ml_snpe_deinit called with invalid backend_private");
return HAL_ML_ERROR_INVALID_PARAMETER;
}

if (snpe->inputMap_h)
Snpe_UserBufferMap_Delete (snpe->inputMap_h);

Expand All @@ -69,13 +61,38 @@ ml_snpe_deinit (void *backend_private)
if (snpe->snpe_h)
Snpe_SNPE_Delete (snpe->snpe_h);

if (snpe->model_path)
g_free (snpe->model_path);
g_free (snpe->model_path);

gst_tensors_info_free (&snpe->inputInfo);
gst_tensors_info_free (&snpe->outputInfo);

_init_snpe_handle (snpe);
}

static int
ml_snpe_init (void **backend_private)
{
snpe_handle_s *snpe = g_new0 (snpe_handle_s, 1);

_init_snpe_handle (snpe);

*backend_private = snpe;
return HAL_ML_ERROR_NONE;
}

static int
ml_snpe_deinit (void *backend_private)
{
snpe_handle_s *snpe = (snpe_handle_s *) backend_private;

if (!snpe) {
g_critical ("[snpe backend] ml_snpe_deinit called with invalid backend_private");
return HAL_ML_ERROR_INVALID_PARAMETER;
}

_clear_snpe_handle (snpe);
g_free (snpe);

return HAL_ML_ERROR_NONE;
}

Expand All @@ -85,11 +102,18 @@ ml_snpe_configure_instance (void *backend_private, const void *prop_)
const GstTensorFilterProperties *prop = (const GstTensorFilterProperties *) prop_;
snpe_handle_s *snpe = (snpe_handle_s *) backend_private;

if (!snpe) {
if (!snpe || !prop) {
g_critical ("[snpe backend] ml_snpe_configure_instance called with invalid backend_private");
return HAL_ML_ERROR_INVALID_PARAMETER;
}

if (snpe->model_path) {
g_critical ("[snpe backend] invalid state, clear old data.");
_clear_snpe_handle (snpe);
}

snpe->model_path = g_strdup (prop->model_files[0]);

Snpe_DlVersion_Handle_t lib_version_h = NULL;
Snpe_RuntimeList_Handle_t runtime_list_h = NULL;
Snpe_DlContainer_Handle_t container_h = NULL;
Expand Down Expand Up @@ -325,7 +349,6 @@ ml_snpe_configure_instance (void *backend_private, const void *prop_)
throw std::invalid_argument (err_msg);
}

snpe->model_path = g_strdup (prop->model_files[0]);
container_h = Snpe_DlContainer_Open (snpe->model_path);
if (!container_h)
throw std::runtime_error (
Expand Down
13 changes: 7 additions & 6 deletions src/hal-backend-ml-util.cc
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -125,15 +125,16 @@ GstTensorInfo * gst_tensors_info_get_nth_info (GstTensorsInfo * info, guint inde
if (index < NNS_TENSOR_MEMORY_MAX)
return &info->info[index];

if (!info->extra) {
info->extra = g_new0 (GstTensorInfo, NNS_TENSOR_SIZE_EXTRA_LIMIT);
if (index < NNS_TENSOR_SIZE_LIMIT) {
if (!info->extra) {
info->extra = g_new0 (GstTensorInfo, NNS_TENSOR_SIZE_EXTRA_LIMIT);

for (i = 0; i < NNS_TENSOR_SIZE_EXTRA_LIMIT; ++i)
gst_tensor_info_init (&info->extra[i]);
}
for (i = 0; i < NNS_TENSOR_SIZE_EXTRA_LIMIT; ++i)
gst_tensor_info_init (&info->extra[i]);
}

if (index < NNS_TENSOR_SIZE_LIMIT)
return &info->extra[index - NNS_TENSOR_MEMORY_MAX];
}

g_critical ("Failed to get the information, invalid index %u (max %d).",
index, NNS_TENSOR_SIZE_LIMIT);
Expand Down
107 changes: 71 additions & 36 deletions src/hal-backend-ml-vivante.cc
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -216,54 +216,61 @@ _helper_parse_tensor_attributes (JsonObject *tensor_obj, vsi_nn_tensor_attr_t *v
static int
_json_create_neural_network (vivante_handle_s *self)
{
g_autofree gchar *json_string = NULL;
g_autoptr (GError) err = NULL;
g_autoptr (JsonParser) parser = NULL;
const guint node_num = 1U; /* single NBG node */
const guint const_tensors_num = 0U; /** @todo support this */

gchar *json_string = NULL;
GError *err = NULL;
JsonParser *parser = NULL;
JsonNode *root_node = NULL;
JsonObject *root_obj = NULL;
JsonArray *input_array = NULL, *output_array = NULL;
guint input_tensors_num = 0, output_tensors_num = 0;
guint normal_tensors_num = 0, virtual_tensors_num = 0;
vsi_nn_node_t *node = NULL;
int ret = HAL_ML_ERROR_RUNTIME_ERROR;
Comment thread
anyj0527 marked this conversation as resolved.

self->ctx = vsi_nn_CreateContext ();
if (!self->ctx) {
g_critical ("[vivante] Failed to create VSI context.");
return HAL_ML_ERROR_RUNTIME_ERROR;
goto cleanup;
}

if (!g_file_get_contents (self->json_path, &json_string, NULL, &err)) {
g_critical ("[vivante] Failed to read JSON file '%s': %s", self->json_path,
err ? err->message : "Unknown error");
return HAL_ML_ERROR_IO_ERROR;
ret = HAL_ML_ERROR_IO_ERROR;
goto cleanup;
}

parser = json_parser_new ();
if (!json_parser_load_from_data (parser, json_string, -1, &err)) {
g_critical ("[vivante] Failed to parse JSON: %s", err ? err->message : "Unknown error");
return HAL_ML_ERROR_INVALID_PARAMETER;
ret = HAL_ML_ERROR_INVALID_PARAMETER;
goto cleanup;
}

root_node = json_parser_get_root (parser);
if (!root_node || !JSON_NODE_HOLDS_OBJECT (root_node)) {
g_critical ("[vivante] JSON root is not a valid object.");
return HAL_ML_ERROR_INVALID_PARAMETER;
ret = HAL_ML_ERROR_INVALID_PARAMETER;
goto cleanup;
}
root_obj = json_node_get_object (root_node);

input_array = json_object_get_array_member (root_obj, "input_tensors");
output_array = json_object_get_array_member (root_obj, "output_tensors");
if (!input_array || !output_array) {
g_critical ("[vivante] JSON must contain 'input_tensors' and 'output_tensors' arrays.");
return HAL_ML_ERROR_INVALID_PARAMETER;
ret = HAL_ML_ERROR_INVALID_PARAMETER;
goto cleanup;
}

input_tensors_num = json_array_get_length (input_array);
output_tensors_num = json_array_get_length (output_array);

const guint node_num = 1U; /* single NBG node */
const guint const_tensors_num = 0U; /** @todo support this */
const guint normal_tensors_num = input_tensors_num + output_tensors_num;
const guint virtual_tensors_num = output_tensors_num;
normal_tensors_num = input_tensors_num + output_tensors_num;
virtual_tensors_num = output_tensors_num;

self->graph = vsi_nn_CreateGraph (self->ctx,
normal_tensors_num + virtual_tensors_num + const_tensors_num, node_num);
Expand Down Expand Up @@ -313,7 +320,7 @@ _json_create_neural_network (vivante_handle_s *self)
}

for (guint i = 0; i < input_tensors_num; ++i) {
g_info ("[vivante] print Input tensor #%u:", self->graph->input.tensors[i]);
g_info ("[vivante] Print input tensor #%u (%u):", i, self->graph->input.tensors[i]);
vsi_nn_tensor_t *tensor
= vsi_nn_GetTensor (self->graph, self->graph->input.tensors[i]);
vsi_nn_PrintTensor (tensor, self->graph->input.tensors[i]);
Expand Down Expand Up @@ -344,7 +351,7 @@ _json_create_neural_network (vivante_handle_s *self)
}

for (guint i = 0; i < output_tensors_num; ++i) {
g_info ("[vivante] print output tensor #%u:", self->graph->output.tensors[i]);
g_info ("[vivante] Print output tensor #%u (%u):", i, self->graph->output.tensors[i]);
vsi_nn_tensor_t *tensor
= vsi_nn_GetTensor (self->graph, self->graph->output.tensors[i]);
vsi_nn_PrintTensor (tensor, self->graph->output.tensors[i]);
Expand All @@ -356,11 +363,16 @@ _json_create_neural_network (vivante_handle_s *self)
goto cleanup;
}

return HAL_ML_ERROR_NONE;
ret = HAL_ML_ERROR_NONE;

cleanup:
_json_release_neural_network (self);
return HAL_ML_ERROR_RUNTIME_ERROR;
if (ret != HAL_ML_ERROR_NONE)
_json_release_neural_network (self);

g_clear_error (&err);
g_clear_pointer (&json_string, g_free);
g_clear_object (&parser);
return ret;
}

/** @brief Releases all resources associated with a JSON-based graph. */
Expand Down Expand Up @@ -424,35 +436,23 @@ _so_create_neural_network (vivante_handle_s *self)
return HAL_ML_ERROR_NONE;
}

/* ===================================================================
* Main HAL Implementation Functions
* ===================================================================
*/
static int
ml_vivante_init (void **backend_private)
/** @brief Initialize handle. */
static void
_init_vivante_handle (vivante_handle_s *vivante)
{
vivante_handle_s *vivante = g_new0 (vivante_handle_s, 1);
memset (vivante, 0, sizeof (vivante_handle_s));

gst_tensors_info_init (&vivante->inputInfo);
gst_tensors_info_init (&vivante->outputInfo);

vivante->use_json_for_graph = TRUE;
vivante->has_post_process = FALSE;

*backend_private = vivante;
return HAL_ML_ERROR_NONE;
}

static int
ml_vivante_deinit (void *backend_private)
/** @brief Close model and clear internal data in handle. */
static void
_clear_vivante_handle (vivante_handle_s *vivante)
{
vivante_handle_s *vivante = (vivante_handle_s *) backend_private;

if (!vivante) {
g_critical ("[vivante] invalid backend_private");
return HAL_ML_ERROR_INVALID_PARAMETER;
}

if (vivante->use_json_for_graph) {
_json_release_neural_network (vivante);
} else {
Expand All @@ -470,6 +470,36 @@ ml_vivante_deinit (void *backend_private)
g_free (vivante->model_path);
g_free (vivante->json_path);
g_free (vivante->so_path);

_init_vivante_handle (vivante);
}

/* ===================================================================
* Main HAL Implementation Functions
* ===================================================================
*/
static int
ml_vivante_init (void **backend_private)
{
vivante_handle_s *vivante = g_new0 (vivante_handle_s, 1);

_init_vivante_handle (vivante);

*backend_private = vivante;
return HAL_ML_ERROR_NONE;
}

static int
ml_vivante_deinit (void *backend_private)
{
vivante_handle_s *vivante = (vivante_handle_s *) backend_private;

if (!vivante) {
g_critical ("[vivante] invalid backend_private");
return HAL_ML_ERROR_INVALID_PARAMETER;
}

_clear_vivante_handle (vivante);
g_free (vivante);

return HAL_ML_ERROR_NONE;
Expand All @@ -486,6 +516,11 @@ ml_vivante_configure_instance (void *backend_private, const void *prop_)
return HAL_ML_ERROR_INVALID_PARAMETER;
}

if (vivante->model_path) {
g_critical ("[vivante] invalid state, clear old data.");
_clear_vivante_handle (vivante);
}

vivante->model_path = g_strdup (prop->model_files[0]);
// Default loading strategy: if more than one model file is given, assume .so loading.
if (prop->num_models > 1) {
Expand Down
Loading