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[vivante] Add FP32 output conversion support for Vivante backend #20

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Merged
myungjoo merged 1 commit into from
Nov 12, 2025
Merged

[vivante] Add FP32 output conversion support for Vivante backend #20

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37 changes: 35 additions & 2 deletions src/hal-backend-ml-vivante.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -22,6 +22,8 @@ typedef struct _vivante_handle_s {
gboolean use_json_for_graph;
gboolean has_post_process; /** @deprecated Do not use it. */

gboolean convert_output_fp32; /* Convert all output tensor into fp32 */

GstTensorsInfo inputInfo;
GstTensorsInfo outputInfo;

Expand Down Expand Up @@ -447,6 +449,7 @@ _init_vivante_handle (vivante_handle_s *vivante)

vivante->use_json_for_graph = TRUE;
vivante->has_post_process = FALSE;
vivante->convert_output_fp32 = FALSE;
}

/** @brief Close model and clear internal data in handle. */
Expand Down Expand Up @@ -510,6 +513,7 @@ ml_vivante_configure_instance (void *backend_private, const void *prop_)
{
const GstTensorFilterProperties *prop = (const GstTensorFilterProperties *) prop_;
vivante_handle_s *vivante = (vivante_handle_s *) backend_private;
gboolean _convert_output_fp32 = FALSE;

if (!vivante || !prop) {
g_critical ("[vivante] invalid backend_private");
Expand Down Expand Up @@ -542,6 +546,15 @@ ml_vivante_configure_instance (void *backend_private, const void *prop_)
vivante->use_json_for_graph = TRUE;
vivante->json_path = g_strdup (option[1]);
g_info ("[vivante] Using JSON for graph setup: %s", vivante->json_path);
} else if (g_ascii_strcasecmp (option[0], "OutputType") == 0) {
/* @todo let each output tensor has different outputtype */
gchar *type = option[1];
if (g_ascii_strcasecmp (type, "FLOAT32") == 0 || g_ascii_strcasecmp (type, "FP32") == 0) {
g_info ("[vivante] Convert output to fp32!");
_convert_output_fp32 = TRUE;
} else {
g_warning ("Ignore unsupported output type (%s)", option[1]);
}
} else {
g_warning ("Unknown option (%s).", options[op]);
}
Expand Down Expand Up @@ -600,6 +613,12 @@ ml_vivante_configure_instance (void *backend_private, const void *prop_)
GstTensorInfo *info = gst_tensors_info_get_nth_info (&vivante->outputInfo, i);

info->type = convert_to_tensor_type (o_tensor->attr.dtype.vx_type);

/* Output tensors should be converted into fp32 */
if (_convert_output_fp32 && info->type != _NNS_FLOAT32) {
info->type = _NNS_FLOAT32;
vivante->convert_output_fp32 = TRUE;
}
info->name = g_strdup_printf ("%i", vivante->graph->output.tensors[i]);
for (unsigned int j = 0; j < o_tensor->attr.dim_num; ++j) {
info->dimension[j] = o_tensor->attr.size[j];
Expand Down Expand Up @@ -641,8 +660,22 @@ ml_vivante_invoke (void *backend_private, const void *input_, void *output_)
for (unsigned int i = 0; i < vivante->graph->output.num; i++) {
vsi_nn_tensor_t *out_tensor
= vsi_nn_GetTensor (vivante->graph, vivante->graph->output.tensors[i]);
/* Do not check return value of vsi_nnCopyTensorToBuffer. It returns error in normal case */
vsi_nn_CopyTensorToBuffer (vivante->graph, out_tensor, output[i].data);

/* Convert to fp32 */
if (vivante->convert_output_fp32) {
float *fp32_data = vsi_nn_ConvertTensorToFloat32Data (vivante->graph, out_tensor);
if (fp32_data == NULL) {
g_critical ("[vivante] Failed to convert output tensor to FP32.");
return HAL_ML_ERROR_RUNTIME_ERROR;
}

vsi_size_t num_elements = vsi_nn_GetElementNum (out_tensor);
memcpy (output[i].data, fp32_data, num_elements * sizeof (float));
vsi_nn_Free (fp32_data);
} else {
/* Do not check return value of vsi_nnCopyTensorToBuffer. It returns error in normal case */
vsi_nn_CopyTensorToBuffer (vivante->graph, out_tensor, output[i].data);
}
}

return HAL_ML_ERROR_NONE;
Expand Down
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