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libavfilter/dnn: support multiple outputs for native mode

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Signed-off-by: Guo, Yejun <yejun.guo@intel.com>
Signed-off-by: Pedro Arthur <bygrandao@gmail.com>
This commit is contained in:
Guo, Yejun 2019-09-20 11:56:10 +08:00 committed by Pedro Arthur
parent 75ca94f3cf
commit 8f13a557ca
2 changed files with 34 additions and 11 deletions
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43
libavfilter/dnn/dnn_backend_native.c
View File

@ -38,6 +38,7 @@ static DNNReturnType set_input_output_native(void *model, DNNInputData *input, c
if (network->layers_num <= 0 || network->operands_num <= 0)
return DNN_ERROR;
/* inputs */
av_assert0(input->dt == DNN_FLOAT);
for (int i = 0; i < network->operands_num; ++i) {
oprd = &network->operands[i];
@ -64,6 +65,28 @@ static DNNReturnType set_input_output_native(void *model, DNNInputData *input, c
return DNN_ERROR;
input->data = oprd->data;
/* outputs */
network->nb_output = 0;
av_freep(&network->output_indexes);
network->output_indexes = av_mallocz_array(nb_output, sizeof(*network->output_indexes));
if (!network->output_indexes)
return DNN_ERROR;
for (uint32_t i = 0; i < nb_output; ++i) {
const char *output_name = output_names[i];
for (int j = 0; j < network->operands_num; ++j) {
oprd = &network->operands[j];
if (strcmp(oprd->name, output_name) == 0) {
network->output_indexes[network->nb_output++] = j;
break;
}
}
}
if (network->nb_output != nb_output)
return DNN_ERROR;
return DNN_SUCCESS;
}
@ -315,6 +338,7 @@ DNNReturnType ff_dnn_execute_model_native(const DNNModel *model, DNNData *output
DepthToSpaceParams *depth_to_space_params;
LayerPadParams *pad_params;
DnnLayerMaximumParams *maximum_params;
uint32_t nb = FFMIN(nb_output, network->nb_output);
if (network->layers_num <= 0 || network->operands_num <= 0)
return DNN_ERROR;
@ -348,17 +372,13 @@ DNNReturnType ff_dnn_execute_model_native(const DNNModel *model, DNNData *output
}
}
// native mode does not support multiple outputs yet
if (nb_output > 1)
return DNN_ERROR;
/**
* as the first step, suppose network->operands[network->operands_num - 1] is the output operand.
*/
outputs[0].data = network->operands[network->operands_num - 1].data;
outputs[0].height = network->operands[network->operands_num - 1].dims[1];
outputs[0].width = network->operands[network->operands_num - 1].dims[2];
outputs[0].channels = network->operands[network->operands_num - 1].dims[3];
for (uint32_t i = 0; i < nb; ++i) {
DnnOperand *oprd = &network->operands[network->output_indexes[i]];
outputs[i].data = oprd->data;
outputs[i].height = oprd->dims[1];
outputs[i].width = oprd->dims[2];
outputs[i].channels = oprd->dims[3];
}
return DNN_SUCCESS;
}
@ -401,6 +421,7 @@ void ff_dnn_free_model_native(DNNModel **model)
av_freep(&network->operands[operand].data);
av_freep(&network->operands);
av_freep(&network->output_indexes);
av_freep(&network);
av_freep(model);
}

2
libavfilter/dnn/dnn_backend_native.h
View File

@ -96,6 +96,8 @@ typedef struct ConvolutionalNetwork{
int32_t layers_num;
DnnOperand *operands;
int32_t operands_num;
int32_t *output_indexes;
uint32_t nb_output;
} ConvolutionalNetwork;
DNNModel *ff_dnn_load_model_native(const char *model_filename);