SCM make_graph(void)
{
SCM retval;
struct tf_graph_t *self = (struct tf_graph_t *)scm_gc_calloc(sizeof(struct tf_graph_t), "make-graph");
SCM_NEWSMOB(retval, tf_graph_tag, self);
self->graph = TF_NewGraph();
return retval;
}
DNNModel *ff_dnn_load_model_tf(const char *model_filename)
{
DNNModel *model = NULL;
TFModel *tf_model = NULL;
TF_Buffer *graph_def;
TF_ImportGraphDefOptions *graph_opts;
model = av_malloc(sizeof(DNNModel));
if (!model){
return NULL;
}
tf_model = av_malloc(sizeof(TFModel));
if (!tf_model){
av_freep(&model);
return NULL;
}
tf_model->session = NULL;
tf_model->input_tensor = NULL;
tf_model->output_data = NULL;
graph_def = read_graph(model_filename);
if (!graph_def){
av_freep(&tf_model);
av_freep(&model);
return NULL;
}
tf_model->graph = TF_NewGraph();
tf_model->status = TF_NewStatus();
graph_opts = TF_NewImportGraphDefOptions();
TF_GraphImportGraphDef(tf_model->graph, graph_def, graph_opts, tf_model->status);
TF_DeleteImportGraphDefOptions(graph_opts);
TF_DeleteBuffer(graph_def);
if (TF_GetCode(tf_model->status) != TF_OK){
TF_DeleteGraph(tf_model->graph);
TF_DeleteStatus(tf_model->status);
av_freep(&tf_model);
av_freep(&model);
return NULL;
}
model->model = (void *)tf_model;
model->set_input_output = &set_input_output_tf;
return model;
}
static DNNReturnType load_tf_model(TFModel *tf_model, const char *model_filename)
{
TF_Buffer *graph_def;
TF_ImportGraphDefOptions *graph_opts;
graph_def = read_graph(model_filename);
if (!graph_def){
return DNN_ERROR;
}
tf_model->graph = TF_NewGraph();
tf_model->status = TF_NewStatus();
graph_opts = TF_NewImportGraphDefOptions();
TF_GraphImportGraphDef(tf_model->graph, graph_def, graph_opts, tf_model->status);
TF_DeleteImportGraphDefOptions(graph_opts);
TF_DeleteBuffer(graph_def);
if (TF_GetCode(tf_model->status) != TF_OK){
TF_DeleteGraph(tf_model->graph);
TF_DeleteStatus(tf_model->status);
return DNN_ERROR;
}
return DNN_SUCCESS;
}
DNNModel *ff_dnn_load_default_model_tf(DNNDefaultModel model_type)
{
DNNModel *model = NULL;
TFModel *tf_model = NULL;
TF_OperationDescription *op_desc;
TF_Operation *op;
TF_Output input;
static const int64_t input_shape[] = {1, -1, -1, 1};
static const char tanh[] = "Tanh";
static const char sigmoid[] = "Sigmoid";
static const char relu[] = "Relu";
static const float *srcnn_consts[] = {
srcnn_conv1_kernel,
srcnn_conv1_bias,
srcnn_conv2_kernel,
srcnn_conv2_bias,
srcnn_conv3_kernel,
srcnn_conv3_bias
};
static const long int *srcnn_consts_dims[] = {
srcnn_conv1_kernel_dims,
srcnn_conv1_bias_dims,
srcnn_conv2_kernel_dims,
srcnn_conv2_bias_dims,
srcnn_conv3_kernel_dims,
srcnn_conv3_bias_dims
};
static const int srcnn_consts_dims_len[] = {
4,
1,
4,
1,
4,
1
};
static const char *srcnn_activations[] = {
relu,
relu,
relu
};
static const float *espcn_consts[] = {
espcn_conv1_kernel,
espcn_conv1_bias,
espcn_conv2_kernel,
espcn_conv2_bias,
espcn_conv3_kernel,
espcn_conv3_bias
};
static const long int *espcn_consts_dims[] = {
espcn_conv1_kernel_dims,
espcn_conv1_bias_dims,
espcn_conv2_kernel_dims,
espcn_conv2_bias_dims,
espcn_conv3_kernel_dims,
espcn_conv3_bias_dims
};
static const int espcn_consts_dims_len[] = {
4,
1,
4,
1,
4,
1
};
static const char *espcn_activations[] = {
tanh,
tanh,
sigmoid
};
input.index = 0;
model = av_malloc(sizeof(DNNModel));
if (!model){
return NULL;
}
tf_model = av_malloc(sizeof(TFModel));
if (!tf_model){
av_freep(&model);
return NULL;
}
tf_model->session = NULL;
tf_model->input_tensor = NULL;
tf_model->output_data = NULL;
tf_model->graph = TF_NewGraph();
tf_model->status = TF_NewStatus();
#define CLEANUP_ON_ERROR(tf_model, model) { \
TF_DeleteGraph(tf_model->graph); \
TF_DeleteStatus(tf_model->status); \
av_freep(&tf_model); \
av_freep(&model); \
return NULL; \
}
op_desc = TF_NewOperation(tf_model->graph, "Placeholder", "x");
TF_SetAttrType(op_desc, "dtype", TF_FLOAT);
TF_SetAttrShape(op_desc, "shape", input_shape, 4);
op = TF_FinishOperation(op_desc, tf_model->status);
if (TF_GetCode(tf_model->status) != TF_OK){
CLEANUP_ON_ERROR(tf_model, model);
}
switch (model_type){
case DNN_SRCNN:
op = add_pad_op(tf_model, op, 6);
if (!op){
CLEANUP_ON_ERROR(tf_model, model);
}
op = add_conv_layers(tf_model, srcnn_consts,
srcnn_consts_dims, srcnn_consts_dims_len,
srcnn_activations, op, 3);
if (!op){
CLEANUP_ON_ERROR(tf_model, model);
}
break;
case DNN_ESPCN:
op = add_pad_op(tf_model, op, 4);
if (!op){
CLEANUP_ON_ERROR(tf_model, model);
}
op = add_conv_layers(tf_model, espcn_consts,
espcn_consts_dims, espcn_consts_dims_len,
espcn_activations, op, 3);
if (!op){
CLEANUP_ON_ERROR(tf_model, model);
}
op_desc = TF_NewOperation(tf_model->graph, "DepthToSpace", "depth_to_space");
input.oper = op;
TF_AddInput(op_desc, input);
TF_SetAttrType(op_desc, "T", TF_FLOAT);
TF_SetAttrInt(op_desc, "block_size", 2);
op = TF_FinishOperation(op_desc, tf_model->status);
if (TF_GetCode(tf_model->status) != TF_OK){
CLEANUP_ON_ERROR(tf_model, model);
}
break;
default:
CLEANUP_ON_ERROR(tf_model, model);
}
op_desc = TF_NewOperation(tf_model->graph, "Identity", "y");
input.oper = op;
TF_AddInput(op_desc, input);
TF_FinishOperation(op_desc, tf_model->status);
if (TF_GetCode(tf_model->status) != TF_OK){
CLEANUP_ON_ERROR(tf_model, model);
}
model->model = (void *)tf_model;
model->set_input_output = &set_input_output_tf;
return model;
}