[C-Api/Single] remove rank list

We implemented 0-initialized dimension in nnstreamer.
Remove unnecessary rank list from single handle.

Signed-off-by: Jaeyun Jung <jy1210.jung@samsung.com>

diff --git a/c/src/ml-api-inference-single.c b/c/src/ml-api-inference-single.c
index 45b0396..f032501 100644 (file)
--- a/c/src/ml-api-inference-single.c
+++ b/c/src/ml-api-inference-single.c
@@ -134,10 +134,6 @@ typedef struct
   ml_tensors_data_s in_tensors;    /**< input tensor wrapper for processing */
   ml_tensors_data_s out_tensors;   /**< output tensor wrapper for processing */
 
-  /** @todo Use only ml_tensor_info_s dimension instead of saving ranks value */
-  guint input_ranks[ML_TENSOR_SIZE_LIMIT];   /**< the rank list of input tensors, it is calculated based on the dimension string. */
-  guint output_ranks[ML_TENSOR_SIZE_LIMIT];  /**< the rank list of output tensors, it is calculated based on the dimension string. */
-
   GList *destroy_data_list;         /**< data to be freed by filter */
 } ml_single;
 
@@ -458,44 +454,6 @@ __process_output (ml_single * single_h, ml_tensors_data_h output)
 }
 
 /**
- * @brief Initializes the rank information with default value.
- */
-static int
-_ml_tensors_rank_initialize (guint * rank)
-{
-  guint i;
-
-  if (!rank)
-    _ml_error_report_return (ML_ERROR_INVALID_PARAMETER,
-        "The parameter, rank, is NULL. Provide a valid pointer.");
-
-  for (i = 0; i < ML_TENSOR_RANK_LIMIT; i++) {
-    rank[i] = 0;
-  }
-
-  return ML_ERROR_NONE;
-}
-
-/**
- * @brief Sets the rank information with given value.
- */
-static int
-_ml_tensors_set_rank (guint * rank, guint val)
-{
-  guint i;
-
-  if (!rank)
-    _ml_error_report_return (ML_ERROR_INVALID_PARAMETER,
-        "The parameter, rank, is NULL. Provide a valid pointer.");
-
-  for (i = 0; i < ML_TENSOR_RANK_LIMIT; i++) {
-    rank[i] = val;
-  }
-
-  return ML_ERROR_NONE;
-}
-
-/**
  * @brief thread to execute calls to invoke
  *
  * @details The thread behavior is detailed as below:
@@ -865,8 +823,6 @@ ml_single_create_handle (ml_nnfw_type_e nnfw)
 
   _ml_tensors_info_initialize (&single_h->in_info);
   _ml_tensors_info_initialize (&single_h->out_info);
-  _ml_tensors_rank_initialize (single_h->input_ranks);
-  _ml_tensors_rank_initialize (single_h->output_ranks);
   g_mutex_init (&single_h->mutex);
   g_cond_init (&single_h->cond);
 
@@ -1143,18 +1099,14 @@ ml_single_open_custom (ml_single_h * single, ml_single_preset * info)
   /* Setup input and output memory buffers for invoke */
   if (in_tensors_info && in_tensors_info->is_extended) {
     ml_tensors_info_create_extended (&single_h->in_tensors.info);
-    _ml_tensors_set_rank (single_h->input_ranks, ML_TENSOR_RANK_LIMIT);
   } else {
     ml_tensors_info_create (&single_h->in_tensors.info);
-    _ml_tensors_set_rank (single_h->input_ranks, ML_TENSOR_RANK_LIMIT_PREV);
   }
 
   if (out_tensors_info && out_tensors_info->is_extended) {
     ml_tensors_info_create_extended (&single_h->out_tensors.info);
-    _ml_tensors_set_rank (single_h->output_ranks, ML_TENSOR_RANK_LIMIT);
   } else {
     ml_tensors_info_create (&single_h->out_tensors.info);
-    _ml_tensors_set_rank (single_h->output_ranks, ML_TENSOR_RANK_LIMIT_PREV);
   }
 
   __setup_in_out_tensors (single_h);
@@ -1797,33 +1749,8 @@ ml_single_set_property (ml_single_h single, const char *name, const char *value)
       num = gst_tensors_info_parse_types_string (&gst_info, value);
     else if (g_str_has_suffix (name, "name"))
       num = gst_tensors_info_parse_names_string (&gst_info, value);
-    else {
-      guint *rank;
-      gchar **str_dims;
-      guint i;
-
-      if (is_input) {
-        rank = single_h->input_ranks;
-      } else {
-        rank = single_h->output_ranks;
-      }
-
-      str_dims = g_strsplit_set (value, ",.", -1);
-      num = g_strv_length (str_dims);
-
-      if (num > ML_TENSOR_SIZE_LIMIT) {
-        _ml_error_report ("Invalid param, dimensions (%d) max (%d)\n",
-            num, ML_TENSOR_SIZE_LIMIT);
-
-        num = ML_TENSOR_SIZE_LIMIT;
-      }
-
-      for (i = 0; i < num; ++i) {
-        rank[i] = gst_tensor_parse_dimension (str_dims[i],
-            gst_tensors_info_get_nth_info (&gst_info, i)->dimension);
-      }
-      g_strfreev (str_dims);
-    }
+    else
+      num = gst_tensors_info_parse_dimensions_string (&gst_info, value);
 
     if (num == gst_info.num_tensors) {
       ml_tensors_info_h ml_info;
@@ -1885,7 +1812,8 @@ ml_single_get_property (ml_single_h single, const char *name, char **value)
 
   ML_SINGLE_GET_VALID_HANDLE_LOCKED (single_h, single, 0);
 
-  if (g_str_equal (name, "inputtype") || g_str_equal (name, "inputname") ||
+  if (g_str_equal (name, "input") || g_str_equal (name, "output") ||
+      g_str_equal (name, "inputtype") || g_str_equal (name, "inputname") ||
       g_str_equal (name, "inputlayout") || g_str_equal (name, "outputtype") ||
       g_str_equal (name, "outputname") || g_str_equal (name, "outputlayout") ||
       g_str_equal (name, "accelerator") || g_str_equal (name, "custom")) {
@@ -1897,42 +1825,6 @@ ml_single_get_property (ml_single_h single, const char *name, char **value)
     /* boolean */
     g_object_get (G_OBJECT (single_h->filter), name, &bool_value, NULL);
     *value = (bool_value) ? g_strdup ("true") : g_strdup ("false");
-  } else if (g_str_equal (name, "input") || g_str_equal (name, "output")) {
-    gchar *dim_str = NULL;
-    const guint *rank;
-    gboolean is_input = g_str_has_prefix (name, "input");
-    GstTensorsInfo gst_info;
-
-    if (is_input) {
-      rank = single_h->input_ranks;
-    } else {
-      rank = single_h->output_ranks;
-    }
-
-    ml_single_get_gst_info (single_h, is_input, &gst_info);
-
-    if (gst_info.num_tensors > 0) {
-      guint i;
-      GString *dimensions = g_string_new (NULL);
-
-      for (i = 0; i < gst_info.num_tensors; ++i) {
-        dim_str =
-            gst_tensor_get_rank_dimension_string (gst_tensors_info_get_nth_info
-            (&gst_info, i)->dimension, *(rank + i));
-        g_string_append (dimensions, dim_str);
-
-        if (i < gst_info.num_tensors - 1) {
-          g_string_append (dimensions, ",");
-        }
-        g_free (dim_str);
-      }
-      dim_str = g_string_free (dimensions, FALSE);
-    } else {
-      dim_str = g_strdup ("");
-    }
-    *value = dim_str;
-
-    gst_tensors_info_free (&gst_info);
   } else {
     _ml_error_report
         ("The property key, '%s', is not available for get_property and not recognized by the API. It should be one of {input, inputtype, inputname, inputlayout, output, outputtype, outputname, outputlayout, accelerator, custom, is-updatable}.",