[Service] Remove deprecated header file

Since ml-api-service-internal.h is deprecated, remove the file.

Signed-off-by: gichan2-jang <gichan2.jang@samsung.com>

diff --git a/c/include/ml-api-service-internal.h b/c/include/ml-api-service-internal.h
deleted file mode 100644 (file)
index 0d3cb81..0000000
--- a/c/include/ml-api-service-internal.h
+++ /dev/null
@@ -1,200 +0,0 @@
-/* SPDX-License-Identifier: Apache-2.0 */
-/**
- * NNStreamer / Tizen Machine-Learning "Service API" Header for OS packages.
- * Copyright (C) 2021 MyungJoo Ham <myungjoo.ham@samsung.com>
- */
-/**
- * @file    ml-api-service-internal.h
- * @date    03 Nov 2021
- * @brief   ML-API Internal Platform Service Header
- * @see     https://github.com/nnstreamer/api
- * @author  MyungJoo Ham <myungjoo.ham@samsung.com>
- * @bug     No known bugs except for NYI items
- *
- * @details
- *      This provides interfaces of ML Service APIs for
- *    platform packages (with "root" or "OS" privileges).
- *      Application developers should use ml-api-service.h
- *    instead.
- *      However, whether to mandate this or not can be decided by
- *    vendors. For Tizen, this is mandated; thus, .rpm packages
- *    may use internal headers and .tpk packages cannot use
- *    internal headers.
- */
-#ifndef __ML_API_SERVICE_INTERNAL_H__
-#define __ML_API_SERVICE_INTERNAL_H__
-
-#include "ml-api-service.h"
-
-#ifdef __cplusplus
-extern "C" {
-#endif /* __cplusplus */
-
-/***************************************************
- * Phase 1 APIs: WIP
- ***************************************************/
-
-/**
- * @brief TBU
- */
-typedef enum {
-  ML_SERV_MODEL_INSTNACE = 0,
-  ML_SERV_MODEL_FUNC,
-  ML_SERV_MODEL_SERIES,
-
-  ML_SERV_MODEL_MAX,
-} ml_service_model_t;
-/**
- * @brief TBU
- */
-typedef struct {
-  ml_service_model_t type;
-  union {
-    struct {
-      char *model; /**< [Mandatory] Ususally, this is the path to model file or directory. Sometimes, this can be a "name" of mechanism supplied by a subplugin */
-      ml_tensors_info_h input_info; /**< [Optional] Supply the initial input dimension if the model has flexible input dimension. Otherwise, you may set it NULL. */
-      ml_tensors_info_h output_info; /**< [Optional] Supply the initial output dimension if the model has flexible output dimension. Otherwise, you may set it NULL. */
-      ml_nnfw_type_e nnfw; /**< [Mandatory] The neural network framework used to open the given model */
-      ml_nnfw_hw_e hw; /**< [Mandatory] The hardware to be used for the inference. Users may override by not using "ANY" with ml_single_open or tensor_filter's option. */
-    } instance; /* instance */
-    struct {
-      ml_custom_easy_invoke_cb func; /**< [Mandatory] The function to be registered */
-      void *user_data; /**< [Optional] Additional information fed to the func in run-time */
-      ml_tensors_info_h input_info; /**< [Mandatory] the input dimension */
-      ml_tensors_info_h output_info; /**< [Mandatory] the output dimension */
-    } func; /* func */
-    struct {
-      const char **names; /**< [Mandatory] The names of models in the series. Terminated by NULL */
-      ml_tensors_info_h input_info; /**< [Mandatory] the input dimension */
-      ml_tensors_info_h output_info; /**< [Mandatory] the output dimension */
-    } series; /* serires */
-  };
-} ml_service_model_description;
-
-/**
- * @brief TBU
- * @detail
- *    You may handle the given pipe as if it's fetched by ml_pipeline_construct().
- */
-int ml_service_pipeline_construct (const char *name, ml_pipeline_state_cb cb, void *user_data, ml_pipeline_h *pipe);
-
-/**
- * @brief Add a model for single API and tensor-filter in a pipeline.
- * @detail Usage Example
- *
- * Service App or Middleware
- *   ml_service_model_add ("V1", desc1);
- *   ml_service_model_add ("V2", desc2);
- *   ml_service_model_add ("V3", desc3);
- *   ml_service_model_description descS1 = { .type = ML_SERV_MODEL_SERIES, .series = { .num_models=3, .names = { "V1", "V2", "V3", NULL }, .input_info = in, .output_info = out } };
- *   ml_service_model_add ("SERIES1", descS1);
- *
- * App
- *   ml_single_open(&handle, "V1", NULL, NULL, ML_NNFW_TYPE_SERVICE, ML_NNFW_HW_ANY);
- *   ml_single_invoke(handle, input, &output);
- *   ...
- *   ml_single_open(&handle2, "SERIES1", in, out, ML_SERV_MODEL_SERIES, ML_NNFW_HW_ANY);
- *   ml_single_invoke(handle, input, &output); // output = model_v3 ( model_v2 ( model_v1 ( input ) ) );
- */
-int ml_service_model_add (const char *name, const ml_service_model_description * desc);
-
-
-/***************************************************
- * Phase 2 APIs: NYI
- *
- * Mode 1.
- * Register a pipeline, a model, or a series of models
- * as an AI service as a pair of tensor-query-server-*.
- *
- * Mode 2.
- * Register a pipeline, a model, or a series of models
- * as an AI service, streaming out with mqtt-sink.
- ***************************************************/
-typedef void *ml_service_server_h;
-
-/** @brief TBU */
-int ml_service_server_getstate (ml_service_server_h h, ml_pipeline_state_e *state);
-/** @brief TBU */
-int ml_service_server_getdesc (ml_service_server_h h, char ** desc);
-/** @brief TBU */
-int ml_service_server_start (ml_service_server_h h);
-/** @brief TBU */
-int ml_service_server_stop (ml_service_server_h h);
-/** @brief TBU */
-int ml_service_server_close (ml_service_server_h h);
-
-/**
- * @brief TBU / Query Server AI Service
- * @detail
- *   Rule 1. The pipeline should not have appsink, tensor_sink, appsrc or any other app-thread dependencies.
- *   Rule 2. Add "#INPUT#" and "#OUTPUT#" elements where input/output streams exist.
- *     E.g., " #INPUT# ! ... ! tensor-filter ... ! ... ! #OUTPUT# ".
- *   Rule 3. There should be exactly one pair of #INPUT# and #OUTPUT#.
- *   Rule 4. Supply input/output metadata with input_info & output_info.
- *   This is the simplist method, but restricted to static tensor streams.
- */
-int ml_service_server_open_queryserver_static_tensors (ml_service_server_h *h, const char *topic_name, const char * desc, const ml_tensors_info_h input_info, const ml_tensors_info_h output_info);
-/**
- * @brief TBU / Query Server AI Service
- * @detail
- *   Rule 1. The pipeline should not have appsink, tensor_sink, appsrc or any other app-thread dependencies.
- *   Rule 2. You may add "#INPUT#" and "#OUTPUT#" elements if you do not know how to use tensor-query-server.
- *     E.g., " #INPUT# ! tensor-filter ... ! ... ! #OUTPUT# ".
- *   Rule 3. There should be exactly one pair of #INPUT# and #OUTPUT#.
- *   Rule 4. Supply input/output metadata with gstcap_in and gstcap_out.
- *   This supports general GStreamer streams and general Tensor streams.
- */
-int ml_service_server_open_queryserver_gstcaps (ml_service_server_h *h, const char *topic_name, const char * desc, const char *gstcap_in, const char *gstcap_out);
-/**
- * @brief TBU / Query Server AI Service
- * @detail
- *   Rule 1. The pipeline should have a single pair of tensor-query-server-{sink / src}.
- *   Rule 2. The pipeline should not have appsink, tensor_sink, appsrc or any other app-thread dependencies.
- *   Rule 3. There should be exactly one pair of #INPUT# and #OUTPUT# if you use them.
- *   Rule 4. Add capsfilter or capssetter after src and before sink.
- *   This is for seasoned gstreamer/nnstreamer users who have some experiences in pipeline writing.
- */
-int ml_service_server_open_queryserver_fulldesc (ml_service_server_h *h, const char *topic_name, const char * desc);
-
-/**
- * @brief TBU / PUB/SUB AI Service
- * @detail
- * use "#OUTPUT#" unless you use fulldesc
- * don't rely on app threads (no appsink, appsrc, tensorsink or so on)
- */
-int ml_service_server_open_publisher_static_tensors (ml_service_server_h *h, const char *topic_name, const char * desc, const ml_tensors_data_h out);
-/** @brief TBU */
-int ml_service_server_open_publisher_gstcaps (ml_service_server_h *h, const char *topic_name, const char * desc, const char *gstcap_out);
-/** @brief TBU */
-int ml_service_server_open_publisher_fulldesc (ml_service_server_h *h, const char *topic_name, const char * desc);
-
-typedef void *ml_service_client_h;
-
-/**
- * @brief TBU / Client-side helpers
- * @detail
- *    Please use a pipeline for more efficient usage. This API is for testing or apps that can afford high-latency
- * @param [out] in Input tensors info. Set null if you don't need this info.
- * @param [out] out Output tensors info. Set null if you don't need this info.
- *    Note that we do not know if in/out is possible for remote clients, yet.
- */
-int ml_service_client_open_query (ml_service_client_h *h, const char *topic_name, ml_tensors_info_h *in, ml_tensors_info_h *out);
-/** @brief TBU */
-int ml_service_client_open_subscriber (ml_service_client_h *h, const char *topic_name, ml_pipeline_sink_cb func, void *user_data);
-
-/** @brief TBU */
-int ml_service_client_query (ml_service_client_h h, const ml_tensors_data_h in, ml_tensors_data_h out);
-
-/** @brief TBU */
-int ml_service_client_close (ml_service_client_h h);
-
-/**
- * @brief TBU
- * @param[in] desc provider_type of desc is not restricted.
- */
-int ml_service_pipeline_description_add_privileged (const ml_service_pipeline_description * desc);
-
-#ifdef __cplusplus
-}
-#endif /* __cplusplus */
-#endif /* __ML_API_SERVICE_H__ */