1 files changed, 0 insertions, 67 deletions
diff --git a/runtime/neurun/sample/minimal/src/minimal.cc b/runtime/neurun/sample/minimal/src/minimal.cc
deleted file mode 100644
index 003c8a323..000000000
--- a/runtime/neurun/sample/minimal/src/minimal.cc
+++ /dev/null
@@ -1,67 +0,0 @@
-/*
- * Copyright (c) 2019 Samsung Electronics Co., Ltd. All Rights Reserved
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- *    http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-#include "nnfw.h"
-#include <vector>
-
-uint64_t num_elems(const nnfw_tensorinfo *ti)
-{
-  uint64_t n = 1;
-  for (uint32_t i = 0; i < ti->rank; ++i)
-  {
-    n *= ti->dims[i];
-  }
-  return n;
-}
-
-int main(const int argc, char **argv)
-{
-  nnfw_session *session = nullptr;
-  nnfw_create_session(&session);
-
-  // Loading nnpackage
-  nnfw_load_model_from_file(session, argv[1]);
-
-  // Use acl_neon backend for CONV_2D and acl_cl for otherwise.
-  // Note that defalut backend is acl_cl
-  nnfw_set_op_backend(session, "CONV_2D", "acl_neon");
-
-  // Compile model
-  nnfw_prepare(session);
-
-  // Prepare input. Here we just allocate dummy input arrays.
-  std::vector<float> input;
-  nnfw_tensorinfo ti;
-  nnfw_input_tensorinfo(session, 0, &ti); // get first input's info
-  uint32_t input_elements = num_elems(&ti);
-  input.resize(input_elements);
-  // TODO: Please add initialization for your input.
-  nnfw_set_input(session, 0, ti.dtype, input.data(), sizeof(float) * input_elements);
-
-  // Prepare output
-  std::vector<float> output;
-  nnfw_output_tensorinfo(session, 0, &ti); // get first output's info
-  uint32_t output_elements = num_elems(&ti);
-  output.resize(output_elements);
-  nnfw_set_output(session, 0, ti.dtype, output.data(), sizeof(float) * output_elements);
-
-  // Do inference
-  nnfw_run(session);
-
-  // TODO: Please print or compare the output value in your way.
-
-  return 0;
-}