1 files changed, 70 insertions, 0 deletions
diff --git a/compiler/ann-ref/src/ops/FullyConnected.cpp b/compiler/ann-ref/src/ops/FullyConnected.cpp
new file mode 100644
index 000000000..d21389e7e
--- /dev/null
+++ b/compiler/ann-ref/src/ops/FullyConnected.cpp
@@ -0,0 +1,70 @@
+/*
+ * Copyright (c) 2018 Samsung Electronics Co., Ltd. All Rights Reserved
+ * Copyright (C) 2017 The Android Open Source Project
+ *
+ * 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 "FullyConnected.h"
+#include "Assert.h"
+
+#if 0
+#include "internal/Matrix.h"
+#include "internal/Fused.h"
+#include "internal/GEMM.h"
+#include "internal/ActivationUtils.h"
+#endif
+
+bool fullyConnectedPrepare(const Shape &input, const Shape &weights, const Shape &bias,
+                           Shape *output)
+{
+  // Check all the parameters of tensor match within themselves and match the
+  // input configuration.
+  ASSERT(input.type == weights.type);
+  if (input.type == OperandType::TENSOR_QUANT8_ASYMM)
+  {
+    ASSERT(bias.type == OperandType::TENSOR_INT32);
+  }
+  else
+  {
+    ASSERT(input.type == bias.type);
+  }
+  ASSERT(getNumberOfDimensions(input) >= 2);
+  uint32_t input_size = getNumberOfElements(input);
+  uint32_t num_units = getSizeOfDimension(weights, 0);
+
+  // modified to resolve Coverity 118949 (Apr 25, 2018) by hyunsik.yoon
+  // Original Code:
+  // uint32_t batch_size = input_size / getSizeOfDimension(weights, 1);
+  //
+  // Coverity Detection: Division by zero
+  //
+  // Code below is modified code
+
+  uint32_t shape_size = getSizeOfDimension(weights, 1);
+  if (shape_size == 0)
+  {
+    return false;
+  }
+
+  uint32_t batch_size = input_size / shape_size;
+
+  ASSERT(getSizeOfDimension(bias, 0) == num_units);
+  ASSERT(getSizeOfDimension(weights, 1) * batch_size == input_size);
+  ASSERT(getNumberOfDimensions(weights) == 2);
+
+  output->type = input.type;
+  output->dimensions = {batch_size, num_units};
+
+  return true;
+}