1 files changed, 84 insertions, 0 deletions
diff --git a/compiler/ann-ref/src/ops/Concatenation.float.cpp b/compiler/ann-ref/src/ops/Concatenation.float.cpp
new file mode 100644
index 000000000..ac32aa0ff
--- /dev/null
+++ b/compiler/ann-ref/src/ops/Concatenation.float.cpp
@@ -0,0 +1,84 @@
+/*
+ * Copyright (c) 2018 Samsung Electronics Co., Ltd. All Rights Reserved
+ * Copyright (C) 2017 The Android Open Source Project
+ * Copyright 2017 The TensorFlow Authors. 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 "Concatenation.float.h"
+
+#include "internal/Array.h"
+#include "internal/Matrix.h"
+#include "internal/Fused.h"
+
+// From optimized_ops.h in TensorFlow Lite
+template <FusedActivationFunctionType Ac, typename Scalar>
+void Concatenation(int concat_dim, const Scalar *const *input_data,
+                   const Dims<4> *const *input_dims, int inputs_count, Scalar *output_data,
+                   const Dims<4> &output_dims)
+{
+  DCHECK_GT(inputs_count, 1);
+  int concat_size = 0;
+  for (int i = 0; i < inputs_count; i++)
+  {
+    for (int j = 0; j < 4; j++)
+    {
+      if (j != concat_dim)
+      {
+        MatchingArraySize(*input_dims[i], j, output_dims, j);
+      }
+    }
+    concat_size += ArraySize(*input_dims[i], concat_dim);
+  }
+  DCHECK_EQ(concat_size, ArraySize(output_dims, concat_dim));
+  DCHECK(IsPackedWithoutStrides(output_dims));
+  // for now we dont have a model with a Concatenation
+  // with fused activation function.
+  DCHECK(Ac == FusedActivationFunctionType::kNone);
+  int outer_size = 1;
+  for (int i = concat_dim + 1; i < 4; i++)
+  {
+    outer_size *= output_dims.sizes[i];
+  }
+  Scalar *output_ptr = output_data;
+  for (int k = 0; k < outer_size; k++)
+  {
+    for (int i = 0; i < inputs_count; ++i)
+    {
+      const int copy_size = input_dims[i]->sizes[concat_dim] * input_dims[i]->strides[concat_dim];
+      memcpy(output_ptr, input_data[i] + k * copy_size, copy_size * sizeof(Scalar));
+      output_ptr += copy_size;
+    }
+  }
+}
+
+bool concatenationFloat32(const std::vector<const float *> &inputDataPtrs,
+                          const std::vector<Shape> &inputShapes, int32_t axis, float *outputData,
+                          const Shape &outputShape)
+{
+  int num_inputs = inputShapes.size();
+  std::vector<Dims<4> *> inputDimsPtr(num_inputs);
+  std::vector<Dims<4>> inputDims(num_inputs);
+  for (int i = 0; i < num_inputs; i++)
+  {
+    inputDims[i] = convertShapeToDims(inputShapes[i]);
+    inputDimsPtr[i] = &inputDims[i];
+  }
+
+  Concatenation<FusedActivationFunctionType::kNone, float>(
+      getNumberOfDimensions(outputShape) - axis - 1, inputDataPtrs.data(), inputDimsPtr.data(),
+      num_inputs, outputData, convertShapeToDims(outputShape));
+
+  return true;
+}