1 files changed, 89 insertions, 0 deletions
diff --git a/compiler/enco/frontend/tflite/src/Op/ReLU.cpp b/compiler/enco/frontend/tflite/src/Op/ReLU.cpp
new file mode 100644
index 000000000..4922f4d1f
--- /dev/null
+++ b/compiler/enco/frontend/tflite/src/Op/ReLU.cpp
@@ -0,0 +1,89 @@
+/*
+ * Copyright (c) 2018 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 "ReLU.h"
+
+#include "IRBuilder.h"
+#include "GraphBuilder.h"
+
+#include <morph/tflite.h>
+#include <coco/IR/Module.h>
+#include <coco/IR/FeatureLayouts.h>
+
+#include <nncc/core/ADT/tensor/Shape.h>
+#include <schema_generated.h>
+
+#include <cassert>
+
+using namespace nncc::core::ADT;
+using namespace morph::tflite;
+
+namespace tflimport
+{
+
+void ReLUGraphBuilder::build(const tflite::Operator *op, GraphBuilderContext *context) const
+{
+  assert(context != nullptr); // check if init(..) is called
+
+  coco::Module *m = context->m();
+  coco::Block *blk = context->block();
+  TensorContext &tensor_context = context->tensor();
+  TensorBags &bags = context->bags();
+
+  IndexVector opinputs = as_index_vector(op->inputs());
+  IndexVector opoutputs = as_index_vector(op->outputs());
+
+  // these are fixed in tflite
+  // input index 0 : input feature
+  // output index 0 : output feature
+  assert(opinputs.size() == 1);
+  assert(opoutputs.size() == 1);
+
+  auto ifm_idx = opinputs.at(0);
+  auto ofm_idx = opoutputs.at(0);
+
+  const tensor::Shape &ifm_shape = tensor_context.shape(ifm_idx);
+  const tensor::Shape &ofm_shape = tensor_context.shape(ofm_idx);
+
+  // Create an object for an input feature map
+  coco::FeatureObject *ifm_obj = m->entity()->object()->create<coco::FeatureObject>();
+  coco::Bag *ifm_bag = bags.bag(ifm_idx);
+  ifm_obj->bag(ifm_bag);
+  ifm_obj->layout(coco::FeatureLayouts::BHWC::create(as_feature_shape(ifm_shape)));
+
+  // Create an object for an output feature map
+  coco::FeatureObject *ofm_obj = m->entity()->object()->create<coco::FeatureObject>();
+  coco::Bag *ofm_bag = bags.bag(ofm_idx);
+  ofm_obj->bag(ofm_bag);
+  ofm_obj->layout(coco::FeatureLayouts::BHWC::create(as_feature_shape(ofm_shape)));
+
+  // Create a Load op
+  auto coco_load = op_builder(m).load(ifm_obj).pop();
+
+  // Create a ReLU
+  auto coco_relu = m->entity()->op()->create<coco::ReLU>();
+
+  // Link ops
+  coco_relu->arg(coco_load);
+
+  // Create an Eval instruction
+  auto eval_ins = instr_builder(m).eval(ofm_obj, coco_relu);
+
+  // Append the instruction to the block
+  blk->instr()->append(eval_ins);
+}
+
+} // namespace tflimport