1 files changed, 139 insertions, 0 deletions
diff --git a/compiler/moco/import/src/Nodes/Conv2D.cpp b/compiler/moco/import/src/Nodes/Conv2D.cpp
new file mode 100644
index 000000000..e6b98dcd1
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+++ b/compiler/moco/import/src/Nodes/Conv2D.cpp
@@ -0,0 +1,139 @@
+/*
+ * 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 "moco/Import/Nodes/Conv2D.h"
+
+#include <moco/IR/Nodes/TFConv2D.h>
+
+#include <moco/Names.h>
+
+#include "Convert.h"
+
+#include <loco.h>
+#include <loco/IR/PermutingCodec.h>
+#include <stdex/Memory.h>
+#include <plier/tf/Convert.h>
+#include <oops/UserExn.h>
+
+#include <cassert>
+#include <stdexcept>
+#include <algorithm>
+
+namespace
+{
+using namespace moco;
+
+class TFConv2DGraphUpdate final : public GraphUpdate
+{
+public:
+  TFConv2DGraphUpdate(TFConv2D *node, std::vector<TensorName> names) : _node(node), _names(names) {}
+
+  void input(const SymbolTable *) const override;
+
+private:
+  TFConv2D *_node;
+  std::vector<TensorName> _names;
+};
+
+void TFConv2DGraphUpdate::input(const SymbolTable *node_table) const
+{
+  assert(_names.size() == 2);
+
+  auto input_node = node_table->node(_names[0]);
+  auto filter_node = node_table->node(_names[1]);
+  assert(input_node != nullptr);
+  assert(filter_node != nullptr);
+
+  _node->input(input_node);
+  _node->filter(filter_node);
+}
+
+} // namespace
+
+namespace moco
+{
+
+bool Conv2DGraphBuilder::validate(const tensorflow::NodeDef &node) const
+{
+  if (node.input_size() != 2)
+    return false;
+
+  // note: even though "data_format" is not entered when a model is written,
+  //       TF seems to generate "data_format" field into a pb file
+  if (!plier::tf::has_attrs(node, {"T", "data_format", "padding", "strides"}))
+    return false;
+
+  auto data_layout = plier::tf::get_string_attr(node, "data_format");
+  if (!(data_layout == "NHWC" || data_layout == "NCHW"))
+  {
+    throw oops::UserExn("Conv2D Unsupported data_format", node.name());
+  }
+
+  // dilation attribute is not fully supported
+  if (plier::tf::has_attr(node, "dilations"))
+  {
+    // TODO Support non-default dilations
+    auto dilation = plier::tf::get_list_attr(node, "dilations").i();
+    if (!std::all_of(dilation.begin(), dilation.end(), [](std::int64_t dil) { return dil == 1; }))
+      return false;
+  }
+  // Else, dilations are automatically set to default [1,1,1,1] which we assumes now
+
+  return true;
+}
+
+void Conv2DGraphBuilder::build(const tensorflow::NodeDef &node, GraphBuilderContext *context) const
+{
+  assert(context != nullptr);
+
+  loco::Graph *graph = context->graph();
+  SymbolTable *tensor_names = context->tensor_names();
+  UpdateQueue *updates = context->updates();
+
+  // name of loco nodes
+  std::string conv2d_name = node.name();
+
+  auto conv2d = graph->nodes()->create<TFConv2D>();
+  conv2d->name(node.name());
+
+  // read attributes
+  auto data_layout = plier::tf::get_string_attr(node, "data_format");
+  assert(data_layout == "NHWC" || data_layout == "NCHW");
+  conv2d->data_layout(data_layout);
+
+  auto tf_strides = plier::tf::get_list_attr(node, "strides");
+  auto strides = plier::tf::as_int64_list(tf_strides);
+  conv2d->strides(strides);
+
+  auto padding = moco::str_toupper(plier::tf::get_string_attr(node, "padding"));
+  assert(padding == "VALID" || padding == "SAME");
+  conv2d->padding(padding);
+
+  // save the name for graph link updates
+  TensorName output_name(conv2d_name, 0);
+  tensor_names->enroll(output_name, conv2d);
+
+  std::vector<TensorName> input_names;
+  input_names.push_back(TensorName(node.input(0))); // input
+  input_names.push_back(TensorName(node.input(1))); // kernel
+
+  // Record ifm inputs to featureEncode_node
+  auto tfconv2d_update = stdex::make_unique<TFConv2DGraphUpdate>(conv2d, input_names);
+
+  updates->enroll(std::move(tfconv2d_update));
+}
+
+} // namespace moco