[moco-tf] copy_shapedata with two inputs (#7499)

* [moco-tf] copy_shapedata with two inputs

This will introduce copy_shapedata that can receive two inputs and return shape from broadcast algorithm for binary operation nodes

Signed-off-by: SaeHie Park <saehie.park@samsung.com>

* add note

1 files changed, 58 insertions, 0 deletions

diff --git a/compiler/moco-tf/src/Transforms/FixShapeTransform.cpp b/compiler/moco-tf/src/Transforms/FixShapeTransform.cpp
index 17de7c262..818a7f7da 100644
--- a/compiler/moco-tf/src/Transforms/FixShapeTransform.cpp
+++ b/compiler/moco-tf/src/Transforms/FixShapeTransform.cpp
@@ -285,6 +285,64 @@ bool copy_shapedata(const loco::Node *src, loco::Node *dst)
 }
 
 /**
+ * @note  This will find broadcast shape from two inputs lhs and rhs using
+ *        broadcast_shape() and return that shape to dst
+ */
+bool copy_shapedata(const loco::Node *lhs, const loco::Node *rhs, loco::Node *dst)
+{
+  // if dst already has ShapeInferenceData, skip
+  if (shape_inference_done(dst))
+    return false;
+
+  loco::NodeShape lhs_shape;
+  loco::NodeShape rhs_shape;
+
+  if (loco::shape_known(lhs))
+  {
+    lhs_shape = loco::shape_get(lhs);
+  }
+  else
+  {
+    if (!shape_inference_done(lhs))
+      return false;
+
+    lhs_shape = as_node_shape(lhs->annot<ShapeInferenceData>());
+  }
+
+  if (loco::shape_known(rhs))
+  {
+    rhs_shape = loco::shape_get(rhs);
+  }
+  else
+  {
+    if (!shape_inference_done(rhs))
+      return false;
+
+    rhs_shape = as_node_shape(rhs->annot<ShapeInferenceData>());
+  }
+
+  if (lhs_shape.domain() != loco::Domain::Tensor || rhs_shape.domain() != loco::Domain::Tensor)
+  {
+    throw std::runtime_error("copy_shapedata supports only for Tensor");
+  }
+
+  loco::TensorShape lhs_tensorshape = lhs_shape.as<loco::TensorShape>();
+  loco::TensorShape rhs_tensorshape = rhs_shape.as<loco::TensorShape>();
+  loco::TensorShape sum_tensorshape = broadcast_shape(lhs_tensorshape, rhs_tensorshape);
+
+  loco::NodeShape sum_shape({sum_tensorshape});
+  auto shape_data = make_shape_inference_data(sum_shape);
+  dst->annot(std::move(shape_data));
+
+  LOGGER(l);
+
+  INFO(l) << "copy_shapedata " << lhs_tensorshape << " or " << rhs_tensorshape << " -> "
+          << sum_tensorshape << std::endl;
+
+  return true;
+}
+
+/**
  * @note  While in shape inference, Node maybe Canonical, TF dialect or other dialects
  *        This will provide common loco::NodeShape as shape information
  */