[Relay][OP]NMS

include/tvm/relay/attrs/vision.h

@@ -40,6 +40,22 @@ struct MultiBoxPriorAttrs : public tvm::AttrsNode<MultiBoxPriorAttrs> {
   }
 };
 
+/*! \brief Attributes used in non_maximum_suppression operators */
+struct NMSAttrs : public tvm::AttrsNode<NMSAttrs>{
+  double overlap_threshold;
+  bool force_suppress;
+  int topk;
+
+  TVM_DECLARE_ATTRS(NMSAttrs, "relay.attrs.NMSAttrs") {
+      TVM_ATTR_FIELD(overlap_threshold).set_default(0.5)
+        .describe("Non-maximum suppression threshold.");
+      TVM_ATTR_FIELD(force_suppress).set_default(false)
+        .describe("Suppress all detections regardless of class_id.");
+      TVM_ATTR_FIELD(topk).set_default(-1)
+        .describe("Keep maximum top k detections before nms, -1 for no limit.");
+  }
+};
+
 }  // namespace relay
 }  // namespace tvm
 #endif  // TVM_RELAY_ATTRS_VISION_H_

python/tvm/relay/op/vision/__init__.py

@@ -3,3 +3,4 @@
 from __future__ import absolute_import as _abs
 
 from .multibox import *
+from .nms import *

python/tvm/relay/op/vision/nms.py

@@ -0,0 +1,36 @@
+"""Non-maximum suppression operations."""
+from __future__ import absolute_import as _abs
+from . import _make
+
+def nms(data,
+        valid_count,
+        overlap_threshold=0.5,
+        force_suppress=False,
+        topk=-1):
+    """Non-maximum suppression operator for object detection.
+
+    Parameters
+    ----------
+    data : relay.Expr
+        3-D tensor with shape [batch_size, num_anchors, 6].
+        The last dimension should be in format of
+        [class_id, score, box_left, box_top, box_right, box_bottom].
+
+    valid_count : relay.Expr
+        1-D tensor for valid number of boxes.
+
+    overlap_threshold : float, optional
+        Non-maximum suppression threshold.
+
+    force_suppress : bool, optional
+        Suppress all detections regardless of class_id.
+
+    topk : int, optional
+        Keep maximum top k detections before nms, -1 for no limit.
+
+    Returns
+    -------
+    out : relay.Expr
+        3-D tensor with shape [batch_size, num_anchors, 6].
+    """
+    return _make.nms(data, valid_count, overlap_threshold, force_suppress, topk)

src/relay/op/vision/multibox_op.cc

@@ -5,7 +5,6 @@
  */
 #include <tvm/relay/op.h>
 #include <tvm/relay/attrs/vision.h>
-#include <vector>
 
 namespace tvm {
 namespace relay {
@@ -66,7 +65,7 @@ RELAY_REGISTER_OP("vision.multibox_prior")
 .set_attrs_type_key("relay.attrs.MultiBoxPriorAttrs")
 .set_num_inputs(1)
 .add_argument("data", "Tensor", "The input tensor.")
-.set_support_level(4)
+.set_support_level(5)
 .add_type_rel("MultiBoxPrior", MultiboxPriorRel);
 
 }  // namespace relay

src/relay/op/vision/nms.cc

@@ -0,0 +1,62 @@
+/*!
+ *  Copyright (c) 2018 by Contributors
+ * \file nms.cc
+ * \brief Non-maximum suppression operators
+ */
+#include <tvm/relay/op.h>
+#include <tvm/relay/attrs/vision.h>
+
+namespace tvm {
+namespace relay {
+
+TVM_REGISTER_NODE_TYPE(NMSAttrs);
+
+bool NMSRel(const Array<Type>& types,
+            int num_inputs,
+            const Attrs& attrs,
+            const TypeReporter& reporter) {
+  CHECK_EQ(types.size(), 3);
+  const auto* data = types[0].as<TensorTypeNode>();
+  const auto* valid_count = types[1].as<TensorTypeNode>();
+  const auto& dshape = data->shape;
+  const auto& vshape = valid_count->shape;
+  CHECK_EQ(dshape.size(), 3) << "Input data should be 3-D.";
+  CHECK_EQ(vshape.size(), 1) << "Input valid count should be 1-D.";
+
+  // assign output type
+  reporter->Assign(types[2], TensorTypeNode::make(dshape, data->dtype));
+  return true;
+}
+
+
+Expr MakeNMS(Expr data,
+             Expr valid_count,
+             double overlap_threshold,
+             bool force_suppress,
+             int topk) {
+  auto attrs = make_node<NMSAttrs>();
+  attrs->overlap_threshold = overlap_threshold;
+  attrs->force_suppress = force_suppress;
+  attrs->topk = topk;
+  static const Op& op = Op::Get("vision.nms");
+  return CallNode::make(op, {data, valid_count}, Attrs(attrs), {});
+}
+
+
+TVM_REGISTER_API("relay.op.vision._make.nms")
+.set_body([](const TVMArgs& args, TVMRetValue* rv) {
+  runtime::detail::unpack_call<Expr, 5>(MakeNMS, args, rv);
+});
+
+
+RELAY_REGISTER_OP("vision.nms")
+.describe(R"doc("Non-maximum suppression."
+)doc" TVM_ADD_FILELINE)
+.set_num_inputs(2)
+.add_argument("data", "Tensor", "Input data.")
+.add_argument("valid_count", "Tensor", "Number of valid anchor boxes.")
+.set_support_level(5)
+.add_type_rel("NMS", NMSRel);
+
+}  // namespace relay
+}  // namespace tvm

tests/python/relay/test_op_level5.py

@@ -18,7 +18,6 @@ def test_resize_infer_type():
     assert zz.checked_type == relay.TensorType((n, c, 100, 200), "int8")
 
 
-
 def test_multibox_prior():
     sizes = (0.3, 1.5, 0.7)
     ratios = (1.3, 2.4)
@@ -44,6 +43,36 @@ def test_multibox_prior():
         (1, h * w, 4), "float32")
 
 
+def test_nms():
+    num_anchors = 60
+
+    overlap_threshold = 0.5
+    force_suppress = True
+    nms_topk = 10
+
+    n = tvm.var("n")
+    x0 = relay.var("x0", relay.ty.TensorType((n, num_anchors, 6), "float32"))
+    x1 = relay.var("x1", relay.ty.TensorType((n,), "int"))
+
+    z = relay.vision.nms(x0, x1, overlap_threshold, force_suppress, nms_topk)
+
+    assert "overlap_threshold" in z.astext()
+    zz = relay.ir_pass.infer_type(z)
+    assert zz.checked_type == relay.ty.TensorType(
+        (n, num_anchors, 6), "float32")
+
+    n = tvm.var("n")
+    x0 = relay.var("x0", relay.ty.TensorType((n, num_anchors, 6), "float32"))
+    x1 = relay.var("x1", relay.ty.TensorType((n,), "int"))
+
+    z = relay.vision.nms(x0, x1)
+
+    zz = relay.ir_pass.infer_type(z)
+    assert zz.checked_type == relay.ty.TensorType(
+        (n, num_anchors, 6), "float32")
+
+
 if __name__ == "__main__":
     test_resize_infer_type()
     test_multibox_prior()
+    test_nms()