[mir2loco] Support DepthwiseConv operation in transformer (#6574)

* Added DepthwiseConv2DOp convertion and test for this

Signed-off-by: Pavel Iliutchenko <p.iliutchenk@samsung.com>

diff --git a/compiler/mir2loco/include/mir2loco.h b/compiler/mir2loco/include/mir2loco.h
index 0ce9671..bb31dcb 100644 (file)
--- a/compiler/mir2loco/include/mir2loco.h
+++ b/compiler/mir2loco/include/mir2loco.h
@@ -30,6 +30,7 @@ public:
   void visit(mir::ops::ConcatOp &op) override;
   void visit(mir::ops::ConstantOp &op) override;
   void visit(mir::ops::Conv2DOp &op) override;
+  void visit(mir::ops::DepthwiseConv2DOp &op) override;
   void visit(mir::ops::InputOp &op) override;
   void visit(mir::ops::MulOp &op) override;
   void visit(mir::ops::OutputOp &op) override;

diff --git a/compiler/mir2loco/src/mir2loco.cpp b/compiler/mir2loco/src/mir2loco.cpp
index 998d668..076b1c3 100644 (file)
--- a/compiler/mir2loco/src/mir2loco.cpp
+++ b/compiler/mir2loco/src/mir2loco.cpp
@@ -20,6 +20,7 @@
 #include "mir/ops/ConcatOp.h"
 #include "mir/ops/ConstantOp.h"
 #include "mir/ops/Conv2DOp.h"
+#include "mir/ops/DepthwiseConv2DOp.h"
 #include "mir/ops/MulOp.h"
 #include "mir/ops/PoolOp.h"
 #include "mir/ops/ReluOp.h"
@@ -112,6 +113,22 @@ loco::FeatureDecode *createNHWCFeatureDecode(loco::Graph *graph)
   return decode_node;
 }
 
+loco::DepthwiseFilterEncode *createHWCMDepthwiseFilterEncode(loco::Graph *graph)
+{
+  auto filter_enc = graph->nodes()->create<loco::DepthwiseFilterEncode>();
+  auto enc = stdex::make_unique<loco::PermutingEncoder<loco::Domain::DepthwiseFilter>>();
+  // mir using filter convention as TF
+  // In TensorFlow, dwconv2d filter is a 4-D tensor of following shape:
+  // [filter_height, filter_width, in_channels, channel_multiplier]
+  enc->perm()->axis(loco::DepthwiseFilterAxis::Height) = 0;
+  enc->perm()->axis(loco::DepthwiseFilterAxis::Width) = 1;
+  enc->perm()->axis(loco::DepthwiseFilterAxis::Depth) = 2;
+  enc->perm()->axis(loco::DepthwiseFilterAxis::Multiplier) = 3;
+
+  filter_enc->encoder(std::move(enc));
+  return filter_enc;
+}
+
 loco::DataType convertDataType(mir::DataType data_type)
 {
   switch (data_type)
@@ -299,6 +316,40 @@ void Transformer::visit(mir::ops::Conv2DOp &op)
   _mir2loco_map.emplace(&op, decode_node);
 }
 
+void Transformer::visit(mir::ops::DepthwiseConv2DOp &op)
+{
+  auto input = op.getInput(0)->getProducer()->getNode();
+  auto kernel = op.getInput(1)->getProducer()->getNode();
+  // Get ConstantOp
+  auto const_node = _mir2loco_map.at(kernel);
+
+  auto filter_enc = createHWCMDepthwiseFilterEncode(_loco_graph.get());
+  // Set filter input
+  filter_enc->input(const_node);
+  // Setting up DepthwiseConv2D
+
+  // FeatureEncode
+  auto feature_enc = createNHWCFeatureEncode(_loco_graph.get());
+  // Set Input
+  auto loco_it = _mir2loco_map.find(input);
+  assert(loco_it != _mir2loco_map.end()); // can't find the input
+  feature_enc->input(loco_it->second);
+  // DepthwiseConv2D
+  auto dw_conv2d_node = _loco_graph->nodes()->create<loco::DepthwiseConv2D>();
+  setupStride(op.getStrides(), dw_conv2d_node->stride());
+  setupPad(op.getPaddingBefore(), op.getPaddingAfter(), dw_conv2d_node->pad());
+  // Set Input
+  dw_conv2d_node->ifm(feature_enc);
+  dw_conv2d_node->ker(filter_enc);
+  // FeatureDecode
+  auto feature_dec = createNHWCFeatureDecode(_loco_graph.get());
+  // Set Input
+  feature_dec->input(dw_conv2d_node);
+  // Not set Shape
+  // Add to map
+  _mir2loco_map.emplace(&op, feature_dec);
+}
+
 void Transformer::visit(mir::ops::InputOp &op)
 {
   auto pull_node = _loco_graph->nodes()->create<loco::Pull>();

diff --git a/compiler/mir2loco/src/mir2loco.test.cpp b/compiler/mir2loco/src/mir2loco.test.cpp
index 7df44d8..3e19098 100644 (file)
--- a/compiler/mir2loco/src/mir2loco.test.cpp
+++ b/compiler/mir2loco/src/mir2loco.test.cpp
@@ -20,6 +20,7 @@
 #include "mir/ops/ConcatOp.h"
 #include "mir/ops/ConstantOp.h"
 #include "mir/ops/Conv2DOp.h"
+#include "mir/ops/DepthwiseConv2DOp.h"
 #include "mir/ops/MulOp.h"
 #include "mir/ops/PoolOp.h"
 #include "mir/ops/ReluOp.h"
@@ -453,3 +454,64 @@ TEST_F(TestTransformer_mir2loco, Mul_Test)
   ASSERT_EQ(pull2_node->dim(2), 7);
   ASSERT_EQ(pull2_node->dim(3), 3);
 }
+
+TEST_F(TestTransformer_mir2loco, DepthwiseConv2D_Test)
+{
+  mir::Graph mir_graph;
+
+  mir::Shape input_shape = mir::Shape({7, 7, 9, 1});
+  auto *input = mir_graph.create<mir::ops::InputOp>("input", input_shape);
+  mir::Shape shape = mir::Shape({2, 3, 1, 1});
+  const float data[] = {5.9, 6.7, 5.32, 54.11231, 43.2444, 3.409};
+  auto mir_tensor = mir::TensorVariant(mir::DataType::FLOAT32, shape, (const void *)data);
+  auto *constant = mir_graph.create<mir::ops::ConstantOp>("constant", mir_tensor);
+  auto *conv = mir_graph.create<mir::ops::DepthwiseConv2DOp>(
+      "dwconv", input->getOutput(0), constant->getOutput(0), mir::Shape{2, 3},
+      std::vector<int32_t>{5, 9}, std::vector<int32_t>{7, 4});
+  auto *output = mir_graph.create<mir::ops::OutputOp>("output", conv->getOutput(0));
+
+  mir2loco::Transformer transformer;
+  auto loco_graph = transformer.transform(&mir_graph);
+
+  // Pull
+  auto inputs = loco_graph->inputs();
+  loco::Pull *pull_node = inputs->at(0)->node();
+  ASSERT_NE(pull_node, nullptr);
+  // FeatureEncode
+  auto pull_uses = loco::succs(pull_node);
+  ASSERT_EQ(pull_uses.size(), 1);
+  loco::FeatureEncode *encode_node = dynamic_cast<loco::FeatureEncode *>(*pull_uses.begin());
+  ASSERT_NE(encode_node, nullptr);
+  ASSERT_EQ(encode_node->input(), pull_node);
+  // DepthwiseConv2D
+  auto encode_uses = loco::succs(encode_node);
+  ASSERT_EQ(encode_uses.size(), 1);
+  loco::DepthwiseConv2D *dw_conv_node = dynamic_cast<loco::DepthwiseConv2D *>(*encode_uses.begin());
+  ASSERT_NE(dw_conv_node, nullptr);
+  loco::DepthwiseFilterEncode *filter_node =
+      dynamic_cast<loco::DepthwiseFilterEncode *>(dw_conv_node->ker());
+  ASSERT_NE(filter_node, nullptr);
+  ASSERT_EQ(dw_conv_node->ifm(), encode_node);
+  // Check params
+  ASSERT_EQ(dw_conv_node->pad()->left(), 5);
+  ASSERT_EQ(dw_conv_node->pad()->top(), 9);
+  ASSERT_EQ(dw_conv_node->pad()->right(), 7);
+  ASSERT_EQ(dw_conv_node->pad()->bottom(), 4);
+  ASSERT_EQ(dw_conv_node->stride()->horizontal(), 2);
+  ASSERT_EQ(dw_conv_node->stride()->vertical(), 3);
+  // ConstGen
+  loco::ConstGen *const_node = dynamic_cast<loco::ConstGen *>(filter_node->input());
+  ASSERT_NE(const_node, nullptr);
+  // FeatureDecode
+  auto dw_conv_uses = loco::succs(dw_conv_node);
+  ASSERT_EQ(dw_conv_uses.size(), 1);
+  loco::FeatureDecode *decode_node = dynamic_cast<loco::FeatureDecode *>(*dw_conv_uses.begin());
+  ASSERT_NE(decode_node, nullptr);
+  ASSERT_EQ(decode_node->input(), dw_conv_node);
+  // Push
+  auto decode_uses = loco::succs(decode_node);
+  ASSERT_EQ(decode_uses.size(), 1);
+  loco::Push *push_node = dynamic_cast<loco::Push *>(*decode_uses.begin());
+  ASSERT_NE(push_node, nullptr);
+  ASSERT_EQ(push_node->from(), decode_node);
+}