1 files changed, 90 insertions, 0 deletions
diff --git a/compiler/locomotiv/src/Node/DepthwiseFilterEncode.test.cpp b/compiler/locomotiv/src/Node/DepthwiseFilterEncode.test.cpp
new file mode 100644
index 000000000..db828c08b
--- /dev/null
+++ b/compiler/locomotiv/src/Node/DepthwiseFilterEncode.test.cpp
@@ -0,0 +1,90 @@
+/*
+ * 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 "NodeExecution.h"
+
+#include "locomotiv/NodeData.h"
+#include "NodeDataImpl.h"
+#include "NodeDomain.h"
+
+#include <loco/IR/PermutingCodec.h>
+
+#include <nncc/core/ADT/tensor/Shape.h>
+#include <nncc/core/ADT/tensor/Buffer.h>
+#include <nncc/core/ADT/tensor/LexicalLayout.h>
+#include <nncc/core/ADT/tensor/IndexEnumerator.h>
+
+#include <gtest/gtest.h>
+
+using nncc::core::ADT::tensor::Index;
+using nncc::core::ADT::tensor::Shape;
+using nncc::core::ADT::tensor::LexicalLayout;
+using nncc::core::ADT::tensor::make_buffer;
+using nncc::core::ADT::tensor::IndexEnumerator;
+
+TEST(NodeExecution_DepthwiseFilterEncode, f32)
+{
+  const uint32_t H = 2;
+  const uint32_t W = 3;
+  const uint32_t C = 4;
+  const uint32_t M = 5;
+
+  auto g = loco::make_graph();
+
+  // Pull
+  auto pull = g->nodes()->create<loco::Pull>();
+  pull->dtype(loco::DataType::FLOAT32);
+
+  // Make and assign "MHWC" data to pull node
+  auto pull_buf = make_buffer<float, LexicalLayout>(Shape{M, H, W, C});
+  float f = 1;
+  for (IndexEnumerator e{pull_buf.shape()}; e.valid(); e.advance())
+  {
+    pull_buf.at(e.current()) = f;
+    f += 0.1f; // Doesn't matter what it is
+  }
+  auto pull_data = locomotiv::make_data(pull_buf);
+  locomotiv::annot_data(pull, std::move(pull_data));
+  locomotiv::annot_domain(pull, loco::Domain::Tensor);
+
+  // Encoder to correctly read input tensor as MHWC
+  auto encoder = std::unique_ptr<loco::PermutingEncoder<loco::Domain::DepthwiseFilter>>(
+      new loco::PermutingEncoder<loco::Domain::DepthwiseFilter>);
+  encoder->perm()->axis(loco::DepthwiseFilterAxis::Multiplier) = 0;
+  encoder->perm()->axis(loco::DepthwiseFilterAxis::Height) = 1;
+  encoder->perm()->axis(loco::DepthwiseFilterAxis::Width) = 2;
+  encoder->perm()->axis(loco::DepthwiseFilterAxis::Depth) = 3;
+
+  // DepthwiseFilterEncode
+  auto enc = g->nodes()->create<loco::DepthwiseFilterEncode>();
+  enc->input(pull);
+  enc->encoder(std::move(encoder));
+
+  locomotiv::NodeExecution::get().run(enc);
+
+  auto enc_data = locomotiv::annot_data(enc);
+  ASSERT_NE(enc_data, nullptr);
+  ASSERT_EQ(enc_data->dtype(), loco::DataType::FLOAT32);
+  ASSERT_EQ(*(enc_data->shape()), (Shape{H, W, C, M})); // locomotiv depthwise filter is HWCM
+  auto enc_buf = enc_data->as_f32_bufptr();
+  for (uint32_t h = 0; h < H; ++h)
+    for (uint32_t w = 0; w < W; ++w)
+      for (uint32_t c = 0; c < C; ++c)
+        for (uint32_t m = 0; m < M; ++m)
+          ASSERT_FLOAT_EQ(pull_buf.at(Index{m, h, w, c}), enc_buf->at(Index{h, w, c, m}));
+
+  ASSERT_EQ(locomotiv::annot_domain(enc), loco::Domain::DepthwiseFilter);
+}