From e62b62015d4a05c3b232dbbffb0399b3d43fd912 Mon Sep 17 00:00:00 2001
From: Chen Xin <jack.chen@verisilicon.com>
Date: Mon, 8 Aug 2022 11:26:12 +0800
Subject: [PATCH] Added conv3d unit test

Signed-off-by: Chen Xin <jack.chen@verisilicon.com>
---
 src/tim/vx/ops/conv3d_test.cc | 57 ++++++++++++++++++++++++++++++++++-
 1 file changed, 56 insertions(+), 1 deletion(-)

diff --git a/src/tim/vx/ops/conv3d_test.cc b/src/tim/vx/ops/conv3d_test.cc
index 53ff47e..c9530cb 100644
--- a/src/tim/vx/ops/conv3d_test.cc
+++ b/src/tim/vx/ops/conv3d_test.cc
@@ -119,7 +119,7 @@ TEST(Conv3d, shape_1_1_2_3_3_float32_simple_cwhdn) {
   auto final_graph = tim::transform::LayoutInference(graph, ctx);
 
   EXPECT_TRUE(final_graph.first->Compile());
-  
+
   final_graph.second[input_tensor]->CopyDataToTensor(input_data.data());
 
   EXPECT_TRUE(final_graph.first->Run());
@@ -133,4 +133,59 @@ TEST(Conv3d, shape_1_1_2_3_3_float32_simple_cwhdn) {
   for (uint32_t idx = 0; idx < golden.size(); idx++) {
       EXPECT_TRUE(std::abs(golden[idx] - output[idx]) < 0.01);
   }
+}
+
+TEST(Conv3d, shape_4_2_2_2_1_float32_simple_whdcn) {
+  auto ctx = tim::vx::Context::Create();
+  auto graph = ctx->CreateGraph();
+
+  tim::vx::ShapeType input_shape({4, 2, 2, 2, 1});   //whdcn
+  tim::vx::ShapeType weight_shape({2, 2, 2, 2, 2});  //whdIcOc
+  tim::vx::ShapeType output_shape(
+      {3, 1, 1, weight_shape[4], input_shape[4]});  //whdcn
+
+  tim::vx::TensorSpec input_spec(tim::vx::DataType::FLOAT32, input_shape,
+                                 tim::vx::TensorAttribute::INPUT);
+  tim::vx::TensorSpec weight_spec(tim::vx::DataType::FLOAT32, weight_shape,
+                                  tim::vx::TensorAttribute::CONSTANT);
+  tim::vx::TensorSpec output_spec(tim::vx::DataType::FLOAT32, output_shape,
+                                  tim::vx::TensorAttribute::OUTPUT);
+
+  std::vector<float> input_data = {
+      0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31};
+
+  std::vector<float> weight_data = {-1, -1, -1, -1, -1, 1, -1, 1, -1, 1,  1,  1, 1, 1,  -1, -1,
+               1,  -1, 1,  1,  1,  1, -1, 1, -1, -1, -1, 1, 1, -1, 1,  -1};
+
+  // whdcn
+  std::vector<float> golden = {26, 24, 22, -8, -6, -4};
+
+  auto input_tensor = graph->CreateTensor(input_spec);
+  auto weight_tensor = graph->CreateTensor(weight_spec, weight_data.data());
+
+  auto output_tensor = graph->CreateTensor(output_spec);
+
+  std::array<int32_t, 3> stride({1, 1, 1});
+  std::array<int32_t, 3> dilation({1, 1, 1});
+
+  auto conv3d = graph->CreateOperation<tim::vx::ops::Conv3d>(
+      tim::vx::PadType::VALID, stride, dilation);
+  (*conv3d)
+      .BindInput(input_tensor)
+      .BindInput(weight_tensor)
+      .BindOutput(output_tensor);
+
+  EXPECT_TRUE(graph->Compile());
+
+  input_tensor->CopyDataToTensor(input_data.data());
+
+  EXPECT_TRUE(graph->Run());
+
+  uint32_t output_size = 1;
+  for (auto i : output_tensor->GetShape()) {
+    output_size *= i;
+  }
+  std::vector<float> output(output_size);
+  EXPECT_TRUE(output_tensor->CopyDataFromTensor(output.data()));
+  EXPECT_EQ(output,golden);
 }
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