1 files changed, 172 insertions, 0 deletions
diff --git a/tests/nnfw_api/src/one_op_tests/Pad.test.cc b/tests/nnfw_api/src/one_op_tests/Pad.test.cc
new file mode 100644
index 000000000..582bd84bc
--- /dev/null
+++ b/tests/nnfw_api/src/one_op_tests/Pad.test.cc
@@ -0,0 +1,172 @@
+/*
+ * Copyright (c) 2020 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 "GenModelTest.h"
+
+// Input shape: {1, 2, 2, 1}
+// Padding: {0, 0, 1, 1, 1, 1, 0, 0}
+// Output shape: {1, 4, 4, 1}
+struct PadParam
+{
+  TestCaseData tcd;
+  circle::TensorType data_type = circle::TensorType::TensorType_FLOAT32;
+  float scale = 0.0f;
+  int64_t zero_point = 0;
+};
+
+class PadVariation : public GenModelTest, public ::testing::WithParamInterface<PadParam>
+{
+};
+
+// Test with different value type
+INSTANTIATE_TEST_SUITE_P(
+  GenModelTest, PadVariation,
+  ::testing::Values(
+    // float value
+    PadParam{uniformTCD<float>({{1, 2, 3, 4}}, {{0, 0, 0, 0, 0, 1, 2, 0, 0, 3, 4, 0, 0, 0, 0, 0}})},
+    // uint8 value
+    PadParam{
+      uniformTCD<uint8_t>({{1, 2, 3, 4}}, {{8, 8, 8, 8, 8, 1, 2, 8, 8, 3, 4, 8, 8, 8, 8, 8}}),
+      circle::TensorType::TensorType_UINT8, 1.0, 8},
+    // int8 value
+    PadParam{uniformTCD<int8_t>({{-2, -1, 1, 2}},
+                                {{-5, -5, -5, -5, -5, -2, -1, -5, -5, 1, 2, -5, -5, -5, -5, -5}}),
+             circle::TensorType::TensorType_INT8, 1.0, -5}));
+
+TEST_P(PadVariation, Test)
+{
+  auto &param = GetParam();
+
+  CircleGen cgen;
+  int in = cgen.addTensor({{1, 2, 2, 1}, param.data_type}, param.scale, param.zero_point);
+  std::vector<int32_t> padding_data{0, 0, 1, 1, 1, 1, 0, 0};
+  uint32_t padding_buf = cgen.addBuffer(padding_data);
+  int padding = cgen.addTensor({{4, 2}, circle::TensorType::TensorType_INT32, padding_buf});
+  int out = cgen.addTensor({{1, 4, 4, 1}, param.data_type}, param.scale, param.zero_point);
+
+  cgen.addOperatorPad({{in, padding}, {out}});
+  cgen.setInputsAndOutputs({in}, {out});
+  _context = std::make_unique<GenModelTestContext>(cgen.finish());
+  _context->addTestCase(param.tcd);
+  _context->setBackends({"acl_cl", "acl_neon", "cpu"});
+
+  SUCCEED();
+}
+
+TEST_P(PadVariation, neg_InvalidPadRank)
+{
+  auto &param = GetParam();
+
+  CircleGen cgen;
+  int in = cgen.addTensor({{1, 2, 2, 1}, param.data_type}, param.scale, param.zero_point);
+  std::vector<int32_t> padding_data{1, 1, 1, 1};
+  uint32_t padding_buf = cgen.addBuffer(padding_data);
+  int padding = cgen.addTensor({{4}, circle::TensorType::TensorType_INT32, padding_buf});
+  int out = cgen.addTensor({{1, 4, 4, 1}, param.data_type}, param.scale, param.zero_point);
+
+  cgen.addOperatorPad({{in, padding}, {out}});
+  cgen.setInputsAndOutputs({in}, {out});
+
+  _context = std::make_unique<GenModelTestContext>(cgen.finish());
+  _context->setBackends({"acl_cl", "acl_neon", "cpu"});
+  _context->expectFailCompile();
+
+  SUCCEED();
+}
+
+TEST_P(PadVariation, neg_InvalidPadDim0)
+{
+  auto &param = GetParam();
+
+  CircleGen cgen;
+  int in = cgen.addTensor({{1, 2, 2, 1}, param.data_type}, param.scale, param.zero_point);
+  std::vector<int32_t> padding_data{1, 1, 1, 1};
+  uint32_t padding_buf = cgen.addBuffer(padding_data);
+  int padding = cgen.addTensor({{2, 2}, circle::TensorType::TensorType_INT32, padding_buf});
+  int out = cgen.addTensor({{1, 4, 4, 1}, param.data_type}, param.scale, param.zero_point);
+
+  cgen.addOperatorPad({{in, padding}, {out}});
+  cgen.setInputsAndOutputs({in}, {out});
+
+  _context = std::make_unique<GenModelTestContext>(cgen.finish());
+  _context->setBackends({"acl_cl", "acl_neon", "cpu"});
+  _context->expectFailCompile();
+
+  SUCCEED();
+}
+
+TEST_P(PadVariation, neg_InvalidPadDim1)
+{
+  auto &param = GetParam();
+
+  CircleGen cgen;
+  int in = cgen.addTensor({{1, 2, 2, 1}, param.data_type}, param.scale, param.zero_point);
+  std::vector<int32_t> padding_data{1, 1, 1, 1};
+  uint32_t padding_buf = cgen.addBuffer(padding_data);
+  int padding = cgen.addTensor({{4, 1}, circle::TensorType::TensorType_INT32, padding_buf});
+  int out = cgen.addTensor({{1, 4, 4, 1}, param.data_type}, param.scale, param.zero_point);
+
+  cgen.addOperatorPad({{in, padding}, {out}});
+  cgen.setInputsAndOutputs({in}, {out});
+
+  _context = std::make_unique<GenModelTestContext>(cgen.finish());
+  _context->setBackends({"acl_cl", "acl_neon", "cpu"});
+  _context->expectFailCompile();
+
+  SUCCEED();
+}
+
+TEST_P(PadVariation, neg_Type)
+{
+  auto &param = GetParam();
+
+  const circle::TensorType output_type = ((param.data_type == circle::TensorType::TensorType_UINT8)
+                                            ? circle::TensorType::TensorType_INT8
+                                            : circle::TensorType::TensorType_UINT8);
+
+  CircleGen cgen;
+  int in = cgen.addTensor({{1, 2, 2, 1}, param.data_type}, param.scale, param.zero_point);
+  std::vector<int32_t> padding_data{0, 0, 1, 1, 1, 1, 0, 0};
+  uint32_t padding_buf = cgen.addBuffer(padding_data);
+  int padding = cgen.addTensor({{4, 2}, circle::TensorType::TensorType_INT32, padding_buf});
+  int out = cgen.addTensor({{1, 4, 4, 1}, output_type}, 1.0, 0);
+
+  cgen.addOperatorPad({{in, padding}, {out}});
+  cgen.setInputsAndOutputs({in}, {out});
+
+  _context = std::make_unique<GenModelTestContext>(cgen.finish());
+  _context->expectFailModelLoad();
+
+  SUCCEED();
+}
+
+TEST_F(GenModelTest, neg_OneOp_Pad_QuantParam)
+{
+  CircleGen cgen;
+  int in = cgen.addTensor({{1, 2, 2, 1}, circle::TensorType::TensorType_UINT8}, 1.0, 1);
+  std::vector<int32_t> padding_data{0, 0, 1, 1, 1, 1, 0, 0};
+  uint32_t padding_buf = cgen.addBuffer(padding_data);
+  int padding = cgen.addTensor({{4, 2}, circle::TensorType::TensorType_INT32, padding_buf});
+  int out = cgen.addTensor({{1, 4, 4, 1}, circle::TensorType::TensorType_UINT8}, 1.0, 3);
+
+  cgen.addOperatorPad({{in, padding}, {out}});
+  cgen.setInputsAndOutputs({in}, {out});
+
+  _context = std::make_unique<GenModelTestContext>(cgen.finish());
+  _context->expectFailModelLoad();
+
+  SUCCEED();
+}