1 files changed, 0 insertions, 172 deletions
diff --git a/tests/nnfw_api/src/one_op_tests/Pad.cc b/tests/nnfw_api/src/one_op_tests/Pad.cc
deleted file mode 100644
index c376c1c02..000000000
--- a/tests/nnfw_api/src/one_op_tests/Pad.cc
+++ /dev/null
@@ -1,172 +0,0 @@
-/*
- * 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_CASE_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();
-}