summaryrefslogtreecommitdiff
path: root/tests/nnfw_api/src/one_op_tests/Concat.cc
diff options
context:
space:
mode:
Diffstat (limited to 'tests/nnfw_api/src/one_op_tests/Concat.cc')
-rw-r--r--tests/nnfw_api/src/one_op_tests/Concat.cc244
1 files changed, 0 insertions, 244 deletions
diff --git a/tests/nnfw_api/src/one_op_tests/Concat.cc b/tests/nnfw_api/src/one_op_tests/Concat.cc
deleted file mode 100644
index f4397ba66..000000000
--- a/tests/nnfw_api/src/one_op_tests/Concat.cc
+++ /dev/null
@@ -1,244 +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"
-
-#include <memory>
-
-TEST_F(GenModelTest, OneOp_Concat_ShareSubTensor)
-{
- CircleGen cgen;
- int lhs = cgen.addTensor({{1, 2, 2, 1}, circle::TensorType::TensorType_FLOAT32});
- int rhs = cgen.addTensor({{1, 2, 2, 1}, circle::TensorType::TensorType_FLOAT32});
- int shared_subtensor = cgen.addTensor({{1, 2, 2, 1}, circle::TensorType::TensorType_FLOAT32});
- int concat_out = cgen.addTensor({{1, 2, 2, 2}, circle::TensorType::TensorType_FLOAT32});
- 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 pad_out = cgen.addTensor({{1, 4, 4, 1}, circle::TensorType::TensorType_FLOAT32});
- cgen.addOperatorAdd({{lhs, rhs}, {shared_subtensor}}, circle::ActivationFunctionType_NONE);
- cgen.addOperatorConcatenation({{rhs, shared_subtensor}, {concat_out}}, 3,
- circle::ActivationFunctionType_NONE);
- cgen.addOperatorPad({{shared_subtensor, padding}, {pad_out}});
- cgen.setInputsAndOutputs({lhs, rhs}, {pad_out, concat_out});
-
- _context = std::make_unique<GenModelTestContext>(cgen.finish());
- _context->addTestCase(uniformTCD<float>(
- {{1, 3, 2, 4}, {5, 4, 7, 4}},
- {{0, 0, 0, 0, 0, 6, 7, 0, 0, 9, 8, 0, 0, 0, 0, 0}, {5, 6, 4, 7, 7, 9, 4, 8}}));
- _context->setBackends({"acl_cl", "acl_neon", "cpu"});
-
- SUCCEED();
-}
-
-struct ConcatVariationParam
-{
- TestCaseData tcd;
- circle::TensorType type = circle::TensorType::TensorType_FLOAT32;
- float scale = 0.0f;
- int64_t zero_point = 0;
-};
-
-class ConcatVariation : public GenModelTest,
- public ::testing::WithParamInterface<ConcatVariationParam>
-{
-};
-
-// Input shape: {2, 3} / {2, 3}
-// Output shape: {4, 3}
-INSTANTIATE_TEST_CASE_P(
- GenModelTest, ConcatVariation,
- ::testing::Values(
- // Float
- ConcatVariationParam{uniformTCD<float>({{1, 2, 3, 4, 5, 6}, {7, 8, 9, 10, 11, 12}},
- {{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}})},
- // Uint8
- ConcatVariationParam{uniformTCD<uint8_t>({{1, 2, 3, 4, 5, 6}, {7, 8, 9, 10, 11, 12}},
- {{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}}),
- circle::TensorType::TensorType_UINT8, 1.0f, -2},
- // Int8
- ConcatVariationParam{uniformTCD<int8_t>({{1, 2, 3, 4, 5, 6}, {7, 8, 9, 10, 11, 12}},
- {{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}}),
- circle::TensorType::TensorType_INT8, 1.0f, -2},
- // Int16
- // TODO Enable when nnfw api support int16 type
- // ConcatVariationParam{
- // uniformTCD<int16_t>({{1, 2, 3, 4, 5, 6}, {7, 8, 9, 10, 11, 12}},
- // {{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}}),
- // circle::TensorType::TensorType_INT16, 1.0f, 0},
- // Int32
- ConcatVariationParam{uniformTCD<int32_t>({{1, 2, 3, 4, 5, 6}, {7, 8, 9, 10, 11, 12}},
- {{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}}),
- circle::TensorType::TensorType_INT32},
- // Int64
- ConcatVariationParam{uniformTCD<int64_t>({{1, 2, 3, 4, 5, 6}, {7, 8, 9, 10, 11, 12}},
- {{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}}),
- circle::TensorType::TensorType_INT64}));
-
-TEST_P(ConcatVariation, Test)
-{
- auto &param = GetParam();
-
- CircleGen cgen;
- int input1 = cgen.addTensor({{2, 3}, param.type}, param.scale, param.zero_point);
- int input2 = cgen.addTensor({{2, 3}, param.type}, param.scale, param.zero_point);
- int output = cgen.addTensor({{4, 3}, param.type}, param.scale, param.zero_point);
- cgen.addOperatorConcatenation({{input1, input2}, {output}}, 0,
- circle::ActivationFunctionType_NONE);
- cgen.setInputsAndOutputs({input1, input2}, {output});
-
- _context = std::make_unique<GenModelTestContext>(cgen.finish());
- _context->addTestCase(param.tcd);
- _context->setBackends({"acl_cl", "acl_neon", "cpu"});
-
- SUCCEED();
-}
-
-TEST_F(GenModelTest, OneOp_Concat_Subtensor_4D)
-{
- CircleGen cgen;
- int in1 = cgen.addTensor({{1, 1, 1, 20}, circle::TensorType::TensorType_FLOAT32});
- int in2 = cgen.addTensor({{1, 1, 1, 10}, circle::TensorType::TensorType_FLOAT32});
- std::vector<int32_t> axis_data{3};
- uint32_t axis_buf = cgen.addBuffer(axis_data);
- int axis = cgen.addTensor({{1}, circle::TensorType::TensorType_INT32, axis_buf});
-
- int s_out1 = cgen.addTensor({{1, 1, 1, 5}, circle::TensorType::TensorType_FLOAT32});
- int s_out2 = cgen.addTensor({{1, 1, 1, 5}, circle::TensorType::TensorType_FLOAT32});
- int s_out3 = cgen.addTensor({{1, 1, 1, 5}, circle::TensorType::TensorType_FLOAT32});
- int s_out4 = cgen.addTensor({{1, 1, 1, 5}, circle::TensorType::TensorType_FLOAT32});
-
- int c_out1 = cgen.addTensor({{1, 1, 1, 10}, circle::TensorType::TensorType_FLOAT32});
- int c_out2 = cgen.addTensor({{1, 1, 1, 10}, circle::TensorType::TensorType_FLOAT32});
- int c_out3 = cgen.addTensor({{1, 1, 1, 10}, circle::TensorType::TensorType_FLOAT32});
-
- int a_out1 = cgen.addTensor({{1, 1, 1, 10}, circle::TensorType::TensorType_FLOAT32});
- int a_out2 = cgen.addTensor({{1, 1, 1, 10}, circle::TensorType::TensorType_FLOAT32});
- int a_out3 = cgen.addTensor({{1, 1, 1, 10}, circle::TensorType::TensorType_FLOAT32});
-
- int final_out = cgen.addTensor({{1, 1, 1, 35}, circle::TensorType::TensorType_FLOAT32});
-
- cgen.addOperatorSplit({{axis, in1}, {s_out1, s_out2, s_out3, s_out4}}, 4);
-
- cgen.addOperatorConcatenation({{s_out1, s_out2}, {c_out1}}, 3,
- circle::ActivationFunctionType::ActivationFunctionType_NONE);
- cgen.addOperatorConcatenation({{s_out1, s_out3}, {c_out2}}, 3,
- circle::ActivationFunctionType::ActivationFunctionType_NONE);
- cgen.addOperatorConcatenation({{s_out1, s_out4}, {c_out3}}, 3,
- circle::ActivationFunctionType::ActivationFunctionType_NONE);
-
- cgen.addOperatorAdd({{c_out1, in2}, {a_out1}},
- circle::ActivationFunctionType::ActivationFunctionType_NONE);
- cgen.addOperatorAdd({{c_out2, in2}, {a_out2}},
- circle::ActivationFunctionType::ActivationFunctionType_NONE);
- cgen.addOperatorAdd({{c_out3, in2}, {a_out3}},
- circle::ActivationFunctionType::ActivationFunctionType_NONE);
-
- cgen.addOperatorConcatenation({{s_out1, a_out1, a_out2, a_out3}, {final_out}}, 3,
- circle::ActivationFunctionType::ActivationFunctionType_NONE);
-
- cgen.setInputsAndOutputs({in1, in2}, {s_out1, s_out2, s_out3, s_out4, c_out1, c_out2, c_out3,
- a_out1, a_out2, a_out3, final_out});
-
- _context = std::make_unique<GenModelTestContext>(cgen.finish());
- _context->addTestCase(uniformTCD<float>(
- {
- // inputs
- {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20}, // in1
- {0, 0, 0, 0, 0, 0, 0, 0, 0, 0} // in2
- },
- {
- // outputs
- {1, 2, 3, 4, 5}, // s_out1
- {6, 7, 8, 9, 10}, // s_out2
- {11, 12, 13, 14, 15}, // s_out3
- {16, 17, 18, 19, 20}, // s_out4
- {1, 2, 3, 4, 5, 6, 7, 8, 9, 10}, // c_out1
- {1, 2, 3, 4, 5, 11, 12, 13, 14, 15}, // c_out2
- {1, 2, 3, 4, 5, 16, 17, 18, 19, 20}, // c_out3
- {1, 2, 3, 4, 5, 6, 7, 8, 9, 10}, // a_out1
- {1, 2, 3, 4, 5, 11, 12, 13, 14, 15}, // a_out2
- {1, 2, 3, 4, 5, 16, 17, 18, 19, 20}, // a_out3
- {1, 2, 3, 4, 5, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 1, 2, 3,
- 4, 5, 11, 12, 13, 14, 15, 1, 2, 3, 4, 5, 16, 17, 18, 19, 20} // final_out
- }));
- _context->setBackends({"acl_cl", "acl_neon", "cpu"});
-
- SUCCEED();
-}
-
-TEST_P(ConcatVariation, neg_InvalidAxis)
-{
- auto &param = GetParam();
-
- CircleGen cgen;
- int input1 = cgen.addTensor({{2, 3}, param.type}, param.scale, param.zero_point);
- int input2 = cgen.addTensor({{2, 3}, param.type}, param.scale, param.zero_point);
- int output = cgen.addTensor({{4, 3}, param.type}, param.scale, param.zero_point);
- int axis = 2;
-
- cgen.addOperatorConcatenation({{input1, input2}, {output}}, axis,
- circle::ActivationFunctionType_NONE);
- cgen.setInputsAndOutputs({input1, input2}, {output});
-
- _context = std::make_unique<GenModelTestContext>(cgen.finish());
- _context->setBackends({"cpu"});
- _context->expectFailCompile();
-
- SUCCEED();
-}
-
-TEST_P(ConcatVariation, neg_InvalidRank)
-{
- auto &param = GetParam();
-
- CircleGen cgen;
- int input1 = cgen.addTensor({{2, 3}, param.type}, param.scale, param.zero_point);
- int input2 = cgen.addTensor({{1, 2, 3}, param.type}, param.scale, param.zero_point);
- int output = cgen.addTensor({{1, 4, 3}, param.type}, param.scale, param.zero_point);
- int axis = 0;
-
- cgen.addOperatorConcatenation({{input1, input2}, {output}}, axis,
- circle::ActivationFunctionType_NONE);
- cgen.setInputsAndOutputs({input1, input2}, {output});
-
- _context = std::make_unique<GenModelTestContext>(cgen.finish());
- _context->setBackends({"acl_cl", "acl_neon", "cpu"});
- _context->expectFailCompile();
-
- SUCCEED();
-}
-
-TEST_P(ConcatVariation, neg_InvalidDimension)
-{
- auto &param = GetParam();
-
- CircleGen cgen;
- int input1 = cgen.addTensor({{2, 3}, param.type}, param.scale, param.zero_point);
- int input2 = cgen.addTensor({{3, 2}, param.type}, param.scale, param.zero_point);
- int output = cgen.addTensor({{4, 3}, param.type}, param.scale, param.zero_point);
- int axis = 0;
-
- cgen.addOperatorConcatenation({{input1, input2}, {output}}, axis,
- circle::ActivationFunctionType_NONE);
- cgen.setInputsAndOutputs({input1, input2}, {output});
-
- _context = std::make_unique<GenModelTestContext>(cgen.finish());
- _context->setBackends({"acl_cl", "acl_neon", "cpu"});
- _context->expectFailCompile();
-
- SUCCEED();
-}
generated by cgit v1.2.3 (git 2.25.1) at 2024-08-16 23:23:22 +0000