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[onert] Simplify IPermuteFunction unittest (Samsung#13834)
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This commit simplifies IPermuteFunction unittest's MockUpLayer usage.

ONE-DCO-1.0-Signed-off-by: Hyeongseok Oh <[email protected]>
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@hseok-oh
hseok-oh authored Aug 29, 2024
1 parent 1eabd3f commit 504d544
Showing 1 changed file with 23 additions and 52 deletions.
75 changes: 23 additions & 52 deletions runtime/onert/core/src/exec/IPermuteFunction.test.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -97,15 +97,19 @@ class MockUpTensor : public ITensor
class MockUpLayer : public IPermuteFunction
{
public:
MockUpLayer(const std::vector<ITensor *> &inputs, const std::vector<ITensor *> &outputs)
MockUpLayer(const std::vector<std::unique_ptr<MockUpTensor>> &inputs,
const std::vector<std::unique_ptr<MockUpTensor>> &outputs)
{
assert(inputs.size() == outputs.size());
_src_tensors = inputs;
_dst_tensors = outputs;
_permute_types.resize(inputs.size());
const uint32_t input_size = inputs.size();
assert(outputs.size() == input_size);
_src_tensors.resize(input_size);
_dst_tensors.resize(input_size);
_permute_types.resize(input_size);

for (uint32_t i = 0; i < inputs.size(); i++)
for (uint32_t i = 0; i < input_size; i++)
{
_src_tensors[i] = inputs[i].get();
_dst_tensors[i] = outputs[i].get();
if (inputs[i]->layout() == outputs[i]->layout())
_permute_types[i] = ir::PermuteType::COPY;
else if (inputs[i]->layout() == ir::Layout::NHWC)
Expand Down Expand Up @@ -143,10 +147,7 @@ TEST(IPermuteFunction, float_to_float)
outputs[i]->setBuffer(output_buffers[i].get());
}

auto mockup_layer = std::make_unique<MockUpLayer>(
std::vector<ITensor *>{inputs[0].get(), inputs[1].get(), inputs[2].get(), inputs[3].get()},
std::vector<ITensor *>{outputs[0].get(), outputs[1].get(), outputs[2].get(),
outputs[3].get()});
auto mockup_layer = std::make_unique<MockUpLayer>(inputs, outputs);
mockup_layer->run();

for (size_t i = 0; i < 4; ++i)
Expand Down Expand Up @@ -185,10 +186,7 @@ TEST(IPermuteFunction, float_to_float)
outputs[i]->setBuffer(output_buffers[i].get());
}

auto mockup_layer = std::make_unique<MockUpLayer>(
std::vector<ITensor *>{inputs[0].get(), inputs[1].get(), inputs[2].get(), inputs[3].get()},
std::vector<ITensor *>{outputs[0].get(), outputs[1].get(), outputs[2].get(),
outputs[3].get()});
auto mockup_layer = std::make_unique<MockUpLayer>(inputs, outputs);
mockup_layer->run();

for (size_t i = 0; i < 4; ++i)
Expand Down Expand Up @@ -230,10 +228,7 @@ TEST(IPermuteFunction, float_to_float)
outputs[i]->setBuffer(output_buffers[i].get());
}

auto mockup_layer = std::make_unique<MockUpLayer>(
std::vector<ITensor *>{inputs[0].get(), inputs[1].get(), inputs[2].get(), inputs[3].get()},
std::vector<ITensor *>{outputs[0].get(), outputs[1].get(), outputs[2].get(),
outputs[3].get()});
auto mockup_layer = std::make_unique<MockUpLayer>(inputs, outputs);
mockup_layer->run();

for (size_t i = 0; i < 4; ++i)
Expand Down Expand Up @@ -278,10 +273,7 @@ TEST(IPermuteFunction, float_to_float)
outputs[i]->setBuffer(output_buffers[i].get());
}

auto mockup_layer = std::make_unique<MockUpLayer>(
std::vector<ITensor *>{inputs[0].get(), inputs[1].get(), inputs[2].get(), inputs[3].get()},
std::vector<ITensor *>{outputs[0].get(), outputs[1].get(), outputs[2].get(),
outputs[3].get()});
auto mockup_layer = std::make_unique<MockUpLayer>(inputs, outputs);
mockup_layer->run();

for (size_t i = 0; i < 4; ++i)
Expand Down Expand Up @@ -346,10 +338,7 @@ TEST(IPermuteFunction, float_to_float)
outputs[i]->setBuffer(output_buffers[i].get());
}

auto mockup_layer = std::make_unique<MockUpLayer>(
std::vector<ITensor *>{inputs[0].get(), inputs[1].get(), inputs[2].get(), inputs[3].get()},
std::vector<ITensor *>{outputs[0].get(), outputs[1].get(), outputs[2].get(),
outputs[3].get()});
auto mockup_layer = std::make_unique<MockUpLayer>(inputs, outputs);
mockup_layer->run();

for (size_t i = 0; i < 4; ++i)
Expand Down Expand Up @@ -417,9 +406,7 @@ TEST(IPermuteFunction, float_to_qasymm8)
outputs[i]->setBuffer(output_buffers[i].get());
}

auto mockup_layer = std::make_unique<MockUpLayer>(
std::vector<ITensor *>{inputs[0].get(), inputs[1].get(), inputs[2].get(), inputs[3].get()},
std::vector<ITensor *>{outputs[0].get(), outputs[1].get(), outputs[2].get(), outputs[3].get()});
auto mockup_layer = std::make_unique<MockUpLayer>(inputs, outputs);
mockup_layer->run();

for (size_t i = 0; i < 4; ++i)
Expand Down Expand Up @@ -470,9 +457,7 @@ TEST(IPermuteFunction, float_to_qsymm8)
outputs[i]->setBuffer(output_buffers[i].get());
}

auto mockup_layer = std::make_unique<MockUpLayer>(
std::vector<ITensor *>{inputs[0].get(), inputs[1].get(), inputs[2].get(), inputs[3].get()},
std::vector<ITensor *>{outputs[0].get(), outputs[1].get(), outputs[2].get(), outputs[3].get()});
auto mockup_layer = std::make_unique<MockUpLayer>(inputs, outputs);
mockup_layer->run();

for (size_t i = 0; i < 4; ++i)
Expand Down Expand Up @@ -523,9 +508,7 @@ TEST(IPermuteFunction, float_to_qsymm16)
outputs[i]->setBuffer(output_buffers[i].get());
}

auto mockup_layer = std::make_unique<MockUpLayer>(
std::vector<ITensor *>{inputs[0].get(), inputs[1].get(), inputs[2].get(), inputs[3].get()},
std::vector<ITensor *>{outputs[0].get(), outputs[1].get(), outputs[2].get(), outputs[3].get()});
auto mockup_layer = std::make_unique<MockUpLayer>(inputs, outputs);
mockup_layer->run();

for (size_t i = 0; i < 4; ++i)
Expand Down Expand Up @@ -585,9 +568,7 @@ TEST(IPermuteFunction, qasymm8_to_float)
outputs[i]->setBuffer(output_buffers[i].get());
}

auto mockup_layer = std::make_unique<MockUpLayer>(
std::vector<ITensor *>{inputs[0].get(), inputs[1].get(), inputs[2].get(), inputs[3].get()},
std::vector<ITensor *>{outputs[0].get(), outputs[1].get(), outputs[2].get(), outputs[3].get()});
auto mockup_layer = std::make_unique<MockUpLayer>(inputs, outputs);
mockup_layer->run();

for (size_t i = 0; i < 4; ++i)
Expand Down Expand Up @@ -647,9 +628,7 @@ TEST(IPermuteFunction, qsymm8_to_float)
outputs[i]->setBuffer(output_buffers[i].get());
}

auto mockup_layer = std::make_unique<MockUpLayer>(
std::vector<ITensor *>{inputs[0].get(), inputs[1].get(), inputs[2].get(), inputs[3].get()},
std::vector<ITensor *>{outputs[0].get(), outputs[1].get(), outputs[2].get(), outputs[3].get()});
auto mockup_layer = std::make_unique<MockUpLayer>(inputs, outputs);
mockup_layer->run();

for (size_t i = 0; i < 4; ++i)
Expand Down Expand Up @@ -709,9 +688,7 @@ TEST(IPermuteFunction, qsymm16_to_float)
outputs[i]->setBuffer(output_buffers[i].get());
}

auto mockup_layer = std::make_unique<MockUpLayer>(
std::vector<ITensor *>{inputs[0].get(), inputs[1].get(), inputs[2].get(), inputs[3].get()},
std::vector<ITensor *>{outputs[0].get(), outputs[1].get(), outputs[2].get(), outputs[3].get()});
auto mockup_layer = std::make_unique<MockUpLayer>(inputs, outputs);
mockup_layer->run();

for (size_t i = 0; i < 4; ++i)
Expand Down Expand Up @@ -782,10 +759,7 @@ TEST(IPermuteFunction, float_qasymm8_layout)
outputs[i]->setBuffer(output_buffers[i].get());
}

auto mockup_layer = std::make_unique<MockUpLayer>(
std::vector<ITensor *>{inputs[0].get(), inputs[1].get(), inputs[2].get(), inputs[3].get()},
std::vector<ITensor *>{outputs[0].get(), outputs[1].get(), outputs[2].get(),
outputs[3].get()});
auto mockup_layer = std::make_unique<MockUpLayer>(inputs, outputs);
mockup_layer->run();

for (size_t i = 0; i < 4; ++i)
Expand Down Expand Up @@ -880,10 +854,7 @@ TEST(IPermuteFunction, float_qasymm8_layout)
outputs[i]->setBuffer(output_buffers[i].get());
}

auto mockup_layer = std::make_unique<MockUpLayer>(
std::vector<ITensor *>{inputs[0].get(), inputs[1].get(), inputs[2].get(), inputs[3].get()},
std::vector<ITensor *>{outputs[0].get(), outputs[1].get(), outputs[2].get(),
outputs[3].get()});
auto mockup_layer = std::make_unique<MockUpLayer>(inputs, outputs);
mockup_layer->run();

for (size_t i = 0; i < 4; ++i)
Expand Down

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