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- /**
- * \file dnn/test/rocm/reduce.cpp
- * MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
- *
- * Copyright (c) 2014-2021 Megvii Inc. All rights reserved.
- *
- * Unless required by applicable law or agreed to in writing,
- * software distributed under the License is distributed on an
- * "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- */
- #include "hcc_detail/hcc_defs_prologue.h"
-
- #include "megdnn/oprs.h"
- #include "test/common/checker.h"
- #include "test/common/rng.h"
- #include "test/rocm/fixture.h"
-
- using namespace megdnn;
- using namespace test;
-
- TEST_F(ROCM, REDUCE) {
- using Mode = Reduce::Param::Mode;
- Checker<Reduce> checker(handle_rocm());
- UniformFloatRNG rng(-1.0f, 1.0f);
- checker.set_epsilon(1e-2);
- checker.set_rng(0, &rng);
- checker.set_param({Mode::SUM, 1});
-
- // 1-step
- checker.execs({{2, 64, 32}, {}});
- // 2-step
- checker.execs({{2, 192, 32}, {}});
- // 3-step
- checker.execs({{2, 4333, 32}, {}});
- // single reduce
- checker.execs({{2, 1, 1}, {}});
- checker.execs({{2, 1 + 1, 1}, {}});
- checker.execs({{2, 2048 + 1, 1}, {}});
- checker.execs({{2, 2048 * 2048 + 1, 1}, {}});
- checker.execs({{2, 1 + 1, 31}, {}});
- checker.execs({{2, 16 + 1, 31}, {}});
- checker.execs({{2, 16 * 16 + 1, 31}, {}});
- checker.execs({{2, 16 * 16 * 16 + 1, 31}, {}});
- checker.execs({{2, 16 * 16 * 16 * 16 + 1, 31}, {}});
- checker.execs({{2, 16 * 16 * 16 * 16 * 16 + 1, 31}, {}});
- checker.execs({{3, 256 * 256 + 1, 2}, {}});
- checker.execs({{3, 128 * 128 + 1, 3}, {}});
- checker.execs({{3, 64 * 64 + 1, 7}, {}});
- checker.execs({{3, 32 * 32 + 1, 15}, {}});
- checker.execs({{3, 512, 500}, {}});
- // very large reduce
- checker.execs({{1, 4194304, 1}, {}});
-
- auto check = [&](Reduce::Mode mode, DType src_dtype, DType dst_dtype,
- Reduce::DataType data_type) {
- for (int32_t axis : {0, 1, 2, 3}) {
- if (data_type == Reduce::DataType::DEFAULT &&
- DNN_FLOAT16_SELECT(src_dtype == dtype::Float16(), false)) {
- checker.set_epsilon(1e-2);
- } else {
- checker.set_epsilon(1e-3);
- }
- Reduce::Param param{mode, axis, data_type};
- auto dst_shape = TensorShape{2, 3, 100, 5};
- dst_shape[axis] = 1;
- checker.set_dtype(0, src_dtype)
- .set_dtype(1, dst_dtype)
- .set_param(param)
- .execs({{2, 3, 100, 5}, dst_shape});
- }
- };
- for (auto mode : {Mode::SUM, Mode::MEAN, Mode::SUM_SQR, Mode::PRODUCT,
- Mode::MIN, Mode::MAX}) {
- for (auto dtype : std::vector<DType>{
- DNN_INC_FLOAT16(dtype::Float16() MEGDNN_COMMA)
- dtype::Float32(),
- dtype::Int32()}) {
- check(mode, dtype, dtype, Reduce::DataType::DEFAULT);
- }
- #if !MEGDNN_DISABLE_FLOAT16
- check(mode, dtype::Float16(), dtype::Float32(),
- Reduce::DataType::FLOAT_O32xC32);
- check(mode, dtype::Float16(), dtype::Float16(),
- Reduce::DataType::FLOAT_O16xC32);
- check(mode, dtype::Float32(), dtype::Float16(),
- Reduce::DataType::FLOAT_O16xC32);
- ASSERT_THROW(check(mode, dtype::Int32(), dtype::Float16(),
- Reduce::DataType::FLOAT_O16xC32),
- MegDNNError);
- ASSERT_THROW(check(mode, dtype::Float16(), dtype::Float16(),
- Reduce::DataType::FLOAT_IO16xC32),
- MegDNNError);
- #endif
- }
-
- #if !MEGDNN_DISABLE_FLOAT16
- {
- // very large reduce for I16CO32
- Reduce::Param param{Mode::SUM_SQR, 1,
- Reduce::Param::DataType::FLOAT_O32xC32};
- checker.set_dtype(0, dtype::Float16())
- .set_dtype(1, dtype::Float32())
- .set_param(param)
- .execs({{1, 4194304, 1}, {1, 1, 1}});
- }
-
- {
- // large reduce_mean for O16C32
- Reduce::Param param{Mode::MEAN, 1,
- Reduce::Param::DataType::FLOAT_O16xC32};
- checker.set_dtype(0, dtype::Float16())
- .set_dtype(1, dtype::Float16())
- .set_param(param)
- .execs({{1, 65536, 5}, {1, 1, 5}});
- }
- #endif
- }
-
- // vim: syntax=cpp.doxygen
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