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- #include "test/common/fake_quant.h"
- #include "megdnn/oprs.h"
- #include "test/common/checker.h"
- #include "test/cuda/fixture.h"
-
- namespace megdnn {
- namespace test {
- using namespace fake_quant;
- TEST_F(CUDA, FAKE_QUANT) {
- std::vector<TestArg> args = get_args();
- auto dtype = dtype::Float32();
- UniformFloatRNG rng(-1.0f, 1.0f);
- const auto nan = std::numeric_limits<float>::quiet_NaN();
- UniformFloatWithValueRNG rng1 = UniformFloatWithValueRNG(-1.0f, 1.0f, 0.5f, nan);
-
- for (auto&& arg : args) {
- auto param = arg.param;
- auto ishape = arg.ishape;
- auto scale_shape = arg.scale_shape;
- auto zeropoint_shape = arg.zeropoint_shape;
- Checker<FakeQuantForward> checker(handle_cuda());
- checker.set_param(param)
- .set_dtype(0, dtype)
- .set_dtype(1, dtype)
- .set_dtype(2, dtype)
- .set_dtype(3, dtype)
- .execs(TensorShapeArray{ishape, scale_shape, zeropoint_shape, ishape});
-
- checker.set_allow_invalid_check(true);
- checker.set_rng(0, &rng1);
- checker.set_param(param)
- .set_dtype(0, dtype)
- .set_dtype(1, dtype)
- .set_dtype(2, dtype)
- .set_dtype(3, dtype)
- .execs(TensorShapeArray{ishape, scale_shape, zeropoint_shape, ishape});
- checker.set_rng(0, &rng);
- checker.set_allow_invalid_check(false);
- }
- // test noncontiguous layout
- for (auto&& arg : args) {
- auto param = arg.param;
- auto ishape = arg.ishape;
- auto scale_shape = arg.scale_shape;
- auto zeropoint_shape = arg.zeropoint_shape;
- Checker<FakeQuantForward> checker(handle_cuda());
- TensorLayout ilayout(
- ishape,
- {(long int)(ishape[1] * ishape[2] * ishape[3] * 2),
- (long int)(ishape[2] * ishape[3]), (long int)ishape[3], 1},
- dtype::Float32());
- checker.set_param(param).execl(
- {ilayout,
- {scale_shape, dtype::Float32()},
- {zeropoint_shape, dtype::Float32()},
- ilayout});
-
- checker.set_allow_invalid_check(true);
- checker.set_rng(0, &rng1);
- checker.set_param(param).execl(
- {ilayout,
- {scale_shape, dtype::Float32()},
- {zeropoint_shape, dtype::Float32()},
- ilayout});
- checker.set_rng(0, &rng);
- checker.set_allow_invalid_check(false);
- }
- }
-
- TEST_F(CUDA, FAKE_QUANT_BACKWARD) {
- std::vector<TestArg> args = get_args();
- auto dtype = dtype::Float32();
- UniformFloatRNG rng(-1.0f, 1.0f);
- const auto nan = std::numeric_limits<float>::quiet_NaN();
- UniformFloatWithValueRNG rng1 = UniformFloatWithValueRNG(-1.0f, 1.0f, 0.5f, nan);
-
- for (auto&& arg : args) {
- auto param = arg.param;
- auto ishape = arg.ishape;
- auto scale_shape = arg.scale_shape;
- auto zeropoint_shape = arg.zeropoint_shape;
- Checker<FakeQuantBackward> checker(handle_cuda());
- checker.set_param(param)
- .set_dtype(0, dtype)
- .set_dtype(1, dtype)
- .set_dtype(2, dtype)
- .set_dtype(3, dtype)
- .set_dtype(4, dtype)
- .execs(TensorShapeArray{
- ishape, ishape, scale_shape, zeropoint_shape, ishape});
-
- checker.set_allow_invalid_check(true);
- checker.set_rng(0, &rng1);
- checker.set_param(param)
- .set_dtype(0, dtype)
- .set_dtype(1, dtype)
- .set_dtype(2, dtype)
- .set_dtype(3, dtype)
- .set_dtype(4, dtype)
- .execs(TensorShapeArray{
- ishape, ishape, scale_shape, zeropoint_shape, ishape});
- checker.set_rng(0, &rng);
- checker.set_allow_invalid_check(false);
- }
- // test noncontiguous layout
- for (auto&& arg : args) {
- auto param = arg.param;
- auto ishape = arg.ishape;
- auto scale_shape = arg.scale_shape;
- auto zeropoint_shape = arg.zeropoint_shape;
- Checker<FakeQuantBackward> checker(handle_cuda());
- TensorLayout ilayout(
- ishape,
- {(long int)(ishape[1] * ishape[2] * ishape[3] * 2),
- (long int)(ishape[2] * ishape[3]), (long int)ishape[3], 1},
- dtype::Float32());
- checker.set_param(param).execl(
- {ilayout,
- ilayout,
- {scale_shape, dtype::Float32()},
- {zeropoint_shape, dtype::Float32()},
- ilayout});
-
- checker.set_allow_invalid_check(true);
- checker.set_rng(0, &rng1);
- checker.set_param(param).execl(
- {ilayout,
- ilayout,
- {scale_shape, dtype::Float32()},
- {zeropoint_shape, dtype::Float32()},
- ilayout});
- checker.set_rng(0, &rng);
- checker.set_allow_invalid_check(false);
- }
- }
-
- } // namespace test
- } // namespace megdnn
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