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Diffstat (limited to 'tests/validation/fixtures/GEMMLowpFixture.h')
-rw-r--r--tests/validation/fixtures/GEMMLowpFixture.h94
1 files changed, 40 insertions, 54 deletions
diff --git a/tests/validation/fixtures/GEMMLowpFixture.h b/tests/validation/fixtures/GEMMLowpFixture.h
index fba44008ba..f9b0dbd959 100644
--- a/tests/validation/fixtures/GEMMLowpFixture.h
+++ b/tests/validation/fixtures/GEMMLowpFixture.h
@@ -43,36 +43,39 @@ namespace test
namespace validation
{
template <typename TensorType, typename AccessorType, typename FunctionType>
-class GEMMLowpOffsetValidationFixture : public framework::Fixture
+class GEMMLowpMatrixMultiplyCoreValidationFixture : public framework::Fixture
{
public:
template <typename...>
- void setup(TensorShape shape_a, TensorShape shape_b, TensorShape shape_c, int32_t a_offset, int32_t b_offset, int32_t c_offset, int32_t c_mult_int, int32_t out_shift, DataType data_type)
+ void setup(TensorShape shape_a, TensorShape shape_b, TensorShape shape_c, int32_t a_offset, int32_t b_offset)
{
- _target = compute_target(shape_a, shape_b, shape_c, a_offset, b_offset, c_offset, c_mult_int, out_shift, data_type);
- _reference = compute_reference(shape_a, shape_b, shape_c, a_offset, b_offset, c_offset, c_mult_int, out_shift, data_type);
+ _target = compute_target(shape_a, shape_b, shape_c, a_offset, b_offset);
+ _reference = compute_reference(shape_a, shape_b, shape_c, a_offset, b_offset);
}
protected:
template <typename U>
void fill(U &&tensor, int i)
{
- ARM_COMPUTE_ERROR_ON(tensor.data_type() != DataType::S8);
- std::uniform_int_distribution<> distribution(0, 3);
+ // Between 1 and 254 in order to avoid having -128 and 128 for the DOT product path
+ std::uniform_int_distribution<> distribution(1, 254);
library->fill(tensor, distribution, i);
}
TensorType compute_target(const TensorShape &shape_a, const TensorShape &shape_b, const TensorShape &shape_c,
- int32_t a_offset, int32_t b_offset, int32_t c_offset, int32_t c_mult_int, int32_t out_shift, DataType data_type)
+ int32_t a_offset, int32_t b_offset)
{
// Create tensors
- TensorType a = create_tensor<TensorType>(shape_a, data_type, 1);
- TensorType b = create_tensor<TensorType>(shape_b, data_type, 1);
- TensorType c = create_tensor<TensorType>(shape_c, data_type, 1);
+ TensorType a = create_tensor<TensorType>(shape_a, DataType::QASYMM8, 1);
+ TensorType b = create_tensor<TensorType>(shape_b, DataType::QASYMM8, 1);
+ TensorType c = create_tensor<TensorType>(shape_c, DataType::S32, 1);
+
+ a.info()->set_quantization_info(QuantizationInfo(1.0f / 255, a_offset));
+ b.info()->set_quantization_info(QuantizationInfo(1.0f / 255, b_offset));
// Create and configure function
FunctionType gemmlowp;
- gemmlowp.configure(&a, &b, &c, a_offset, b_offset, c_offset, c_mult_int, out_shift);
+ gemmlowp.configure(&a, &b, &c);
ARM_COMPUTE_EXPECT(a.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(b.info()->is_resizable(), framework::LogLevel::ERRORS);
@@ -90,108 +93,91 @@ protected:
// Fill tensors
fill(AccessorType(a), 0);
fill(AccessorType(b), 1);
- fill(AccessorType(c), 2);
// Compute GEMM function
gemmlowp.run();
return c;
}
- SimpleTensor<int8_t> compute_reference(const TensorShape &shape_a, const TensorShape &shape_b, const TensorShape &shape_c,
- int32_t a_offset, int32_t b_offset, int32_t c_offset, int32_t c_mult_int, int32_t out_shift, DataType data_type)
+ SimpleTensor<int32_t> compute_reference(const TensorShape &shape_a, const TensorShape &shape_b, const TensorShape &shape_c,
+ int32_t a_offset, int32_t b_offset)
{
// Create reference
- SimpleTensor<int8_t> a{ shape_a, data_type, 1 };
- SimpleTensor<int8_t> b{ shape_b, data_type, 1 };
- SimpleTensor<int8_t> c{ shape_c, data_type, 1 };
+ SimpleTensor<uint8_t> a{ shape_a, DataType::QASYMM8, 1 };
+ SimpleTensor<uint8_t> b{ shape_b, DataType::QASYMM8, 1 };
// Fill reference
fill(a, 0);
fill(b, 1);
- fill(c, 2);
- return reference::gemmlowp<int8_t>(a, b, c, a_offset, b_offset, c_offset, c_mult_int, out_shift);
+ return reference::gemmlowp_matrix_multiply_core<uint8_t>(a, b, a_offset, b_offset);
}
- TensorType _target{};
- SimpleTensor<int8_t> _reference{};
+ TensorType _target{};
+ SimpleTensor<int32_t> _reference{};
};
template <typename TensorType, typename AccessorType, typename FunctionType>
-class GEMMLowpMatrixMultiplyValidationFixture : public framework::Fixture
+class GEMMLowpQuantizeDownInt32ToUint8ScaleValidationFixture : public framework::Fixture
{
public:
template <typename...>
- void setup(size_t m, size_t n, size_t k)
+ void setup(TensorShape shape, int32_t result_offset, int32_t result_mult_int, int32_t result_shift)
{
- const TensorShape shape_a(k, m);
- const TensorShape shape_b(n, k);
- const TensorShape shape_c(n, m);
- _target = compute_target(shape_a, shape_b, shape_c);
- _reference = compute_reference(shape_a, shape_b, shape_c);
+ _target = compute_target(shape, result_offset, result_mult_int, result_shift);
+ _reference = compute_reference(shape, result_offset, result_mult_int, result_shift);
}
protected:
template <typename U>
- void fill(U &&tensor, int i, int lo, int hi)
+ void fill(U &&tensor, int i)
{
- std::uniform_int_distribution<> distribution(lo, hi);
+ std::uniform_int_distribution<> distribution(-6000, 6000);
library->fill(tensor, distribution, i);
}
- TensorType compute_target(const TensorShape &shape_a, const TensorShape &shape_b, const TensorShape &shape_c)
+ TensorType compute_target(const TensorShape &shape, int32_t result_offset, int32_t result_mult_int, int32_t result_shift)
{
// Create tensors
- TensorType a = create_tensor<TensorType>(shape_a, DataType::S8, 1);
- TensorType b = create_tensor<TensorType>(shape_b, DataType::S8, 1);
- TensorType c = create_tensor<TensorType>(shape_c, DataType::S32, 1);
+ TensorType a = create_tensor<TensorType>(shape, DataType::S32, 1);
+ TensorType b = create_tensor<TensorType>(shape, DataType::QASYMM8, 1);
// Create and configure function
- FunctionType gemmlowp;
- gemmlowp.configure(&a, &b, &c);
+ FunctionType output_stage;
+ output_stage.configure(&a, &b, result_offset, result_mult_int, result_shift);
ARM_COMPUTE_EXPECT(a.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(b.info()->is_resizable(), framework::LogLevel::ERRORS);
- ARM_COMPUTE_EXPECT(c.info()->is_resizable(), framework::LogLevel::ERRORS);
// Allocate tensors
a.allocator()->allocate();
b.allocator()->allocate();
- c.allocator()->allocate();
ARM_COMPUTE_EXPECT(!a.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(!b.info()->is_resizable(), framework::LogLevel::ERRORS);
- ARM_COMPUTE_EXPECT(!c.info()->is_resizable(), framework::LogLevel::ERRORS);
// Fill tensors
- fill(AccessorType(a), 0, -128, 127);
- fill(AccessorType(b), 1, -128, 127);
- fill(AccessorType(c), 2, 0, 0);
+ fill(AccessorType(a), 0);
// Compute GEMM function
- gemmlowp.run();
- return c;
+ output_stage.run();
+ return b;
}
- SimpleTensor<int32_t> compute_reference(const TensorShape &shape_a, const TensorShape &shape_b, const TensorShape &shape_c)
+ SimpleTensor<uint8_t> compute_reference(const TensorShape &shape, int32_t result_offset, int32_t result_mult_int, int32_t result_shift)
{
// Create reference
- SimpleTensor<int8_t> a{ shape_a, DataType::S8, 1 };
- SimpleTensor<int8_t> b{ shape_b, DataType::S8, 1 };
- SimpleTensor<int32_t> c{ shape_c, DataType::S32, 1 };
+ SimpleTensor<int32_t> a{ shape, DataType::S32, 1 };
// Fill reference
- fill(a, 0, -128, 127);
- fill(b, 1, -128, 127);
- fill(c, 2, 0, 0);
+ fill(a, 0);
- return reference::gemmlowp(a, b, c);
+ return reference::gemmlowp_quantize_down_int32_to_uint8_scale<int32_t>(a, result_offset, result_mult_int, result_shift);
}
TensorType _target{};
- SimpleTensor<int32_t> _reference{};
+ SimpleTensor<uint8_t> _reference{};
};
-
} // namespace validation
} // namespace test
} // namespace arm_compute
generated by cgit v1.2.1 (git 2.23.0) at 2024-05-29 01:11:31 +0000