COMPMID-2406: Create a new GEMMLowpQuantizeDownInt32ToInt16ScaleKernel for NEON
Change-Id: I3f3e247728fd6dafca066e41835f0ef9442d9b7a
Signed-off-by: giuros01 <giuseppe.rossini@arm.com>
Reviewed-on: https://review.mlplatform.org/c/1379
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
diff --git a/tests/validation/NEON/GEMMLowp.cpp b/tests/validation/NEON/GEMMLowp.cpp
index f0460b4..2f604c9 100644
--- a/tests/validation/NEON/GEMMLowp.cpp
+++ b/tests/validation/NEON/GEMMLowp.cpp
@@ -294,6 +294,9 @@
using NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointFixture =
GEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointValidationFixture<Tensor, Accessor, NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint>;
+using NEGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPointFixture =
+ GEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPointValidationFixture<Tensor, Accessor, NEGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPoint>;
+
// *INDENT-OFF*
// clang-format off
DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(
@@ -404,6 +407,117 @@
TEST_SUITE_END() // BoundedReLu
TEST_SUITE_END() // QuantizeDownInt32ToUint8ScaleByFixedPoint
+
+TEST_SUITE(QuantizeDownInt32ToInt16ScaleByFixedPoint)
+
+const auto quantize_down_int32_to_int16_scale_by_fixedpoint_cases = framework::dataset::make("result_fixedpoint_multiplier", 254601600, 254601602) * framework::dataset::make("result_shift", 1,
+ 2)
+ * framework::dataset::make("min", 0) * framework::dataset::make("max", 0) * framework::dataset::make("addBias", { false, true });
+
+const auto quantize_down_int32_to_int16_scale_by_fixedpoint_relu_cases = framework::dataset::make("result_fixedpoint_multiplier", 254601600, 254601602) * framework::dataset::make("result_shift", 1,
+ 2)
+ * framework::dataset::make("min", -2, 0) * framework::dataset::make("max", 1, 3) * framework::dataset::make("addBias", { false, true });
+
+using NEGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPointFixture =
+ GEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPointValidationFixture<Tensor, Accessor, NEGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPoint>;
+
+// *INDENT-OFF*
+// clang-format off
+DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(
+ framework::dataset::make("InputAInfo", { TensorInfo(TensorShape(21U, 13U), 1, DataType::S32), // Input not a multiple of 16
+ TensorInfo(TensorShape(21U, 13U), 1, DataType::S32), // Invalid min and max
+ TensorInfo(TensorShape(20U, 13U), 1, DataType::S32), // Wrong output data type
+ }),
+ framework::dataset::make("InputBInfo",{ TensorInfo(TensorShape(21U), 1, DataType::S32),
+ TensorInfo(TensorShape(21U), 1, DataType::S32),
+ TensorInfo(TensorShape(20U), 1, DataType::S32),
+ })),
+ framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(21U, 13U), 1, DataType::QSYMM16),
+ TensorInfo(TensorShape(21U, 13U), 1, DataType::QSYMM16),
+ TensorInfo(TensorShape(20U, 13U), 1, DataType::S32),
+ })),
+ framework::dataset::make("Min",{ -205,
+ -60000,
+ -180,
+ })),
+ framework::dataset::make("Max",{ 205,
+ 60000,
+ 180,
+ })),
+ framework::dataset::make("Expected", { true, false, false })),
+ a_info, b_info, output_info, min, max, expected)
+{
+ // Lock tensors
+ Status status = NEGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPoint::validate(&a_info.clone()->set_is_resizable(false),
+ &b_info.clone()->set_is_resizable(false),
+ &output_info.clone()->set_is_resizable(false),
+ min,
+ max);
+ ARM_COMPUTE_EXPECT(bool(status) == expected, framework::LogLevel::ERRORS);
+}
+// clang-format on
+// *INDENT-ON*
+
+DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(datasets::SmallShapes(),
+ quantize_down_int32_to_int16_scale_by_fixedpoint_cases),
+ shape, result_fixedpoint_multiplier, result_shift, min, max, add_bias)
+{
+ TensorShape shape_bias(shape[0]);
+
+ // Create tensors
+ Tensor in = create_tensor<Tensor>(shape, DataType::S32);
+ Tensor bias = create_tensor<Tensor>(shape_bias, DataType::S32);
+ Tensor out = create_tensor<Tensor>(shape, DataType::QSYMM16);
+
+ ARM_COMPUTE_EXPECT(in.info()->is_resizable(), framework::LogLevel::ERRORS);
+ ARM_COMPUTE_EXPECT(bias.info()->is_resizable(), framework::LogLevel::ERRORS);
+ ARM_COMPUTE_EXPECT(out.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+ // Create and configure function
+ NEGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPoint output_stage;
+ output_stage.configure(&in, add_bias ? &bias : nullptr, &out, result_fixedpoint_multiplier, result_shift, min, max);
+
+ // Validate valid region input and output
+ const ValidRegion valid_region = shape_to_valid_region(shape);
+ validate(in.info()->valid_region(), valid_region);
+ validate(out.info()->valid_region(), valid_region);
+
+ // Validate valid region bias
+ if(add_bias)
+ {
+ const ValidRegion valid_region_bias = shape_to_valid_region(shape_bias);
+ validate(bias.info()->valid_region(), valid_region_bias);
+ }
+
+ // Validate padding
+ const PaddingSize padding(0);
+ validate(in.info()->padding(), padding);
+ validate(out.info()->padding(), padding);
+
+ if(add_bias)
+ {
+ validate(bias.info()->padding(), padding);
+ }
+}
+
+FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPointFixture, framework::DatasetMode::ALL, combine(datasets::SmallShapes(),
+ quantize_down_int32_to_int16_scale_by_fixedpoint_cases))
+{
+ // Validate output
+ validate(Accessor(_target), _reference);
+}
+
+TEST_SUITE(BoundedReLu)
+FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPointFixture, framework::DatasetMode::ALL, combine(datasets::SmallShapes(),
+ quantize_down_int32_to_int16_scale_by_fixedpoint_relu_cases))
+{
+ // Validate output
+ validate(Accessor(_target), _reference);
+}
+TEST_SUITE_END() // BoundedReLu
+
+TEST_SUITE_END() // QuantizeDownInt32ToInt16ScaleByFixedPoint
+
TEST_SUITE_END() // OutputStage
TEST_SUITE_END() // GEMMLowp