Improved testing for ArgMinMax
* ArgMinMax output was fixed to S32, this patch makes the changes required
to allow other output types like U64/S64
* Made changes to the ArgMinMax fixture and tests to allow specifying output data type.
* Made changes to the reference reduction_operation to allow specifying the output type
* Added tests case to output S64 for the CL backend.
* Added missing test cases in the neon backend.
* Partially resolves MLCE-1089
Change-Id: I6f1cbc7093669d12c2a3aff6974cf19d83b2ecda
Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10003
Reviewed-by: Viet-Hoa Do <viet-hoa.do@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
diff --git a/tests/validation/reference/ReductionOperation.cpp b/tests/validation/reference/ReductionOperation.cpp
index e2890af..c189bc2 100644
--- a/tests/validation/reference/ReductionOperation.cpp
+++ b/tests/validation/reference/ReductionOperation.cpp
@@ -181,12 +181,12 @@
} // namespace
template <typename T, typename OT>
-SimpleTensor<OT> compute_reduction_operation(const SimpleTensor<T> &src, const TensorShape &dst_shape, unsigned int axis, ReductionOperation op, RoundingPolicy policy)
+SimpleTensor<OT> compute_reduction_operation(const SimpleTensor<T> &src, const TensorShape &dst_shape, unsigned int axis, ReductionOperation op,
+ DataType output_type, RoundingPolicy policy)
{
// Create reference
- const bool is_arg_min_max = (op == ReductionOperation::ARG_IDX_MIN || op == ReductionOperation::ARG_IDX_MAX);
- DataType output_data_type = is_arg_min_max ? DataType::S32 : src.data_type();
- SimpleTensor<OT> dst{ dst_shape, output_data_type, 1, src.quantization_info() };
+ const bool is_arg_min_max = (op == ReductionOperation::ARG_IDX_MIN || op == ReductionOperation::ARG_IDX_MAX);
+ SimpleTensor<OT> dst{ dst_shape, output_type, 1, src.quantization_info() };
const unsigned int src_width = src.shape().x();
const unsigned int src_height = src.shape().y();
const unsigned int src_depth = src.shape().z();
@@ -275,74 +275,89 @@
}
template <typename T, typename OT>
-SimpleTensor<OT> reduction_operation(const SimpleTensor<T> &src, const TensorShape &dst_shape, unsigned int axis, ReductionOperation op, QuantizationInfo quantization_info_output, RoundingPolicy policy)
+SimpleTensor<OT> reduction_operation(const SimpleTensor<T> &src, const TensorShape &dst_shape, unsigned int axis, ReductionOperation op,
+ DataType output_type, QuantizationInfo quantization_info_output, RoundingPolicy policy)
{
ARM_COMPUTE_UNUSED(quantization_info_output);
- return compute_reduction_operation<T, OT>(src, dst_shape, axis, op, policy);
+ return compute_reduction_operation<T, OT>(src, dst_shape, axis, op, output_type, policy);
}
template <>
-SimpleTensor<uint8_t> reduction_operation(const SimpleTensor<uint8_t> &src, const TensorShape &dst_shape, unsigned int axis, ReductionOperation op, QuantizationInfo quantization_info_output, RoundingPolicy policy)
+SimpleTensor<uint8_t> reduction_operation(const SimpleTensor<uint8_t> &src, const TensorShape &dst_shape, unsigned int axis, ReductionOperation op,
+ DataType output_type, QuantizationInfo quantization_info_output, RoundingPolicy policy)
{
if(src.data_type() == DataType::QASYMM8)
{
// If the operation is MEAN_SUM, we can directly use the uint8 implementation without taking into account scale and offset
if(op == ReductionOperation::MEAN_SUM && src.quantization_info() == quantization_info_output)
{
- return compute_reduction_operation<uint8_t, uint8_t>(src, dst_shape, axis, op, policy);
+ return compute_reduction_operation<uint8_t, uint8_t>(src, dst_shape, axis, op, output_type, policy);
}
else
{
SimpleTensor<float> src_f = convert_from_asymmetric(src);
- SimpleTensor<float> dst_f = reference::reduction_operation<float, float>(src_f, dst_shape, axis, op);
+ SimpleTensor<float> dst_f = reference::reduction_operation<float, float>(src_f, dst_shape, axis, op, output_type);
return convert_to_asymmetric<uint8_t>(dst_f, quantization_info_output);
}
}
else
{
- return compute_reduction_operation<uint8_t, uint8_t>(src, dst_shape, axis, op, policy);
+ return compute_reduction_operation<uint8_t, uint8_t>(src, dst_shape, axis, op, output_type, policy);
}
}
template <>
-SimpleTensor<int8_t> reduction_operation(const SimpleTensor<int8_t> &src, const TensorShape &dst_shape, unsigned int axis, ReductionOperation op, QuantizationInfo quantization_info_output, RoundingPolicy policy)
+SimpleTensor<int8_t> reduction_operation(const SimpleTensor<int8_t> &src, const TensorShape &dst_shape, unsigned int axis,
+ ReductionOperation op, DataType output_type, QuantizationInfo quantization_info_output, RoundingPolicy policy)
{
if(src.data_type() == DataType::QASYMM8_SIGNED)
{
// If the operation is MEAN_SUM, we can directly use the int8 implementation without taking into account scale and offset
if(op == ReductionOperation::MEAN_SUM && src.quantization_info() == quantization_info_output)
{
- return compute_reduction_operation<int8_t, int8_t>(src, dst_shape, axis, op, policy);
+ return compute_reduction_operation<int8_t, int8_t>(src, dst_shape, axis, op, output_type, policy);
}
else
{
SimpleTensor<float> src_f = convert_from_asymmetric(src);
- SimpleTensor<float> dst_f = reference::reduction_operation<float, float>(src_f, dst_shape, axis, op);
+ SimpleTensor<float> dst_f = reference::reduction_operation<float, float>(src_f, dst_shape, axis, op, output_type);
return convert_to_asymmetric<int8_t>(dst_f, quantization_info_output);
}
}
else
{
- return compute_reduction_operation<int8_t, int8_t>(src, dst_shape, axis, op, policy);
+ return compute_reduction_operation<int8_t, int8_t>(src, dst_shape, axis, op, output_type, policy);
}
}
template SimpleTensor<float> reduction_operation(const SimpleTensor<float> &src, const TensorShape &dst_shape, unsigned int axis, ReductionOperation op,
- QuantizationInfo quantization_info_output = QuantizationInfo(), RoundingPolicy policy = RoundingPolicy::TO_ZERO);
+ DataType output_type = DataType::S32, QuantizationInfo quantization_info_output = QuantizationInfo(),
+ RoundingPolicy policy = RoundingPolicy::TO_ZERO);
+
template SimpleTensor<half> reduction_operation(const SimpleTensor<half> &src, const TensorShape &dst_shape, unsigned int axis, ReductionOperation op,
+ DataType output_type = DataType::S32,
QuantizationInfo quantization_info_output = QuantizationInfo(), RoundingPolicy policy = RoundingPolicy::TO_ZERO);
template SimpleTensor<int32_t> reduction_operation(const SimpleTensor<float> &src, const TensorShape &dst_shape, unsigned int axis, ReductionOperation op,
- QuantizationInfo quantization_info_output = QuantizationInfo(), RoundingPolicy policy = RoundingPolicy::TO_ZERO);
-template SimpleTensor<int32_t> reduction_operation(const SimpleTensor<int32_t> &src, const TensorShape &dst_shape, unsigned int axis, ReductionOperation op,
- QuantizationInfo quantization_info_output = QuantizationInfo(), RoundingPolicy policy = RoundingPolicy::TO_ZERO);
-template SimpleTensor<int32_t> reduction_operation(const SimpleTensor<half> &src, const TensorShape &dst_shape, unsigned int axis, ReductionOperation op,
- QuantizationInfo quantization_info_output = QuantizationInfo(), RoundingPolicy policy = RoundingPolicy::TO_ZERO);
-template SimpleTensor<int32_t> reduction_operation(const SimpleTensor<uint8_t> &src, const TensorShape &dst_shape, unsigned int axis, ReductionOperation op,
- QuantizationInfo quantization_info_output = QuantizationInfo(), RoundingPolicy policy = RoundingPolicy::TO_ZERO);
-template SimpleTensor<int32_t> reduction_operation(const SimpleTensor<int8_t> &src, const TensorShape &dst_shape, unsigned int axis, ReductionOperation op,
+ DataType output_type = DataType::S32,
QuantizationInfo quantization_info_output = QuantizationInfo(), RoundingPolicy policy = RoundingPolicy::TO_ZERO);
+template SimpleTensor<int32_t> reduction_operation(const SimpleTensor<int32_t> &src, const TensorShape &dst_shape, unsigned int axis, ReductionOperation op,
+ DataType output_type = DataType::S32,
+ QuantizationInfo quantization_info_output = QuantizationInfo(), RoundingPolicy policy = RoundingPolicy::TO_ZERO);
+template SimpleTensor<int32_t> reduction_operation(const SimpleTensor<half> &src, const TensorShape &dst_shape, unsigned int axis, ReductionOperation op,
+ DataType output_type = DataType::S32,
+ QuantizationInfo quantization_info_output = QuantizationInfo(), RoundingPolicy policy = RoundingPolicy::TO_ZERO);
+template SimpleTensor<int32_t> reduction_operation(const SimpleTensor<uint8_t> &src, const TensorShape &dst_shape, unsigned int axis, ReductionOperation op,
+ DataType output_type = DataType::S32,
+ QuantizationInfo quantization_info_output = QuantizationInfo(), RoundingPolicy policy = RoundingPolicy::TO_ZERO);
+template SimpleTensor<int32_t> reduction_operation(const SimpleTensor<int8_t> &src, const TensorShape &dst_shape, unsigned int axis, ReductionOperation op,
+ DataType output_type = DataType::S32,
+ QuantizationInfo quantization_info_output = QuantizationInfo(), RoundingPolicy policy = RoundingPolicy::TO_ZERO);
+
+template SimpleTensor<int64_t> reduction_operation(const SimpleTensor<float> &src, const TensorShape &dst_shape, unsigned int axis, ReductionOperation op,
+ DataType output_type = DataType::S32, QuantizationInfo quantization_info_output = QuantizationInfo(),
+ RoundingPolicy policy = RoundingPolicy::TO_ZERO);
} // namespace reference
} // namespace validation
} // namespace test