COMPMID-3502: Add support of different quantization input/output for ReduceMean
Change-Id: If9a5c6ee3902a7381f4117e473adbddf006f3347
Signed-off-by: Manuel Bottini <manuel.bottini@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/3731
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Sang-Hoon Park <sang-hoon.park@arm.com>
diff --git a/arm_compute/core/utils/misc/ShapeCalculator.h b/arm_compute/core/utils/misc/ShapeCalculator.h
index 0be4caf..f2f5a30 100644
--- a/arm_compute/core/utils/misc/ShapeCalculator.h
+++ b/arm_compute/core/utils/misc/ShapeCalculator.h
@@ -47,13 +47,13 @@
*
* @return the calculated shape
*/
-inline TensorShape calculate_reduce_mean_shape(ITensor *input, const Coordinates &reduction_axis, bool keep_dims)
+inline TensorShape calculate_reduce_mean_shape(ITensorInfo *input, const Coordinates &reduction_axis, bool keep_dims)
{
const int reduction_ops = reduction_axis.num_dimensions();
Coordinates axis_local = reduction_axis;
- const int input_dims = input->info()->num_dimensions();
+ const int input_dims = input->num_dimensions();
convert_negative_axis(axis_local, input_dims);
- TensorShape out_shape = input->info()->tensor_shape();
+ TensorShape out_shape = input->tensor_shape();
// Configure reshape layer if we want to drop the dimensions
if(!keep_dims)
{
diff --git a/arm_compute/runtime/CL/functions/CLReduceMean.h b/arm_compute/runtime/CL/functions/CLReduceMean.h
index 88ead9d..c37ee8c 100644
--- a/arm_compute/runtime/CL/functions/CLReduceMean.h
+++ b/arm_compute/runtime/CL/functions/CLReduceMean.h
@@ -25,7 +25,9 @@
#define ARM_COMPUTE_CL_REDUCE_MEAN_H
#include "arm_compute/runtime/CL/ICLSimpleFunction.h"
+#include "arm_compute/runtime/CL/functions/CLDequantizationLayer.h"
#include "arm_compute/runtime/CL/functions/CLElementwiseOperations.h"
+#include "arm_compute/runtime/CL/functions/CLQuantizationLayer.h"
#include "arm_compute/runtime/CL/functions/CLReductionOperation.h"
#include "arm_compute/runtime/CL/functions/CLReshapeLayer.h"
#include "arm_compute/runtime/IMemoryManager.h"
@@ -82,8 +84,13 @@
std::vector<CLReductionOperation> _reduction_kernels;
std::vector<CLTensor> _reduced_outs;
CLReshapeLayer _reshape;
+ CLDequantizationLayer _dequant;
+ CLQuantizationLayer _requant;
int _reduction_ops;
bool _keep_dims;
+ bool _do_requant;
+ CLTensor _input_no_quant;
+ CLTensor _output_no_quant;
};
} // namespace arm_compute
#endif /* ARM_COMPUTE_CL_REDUCE_MEAN_H */
diff --git a/arm_compute/runtime/NEON/functions/NEReduceMean.h b/arm_compute/runtime/NEON/functions/NEReduceMean.h
index a1b6e34..eee3f7f 100644
--- a/arm_compute/runtime/NEON/functions/NEReduceMean.h
+++ b/arm_compute/runtime/NEON/functions/NEReduceMean.h
@@ -29,6 +29,8 @@
#include "arm_compute/core/NEON/kernels/NEFillBorderKernel.h"
#include "arm_compute/core/Types.h"
#include "arm_compute/runtime/MemoryGroup.h"
+#include "arm_compute/runtime/NEON/functions/NEDequantizationLayer.h"
+#include "arm_compute/runtime/NEON/functions/NEQuantizationLayer.h"
#include "arm_compute/runtime/NEON/functions/NEReductionOperation.h"
#include "arm_compute/runtime/NEON/functions/NEReshapeLayer.h"
#include "arm_compute/runtime/Tensor.h"
@@ -71,8 +73,13 @@
std::vector<NEReductionOperation> _reduction_kernels;
std::vector<Tensor> _reduced_outs;
NEReshapeLayer _reshape;
+ NEDequantizationLayer _dequant;
+ NEQuantizationLayer _requant;
int _reduction_ops;
bool _keep_dims;
+ bool _do_requant;
+ Tensor _input_no_quant;
+ Tensor _output_no_quant;
};
} // namespace arm_compute
#endif /* ARM_COMPUTE_NEON_REDUCE_MEAN_H */
diff --git a/src/runtime/CL/functions/CLReduceMean.cpp b/src/runtime/CL/functions/CLReduceMean.cpp
index c8eb542..0e2ede7 100644
--- a/src/runtime/CL/functions/CLReduceMean.cpp
+++ b/src/runtime/CL/functions/CLReduceMean.cpp
@@ -83,15 +83,25 @@
}
const TensorInfo out_info = input->clone()->set_tensor_shape(out_shape);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(output, &out_info);
- ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_QUANTIZATION_INFO(input, output);
+ const bool requant = is_data_type_quantized(input->data_type()) && input->quantization_info() != output->quantization_info();
+ if(requant)
+ {
+ TensorInfo input_no_quant(input->clone()->set_data_type(DataType::F32));
+ CLDequantizationLayer::validate(input, &input_no_quant);
+ TensorInfo output_no_quant(output->clone()->set_data_type(DataType::F32));
+ CLQuantizationLayer::validate(&output_no_quant, output);
+ }
}
return Status{};
}
}
+
CLReduceMean::CLReduceMean(std::shared_ptr<IMemoryManager> memory_manager)
- : _memory_group(std::move(memory_manager)), _reduction_kernels(), _reduced_outs(), _reshape(), _reduction_ops(), _keep_dims()
+ : _memory_group(std::move(memory_manager)), _reduction_kernels(), _reduced_outs(), _reshape(), _dequant(), _requant(), _reduction_ops(), _keep_dims(), _do_requant(), _input_no_quant(),
+ _output_no_quant()
{
}
+
void CLReduceMean::configure(ICLTensor *input, const Coordinates &reduction_axis, bool keep_dims, ICLTensor *output)
{
configure(CLKernelLibrary::get().get_compile_context(), input, reduction_axis, keep_dims, output);
@@ -102,33 +112,49 @@
// Perform validate step
ARM_COMPUTE_ERROR_THROW_ON(CLReduceMean::validate(input->info(), reduction_axis, keep_dims, output->info()));
// Output auto inizialitation if not yet initialized
- const TensorShape output_shape = arm_compute::misc::shape_calculator::calculate_reduce_mean_shape(input, reduction_axis, keep_dims);
+ const TensorShape output_shape = arm_compute::misc::shape_calculator::calculate_reduce_mean_shape(input->info(), reduction_axis, keep_dims);
auto_init_if_empty(*output->info(), input->info()->clone()->set_tensor_shape(output_shape));
+ _do_requant = is_data_type_quantized(input->info()->data_type()) && input->info()->quantization_info() != output->info()->quantization_info();
_reduction_ops = reduction_axis.num_dimensions();
_reduction_kernels.resize(_reduction_ops);
_reduced_outs.resize(_reduction_ops - (keep_dims ? 1 : 0));
_keep_dims = keep_dims;
+ ICLTensor *tmp_input = input;
+ ICLTensor *tmp_output = output;
+ if(_do_requant)
+ {
+ _memory_group.manage(&_input_no_quant);
+ _memory_group.manage(&_output_no_quant);
+ TensorInfo output_no_quant_info = input->info()->clone()->set_tensor_shape(output_shape);
+ output_no_quant_info.set_data_type(DataType::F32);
+ auto_init_if_empty(*_output_no_quant.info(), output_no_quant_info);
+ auto_init_if_empty(*_input_no_quant.info(), input->info()->clone()->set_data_type(DataType::F32));
+ _dequant.configure(compile_context, input, &_input_no_quant);
+ tmp_input = &_input_no_quant;
+ tmp_output = &_output_no_quant;
+ }
+
Coordinates axis_local = reduction_axis;
- const int input_dims = input->info()->num_dimensions();
+ const int input_dims = tmp_input->info()->num_dimensions();
convert_negative_axis(axis_local, input_dims);
// Perform reduction for every axis
for(int i = 0; i < _reduction_ops; ++i)
{
- TensorShape out_shape = i == 0 ? input->info()->tensor_shape() : (&_reduced_outs[i - 1])->info()->tensor_shape();
+ TensorShape out_shape = i == 0 ? tmp_input->info()->tensor_shape() : (&_reduced_outs[i - 1])->info()->tensor_shape();
out_shape.set(axis_local[i], 1);
- auto in = (i == 0) ? input : (&_reduced_outs[i - 1]);
+ auto in = (i == 0) ? tmp_input : (&_reduced_outs[i - 1]);
if(i == _reduction_ops - 1 && keep_dims)
{
- _reduction_kernels[i].configure(compile_context, in, output, axis_local[i], ReductionOperation::MEAN_SUM);
+ _reduction_kernels[i].configure(compile_context, in, tmp_output, axis_local[i], ReductionOperation::MEAN_SUM);
}
else
{
- _reduced_outs[i].allocator()->init(TensorInfo(out_shape, input->info()->num_channels(), input->info()->data_type(), input->info()->quantization_info()));
+ _reduced_outs[i].allocator()->init(TensorInfo(out_shape, tmp_input->info()->num_channels(), tmp_input->info()->data_type(), tmp_input->info()->quantization_info()));
_memory_group.manage(&_reduced_outs[i]);
_reduction_kernels[i].configure(compile_context, in, &_reduced_outs[i], axis_local[i], ReductionOperation::MEAN_SUM);
}
@@ -141,9 +167,9 @@
}
// Configure reshape layer if we want to drop the dimensions
- if(!keep_dims)
+ if(!_keep_dims)
{
- TensorShape out_shape = input->info()->tensor_shape();
+ TensorShape out_shape = tmp_input->info()->tensor_shape();
// We have to sort the reduction axis vectors in order for remove_dimension
// to work properly
@@ -152,8 +178,14 @@
{
out_shape.remove_dimension(axis_local[i] - i);
}
- auto_init_if_empty(*output->info(), input->info()->clone()->set_tensor_shape(out_shape));
- _reshape.configure(compile_context, &_reduced_outs[_reduction_ops - 1], output);
+ auto_init_if_empty(*tmp_output->info(), tmp_input->info()->clone()->set_tensor_shape(out_shape));
+ _reshape.configure(compile_context, &_reduced_outs[_reduction_ops - 1], tmp_output);
+ }
+ if(_do_requant)
+ {
+ _requant.configure(compile_context, &_output_no_quant, output);
+ _input_no_quant.allocator()->allocate();
+ _output_no_quant.allocator()->allocate();
}
}
@@ -166,14 +198,21 @@
{
MemoryGroupResourceScope scope_mg(_memory_group);
+ if(_do_requant)
+ {
+ _dequant.run();
+ }
for(auto &kernel : _reduction_kernels)
{
kernel.run();
}
-
if(!_keep_dims)
{
_reshape.run();
}
+ if(_do_requant)
+ {
+ _requant.run();
+ }
}
} // namespace arm_compute
diff --git a/src/runtime/NEON/functions/NEReduceMean.cpp b/src/runtime/NEON/functions/NEReduceMean.cpp
index 079c7c6..021f7b5 100644
--- a/src/runtime/NEON/functions/NEReduceMean.cpp
+++ b/src/runtime/NEON/functions/NEReduceMean.cpp
@@ -33,13 +33,6 @@
{
namespace
{
-} // namespace
-
-NEReduceMean::NEReduceMean(std::shared_ptr<IMemoryManager> memory_manager)
- : _memory_group(std::move(memory_manager)), _reduction_kernels(), _reduced_outs(), _reshape(), _reduction_ops(), _keep_dims()
-{
-}
-
Status validate_config(const ITensorInfo *input, const Coordinates &reduction_axis, bool keep_dims, const ITensorInfo *output)
{
ARM_COMPUTE_UNUSED(keep_dims);
@@ -89,10 +82,24 @@
}
const TensorInfo out_info = input->clone()->set_tensor_shape(out_shape);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(output, &out_info);
- ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_QUANTIZATION_INFO(input, output);
+ const bool requant = is_data_type_quantized(input->data_type()) && input->quantization_info() != output->quantization_info();
+ if(requant)
+ {
+ TensorInfo input_no_quant(input->clone()->set_data_type(DataType::F32));
+ NEDequantizationLayer::validate(input, &input_no_quant);
+ TensorInfo output_no_quant(output->clone()->set_data_type(DataType::F32));
+ NEQuantizationLayer::validate(&output_no_quant, output);
+ }
}
return Status{};
}
+} // namespace
+
+NEReduceMean::NEReduceMean(std::shared_ptr<IMemoryManager> memory_manager)
+ : _memory_group(std::move(memory_manager)), _reduction_kernels(), _reduced_outs(), _reshape(), _dequant(), _requant(), _reduction_ops(), _keep_dims(), _do_requant(), _input_no_quant(),
+ _output_no_quant()
+{
+}
Status NEReduceMean::validate(const ITensorInfo *input, const Coordinates &reduction_axis, bool keep_dims, const ITensorInfo *output)
{
@@ -104,33 +111,49 @@
// Perform validate step
ARM_COMPUTE_ERROR_THROW_ON(NEReduceMean::validate(input->info(), reduction_axis, keep_dims, output->info()));
// Output auto inizialitation if not yet initialized
- const TensorShape output_shape = arm_compute::misc::shape_calculator::calculate_reduce_mean_shape(input, reduction_axis, keep_dims);
+ const TensorShape output_shape = arm_compute::misc::shape_calculator::calculate_reduce_mean_shape(input->info(), reduction_axis, keep_dims);
auto_init_if_empty(*output->info(), input->info()->clone()->set_tensor_shape(output_shape));
+ _do_requant = is_data_type_quantized(input->info()->data_type()) && input->info()->quantization_info() != output->info()->quantization_info();
_reduction_ops = reduction_axis.num_dimensions();
_reduction_kernels.resize(_reduction_ops);
_reduced_outs.resize(_reduction_ops - (keep_dims ? 1 : 0));
_keep_dims = keep_dims;
+ ITensor *tmp_input = input;
+ ITensor *tmp_output = output;
+ if(_do_requant)
+ {
+ _memory_group.manage(&_input_no_quant);
+ _memory_group.manage(&_output_no_quant);
+ TensorInfo output_no_quant_info = input->info()->clone()->set_tensor_shape(output_shape);
+ output_no_quant_info.set_data_type(DataType::F32);
+ auto_init_if_empty(*_output_no_quant.info(), output_no_quant_info);
+ auto_init_if_empty(*_input_no_quant.info(), input->info()->clone()->set_data_type(DataType::F32));
+ _dequant.configure(input, &_input_no_quant);
+ tmp_input = &_input_no_quant;
+ tmp_output = &_output_no_quant;
+ }
+
Coordinates axis_local = reduction_axis;
- const int input_dims = input->info()->num_dimensions();
+ const int input_dims = tmp_input->info()->num_dimensions();
convert_negative_axis(axis_local, input_dims);
// Perform reduction for every axis
for(int i = 0; i < _reduction_ops; ++i)
{
- TensorShape out_shape = i == 0 ? input->info()->tensor_shape() : (&_reduced_outs[i - 1])->info()->tensor_shape();
+ TensorShape out_shape = i == 0 ? tmp_input->info()->tensor_shape() : (&_reduced_outs[i - 1])->info()->tensor_shape();
out_shape.set(axis_local[i], 1);
- auto in = (i == 0) ? input : (&_reduced_outs[i - 1]);
+ auto in = (i == 0) ? tmp_input : (&_reduced_outs[i - 1]);
if(i == _reduction_ops - 1 && keep_dims)
{
- _reduction_kernels[i].configure(in, output, axis_local[i], ReductionOperation::MEAN_SUM);
+ _reduction_kernels[i].configure(in, tmp_output, axis_local[i], ReductionOperation::MEAN_SUM);
}
else
{
- _reduced_outs[i].allocator()->init(TensorInfo(out_shape, input->info()->num_channels(), input->info()->data_type(), input->info()->quantization_info()));
+ _reduced_outs[i].allocator()->init(TensorInfo(out_shape, tmp_input->info()->num_channels(), tmp_input->info()->data_type(), tmp_input->info()->quantization_info()));
_memory_group.manage(&_reduced_outs[i]);
_reduction_kernels[i].configure(in, &_reduced_outs[i], axis_local[i], ReductionOperation::MEAN_SUM);
}
@@ -145,7 +168,7 @@
// Configure reshape layer if we want to drop the dimensions
if(!keep_dims)
{
- TensorShape out_shape = input->info()->tensor_shape();
+ TensorShape out_shape = tmp_input->info()->tensor_shape();
// We have to sort the reduction axis vectors in order for remove_dimension
// to work properly
std::sort(axis_local.begin(), axis_local.begin() + _reduction_ops);
@@ -153,22 +176,35 @@
{
out_shape.remove_dimension(axis_local[i] - i);
}
- auto_init_if_empty(*output->info(), input->info()->clone()->set_tensor_shape(out_shape));
- _reshape.configure(&_reduced_outs[_reduction_ops - 1], output);
+ auto_init_if_empty(*tmp_output->info(), tmp_input->info()->clone()->set_tensor_shape(out_shape));
+ _reshape.configure(&_reduced_outs[_reduction_ops - 1], tmp_output);
+ }
+ if(_do_requant)
+ {
+ _requant.configure(&_output_no_quant, output);
+ _input_no_quant.allocator()->allocate();
+ _output_no_quant.allocator()->allocate();
}
}
void NEReduceMean::run()
{
MemoryGroupResourceScope scope_mg(_memory_group);
+ if(_do_requant)
+ {
+ _dequant.run();
+ }
for(auto &kernel : _reduction_kernels)
{
kernel.run();
}
-
if(!_keep_dims)
{
_reshape.run();
}
+ if(_do_requant)
+ {
+ _requant.run();
+ }
}
} // namespace arm_compute
diff --git a/tests/validation/CL/ReduceMean.cpp b/tests/validation/CL/ReduceMean.cpp
index cb1e38e..1dc6c61 100644
--- a/tests/validation/CL/ReduceMean.cpp
+++ b/tests/validation/CL/ReduceMean.cpp
@@ -133,16 +133,33 @@
FIXTURE_DATA_TEST_CASE(RunSmall,
CLReduceMeanQuantizedFixture<uint8_t>,
framework::DatasetMode::PRECOMMIT,
- combine(combine(combine(datasets::Small4DShapes(), framework::dataset::make("DataType", DataType::QASYMM8)), concat(axis_keep, axis_drop)), framework::dataset::make("QuantizationInfo", { QuantizationInfo(1.f / 255, 5) })))
+ combine(combine(combine(combine(datasets::Small4DShapes(), framework::dataset::make("DataType", DataType::QASYMM8)), concat(axis_keep, axis_drop)),
+ framework::dataset::make("QuantizationInfoInput", { QuantizationInfo(1.f / 255, 5) })),
+ framework::dataset::make("QuantizationInfoOutput", { QuantizationInfo(1.f / 255, 5) })))
{
// Validate output
validate(CLAccessor(_target), _reference, tolerance_qasymm8);
}
+TEST_SUITE(Requant)
+FIXTURE_DATA_TEST_CASE(RunSmall,
+ CLReduceMeanQuantizedFixture<uint8_t>,
+ framework::DatasetMode::PRECOMMIT,
+ combine(combine(combine(combine(datasets::Small4DShapes(), framework::dataset::make("DataType", DataType::QASYMM8)), axis_drop),
+ framework::dataset::make("QuantizationInfoInput", { QuantizationInfo(1.f / 255, 5) })),
+ framework::dataset::make("QuantizationInfoOutput", { QuantizationInfo(1.f / 200, 16) })))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference, tolerance_qasymm8);
+}
+TEST_SUITE_END() // Requant
+
FIXTURE_DATA_TEST_CASE(RunLarge,
CLReduceMeanQuantizedFixture<uint8_t>,
framework::DatasetMode::NIGHTLY,
- combine(combine(combine(datasets::Large4DShapes(), framework::dataset::make("DataType", DataType::QASYMM8)), concat(axis_keep, axis_drop)), framework::dataset::make("QuantizationInfo", { QuantizationInfo(1.f / 255, 5) })))
+ combine(combine(combine(combine(datasets::Large4DShapes(), framework::dataset::make("DataType", DataType::QASYMM8)), concat(axis_keep, axis_drop)),
+ framework::dataset::make("QuantizationInfoInput", { QuantizationInfo(1.f / 255, 5) })),
+ framework::dataset::make("QuantizationInfoOutput", { QuantizationInfo(1.f / 255, 5) })))
{
// Validate output
validate(CLAccessor(_target), _reference, tolerance_qasymm8);
@@ -153,16 +170,33 @@
FIXTURE_DATA_TEST_CASE(RunSmall,
CLReduceMeanQuantizedFixture<int8_t>,
framework::DatasetMode::PRECOMMIT,
- combine(combine(combine(datasets::Small4DShapes(), framework::dataset::make("DataType", DataType::QASYMM8_SIGNED)), concat(axis_keep, axis_drop)), framework::dataset::make("QuantizationInfo", { QuantizationInfo(1.f / 102, 2) })))
+ combine(combine(combine(combine(datasets::Small4DShapes(), framework::dataset::make("DataType", DataType::QASYMM8_SIGNED)), concat(axis_keep, axis_drop)),
+ framework::dataset::make("QuantizationInfoInput", { QuantizationInfo(1.f / 102, 2) })),
+ framework::dataset::make("QuantizationInfoOutput", { QuantizationInfo(1.f / 102, 2) })))
{
// Validate output
validate(CLAccessor(_target), _reference, tolerance_qasymm8);
}
+TEST_SUITE(Requant)
+FIXTURE_DATA_TEST_CASE(RunSmall,
+ CLReduceMeanQuantizedFixture<int8_t>,
+ framework::DatasetMode::PRECOMMIT,
+ combine(combine(combine(combine(datasets::Small4DShapes(), framework::dataset::make("DataType", DataType::QASYMM8_SIGNED)), axis_drop),
+ framework::dataset::make("QuantizationInfoInput", { QuantizationInfo(1.f / 102, 2) })),
+ framework::dataset::make("QuantizationInfoOutput", { QuantizationInfo(1.f / 113, 10) })))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference, tolerance_qasymm8);
+}
+TEST_SUITE_END() // Requant
+
FIXTURE_DATA_TEST_CASE(RunLarge,
CLReduceMeanQuantizedFixture<int8_t>,
framework::DatasetMode::NIGHTLY,
- combine(combine(combine(datasets::Large4DShapes(), framework::dataset::make("DataType", DataType::QASYMM8_SIGNED)), concat(axis_keep, axis_drop)), framework::dataset::make("QuantizationInfo", { QuantizationInfo(1.f / 102, 2) })))
+ combine(combine(combine(combine(datasets::Large4DShapes(), framework::dataset::make("DataType", DataType::QASYMM8_SIGNED)), concat(axis_keep, axis_drop)),
+ framework::dataset::make("QuantizationInfoInput", { QuantizationInfo(1.f / 102, 2) })),
+ framework::dataset::make("QuantizationInfoOutput", { QuantizationInfo(1.f / 102, 2) })))
{
// Validate output
validate(CLAccessor(_target), _reference, tolerance_qasymm8);
diff --git a/tests/validation/NEON/ReduceMean.cpp b/tests/validation/NEON/ReduceMean.cpp
index 23229a0..e5a5a17 100644
--- a/tests/validation/NEON/ReduceMean.cpp
+++ b/tests/validation/NEON/ReduceMean.cpp
@@ -160,16 +160,33 @@
FIXTURE_DATA_TEST_CASE(RunSmall,
NEReduceMeanQuantizedFixture<uint8_t>,
framework::DatasetMode::PRECOMMIT,
- combine(combine(combine(datasets::Small4DShapes(), framework::dataset::make("DataType", DataType::QASYMM8)), concat(axis_keep, axis_drop)), framework::dataset::make("QuantizationInfo", { QuantizationInfo(1.f / 255, 5) })))
+ combine(combine(combine(combine(datasets::Small4DShapes(), framework::dataset::make("DataType", DataType::QASYMM8)), concat(axis_keep, axis_drop)),
+ framework::dataset::make("QuantizationInfoInput", { QuantizationInfo(1.f / 255, 5) })),
+ framework::dataset::make("QuantizationInfoOutput", { QuantizationInfo(1.f / 255, 5) })))
{
// Validate output
validate(Accessor(_target), _reference, tolerance_u8);
}
+TEST_SUITE(Requant)
+FIXTURE_DATA_TEST_CASE(RunSmall,
+ NEReduceMeanQuantizedFixture<uint8_t>,
+ framework::DatasetMode::PRECOMMIT,
+ combine(combine(combine(combine(datasets::Small4DShapes(), framework::dataset::make("DataType", DataType::QASYMM8)), axis_drop),
+ framework::dataset::make("QuantizationInfoInput", { QuantizationInfo(1.f / 255, 5) })),
+ framework::dataset::make("QuantizationInfoOutput", { QuantizationInfo(1.f / 200, 16) })))
+{
+ // Validate output
+ validate(Accessor(_target), _reference, tolerance_u8);
+}
+TEST_SUITE_END() // Requant
+
FIXTURE_DATA_TEST_CASE(RunLarge,
NEReduceMeanQuantizedFixture<uint8_t>,
framework::DatasetMode::NIGHTLY,
- combine(combine(combine(datasets::Large4DShapes(), framework::dataset::make("DataType", DataType::QASYMM8)), concat(axis_keep, axis_drop)), framework::dataset::make("QuantizationInfo", { QuantizationInfo(1.f / 255, 5) })))
+ combine(combine(combine(combine(datasets::Large4DShapes(), framework::dataset::make("DataType", DataType::QASYMM8)), concat(axis_keep, axis_drop)),
+ framework::dataset::make("QuantizationInfoInput", { QuantizationInfo(1.f / 255, 5) })),
+ framework::dataset::make("QuantizationInfoOutput", { QuantizationInfo(1.f / 255, 5) })))
{
// Validate output
validate(Accessor(_target), _reference, tolerance_u8);
@@ -180,15 +197,32 @@
FIXTURE_DATA_TEST_CASE(RunSmall,
NEReduceMeanQuantizedFixture<int8_t>,
framework::DatasetMode::PRECOMMIT,
- combine(combine(combine(datasets::Small4DShapes(), framework::dataset::make("DataType", DataType::QASYMM8_SIGNED)), concat(axis_keep, axis_drop)), framework::dataset::make("QuantizationInfo", { QuantizationInfo(1.f / 127, -10), QuantizationInfo(1.f / 250, -20) })))
+ combine(combine(combine(combine(datasets::Small4DShapes(), framework::dataset::make("DataType", DataType::QASYMM8_SIGNED)), concat(axis_keep, axis_drop)),
+ framework::dataset::make("QuantizationInfoInput", { QuantizationInfo(1.f / 127, -10), QuantizationInfo(1.f / 250, -20) })),
+ framework::dataset::make("QuantizationInfoInputOutput", { QuantizationInfo(1.f / 127, -10) })))
{
// Validate output
validate(Accessor(_target), _reference, tolerance_s8);
}
+TEST_SUITE(Requant)
+FIXTURE_DATA_TEST_CASE(RunSmall,
+ NEReduceMeanQuantizedFixture<int8_t>,
+ framework::DatasetMode::PRECOMMIT,
+ combine(combine(combine(combine(datasets::Small4DShapes(), framework::dataset::make("DataType", DataType::QASYMM8_SIGNED)), axis_drop),
+ framework::dataset::make("QuantizationInfoInput", { QuantizationInfo(1.f / 102, 2) })),
+ framework::dataset::make("QuantizationInfoOutput", { QuantizationInfo(1.f / 113, 10) })))
+{
+ // Validate output
+ validate(Accessor(_target), _reference, tolerance_s8);
+}
+TEST_SUITE_END() // Requant
+
FIXTURE_DATA_TEST_CASE(RunLarge,
NEReduceMeanQuantizedFixture<int8_t>,
framework::DatasetMode::NIGHTLY,
- combine(combine(combine(datasets::Large4DShapes(), framework::dataset::make("DataType", DataType::QASYMM8_SIGNED)), concat(axis_keep, axis_drop)), framework::dataset::make("QuantizationInfo", { QuantizationInfo(1.f / 127, 0) })))
+ combine(combine(combine(combine(datasets::Large4DShapes(), framework::dataset::make("DataType", DataType::QASYMM8_SIGNED)), concat(axis_keep, axis_drop)),
+ framework::dataset::make("QuantizationInfoInput", { QuantizationInfo(1.f / 127, -10) })),
+ framework::dataset::make("QuantizationInfoInputOutput", { QuantizationInfo(1.f / 127, -10) })))
{
// Validate output
validate(Accessor(_target), _reference, tolerance_s8);
diff --git a/tests/validation/fixtures/ReduceMeanFixture.h b/tests/validation/fixtures/ReduceMeanFixture.h
index d102921..7288761 100644
--- a/tests/validation/fixtures/ReduceMeanFixture.h
+++ b/tests/validation/fixtures/ReduceMeanFixture.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2018-2019 Arm Limited.
+ * Copyright (c) 2018-2020 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -26,6 +26,7 @@
#include "arm_compute/core/TensorShape.h"
#include "arm_compute/core/Types.h"
+#include "arm_compute/core/utils/misc/ShapeCalculator.h"
#include "arm_compute/runtime/Tensor.h"
#include "tests/AssetsLibrary.h"
#include "tests/Globals.h"
@@ -47,10 +48,10 @@
{
public:
template <typename...>
- void setup(TensorShape shape, DataType data_type, Coordinates axis, bool keep_dims, QuantizationInfo quantization_info)
+ void setup(TensorShape shape, DataType data_type, Coordinates axis, bool keep_dims, QuantizationInfo quantization_info_input, QuantizationInfo quantization_info_output)
{
- _target = compute_target(shape, data_type, axis, keep_dims, quantization_info);
- _reference = compute_reference(shape, data_type, axis, keep_dims, quantization_info);
+ _target = compute_target(shape, data_type, axis, keep_dims, quantization_info_input, quantization_info_output);
+ _reference = compute_reference(shape, data_type, axis, keep_dims, quantization_info_input, quantization_info_output);
}
protected:
@@ -71,11 +72,12 @@
}
}
- TensorType compute_target(TensorShape &src_shape, DataType data_type, Coordinates axis, bool keep_dims, QuantizationInfo quantization_info)
+ TensorType compute_target(TensorShape &src_shape, DataType data_type, Coordinates axis, bool keep_dims, QuantizationInfo quantization_info_input, QuantizationInfo quantization_info_output)
{
// Create tensors
- TensorType src = create_tensor<TensorType>(src_shape, data_type, 1, quantization_info);
- TensorType dst;
+ TensorType src = create_tensor<TensorType>(src_shape, data_type, 1, quantization_info_input);
+ TensorShape dst_shape = arm_compute::misc::shape_calculator::calculate_reduce_mean_shape(src.info(), axis, keep_dims);
+ TensorType dst = create_tensor<TensorType>(dst_shape, data_type, 1, quantization_info_output);
// Create and configure function
FunctionType reduction_mean;
@@ -100,10 +102,10 @@
return dst;
}
- SimpleTensor<T> compute_reference(TensorShape &src_shape, DataType data_type, Coordinates axis, bool keep_dims, QuantizationInfo quantization_info)
+ SimpleTensor<T> compute_reference(TensorShape &src_shape, DataType data_type, Coordinates axis, bool keep_dims, QuantizationInfo quantization_info_input, QuantizationInfo quantization_info_output)
{
// Create reference
- SimpleTensor<T> src{ src_shape, data_type, 1, quantization_info };
+ SimpleTensor<T> src{ src_shape, data_type, 1, quantization_info_input };
// Fill reference
fill(src);
@@ -113,7 +115,7 @@
{
TensorShape output_shape = i == 0 ? src_shape : out.shape();
output_shape.set(axis[i], 1);
- out = reference::reduction_operation<T, T>(i == 0 ? src : out, output_shape, axis[i], ReductionOperation::MEAN_SUM);
+ out = reference::reduction_operation<T, T>(i == 0 ? src : out, output_shape, axis[i], ReductionOperation::MEAN_SUM, quantization_info_output);
}
if(!keep_dims)
@@ -139,9 +141,9 @@
{
public:
template <typename...>
- void setup(TensorShape shape, DataType data_type, Coordinates axis, bool keep_dims, QuantizationInfo quantization_info = QuantizationInfo())
+ void setup(TensorShape shape, DataType data_type, Coordinates axis, bool keep_dims, QuantizationInfo quantization_info_input, QuantizationInfo quantization_info_output)
{
- ReduceMeanValidationFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, data_type, axis, keep_dims, quantization_info);
+ ReduceMeanValidationFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, data_type, axis, keep_dims, quantization_info_input, quantization_info_output);
}
};
@@ -152,7 +154,7 @@
template <typename...>
void setup(TensorShape shape, DataType data_type, Coordinates axis, bool keep_dims)
{
- ReduceMeanValidationFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, data_type, axis, keep_dims, QuantizationInfo());
+ ReduceMeanValidationFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, data_type, axis, keep_dims, QuantizationInfo(), QuantizationInfo());
}
};
} // namespace validation
diff --git a/tests/validation/fixtures/ReductionOperationFixture.h b/tests/validation/fixtures/ReductionOperationFixture.h
index 3fb8544..646518d 100644
--- a/tests/validation/fixtures/ReductionOperationFixture.h
+++ b/tests/validation/fixtures/ReductionOperationFixture.h
@@ -126,7 +126,7 @@
// Fill reference
fill(src);
- return reference::reduction_operation<T, T>(src, dst_shape, axis, op);
+ return reference::reduction_operation<T, T>(src, dst_shape, axis, op, quantization_info);
}
TensorType _target{};
diff --git a/tests/validation/reference/ReductionOperation.cpp b/tests/validation/reference/ReductionOperation.cpp
index 5bdd4f7..ffb79f8 100644
--- a/tests/validation/reference/ReductionOperation.cpp
+++ b/tests/validation/reference/ReductionOperation.cpp
@@ -269,18 +269,19 @@
}
template <typename T, typename OT>
-SimpleTensor<OT> reduction_operation(const SimpleTensor<T> &src, const TensorShape &dst_shape, unsigned int axis, ReductionOperation op)
+SimpleTensor<OT> reduction_operation(const SimpleTensor<T> &src, const TensorShape &dst_shape, unsigned int axis, ReductionOperation op, QuantizationInfo quantization_info_output)
{
+ ARM_COMPUTE_UNUSED(quantization_info_output);
return compute_reduction_operation<T, OT>(src, dst_shape, axis, op);
}
template <>
-SimpleTensor<uint8_t> reduction_operation(const SimpleTensor<uint8_t> &src, const TensorShape &dst_shape, unsigned int axis, ReductionOperation op)
+SimpleTensor<uint8_t> reduction_operation(const SimpleTensor<uint8_t> &src, const TensorShape &dst_shape, unsigned int axis, ReductionOperation op, QuantizationInfo quantization_info_output)
{
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)
+ if(op == ReductionOperation::MEAN_SUM && src.quantization_info() == quantization_info_output)
{
return compute_reduction_operation<uint8_t, uint8_t>(src, dst_shape, axis, op);
}
@@ -288,7 +289,7 @@
{
SimpleTensor<float> src_f = convert_from_asymmetric(src);
SimpleTensor<float> dst_f = reference::reduction_operation<float, float>(src_f, dst_shape, axis, op);
- return convert_to_asymmetric<uint8_t>(dst_f, src.quantization_info());
+ return convert_to_asymmetric<uint8_t>(dst_f, quantization_info_output);
}
}
else
@@ -298,12 +299,12 @@
}
template <>
-SimpleTensor<int8_t> reduction_operation(const SimpleTensor<int8_t> &src, const TensorShape &dst_shape, unsigned int axis, ReductionOperation op)
+SimpleTensor<int8_t> reduction_operation(const SimpleTensor<int8_t> &src, const TensorShape &dst_shape, unsigned int axis, ReductionOperation op, QuantizationInfo quantization_info_output)
{
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)
+ if(op == ReductionOperation::MEAN_SUM && src.quantization_info() == quantization_info_output)
{
return compute_reduction_operation<int8_t, int8_t>(src, dst_shape, axis, op);
}
@@ -311,7 +312,7 @@
{
SimpleTensor<float> src_f = convert_from_asymmetric(src);
SimpleTensor<float> dst_f = reference::reduction_operation<float, float>(src_f, dst_shape, axis, op);
- return convert_to_asymmetric<int8_t>(dst_f, src.quantization_info());
+ return convert_to_asymmetric<int8_t>(dst_f, quantization_info_output);
}
}
else
@@ -320,14 +321,21 @@
}
}
-template SimpleTensor<float> reduction_operation(const SimpleTensor<float> &src, const TensorShape &dst_shape, unsigned int axis, ReductionOperation op);
-template SimpleTensor<half> reduction_operation(const SimpleTensor<half> &src, const TensorShape &dst_shape, unsigned int axis, ReductionOperation op);
+template SimpleTensor<float> reduction_operation(const SimpleTensor<float> &src, const TensorShape &dst_shape, unsigned int axis, ReductionOperation op,
+ QuantizationInfo quantization_info_output = QuantizationInfo());
+template SimpleTensor<half> reduction_operation(const SimpleTensor<half> &src, const TensorShape &dst_shape, unsigned int axis, ReductionOperation op,
+ QuantizationInfo quantization_info_output = QuantizationInfo());
-template SimpleTensor<int32_t> reduction_operation(const SimpleTensor<float> &src, const TensorShape &dst_shape, unsigned int axis, ReductionOperation op);
-template SimpleTensor<int32_t> reduction_operation(const SimpleTensor<int32_t> &src, const TensorShape &dst_shape, unsigned int axis, ReductionOperation op);
-template SimpleTensor<int32_t> reduction_operation(const SimpleTensor<half> &src, const TensorShape &dst_shape, unsigned int axis, ReductionOperation op);
-template SimpleTensor<int32_t> reduction_operation(const SimpleTensor<uint8_t> &src, const TensorShape &dst_shape, unsigned int axis, ReductionOperation op);
-template SimpleTensor<int32_t> reduction_operation(const SimpleTensor<int8_t> &src, const TensorShape &dst_shape, unsigned int axis, ReductionOperation op);
+template SimpleTensor<int32_t> reduction_operation(const SimpleTensor<float> &src, const TensorShape &dst_shape, unsigned int axis, ReductionOperation op,
+ QuantizationInfo quantization_info_output = QuantizationInfo());
+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());
+template SimpleTensor<int32_t> reduction_operation(const SimpleTensor<half> &src, const TensorShape &dst_shape, unsigned int axis, ReductionOperation op,
+ QuantizationInfo quantization_info_output = QuantizationInfo());
+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());
+template SimpleTensor<int32_t> reduction_operation(const SimpleTensor<int8_t> &src, const TensorShape &dst_shape, unsigned int axis, ReductionOperation op,
+ QuantizationInfo quantization_info_output = QuantizationInfo());
} // namespace reference
} // namespace validation
diff --git a/tests/validation/reference/ReductionOperation.h b/tests/validation/reference/ReductionOperation.h
index 56d37e4..9c9e721 100644
--- a/tests/validation/reference/ReductionOperation.h
+++ b/tests/validation/reference/ReductionOperation.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017-2019 Arm Limited.
+ * Copyright (c) 2017-2020 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -36,7 +36,8 @@
namespace reference
{
template <typename T, typename OT>
-SimpleTensor<OT> reduction_operation(const SimpleTensor<T> &src, const TensorShape &dst_shape, unsigned int axis, ReductionOperation op);
+SimpleTensor<OT> reduction_operation(const SimpleTensor<T> &src, const TensorShape &dst_shape, unsigned int axis, ReductionOperation op,
+ QuantizationInfo quantization_info_output = QuantizationInfo());
} // namespace reference
} // namespace validation
} // namespace test