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/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