diff options
Diffstat (limited to 'src/runtime/CL/functions/CLReduceMean.cpp')
| -rw-r--r-- | src/runtime/CL/functions/CLReduceMean.cpp | 120 |
1 files changed, 69 insertions, 51 deletions
diff --git a/src/runtime/CL/functions/CLReduceMean.cpp b/src/runtime/CL/functions/CLReduceMean.cpp index a3634cd46e..c5de43da35 100644 --- a/src/runtime/CL/functions/CLReduceMean.cpp +++ b/src/runtime/CL/functions/CLReduceMean.cpp @@ -26,20 +26,81 @@ #include "arm_compute/core/CL/CLValidate.h" #include "arm_compute/core/CL/ICLTensor.h" #include "arm_compute/core/CL/kernels/CLReductionOperationKernel.h" +#include "arm_compute/core/Error.h" #include "arm_compute/core/Types.h" #include "arm_compute/core/utils/helpers/tensor_transform.h" +#include "arm_compute/core/utils/misc/ShapeCalculator.h" #include "arm_compute/runtime/CL/CLScheduler.h" #include "support/ToolchainSupport.h" namespace arm_compute { +namespace +{ +Status validate_config(const ITensorInfo *input, const Coordinates &reduction_axis, bool keep_dims, const ITensorInfo *output) +{ + ARM_COMPUTE_UNUSED(keep_dims); + ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output); + ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input); + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::F16, DataType::F32); + ARM_COMPUTE_RETURN_ERROR_ON(reduction_axis.num_dimensions() < 1); + ARM_COMPUTE_RETURN_ERROR_ON(reduction_axis.num_dimensions() > input->num_dimensions()); + + const unsigned int reduction_ops = reduction_axis.num_dimensions(); + const int input_dims = input->num_dimensions(); + Coordinates axis_local = reduction_axis; + + for(unsigned int i = 0; i < axis_local.num_dimensions(); ++i) + { + //axis: The dimensions to reduce. Must be in the range [-rank(input_tensor), rank(input_tensor)). + ARM_COMPUTE_RETURN_ERROR_ON(axis_local[i] < (-static_cast<int>(input->num_dimensions()))); + ARM_COMPUTE_RETURN_ERROR_ON(axis_local[i] >= static_cast<int>(input->num_dimensions())); + } + + if(output->tensor_shape().total_size() != 0) + { + // Only validate if not using auto_init for the output tensor + TensorShape out_shape = input->tensor_shape(); + // Validate output_shape only if not using auto_init + convert_negative_axis(axis_local, input_dims); + std::sort(axis_local.begin(), axis_local.begin() + reduction_ops); + for(unsigned int i = 0; i < reduction_ops; ++i) + { + ARM_COMPUTE_RETURN_ERROR_ON(axis_local[i] > 3); + ARM_COMPUTE_RETURN_ERROR_ON(static_cast<unsigned int>(axis_local[i]) > input->num_dimensions() - 1); + if(output->total_size() > 0 && keep_dims) + { + ARM_COMPUTE_RETURN_ERROR_ON(output->dimension(axis_local[i]) != 1); + } + if(keep_dims) + { + out_shape.set(axis_local[i], 1); + } + else + { + ARM_COMPUTE_RETURN_ERROR_ON(i > static_cast<unsigned int>(axis_local[i])); + const unsigned int remove_index = axis_local[i] - i; + ARM_COMPUTE_RETURN_ERROR_ON(remove_index >= out_shape.num_dimensions()); + out_shape.remove_dimension(remove_index); + } + } + const TensorInfo out_info = input->clone()->set_tensor_shape(out_shape); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(output, &out_info); + } + 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() { } void CLReduceMean::configure(ICLTensor *input, const Coordinates &reduction_axis, bool keep_dims, ICLTensor *output) { - ARM_COMPUTE_ERROR_ON_NULLPTR(input); + // 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); + auto_init_if_empty(*output->info(), input->info()->clone()->set_tensor_shape(output_shape)); _reduction_ops = reduction_axis.num_dimensions(); _reduction_kernels.resize(_reduction_ops); @@ -49,14 +110,10 @@ void CLReduceMean::configure(ICLTensor *input, const Coordinates &reduction_axis Coordinates axis_local = reduction_axis; const int input_dims = input->info()->num_dimensions(); - // Convert negative axis - for(unsigned int i = 0; i < _reduction_ops; ++i) - { - axis_local[i] = wrap_around(axis_local[i], input_dims); - } + convert_negative_axis(axis_local, input_dims); // Perform reduction for every axis - for(unsigned int i = 0; i < _reduction_ops; ++i) + for(int i = 0; i < _reduction_ops; ++i) { TensorShape out_shape = i == 0 ? input->info()->tensor_shape() : (&_reduced_outs[i - 1])->info()->tensor_shape(); out_shape.set(axis_local[i], 1); @@ -75,7 +132,7 @@ void CLReduceMean::configure(ICLTensor *input, const Coordinates &reduction_axis } // Allocate intermediate tensors - for(unsigned int i = 0; i < _reduction_ops - (keep_dims ? 1 : 0); ++i) + for(int i = 0; i < _reduction_ops - (keep_dims ? 1 : 0); ++i) { _reduced_outs[i].allocator()->allocate(); } @@ -88,7 +145,7 @@ void CLReduceMean::configure(ICLTensor *input, const Coordinates &reduction_axis // 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); - for(unsigned int i = 0; i < _reduction_ops; ++i) + for(int i = 0; i < _reduction_ops; ++i) { out_shape.remove_dimension(axis_local[i] - i); } @@ -99,55 +156,16 @@ void CLReduceMean::configure(ICLTensor *input, const Coordinates &reduction_axis Status CLReduceMean::validate(const ITensorInfo *input, const Coordinates &reduction_axis, bool keep_dims, const ITensorInfo *output) { - ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input); - ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input); - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::F16, DataType::F32); - ARM_COMPUTE_RETURN_ERROR_ON(reduction_axis.num_dimensions() > input->num_dimensions()); - - TensorShape out_shape = input->tensor_shape(); - - Coordinates axis_sorted = reduction_axis; - const unsigned int reduction_ops = reduction_axis.num_dimensions(); - const int input_dims = input->num_dimensions(); - - // Convert negative axis - for(unsigned int i = 0; i < reduction_ops; ++i) - { - axis_sorted[i] = wrap_around(axis_sorted[i], input_dims); - } - - std::sort(axis_sorted.begin(), axis_sorted.begin() + reduction_ops); - for(unsigned int i = 0; i < reduction_ops; ++i) - { - ARM_COMPUTE_RETURN_ERROR_ON(axis_sorted[i] > 3); - ARM_COMPUTE_RETURN_ERROR_ON(static_cast<unsigned int>(axis_sorted[i]) > input->num_dimensions() - 1); - if(output->total_size() > 0 && keep_dims) - { - ARM_COMPUTE_RETURN_ERROR_ON(output->dimension(axis_sorted[i]) != 1); - } - if(keep_dims) - { - out_shape.set(axis_sorted[i], 1); - } - else - { - out_shape.remove_dimension(axis_sorted[i] - i); - } - } - - const TensorInfo out_info = input->clone()->set_tensor_shape(out_shape); - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(output, &out_info); - - return Status{}; + return validate_config(input, reduction_axis, keep_dims, output); } void CLReduceMean::run() { MemoryGroupResourceScope scope_mg(_memory_group); - for(unsigned int i = 0; i < _reduction_ops; ++i) + for(auto &kernel : _reduction_kernels) { - _reduction_kernels[i].run(); + kernel.run(); } if(!_keep_dims) |