arm_compute v19.11
diff --git a/src/runtime/CL/functions/CLPadLayer.cpp b/src/runtime/CL/functions/CLPadLayer.cpp
index 99e3121..8f36a69 100644
--- a/src/runtime/CL/functions/CLPadLayer.cpp
+++ b/src/runtime/CL/functions/CLPadLayer.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2018-2019 ARM Limited.
+ * Copyright (c) 2019 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -23,183 +23,25 @@
*/
#include "arm_compute/runtime/CL/functions/CLPadLayer.h"
-#include "arm_compute/core/CL/ICLTensor.h"
-#include "arm_compute/core/Types.h"
-#include "arm_compute/core/utils/misc/ShapeCalculator.h"
-#include "support/ToolchainSupport.h"
-
namespace arm_compute
{
CLPadLayer::CLPadLayer()
- : _copy_kernel(), _mode(), _padding(), _memset_kernel(), _num_dimensions(0), _slice_functions(), _concat_functions(), _slice_results(), _concat_results()
+ : _pad_kernel(), _copy_kernel(), _perform_pad(false)
{
}
-void CLPadLayer::configure_constant_mode(ICLTensor *input, ICLTensor *output, const PaddingList &padding, const PixelValue constant_value)
-{
- // Set the pages of the output to the constant_value.
- _memset_kernel.configure(output, constant_value);
-
- // Fill out padding list with zeroes.
- PaddingList padding_extended = padding;
- for(size_t i = padding.size(); i < TensorShape::num_max_dimensions; i++)
- {
- padding_extended.emplace_back(PaddingInfo{ 0, 0 });
- }
-
- // Create a window within the output tensor where the input will be copied.
- Window copy_window = Window();
- for(uint32_t i = 0; i < output->info()->num_dimensions(); ++i)
- {
- copy_window.set(i, Window::Dimension(padding_extended[i].first, padding_extended[i].first + input->info()->dimension(i), 1));
- }
- // Copy the input to the output, leaving the padding filled with the constant_value.
- _copy_kernel.configure(input, output, PaddingList(), ©_window);
-}
-
-void CLPadLayer::configure_reflect_symmetric_mode(ICLTensor *input, ICLTensor *output)
-{
- int64_t last_padding_dimension = _padding.size() - 1;
- // Reflecting can be performed by effectively unfolding the input as follows:
- // For each dimension starting at DimX:
- // Create a before and after slice, which values depend on the selected padding mode
- // Concatenate the before and after padding with the tensor to be padded
-
- // Two strided slice functions will be required for each dimension padded as well as a
- // concatenate function and the tensors to hold the temporary results.
- _slice_functions.resize(2 * _num_dimensions);
- _slice_results.resize(2 * _num_dimensions);
- _concat_functions.resize(_num_dimensions);
- _concat_results.resize(_num_dimensions - 1);
-
- Coordinates starts_before{};
- Coordinates ends_before{};
- Coordinates starts_after{};
- Coordinates ends_after{};
- Coordinates strides{};
- ICLTensor *prev = input;
- for(uint32_t i = 0; i < _num_dimensions; ++i)
- {
- // Values in strides from the previous dimensions need to be set to 1 to avoid reversing again.
- if(i > 0)
- {
- strides.set(i - 1, 1);
- }
-
- if(_padding[i].first > 0 || _padding[i].second > 0)
- {
- // Set the starts, ends, and strides values for the current dimension.
- // Due to the bit masks passed to strided slice, the values below the current dimension in
- // starts and ends will be ignored so do not need to be modified.
- if(_mode == PaddingMode::REFLECT)
- {
- starts_before.set(i, _padding[i].first);
- ends_before.set(i, 0);
- starts_after.set(i, input->info()->dimension(i) - 2);
- ends_after.set(i, input->info()->dimension(i) - _padding[i].second - 2);
- strides.set(i, -1);
- }
- else
- {
- starts_before.set(i, _padding[i].first - 1);
- ends_before.set(i, -1);
- starts_after.set(i, input->info()->dimension(i) - 1);
- ends_after.set(i, input->info()->dimension(i) - _padding[i].second - 1);
- strides.set(i, -1);
- }
-
- // Strided slice wraps negative indexes around to the end of the range,
- // instead this should indicate use of the full range and so the bit mask will be modified.
- const int32_t begin_mask_before = starts_before[i] < 0 ? ~0 : ~(1u << i);
- const int32_t end_mask_before = ends_before[i] < 0 ? ~0 : ~(1u << i);
- const int32_t begin_mask_after = starts_after[i] < 0 ? ~0 : ~(1u << i);
- const int32_t end_mask_after = ends_after[i] < 0 ? ~0 : ~(1u << i);
-
- // Reflect the input values for the padding before and after the input.
- std::vector<ICLTensor *> concat_vector;
- if(_padding[i].first > 0)
- {
- if(i < prev->info()->num_dimensions())
- {
- _slice_functions[2 * i].configure(prev, &_slice_results[2 * i], starts_before, ends_before, strides, begin_mask_before, end_mask_before);
- concat_vector.push_back(&_slice_results[2 * i]);
- }
- else
- {
- // Performing the slice is unnecessary if the result would simply be a copy of the tensor.
- concat_vector.push_back(prev);
- }
- }
- concat_vector.push_back(prev);
- if(_padding[i].second > 0)
- {
- if(i < prev->info()->num_dimensions())
- {
- _slice_functions[2 * i + 1].configure(prev, &_slice_results[2 * i + 1], starts_after, ends_after, strides, begin_mask_after, end_mask_after);
- concat_vector.push_back(&_slice_results[2 * i + 1]);
- }
- else
- {
- // Performing the slice is unnecessary if the result would simply be a copy of the tensor.
- concat_vector.push_back(prev);
- }
- }
- // Concatenate the padding before and after with the input.
- ICLTensor *out = (static_cast<int32_t>(i) == last_padding_dimension) ? output : &_concat_results[i];
- _concat_functions[i].configure(concat_vector, out, i);
- prev = out;
- }
- }
- for(uint32_t i = 0; i < _num_dimensions; ++i)
- {
- if((static_cast<int32_t>(i) != last_padding_dimension))
- {
- _concat_results[i].allocator()->allocate();
- }
- _slice_results[2 * i].allocator()->allocate();
- _slice_results[2 * i + 1].allocator()->allocate();
- }
-}
-
void CLPadLayer::configure(ICLTensor *input, ICLTensor *output, const PaddingList &padding, PixelValue constant_value, PaddingMode mode)
{
ARM_COMPUTE_ERROR_THROW_ON(validate(input->info(), output->info(), padding, constant_value, mode));
- _padding = padding;
- _mode = mode;
-
- TensorShape padded_shape = misc::shape_calculator::compute_padded_shape(input->info()->tensor_shape(), _padding);
-
- auto_init_if_empty(*output->info(), input->info()->clone()->set_tensor_shape(padded_shape));
-
- // Find the last dimension requiring padding so that it is known when to write to output and whether any padding is applied.
- int64_t last_padding_dimension = _padding.size() - 1;
- for(; last_padding_dimension >= 0; --last_padding_dimension)
+ _perform_pad = std::any_of(padding.begin(), padding.end(), [](PaddingInfo info)
{
- if(_padding[last_padding_dimension].first > 0 || _padding[last_padding_dimension].second > 0)
- {
- break;
- }
- }
- _num_dimensions = last_padding_dimension + 1;
- if(_num_dimensions > 0)
+ return info.first > 0 || info.second > 0;
+ });
+
+ if(_perform_pad)
{
- switch(_mode)
- {
- case PaddingMode::CONSTANT:
- {
- configure_constant_mode(input, output, padding, constant_value);
- break;
- }
- case PaddingMode::REFLECT:
- case PaddingMode::SYMMETRIC:
- {
- configure_reflect_symmetric_mode(input, output);
- break;
- }
- default:
- ARM_COMPUTE_ERROR("Padding mode not supported.");
- }
+ _pad_kernel.configure(input, output, padding, constant_value, mode);
}
else
{
@@ -207,111 +49,34 @@
_copy_kernel.configure(input, output);
}
}
-
Status CLPadLayer::validate(const ITensorInfo *input, const ITensorInfo *output, const PaddingList &padding, PixelValue constant_value, PaddingMode mode)
{
- ARM_COMPUTE_RETURN_ERROR_ON(padding.size() > input->num_dimensions());
-
- TensorShape padded_shape = misc::shape_calculator::compute_padded_shape(input->tensor_shape(), padding);
-
- // Use CLCopyKernel and CLMemsetKernel to validate all padding modes as this includes all of the shape and info validation.
- PaddingList padding_extended = padding;
- for(size_t i = padding.size(); i < TensorShape::num_max_dimensions; i++)
+ bool perform_pad = std::any_of(padding.begin(), padding.end(), [](PaddingInfo info)
{
- padding_extended.emplace_back(PaddingInfo{ 0, 0 });
- }
+ return info.first > 0 || info.second > 0;
+ });
- Window copy_window = Window();
- for(uint32_t i = 0; i < padded_shape.num_dimensions(); ++i)
+ if(perform_pad)
{
- copy_window.set(i, Window::Dimension(padding_extended[i].first, padding_extended[i].first + input->dimension(i), 1));
- }
- if(output->total_size() > 0)
- {
- ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(output->tensor_shape(), padded_shape);
- ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(output, input);
- ARM_COMPUTE_RETURN_ON_ERROR(CLCopyKernel::validate(input, output, PaddingList(), ©_window));
- ARM_COMPUTE_RETURN_ON_ERROR(CLMemsetKernel::validate(output, constant_value));
+ ARM_COMPUTE_RETURN_ON_ERROR(CLPadLayerKernel::validate(input, output, padding, constant_value, mode));
}
else
{
- ARM_COMPUTE_RETURN_ON_ERROR(CLCopyKernel::validate(input, &input->clone()->set_tensor_shape(padded_shape), PaddingList(), ©_window));
- ARM_COMPUTE_RETURN_ON_ERROR(CLMemsetKernel::validate(&input->clone()->set_tensor_shape(padded_shape), constant_value));
- }
-
- switch(mode)
- {
- case PaddingMode::CONSTANT:
- {
- break;
- }
- case PaddingMode::REFLECT:
- case PaddingMode::SYMMETRIC:
- {
- for(uint32_t i = 0; i < padding.size(); ++i)
- {
- if(mode == PaddingMode::REFLECT)
- {
- ARM_COMPUTE_RETURN_ERROR_ON(padding[i].first >= input->dimension(i));
- ARM_COMPUTE_RETURN_ERROR_ON(padding[i].second >= input->dimension(i));
- }
- else
- {
- ARM_COMPUTE_RETURN_ERROR_ON(padding[i].first > input->dimension(i));
- ARM_COMPUTE_RETURN_ERROR_ON(padding[i].second > input->dimension(i));
- }
- }
- break;
- }
- default:
- {
- ARM_COMPUTE_ERROR("Invalid mode");
- }
+ Window copy_window = Window();
+ copy_window.use_tensor_dimensions(output->tensor_shape());
+ ARM_COMPUTE_RETURN_ON_ERROR(CLCopyKernel::validate(input, output, PaddingList(), ©_window));
}
return Status{};
}
-
void CLPadLayer::run()
{
- if(_num_dimensions > 0)
+ if(_perform_pad)
{
- switch(_mode)
- {
- case PaddingMode::CONSTANT:
- {
- CLScheduler::get().enqueue(_memset_kernel, false);
- CLScheduler::get().enqueue(_copy_kernel, true);
- break;
- }
- case PaddingMode::REFLECT:
- case PaddingMode::SYMMETRIC:
- {
- for(uint32_t i = 0; i < _num_dimensions; ++i)
- {
- if(_padding[i].first > 0 || _padding[i].second > 0)
- {
- if(_padding[i].first > 0 && _slice_results[2 * i].info()->total_size() > 0)
- {
- _slice_functions[2 * i].run();
- }
- if(_padding[i].second > 0 && _slice_results[2 * i + 1].info()->total_size() > 0)
- {
- _slice_functions[2 * i + 1].run();
- }
- CLScheduler::get().sync();
- _concat_functions[i].run();
- CLScheduler::get().sync();
- }
- }
- break;
- }
- default:
- ARM_COMPUTE_ERROR("Padding mode not supported.");
- }
+ CLScheduler::get().enqueue(_pad_kernel);
}
else
{
- CLScheduler::get().enqueue(_copy_kernel, true);
+ CLScheduler::get().enqueue(_copy_kernel);
}
}
-} // namespace arm_compute
+} // namespace arm_compute
\ No newline at end of file