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authorGeorgios Pinitas <georgios.pinitas@arm.com>2018-02-19 13:58:22 +0000
committerAnthony Barbier <anthony.barbier@arm.com>2018-11-02 16:47:40 +0000
commit15997879873b374ea297197fc4aafb15e38b938b (patch)
tree1822578068bd63965865b3898e8d9a1d280c7274 /src/core/CL/kernels
parent933fe86bdc0603c5350fa131df72549933632233 (diff)
downloadComputeLibrary-15997879873b374ea297197fc4aafb15e38b938b.tar.gz
COMPMID-934: Asymmetric padding support.
Change-Id: Ibe7a679e4c053a088b8c893e495c97cb24bf7272 Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/121298 Tested-by: Jenkins <bsgcomp@arm.com> Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
Diffstat (limited to 'src/core/CL/kernels')
-rw-r--r--src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3Kernel.cpp8
-rw-r--r--src/core/CL/kernels/CLDirectConvolutionLayerKernel.cpp25
-rw-r--r--src/core/CL/kernels/CLPoolingLayerKernel.cpp48
3 files changed, 36 insertions, 45 deletions
diff --git a/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3Kernel.cpp b/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3Kernel.cpp
index c7cee4c387..c24420a7e3 100644
--- a/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3Kernel.cpp
+++ b/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3Kernel.cpp
@@ -121,10 +121,10 @@ void CLDepthwiseConvolutionLayer3x3Kernel::configure(const ICLTensor *input, con
const GPUTarget gpu_target = get_arch_from_target(get_target());
// Configure kernel window
- const unsigned int conv_pad_left = std::max(conv_info.pad_left(), 1U);
- const unsigned int conv_pad_top = std::max(conv_info.pad_top(), 1U);
- const unsigned int conv_pad_right = std::max(conv_info.pad_right(), 1U);
- const unsigned int conv_pad_bottom = std::max(conv_info.pad_bottom(), 1U);
+ const unsigned int conv_pad_left = conv_info.pad_left();
+ const unsigned int conv_pad_top = conv_info.pad_top();
+ const unsigned int conv_pad_right = conv_info.pad_right();
+ const unsigned int conv_pad_bottom = conv_info.pad_bottom();
unsigned int num_elems_read_per_iteration_x = 0;
unsigned int num_elems_read_per_iteration_y = 0;
diff --git a/src/core/CL/kernels/CLDirectConvolutionLayerKernel.cpp b/src/core/CL/kernels/CLDirectConvolutionLayerKernel.cpp
index 4b141f7ecd..ac3c9ac4a6 100644
--- a/src/core/CL/kernels/CLDirectConvolutionLayerKernel.cpp
+++ b/src/core/CL/kernels/CLDirectConvolutionLayerKernel.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -126,10 +126,10 @@ std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITen
unsigned int conv_stride_x = std::get<0>(conv_info.stride());
unsigned int conv_stride_y = std::get<1>(conv_info.stride());
- unsigned int conv_pad_left = std::max(conv_info.pad_left(), kernel_size / 2);
- unsigned int conv_pad_top = std::max(conv_info.pad_top(), kernel_size / 2);
- unsigned int conv_pad_right = std::max(conv_info.pad_right(), kernel_size / 2);
- unsigned int conv_pad_bottom = std::max(conv_info.pad_bottom(), kernel_size / 2);
+ unsigned int conv_pad_left = conv_info.pad_left();
+ unsigned int conv_pad_top = conv_info.pad_top();
+ unsigned int conv_pad_right = conv_info.pad_right();
+ unsigned int conv_pad_bottom = conv_info.pad_bottom();
unsigned int num_elems_read_per_iteration_x = 0;
unsigned int num_elems_read_per_iteration_y = 0;
@@ -302,18 +302,13 @@ void CLDirectConvolutionLayerKernel::configure(const ICLTensor *input, const ICL
_conv_stride_x = std::get<0>(conv_info.stride());
_conv_stride_y = std::get<1>(conv_info.stride());
+ _border_size = BorderSize(conv_info.pad_top(), conv_info.pad_right(), conv_info.pad_bottom(), conv_info.pad_left());
_input = input;
_weights = weights;
_output = output;
_biases = biases;
- int conv_pad_left = std::min(conv_info.pad_left(), kernel_size / 2);
- int conv_pad_top = std::min(conv_info.pad_top(), kernel_size / 2);
- int conv_pad_right = std::min(conv_info.pad_right(), kernel_size / 2);
- int conv_pad_bottom = std::min(conv_info.pad_bottom(), kernel_size / 2);
- _border_size = BorderSize(conv_pad_top, conv_pad_right, conv_pad_bottom, conv_pad_left);
-
const GPUTarget gpu_target = get_arch_from_target(get_target());
std::stringstream kernel_name;
@@ -450,13 +445,13 @@ void CLDirectConvolutionLayerKernel::configure(const ICLTensor *input, const ICL
_config_id += "_";
_config_id += support::cpp11::to_string(kernel_size);
_config_id += "_";
- _config_id += support::cpp11::to_string(conv_pad_left);
+ _config_id += support::cpp11::to_string(border_size().left);
_config_id += "_";
- _config_id += support::cpp11::to_string(conv_pad_top);
+ _config_id += support::cpp11::to_string(border_size().top);
_config_id += "_";
- _config_id += support::cpp11::to_string(conv_pad_right);
+ _config_id += support::cpp11::to_string(border_size().right);
_config_id += "_";
- _config_id += support::cpp11::to_string(conv_pad_bottom);
+ _config_id += support::cpp11::to_string(border_size().bottom);
_config_id += "_";
_config_id += support::cpp11::to_string(_conv_stride_x);
_config_id += "_";
diff --git a/src/core/CL/kernels/CLPoolingLayerKernel.cpp b/src/core/CL/kernels/CLPoolingLayerKernel.cpp
index c515ed68e7..b3034e10cc 100644
--- a/src/core/CL/kernels/CLPoolingLayerKernel.cpp
+++ b/src/core/CL/kernels/CLPoolingLayerKernel.cpp
@@ -61,15 +61,11 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, c
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::QS8, DataType::QS16, DataType::F16, DataType::F32);
ARM_COMPUTE_RETURN_ERROR_ON_MSG((is_data_type_quantized_asymmetric(input->data_type()) && pool_info.pool_type() == PoolingType::L2),
"Unsupported combination of parameters!");
- ARM_COMPUTE_RETURN_ERROR_ON(!pool_info.pad_stride_info().padding_is_symmetric());
const bool is_global_pooling = pool_info.is_global_pooling();
const unsigned int pool_size_x = is_global_pooling ? input->tensor_shape().x() : pool_info.pool_size().width;
const unsigned int pool_size_y = is_global_pooling ? input->tensor_shape().y() : pool_info.pool_size().height;
- ARM_COMPUTE_RETURN_ERROR_ON_MSG(!is_global_pooling && ((pool_info.pad_stride_info().pad().first >= pool_size_x) || (pool_info.pad_stride_info().pad().second >= pool_size_y)),
- "Invalid pool size and pool pad combination!");
-
// Checks performed when output is configured
if(output->total_size() != 0)
{
@@ -92,8 +88,6 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, c
std::tuple<Status, Window, CLPoolingConfig> validate_and_configure_window(ITensorInfo *input, ITensorInfo *output, const PoolingLayerInfo &pool_info)
{
- int pool_pad_x = 0;
- int pool_pad_y = 0;
int pool_stride_x = 0;
int pool_stride_y = 0;
unsigned int pooled_w = 0;
@@ -101,8 +95,11 @@ std::tuple<Status, Window, CLPoolingConfig> validate_and_configure_window(ITenso
int pool_size_x = pool_info.is_global_pooling() ? input->dimension(0) : pool_info.pool_size().width;
int pool_size_y = pool_info.is_global_pooling() ? input->dimension(1) : pool_info.pool_size().height;
const PadStrideInfo pad_stride_info = pool_info.pad_stride_info();
- std::tie(pool_pad_x, pool_pad_y) = pad_stride_info.pad();
std::tie(pool_stride_x, pool_stride_y) = pad_stride_info.stride();
+ const int pool_pad_right = pad_stride_info.pad_right();
+ const int pool_pad_top = pad_stride_info.pad_top();
+ const int pool_pad_left = pad_stride_info.pad_left();
+ const int pool_pad_bottom = pad_stride_info.pad_bottom();
ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
@@ -115,7 +112,7 @@ std::tuple<Status, Window, CLPoolingConfig> validate_and_configure_window(ITenso
auto_init(input, output, pooled_w, pooled_h);
- BorderSize border_size = BorderSize(pool_pad_y, pool_pad_x);
+ BorderSize border_size = BorderSize(pool_pad_top, pool_pad_right, pool_pad_bottom, pool_pad_left);
const DataType data_type = input->data_type();
const int input_width = input->dimension(0);
@@ -131,15 +128,15 @@ std::tuple<Status, Window, CLPoolingConfig> validate_and_configure_window(ITenso
const int num_iterations_x = (pooled_w + num_elems_processed_per_iteration - 1) / num_elems_processed_per_iteration;
// Upper limit for the number of right/bottom border elements that are accessed
- const int upper_bound_w = ((num_iterations_x - 1) * num_elems_processed_per_iteration * pool_stride_x - pool_pad_x + num_elems_read_per_iteration) - input_width;
- const int upper_bound_h = ((pooled_h - 1) * pool_stride_y - pool_pad_y + pool_size_y) - input_height;
+ const int upper_bound_w = ((num_iterations_x - 1) * num_elems_processed_per_iteration * pool_stride_x - pool_pad_left + num_elems_read_per_iteration) - input_width;
+ const int upper_bound_h = ((pooled_h - 1) * pool_stride_y - pool_pad_top + pool_size_y) - input_height;
- border_size.right = std::max(upper_bound_w, pool_pad_x);
- border_size.bottom = std::max(upper_bound_h, pool_pad_y);
+ border_size.right = std::max(upper_bound_w, pool_pad_right);
+ border_size.bottom = std::max(upper_bound_h, pool_pad_bottom);
Window win = calculate_max_window(*output, Steps(num_elems_processed_per_iteration));
- AccessWindowRectangle input_access(input, -pool_pad_x, -pool_pad_y, num_elems_read_per_iteration, pool_size_y,
+ AccessWindowRectangle input_access(input, -pool_pad_left, -pool_pad_top, num_elems_read_per_iteration, pool_size_y,
pool_stride_x * num_elems_processed_per_iteration, pool_stride_y);
AccessWindowHorizontal output_access(output, 0, num_elems_processed_per_iteration);
bool window_changed = update_window_and_padding(win, input_access, output_access);
@@ -162,8 +159,6 @@ BorderSize CLPoolingLayerKernel::border_size() const
void CLPoolingLayerKernel::configure(const ICLTensor *input, ICLTensor *output, const PoolingLayerInfo &pool_info)
{
- int pool_pad_x = 0;
- int pool_pad_y = 0;
int pool_stride_x = 0;
int pool_stride_y = 0;
unsigned int pooled_w = 0;
@@ -173,8 +168,9 @@ void CLPoolingLayerKernel::configure(const ICLTensor *input, ICLTensor *output,
const int pool_size_y = pool_info.is_global_pooling() ? input->info()->dimension(1) : pool_info.pool_size().height;
const PadStrideInfo pad_stride_info = pool_info.pad_stride_info();
const bool exclude_padding = pool_info.exclude_padding();
- std::tie(pool_pad_x, pool_pad_y) = pad_stride_info.pad();
std::tie(pool_stride_x, pool_stride_y) = pad_stride_info.stride();
+ const int pool_pad_top = pad_stride_info.pad_top();
+ const int pool_pad_left = pad_stride_info.pad_left();
ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
@@ -207,11 +203,11 @@ void CLPoolingLayerKernel::configure(const ICLTensor *input, ICLTensor *output,
if(pool_type != PoolingType::MAX)
{
build_opts.add_option_if(exclude_padding, "-DEXCLUDE_PADDING");
- build_opts.add_option("-DMAX_WIDTH=" + support::cpp11::to_string(input->info()->dimension(0) + (exclude_padding ? 0 : pool_pad_x)));
- build_opts.add_option("-DMAX_HEIGHT=" + support::cpp11::to_string(input->info()->dimension(1) + (exclude_padding ? 0 : pool_pad_y)));
+ build_opts.add_option("-DMAX_WIDTH=" + support::cpp11::to_string(input->info()->dimension(0) + (exclude_padding ? 0 : pool_pad_left)));
+ build_opts.add_option("-DMAX_HEIGHT=" + support::cpp11::to_string(input->info()->dimension(1) + (exclude_padding ? 0 : pool_pad_top)));
build_opts.add_option("-DSTRIDE_Y=" + support::cpp11::to_string(pool_stride_y));
- build_opts.add_option("-DPAD_X=" + support::cpp11::to_string(pool_pad_x));
- build_opts.add_option("-DPAD_Y=" + support::cpp11::to_string(pool_pad_y));
+ build_opts.add_option("-DPAD_X=" + support::cpp11::to_string(pool_pad_left));
+ build_opts.add_option("-DPAD_Y=" + support::cpp11::to_string(pool_pad_top));
}
// Create kernel
@@ -278,8 +274,8 @@ void CLPoolingLayerKernel::run(const Window &window, cl::CommandQueue &queue)
ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window);
- unsigned int pool_pad_x, pool_pad_y, pool_stride_x, pool_stride_y = 0;
- std::tie(pool_pad_x, pool_pad_y) = _pool_info.pad_stride_info().pad();
+ unsigned int pool_stride_x = 0;
+ unsigned int pool_stride_y = 0;
std::tie(pool_stride_x, pool_stride_y) = _pool_info.pad_stride_info().stride();
Window window_collapsed = window.collapse_if_possible(ICLKernel::window(), Window::DimZ);
@@ -289,11 +285,11 @@ void CLPoolingLayerKernel::run(const Window &window, cl::CommandQueue &queue)
{
// Upsample input by pool size
Window in_slice(slice);
- in_slice.set(Window::DimX, Window::Dimension(in_slice.x().start() - pool_pad_x,
- (in_slice.x().end() - pool_pad_x) * pool_stride_x,
+ in_slice.set(Window::DimX, Window::Dimension(in_slice.x().start() - _pool_info.pad_stride_info().pad_left(),
+ (in_slice.x().end() - _pool_info.pad_stride_info().pad_left()) * pool_stride_x,
pool_stride_x * _num_elems_processed_per_iteration));
- in_slice.set(Window::DimY, Window::Dimension(in_slice.y().start() - pool_pad_y,
- (in_slice.y().end() - pool_pad_y) * pool_stride_y,
+ in_slice.set(Window::DimY, Window::Dimension(in_slice.y().start() - _pool_info.pad_stride_info().pad_top(),
+ (in_slice.y().end() - _pool_info.pad_stride_info().pad_top()) * pool_stride_y,
pool_stride_y));
// Set inputs