Remove padding from ClPool2dKernel NCHW
- Simplify NCHW kernel structure by removing old optimized paths
- Merge quantized with fp kernels
Resolve COMPMID-4722
Signed-off-by: Giorgio Arena <giorgio.arena@arm.com>
Change-Id: I79016b119619aed6a6193295601cd6517f14b88c
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/6183
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
diff --git a/src/gpu/cl/ClKernelLibrary.cpp b/src/gpu/cl/ClKernelLibrary.cpp
index 5cd969e..c05bb96 100644
--- a/src/gpu/cl/ClKernelLibrary.cpp
+++ b/src/gpu/cl/ClKernelLibrary.cpp
@@ -328,10 +328,6 @@
{ "pixelwise_mul_float", "common/pixelwise_mul_float.cl" },
{ "pixelwise_mul_int", "common/pixelwise_mul_int.cl" },
{ "pixelwise_mul_quantized", "common/pixelwise_mul_int.cl" },
- { "pooling_layer_2", "common/pooling_layer.cl" },
- { "pooling_layer_3", "common/pooling_layer.cl" },
- { "pooling_layer_optimized_3", "common/pooling_layer.cl" },
- { "pooling_layer_7", "common/pooling_layer.cl" },
{ "qlstm_layer_normalization", "common/qlstm_layer_normalization.cl" },
{ "quantization_layer", "common/quantization_layer.cl" },
{ "range", "common/range.cl" },
@@ -385,9 +381,7 @@
{ "normalize_planar_yuv_layer_nchw", "nchw/normalize_planar_yuv_layer.cl" },
{ "normalize_planar_yuv_layer_q8_nchw", "nchw/normalize_planar_yuv_layer_quantized.cl" },
{ "pooling_layer_MxN_nchw", "nchw/pooling_layer.cl" },
- { "pooling_layer_2_nchw_indices_fp32", "nchw/pooling_layer.cl" },
- { "pooling_layer_2_nchw_indices_fp16", "nchw/pooling_layer.cl" },
- { "pooling_layer_MxN_quantized_nchw", "nchw/pooling_layer_quantized.cl" },
+ { "pooling_layer_2_nchw_indices", "nchw/pooling_layer.cl" },
{ "prior_box_layer_nchw", "nchw/prior_box_layer.cl" },
{ "remap_nearest_neighbour_nchw", "nchw/remap.cl" },
{ "remap_bilinear_nchw", "nchw/remap.cl" },
@@ -668,10 +662,6 @@
#include "./cl_kernels/common/pixelwise_mul_int.clembed"
},
{
- "common/pooling_layer.cl",
-#include "./cl_kernels/common/pooling_layer.clembed"
- },
- {
"common/qlstm_layer_normalization.cl",
#include "./cl_kernels/common/qlstm_layer_normalization.clembed"
},
@@ -805,10 +795,6 @@
#include "./cl_kernels/nchw/pooling_layer.clembed"
},
{
- "nchw/pooling_layer_quantized.cl",
-#include "./cl_kernels/nchw/pooling_layer_quantized.clembed"
- },
- {
"nchw/prior_box_layer.cl",
#include "./cl_kernels/nchw/prior_box_layer.clembed"
},
diff --git a/src/gpu/cl/kernels/ClPool2dKernel.cpp b/src/gpu/cl/kernels/ClPool2dKernel.cpp
index 04f2b14..5e53799 100644
--- a/src/gpu/cl/kernels/ClPool2dKernel.cpp
+++ b/src/gpu/cl/kernels/ClPool2dKernel.cpp
@@ -23,18 +23,13 @@
*/
#include "src/gpu/cl/kernels/ClPool2dKernel.h"
-#include "arm_compute/core/CL/CLHelpers.h"
-#include "arm_compute/core/CL/CLKernelLibrary.h"
#include "arm_compute/core/CL/ICLTensor.h"
#include "arm_compute/core/TensorInfo.h"
-#include "arm_compute/core/Utils.h"
-#include "arm_compute/core/Validate.h"
#include "arm_compute/core/utils/misc/ShapeCalculator.h"
#include "src/core/CL/CLValidate.h"
#include "src/core/helpers/AutoConfiguration.h"
#include "src/core/helpers/WindowHelpers.h"
#include "support/Cast.h"
-#include "support/StringSupport.h"
namespace arm_compute
{
@@ -46,19 +41,6 @@
namespace
{
-// Internal window config info
-using ClPoolingConfig = std::pair<unsigned int, BorderSize>; //num_elems_processed_per_iteration, border_size
-
-void auto_init(const ITensorInfo *src, ITensorInfo *dst, ITensorInfo *indices, PoolingLayerInfo pool_info)
-{
- TensorShape out_shape = compute_pool_shape(*src, pool_info);
- auto_init_if_empty(*dst, src->clone()->set_tensor_shape(out_shape));
- if(indices)
- {
- auto_init_if_empty(*indices, src->clone()->set_tensor_shape(out_shape).set_data_type(DataType::U32));
- }
-}
-
Status validate_arguments(const ITensorInfo *src, const ITensorInfo *dst, const PoolingLayerInfo &pool_info, const ITensorInfo *indices)
{
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(src, dst);
@@ -104,102 +86,6 @@
return Status{};
}
-
-std::tuple<Status, Window, ClPoolingConfig> validate_and_configure_window(ITensorInfo *src, ITensorInfo *dst, const PoolingLayerInfo &pool_info, ITensorInfo *indices = nullptr)
-{
- ARM_COMPUTE_ERROR_ON_NULLPTR(src, dst);
-
- // Get data layout
- const DataLayout data_layout = pool_info.data_layout == DataLayout::UNKNOWN ? src->data_layout() : pool_info.data_layout;
- const int idx_width = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH);
- const int idx_height = get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT);
-
- int pool_stride_x = 0;
- int pool_stride_y = 0;
- unsigned int pooled_w = 0;
- unsigned int pooled_h = 0;
- int pool_size_x = pool_info.is_global_pooling ? src->dimension(idx_width) : pool_info.pool_size.width;
- int pool_size_y = pool_info.is_global_pooling ? src->dimension(idx_height) : pool_info.pool_size.height;
- const PadStrideInfo pad_stride_info = pool_info.pad_stride_info;
- 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();
- BorderSize border_size = BorderSize();
-
- auto_init(src, dst, indices, pool_info);
- pooled_w = dst->tensor_shape()[idx_width];
- pooled_h = dst->tensor_shape()[idx_height];
-
- const DataType data_type = src->data_type();
-
- const int src_width = src->dimension(idx_width);
- const int src_height = src->dimension(idx_height);
-
- unsigned int num_elems_processed_per_iteration = 0;
- bool window_changed = false;
- Window win{};
- switch(data_layout)
- {
- case DataLayout::NCHW:
- {
- // Initialize border size
- border_size = BorderSize(pool_pad_top, pool_pad_right, pool_pad_bottom, pool_pad_left);
- // Change the number of elements processed per iteration
- // for pooling 3x3 with stride less equal than 3
- const bool can_optimize = (pool_size_x == 3) && (pool_size_y == 3) && (pool_stride_x <= 3) && !is_data_type_quantized(data_type);
- num_elems_processed_per_iteration = can_optimize ? 4 : 1;
- const unsigned int num_elems_read_per_iteration = (num_elems_processed_per_iteration - 1) * pool_stride_x + pool_size_x;
-
- // Number of iterations in X dimension
- 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_left + num_elems_read_per_iteration) - src_width;
- const int upper_bound_h = ((pooled_h - 1) * pool_stride_y - pool_pad_top + pool_size_y) - src_height;
-
- border_size.right = std::max(upper_bound_w, pool_pad_right);
- border_size.bottom = std::max(upper_bound_h, pool_pad_bottom);
-
- win = calculate_max_window(*dst, Steps(num_elems_processed_per_iteration));
-
- AccessWindowRectangle src_access(src, -pool_pad_left, -pool_pad_top, num_elems_read_per_iteration, pool_size_y,
- pool_stride_x, pool_stride_y);
- AccessWindowHorizontal dst_access(dst, 0, num_elems_processed_per_iteration);
-
- // Update indices window
- if(indices)
- {
- AccessWindowHorizontal indices_access(indices, 0, num_elems_processed_per_iteration);
- window_changed = update_window_and_padding(win, src_access, dst_access, indices_access);
- indices_access.set_valid_region(win, ValidRegion(Coordinates(), indices->tensor_shape()));
- }
- else
- {
- window_changed = update_window_and_padding(win, src_access, dst_access);
- }
-
- dst_access.set_valid_region(win, ValidRegion(Coordinates(), dst->tensor_shape()));
- break;
- }
- case DataLayout::NHWC:
- {
- const size_t vec_size = dst->data_type() == DataType::F32 ? 2 : 4;
-
- // Initialize border size
- border_size = BorderSize();
- num_elems_processed_per_iteration = adjust_vec_size(vec_size, dst->dimension(0));
- win = calculate_max_window(*dst, Steps(num_elems_processed_per_iteration));
- break;
- }
- default:
- ARM_COMPUTE_ERROR("Not implemented");
- }
-
- Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{};
- return std::make_tuple(err, win, ClPoolingConfig(num_elems_processed_per_iteration, border_size));
-}
} // namespace
ClPool2dKernel::ClPool2dKernel()
@@ -207,20 +93,27 @@
_type = CLKernelType::POOL;
}
-BorderSize ClPool2dKernel::border_size() const
-{
- return _border_size;
-}
-
void ClPool2dKernel::configure(const ClCompileContext &compile_context, ITensorInfo *src, ITensorInfo *dst, const PoolingLayerInfo &pool_info, ITensorInfo *indices)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(src, dst);
+ ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(src, dst, pool_info, indices));
auto padding_info = get_padding_info({ src, dst, indices });
+ // Auto init if empty
+ TensorShape out_shape = compute_pool_shape(*src, pool_info);
+ auto_init_if_empty(*dst, src->clone()->set_tensor_shape(out_shape));
+ if(indices)
+ {
+ auto_init_if_empty(*indices, src->clone()->set_tensor_shape(out_shape).set_data_type(DataType::U32));
+ }
+
// Set instance variables
- _pool_info = pool_info;
- _data_layout = pool_info.data_layout == DataLayout::UNKNOWN ? src->data_layout() : pool_info.data_layout;
+ _pool_info = pool_info;
+ _data_layout = pool_info.data_layout == DataLayout::UNKNOWN ? src->data_layout() : pool_info.data_layout;
+ _num_elems_processed_per_iteration = (_data_layout == DataLayout::NCHW) ? 1 : ((dst->data_type() == DataType::F32) ? 2 : 4);
+ _num_elems_processed_per_iteration = adjust_vec_size(_num_elems_processed_per_iteration, dst->dimension(0));
+
int pool_stride_x = 0;
int pool_stride_y = 0;
const PoolingType pool_type = pool_info.pool_type;
@@ -233,53 +126,13 @@
const PadStrideInfo pad_stride_info = pool_info.pad_stride_info;
const bool exclude_padding = pool_info.exclude_padding;
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();
+ const int pool_pad_top = pad_stride_info.pad_top();
+ const int pool_pad_left = pad_stride_info.pad_left();
+ const DataType data_type = src->data_type();
// Set build options
CLBuildOptions build_opts;
- const DataType data_type = src->data_type();
-
- // Configure kernel window
- auto win_config = validate_and_configure_window(src, dst, pool_info, indices);
-
- ARM_COMPUTE_ERROR_THROW_ON(std::get<0>(win_config));
- ICLKernel::configure_internal(std::get<1>(win_config));
-
- ClPoolingConfig pooling_config = std::get<2>(win_config);
- _num_elems_processed_per_iteration = pooling_config.first;
- _border_size = pooling_config.second;
-
build_opts.add_option("-DVEC_SIZE=" + support::cpp11::to_string(_num_elems_processed_per_iteration));
-
- // Tensor paddings are used to calculate the indicies for MAX pooling
- if(pool_info.pool_size == Size2D(2, 2) && pool_type == PoolingType::MAX && indices && is_data_type_float(data_type))
- {
- build_opts.add_option("-DPAD_TENSOR_LEFT=" + support::cpp11::to_string(src->padding().left));
- build_opts.add_option("-DPAD_TENSOR_RIGHT=" + support::cpp11::to_string(src->padding().right));
- build_opts.add_option("-DPAD_TENSOR_TOP=" + support::cpp11::to_string(src->padding().top));
- build_opts.add_option("-DPAD_TENSOR_BOTTOM=" + support::cpp11::to_string(src->padding().bottom));
- build_opts.add_option("-DTENSOR_CHANNEL=" + support::cpp11::to_string(src->dimension(idx_channel)));
- build_opts.add_option("-DTENSOR_WIDTH=" + support::cpp11::to_string(src->dimension(idx_width)));
- build_opts.add_option("-DTENSOR_HEIGHT=" + support::cpp11::to_string(src->dimension(idx_height)));
- }
-
- if(is_data_type_quantized_asymmetric(data_type) && src->quantization_info() != dst->quantization_info())
- {
- const UniformQuantizationInfo iq_info = src->quantization_info().uniform();
- const UniformQuantizationInfo oq_info = dst->quantization_info().uniform();
-
- build_opts.add_option("-DOFFSET_IN1=" + float_to_string_with_full_precision(iq_info.offset));
- build_opts.add_option("-DOFFSET_OUT=" + float_to_string_with_full_precision(oq_info.offset));
- build_opts.add_option("-DSCALE_IN1=" + float_to_string_with_full_precision(iq_info.scale));
- build_opts.add_option("-DSCALE_OUT=" + float_to_string_with_full_precision(oq_info.scale));
- }
-
- // Check dst dimensions
- auto_init(src, dst, indices, pool_info);
-
- ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(src, dst, pool_info, indices));
-
build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(data_type));
build_opts.add_option("-DPOOL_" + string_from_pooling_type(pool_type));
build_opts.add_option("-DSTRIDE_X=" + support::cpp11::to_string(pool_stride_x));
@@ -288,6 +141,32 @@
build_opts.add_option("-DPAD_Y=" + support::cpp11::to_string(pool_pad_top));
build_opts.add_option("-DPOOL_SIZE_X=" + support::cpp11::to_string(pool_size_x));
build_opts.add_option("-DPOOL_SIZE_Y=" + support::cpp11::to_string(pool_size_y));
+ build_opts.add_option("-DSRC_WIDTH=" + support::cpp11::to_string(src->dimension(idx_width)));
+ build_opts.add_option("-DSRC_HEIGHT=" + support::cpp11::to_string(src->dimension(idx_height)));
+ build_opts.add_option("-DMAX_WIDTH=" + support::cpp11::to_string(src->dimension(idx_width) + (exclude_padding ? 0 : pool_pad_left)));
+ build_opts.add_option("-DMAX_HEIGHT=" + support::cpp11::to_string(src->dimension(idx_height) + (exclude_padding ? 0 : pool_pad_top)));
+
+ // Tensor paddings are used to calculate the indicies for MAX pooling
+ if(pool_info.pool_size == Size2D(2, 2) && pool_type == PoolingType::MAX && indices && is_data_type_float(data_type))
+ {
+ build_opts.add_option("-DSRC_BATCH=" + support::cpp11::to_string(src->tensor_shape().total_size_lower(3)));
+ }
+
+ if(is_data_type_quantized_asymmetric(data_type))
+ {
+ build_opts.add_option("-DQUANTIZED");
+
+ if(src->quantization_info() != dst->quantization_info())
+ {
+ const UniformQuantizationInfo iq_info = src->quantization_info().uniform();
+ const UniformQuantizationInfo oq_info = dst->quantization_info().uniform();
+
+ build_opts.add_option("-DOFFSET_IN1=" + float_to_string_with_full_precision(iq_info.offset));
+ build_opts.add_option("-DOFFSET_OUT=" + float_to_string_with_full_precision(oq_info.offset));
+ build_opts.add_option("-DSCALE_IN1=" + float_to_string_with_full_precision(iq_info.scale));
+ build_opts.add_option("-DSCALE_OUT=" + float_to_string_with_full_precision(oq_info.scale));
+ }
+ }
// Set the initial value for the pooling operation accordingly with the data type
if(pool_type == PoolingType::MAX)
@@ -309,9 +188,6 @@
build_opts.add_option("-DINITIAL_VALUE=0");
}
- build_opts.add_option("-DMAX_WIDTH=" + support::cpp11::to_string(src->dimension(idx_width) + (exclude_padding ? 0 : pool_pad_left)));
- build_opts.add_option("-DMAX_HEIGHT=" + support::cpp11::to_string(src->dimension(idx_height) + (exclude_padding ? 0 : pool_pad_top)));
-
// Create kernel
switch(_data_layout)
{
@@ -319,7 +195,7 @@
{
const auto use_fp_mixed_precision = (data_type == DataType::F16) && pool_info.fp_mixed_precision;
const auto use_wider_accumulator = use_fp_mixed_precision && (pool_type != PoolingType::MAX);
- const auto acc_data_type = get_cl_type_from_data_type(use_wider_accumulator ? DataType::F32 : data_type);
+ const auto acc_data_type = get_cl_type_from_data_type(use_wider_accumulator ? DataType::F32 : (is_data_type_quantized(data_type) ? DataType::S32 : data_type));
build_opts.add_option("-DACC_DATA_TYPE=" + acc_data_type);
build_opts.add_option_if(use_wider_accumulator, "-DFP_MIXED_PRECISION");
@@ -328,33 +204,15 @@
build_opts.add_option_if(exclude_padding, "-DEXCLUDE_PADDING");
}
- if((pool_size_x == 3) && (pool_size_y == 3) && !is_data_type_quantized_asymmetric(data_type))
- {
- // Check if we have pool3x3 with stride_x less equal than 3. In these cases, run an optimized OpenCL kernel where
- // each thread computes 4 dst elements
- const bool is_pool3x3_stride_le3 = (pool_size_x == 3) && (pool_size_y == 3) && (pool_stride_x <= 3);
-
- std::string kernel_name = ((is_pool3x3_stride_le3) ? "pooling_layer_optimized_" : "pooling_layer_")
- + support::cpp11::to_string(pool_size_x);
- _kernel = create_kernel(compile_context, kernel_name, build_opts.options());
- }
- else if(pool_info.pool_size == Size2D(2, 2) && pool_type == PoolingType::MAX && indices && is_data_type_float(data_type))
+ if(pool_info.pool_size == Size2D(2, 2) && pool_type == PoolingType::MAX && indices && is_data_type_float(data_type))
{
// For max pooling with pool2x2, store indicies which will be used in max unpooling
- if(data_type == DataType::F32)
- {
- std::string kernel_name = "pooling_layer_2_nchw_indices_fp32";
- _kernel = create_kernel(compile_context, kernel_name, build_opts.options());
- }
- else if(data_type == DataType::F16)
- {
- std::string kernel_name = "pooling_layer_2_nchw_indices_fp16";
- _kernel = create_kernel(compile_context, kernel_name, build_opts.options());
- }
+ std::string kernel_name = "pooling_layer_2_nchw_indices";
+ _kernel = create_kernel(compile_context, kernel_name, build_opts.options());
}
else // Run general case
{
- std::string kernel_name = is_data_type_quantized_asymmetric(data_type) ? "pooling_layer_MxN_quantized_nchw" : "pooling_layer_MxN_nchw";
+ std::string kernel_name = "pooling_layer_MxN_nchw";
_kernel = create_kernel(compile_context, kernel_name, build_opts.options());
}
break;
@@ -405,6 +263,10 @@
ARM_COMPUTE_ERROR("Not implemented");
}
+ // Configure kernel window
+ Window win = calculate_max_window(*dst, Steps(_num_elems_processed_per_iteration));
+ ICLKernel::configure_internal(win);
+
// Set config_id for enabling LWS tuning
_config_id = "pooling_layer_";
_config_id += lower_string(string_from_data_type(data_type));
@@ -419,14 +281,12 @@
_config_id += "_";
_config_id += lower_string(string_from_data_layout(src->data_layout()));
- ARM_COMPUTE_ERROR_ON(src->data_layout() == DataLayout::NHWC && has_padding_changed(padding_info));
+ ARM_COMPUTE_ERROR_ON(has_padding_changed(padding_info));
}
Status ClPool2dKernel::validate(const ITensorInfo *src, const ITensorInfo *dst, const PoolingLayerInfo &pool_info, const ITensorInfo *indices)
{
ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(src, dst, pool_info, indices));
- ARM_COMPUTE_RETURN_ON_ERROR(std::get<0>(validate_and_configure_window(src->clone().get(), dst->clone().get(), pool_info)));
-
return Status{};
}
@@ -453,18 +313,9 @@
Window slice = window_collapsed.first_slice_window_3D();
do
{
- // Upsample src by pool size
- Window in_slice(slice);
- 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_info.pad_stride_info.pad_top(),
- (in_slice.y().end() - _pool_info.pad_stride_info.pad_top()) * pool_stride_y,
- pool_stride_y));
-
// Set srcs
unsigned int idx = 0;
- add_3D_tensor_argument(idx, src, in_slice);
+ add_3D_tensor_argument(idx, src, slice);
add_3D_tensor_argument(idx, dst, slice);
if(indices && is_data_type_float(src->info()->data_type()) && (_pool_info.pool_size == Size2D(2, 2)))
{
diff --git a/src/gpu/cl/kernels/ClPool2dKernel.h b/src/gpu/cl/kernels/ClPool2dKernel.h
index 61d204d..f5bb068 100644
--- a/src/gpu/cl/kernels/ClPool2dKernel.h
+++ b/src/gpu/cl/kernels/ClPool2dKernel.h
@@ -61,12 +61,10 @@
// Inherited methods overridden:
void run_op(ITensorPack &tensors, const Window &window, cl::CommandQueue &queue) override;
- BorderSize border_size() const override;
public:
PoolingLayerInfo _pool_info{};
DataLayout _data_layout{ DataLayout::UNKNOWN };
- BorderSize _border_size{ 0 };
unsigned int _num_elems_processed_per_iteration{ 1 };
};
} // namespace kernels
diff --git a/src/gpu/cl/operators/ClPool2d.cpp b/src/gpu/cl/operators/ClPool2d.cpp
index fdadd19..a5b18a2 100644
--- a/src/gpu/cl/operators/ClPool2d.cpp
+++ b/src/gpu/cl/operators/ClPool2d.cpp
@@ -25,7 +25,6 @@
#include "arm_compute/runtime/CL/CLScheduler.h"
-#include "src/core/CL/kernels/CLFillBorderKernel.h"
#include "src/gpu/cl/ClCompileContext.h"
#include "src/gpu/cl/kernels/ClPool2dKernel.h"
@@ -40,62 +39,15 @@
auto k = std::make_unique<kernels::ClPool2dKernel>();
k->set_target(CLScheduler::get().target());
k->configure(compile_context, src, dst, info, indices);
- _pooling = std::move(k);
-
- const DataType data_type = src->data_type();
-
- // Configure border depending on operation required (quantize border in case of asymmetric data_type)
- BorderMode border_mode{};
- PixelValue pixel_value(0.f);
- if(is_data_type_quantized_asymmetric(data_type) && !info.exclude_padding)
- {
- pixel_value = PixelValue(0, data_type, src->quantization_info());
- }
-
- // Data layout
- const auto data_layout = info.data_layout == DataLayout::UNKNOWN ? src->data_layout() : info.data_layout;
-
- switch(data_layout)
- {
- case DataLayout::NCHW:
- border_mode = (PoolingType::MAX == info.pool_type) ? BorderMode::REPLICATE : BorderMode::CONSTANT;
- break;
- case DataLayout::NHWC:
- border_mode = BorderMode::CONSTANT;
- if(PoolingType::MAX == info.pool_type)
- {
- if(is_data_type_quantized(data_type))
- {
- std::tie(pixel_value, std::ignore) = get_min_max(data_type);
- }
- else
- {
- pixel_value = PixelValue(std::numeric_limits<float>::lowest());
- }
- }
- break;
- default:
- ARM_COMPUTE_ERROR("Data layout not supported");
- }
- auto b = std::make_unique<CLFillBorderKernel>();
- b->configure(compile_context, src, _pooling->border_size(), border_mode, pixel_value);
- _border_handler = std::move(b);
+ _kernel = std::move(k);
// Tune kernels
- CLScheduler::get().tune_kernel_static(*_pooling);
+ CLScheduler::get().tune_kernel_static(*_kernel);
}
Status ClPool2d::validate(const ITensorInfo *src, const ITensorInfo *dst, const PoolingLayerInfo &info, const ITensorInfo *indices)
{
return kernels::ClPool2dKernel::validate(src, dst, info, indices);
}
-
-void ClPool2d::run(ITensorPack &tensors)
-{
- ARM_COMPUTE_ERROR_ON_MSG(tensors.empty(), "No inputs provided");
-
- CLScheduler::get().enqueue_op(*_border_handler.get(), tensors, false);
- CLScheduler::get().enqueue_op(*_pooling.get(), tensors, false);
-}
} // namespace opencl
} // namespace arm_compute
diff --git a/src/gpu/cl/operators/ClPool2d.h b/src/gpu/cl/operators/ClPool2d.h
index a041053..f353ba2 100644
--- a/src/gpu/cl/operators/ClPool2d.h
+++ b/src/gpu/cl/operators/ClPool2d.h
@@ -35,7 +35,6 @@
{
/** Basic function to simulate a pooling layer with the specified pooling operation. This function calls the following OpenCL kernels:
*
- * -# @ref CLFillBorderKernel (executed if padding size is different from zero)
* -# @ref opencl::ClPool2d
*/
class ClPool2d : public IClOperator
@@ -59,13 +58,6 @@
* @return a status
*/
static Status validate(const ITensorInfo *src, const ITensorInfo *dst, const PoolingLayerInfo &info, const ITensorInfo *indices = nullptr);
-
- // Inherited method overridden
- void run(ITensorPack &tensors) override;
-
-private:
- std::unique_ptr<ICLKernel> _pooling{ nullptr };
- std::unique_ptr<ICLKernel> _border_handler{ nullptr };
};
} // namespace opencl
} // namespace arm_compute