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Diffstat (limited to 'src/dynamic_fusion/sketch/gpu/template_writer/cl/ClTemplateElementwiseBinary.cpp')
-rw-r--r--src/dynamic_fusion/sketch/gpu/template_writer/cl/ClTemplateElementwiseBinary.cpp94
1 files changed, 39 insertions, 55 deletions
diff --git a/src/dynamic_fusion/sketch/gpu/template_writer/cl/ClTemplateElementwiseBinary.cpp b/src/dynamic_fusion/sketch/gpu/template_writer/cl/ClTemplateElementwiseBinary.cpp
index c0481ae190..78bff3c3f3 100644
--- a/src/dynamic_fusion/sketch/gpu/template_writer/cl/ClTemplateElementwiseBinary.cpp
+++ b/src/dynamic_fusion/sketch/gpu/template_writer/cl/ClTemplateElementwiseBinary.cpp
@@ -23,14 +23,13 @@
*/
#include "ClTemplateElementwiseBinary.h"
-#include "src/dynamic_fusion/sketch/gpu/GpuKernelComponentGroup.h"
-#include "src/dynamic_fusion/sketch/gpu/components/cl/ClComponentElementwiseBinary.h"
-
#include "arm_compute/core/utils/helpers/AdjustVecSize.h"
#include "arm_compute/core/utils/misc/ShapeCalculator.h"
#include "arm_compute/core/utils/StringUtils.h"
-#include "src/core/helpers/WindowHelpers.h"
+#include "src/core/helpers/WindowHelpers.h"
+#include "src/dynamic_fusion/sketch/gpu/components/cl/ClComponentElementwiseBinary.h"
+#include "src/dynamic_fusion/sketch/gpu/GpuKernelComponentGroup.h"
#include "support/StringSupport.h"
namespace arm_compute
@@ -44,11 +43,7 @@ constexpr unsigned int vector_size_byte_opencl = 16;
ClTemplateElementwiseBinary::ClTemplateElementwiseBinary(ComponentId id,
const ArgumentPack<ITensorInfo> &tensors,
const Attributes &attributes)
- : IGpuTemplateComponentWriter{ id, tensors },
- _lhs{},
- _rhs{},
- _dst{},
- _attributes{ attributes }
+ : IGpuTemplateComponentWriter{id, tensors}, _lhs{}, _rhs{}, _dst{}, _attributes{attributes}
{
_lhs = this->tensors().get_const_tensor(TensorType::ACL_SRC_0);
_rhs = this->tensors().get_const_tensor(TensorType::ACL_SRC_1);
@@ -69,67 +64,67 @@ std::string ClTemplateElementwiseBinary::get_component_code(const ComponentGroup
const bool is_rhs_input = comp_group.is_input_tensor(_rhs);
code =
-R"_(
+ R"_(
//------------------ START KERNEL {{meta_kernel_id}} {{ELTWISE_OP}} ---------------------
)_";
- if(is_root)
+ if (is_root)
{
code +=
-R"_(
+ R"_(
TILE(uint, M0, 1, g_dst_indirect_y);
)_";
}
- if(is_lhs_input)
+ if (is_lhs_input)
{
code +=
-R"_(
+ R"_(
TILE({{DATA_TYPE}}, {{lhs_m0}}, N0, {{lhs}});
)_";
}
- if(is_rhs_input)
+ if (is_rhs_input)
{
code +=
-R"_(
+ R"_(
TILE({{DATA_TYPE}}, {{rhs_m0}}, N0, {{rhs}});
)_";
}
code +=
-R"_(
+ R"_(
{
)_";
- if(is_lhs_input)
+ if (is_lhs_input)
{
code +=
-R"_(
+ R"_(
{{lhs}}_offset_first_element_in_bytes += g_ind_2 * {{lhs}}_stride_w;
T_LOAD({{DATA_TYPE}}, {{lhs_m0}}, {{lhs_n0}}, BUFFER, {{lhs}}, {{lhs_start_ind_0}}, {{lhs_start_ind_1}}, 1, {{lhs}}_stride_y, {{lhs}});
)_";
}
- if(is_rhs_input)
+ if (is_rhs_input)
{
code +=
-R"_(
+ R"_(
{{rhs}}_offset_first_element_in_bytes += g_ind_2 * {{rhs}}_stride_w;
T_LOAD({{DATA_TYPE}}, {{rhs_m0}}, {{rhs_n0}}, BUFFER, {{rhs}}, {{rhs_start_ind_0}}, {{rhs_start_ind_1}}, 1, {{rhs}}_stride_y, {{rhs}});
)_";
}
code +=
-R"_(
+ R"_(
T_ELTWISE_{{BROADCAST_OP}}{{ELTWISE_OP}}({{DATA_TYPE}}, M0, N0, {{lhs}}, {{rhs}}, {{dst}});
)_";
- if(is_root)
+ if (is_root)
{
// Calculate the destination indirect Y
code +=
-R"_(
+ R"_(
LOOP_UNROLLING(int, i, 0, 1, M0,
{
g_dst_indirect_y[i].v = (uint)min(g_ind_1 + i, (int)({{arg_dst}}_w * {{arg_dst}}_h) - 1);
@@ -139,7 +134,7 @@ R"_(
}
code +=
-R"_(
+ R"_(
}
//------------------ END KERNEL {{meta_kernel_id}} {{ELTWISE_OP}} ---------------------
)_";
@@ -147,28 +142,18 @@ R"_(
return code;
}
-void ClTemplateElementwiseBinary::declare_variables(GpuKernelVariableTable &vtable, const ComponentGroup &comp_group) const
+void ClTemplateElementwiseBinary::declare_variables(GpuKernelVariableTable &vtable,
+ const ComponentGroup &comp_group) const
{
- vtable.declare_variable(
- comp_group,
- _lhs,
- GpuKernelArgumentInfo(common_tensor_type),
- "lhs");
-
- vtable.declare_variable(
- comp_group,
- _rhs,
- GpuKernelArgumentInfo(common_tensor_type),
- "rhs");
-
- vtable.declare_variable(
- comp_group,
- _dst,
- GpuKernelArgumentInfo(common_tensor_type),
- "dst");
+ vtable.declare_variable(comp_group, _lhs, GpuKernelArgumentInfo(common_tensor_type), "lhs");
+
+ vtable.declare_variable(comp_group, _rhs, GpuKernelArgumentInfo(common_tensor_type), "rhs");
+
+ vtable.declare_variable(comp_group, _dst, GpuKernelArgumentInfo(common_tensor_type), "dst");
}
-TagLUT ClTemplateElementwiseBinary::get_tag_lut(const GpuKernelVariableTable &vtable, const ComponentGroup &comp_group) const
+TagLUT ClTemplateElementwiseBinary::get_tag_lut(const GpuKernelVariableTable &vtable,
+ const ComponentGroup &comp_group) const
{
TagLUT lut{};
@@ -182,7 +167,7 @@ TagLUT ClTemplateElementwiseBinary::get_tag_lut(const GpuKernelVariableTable &vt
lut["dst"] = vtable.get_variable(_dst);
lut["arg_dst"] = vtable.get_variable(comp_group.get_any_dst_tensor());
- switch(_attributes.operation())
+ switch (_attributes.operation())
{
case Attributes::ElementwiseOp::Add:
lut["ELTWISE_OP"] = "ADD";
@@ -197,10 +182,10 @@ TagLUT ClTemplateElementwiseBinary::get_tag_lut(const GpuKernelVariableTable &vt
ARM_COMPUTE_ERROR("Arithmetic Operation not supported");
}
- ARM_COMPUTE_ERROR_ON(
- comp_group.is_intermediate_tensor(_lhs) && detail::have_different_dimensions(_lhs->tensor_shape(), _dst->tensor_shape(), 0));
- ARM_COMPUTE_ERROR_ON(
- comp_group.is_intermediate_tensor(_rhs) && detail::have_different_dimensions(_rhs->tensor_shape(), _dst->tensor_shape(), 0));
+ ARM_COMPUTE_ERROR_ON(comp_group.is_intermediate_tensor(_lhs) &&
+ detail::have_different_dimensions(_lhs->tensor_shape(), _dst->tensor_shape(), 0));
+ ARM_COMPUTE_ERROR_ON(comp_group.is_intermediate_tensor(_rhs) &&
+ detail::have_different_dimensions(_rhs->tensor_shape(), _dst->tensor_shape(), 0));
// Set broadcast parameters
// PRE: All tensors are broadcast-compatible
@@ -228,9 +213,7 @@ TagLUT ClTemplateElementwiseBinary::get_tag_lut(const GpuKernelVariableTable &vt
lut["rhs_m0"] = (rhs_broadcast_yz) ? "1" : "M0";
lut["rhs_start_ind_1"] = (rhs_broadcast_yz) ? "0" : "g_ind_1";
- lut["BROADCAST_OP"] = (lhs_broadcast_yz) ? "BROADCAST_LHS_X_" :
- (rhs_broadcast_yz) ? "BROADCAST_RHS_X_" :
- "";
+ lut["BROADCAST_OP"] = (lhs_broadcast_yz) ? "BROADCAST_LHS_X_" : (rhs_broadcast_yz) ? "BROADCAST_RHS_X_" : "";
return lut;
}
@@ -268,7 +251,7 @@ std::string ClTemplateElementwiseBinary::get_config_id() const
std::set<std::string> ClTemplateElementwiseBinary::get_headers_list() const
{
- return std::set<std::string>{ "helpers.h", "tile_helpers.h" };
+ return std::set<std::string>{"helpers.h", "tile_helpers.h"};
}
Window ClTemplateElementwiseBinary::get_window() const
@@ -279,8 +262,9 @@ Window ClTemplateElementwiseBinary::get_window() const
// Collapse Dim 1 (W) and Dim 2 (H) together, leave Dim 0 (C) and upper dimensions unchanged
// This is in line with the collapsing convention used by operators like Conv2d
output_shape.collapse(2U, 1U);
- const unsigned int num_elems_processed_per_iteration = adjust_vec_size(vector_size_byte_opencl / _dst->element_size(), _dst->dimension(0));
- Window win = calculate_max_window(output_shape, Steps(num_elems_processed_per_iteration));
+ const unsigned int num_elems_processed_per_iteration =
+ adjust_vec_size(vector_size_byte_opencl / _dst->element_size(), _dst->dimension(0));
+ Window win = calculate_max_window(output_shape, Steps(num_elems_processed_per_iteration));
return win;
}
generated by cgit v1.2.1 (git 2.23.0) at 2024-05-20 02:14:00 +0000