COMPMID-2012: Remove unnecessary templates from NEON kernels
Change-Id: I2deb26188c7de7c6ad10d2f51f83e729fed7e5e2
Signed-off-by: Michalis Spyrou <michalis.spyrou@arm.com>
Reviewed-on: https://review.mlplatform.org/c/961
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
diff --git a/arm_compute/core/NEON/kernels/NEReorgLayerKernel.h b/arm_compute/core/NEON/kernels/NEReorgLayerKernel.h
index 7e0fb43..076af4f 100644
--- a/arm_compute/core/NEON/kernels/NEReorgLayerKernel.h
+++ b/arm_compute/core/NEON/kernels/NEReorgLayerKernel.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2018 ARM Limited.
+ * Copyright (c) 2018-2019 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -75,24 +75,9 @@
void run(const Window &window, const ThreadInfo &info) override;
private:
- /** Template function to run the reorg
- *
- * @param[in] window Region on which to execute the kernel. (Must be a valid region of the window returned by window()).
- */
- template <typename T>
- void run_reorg(const Window &window);
-
- /** Common signature for all the specialised reorg functions
- *
- * @param[in] window Region on which to execute the kernel.
- */
- using ReorgFunctionPtr = void (NEReorgLayerKernel::*)(const Window &window);
-
-private:
- ReorgFunctionPtr _func;
- const ITensor *_input;
- ITensor *_output;
- int32_t _stride;
+ const ITensor *_input;
+ ITensor *_output;
+ int32_t _stride;
};
} // namespace arm_compute
#endif /*__ARM_COMPUTE_NEREORGLAYERKERNEL_H__ */
diff --git a/arm_compute/core/NEON/kernels/NEStackLayerKernel.h b/arm_compute/core/NEON/kernels/NEStackLayerKernel.h
index 3a9e81f..42a0539 100644
--- a/arm_compute/core/NEON/kernels/NEStackLayerKernel.h
+++ b/arm_compute/core/NEON/kernels/NEStackLayerKernel.h
@@ -84,24 +84,10 @@
void run(const Window &window, const ThreadInfo &info) override;
private:
- /** Template function to run the stack
- *
- * @param[in] window Region on which to execute the kernel. (Must be a valid region of the window returned by window()).
- */
- template <typename T>
- void run_stack(const Window &window);
-
- /** Common signature for all the specialised stack functions
- *
- * @param[in] window Region on which to execute the kernel.
- */
- using StackFunctionPtr = void (NEStackLayerKernel::*)(const Window &window);
-
const ITensor *_input;
ITensor *_output;
unsigned int _axis;
unsigned int _idx_input;
- StackFunctionPtr _func;
};
} // namespace arm_compute
#endif /* __ARM_COMPUTE_NESTACKLAYERKERNEL_H__ */
diff --git a/arm_compute/core/NEON/kernels/NEWeightsReshapeKernel.h b/arm_compute/core/NEON/kernels/NEWeightsReshapeKernel.h
index 21f36f6..bba18a8 100644
--- a/arm_compute/core/NEON/kernels/NEWeightsReshapeKernel.h
+++ b/arm_compute/core/NEON/kernels/NEWeightsReshapeKernel.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017-2018 ARM Limited.
+ * Copyright (c) 2017-2019 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -99,12 +99,9 @@
void run(const Window &window, const ThreadInfo &info) override;
private:
- using WeightsReshapeKernel = void(const ITensor *input, const ITensor *bias, ITensor *output, const Window &window);
-
- WeightsReshapeKernel *_func;
- const ITensor *_input;
- const ITensor *_bias;
- ITensor *_output;
+ const ITensor *_input;
+ const ITensor *_bias;
+ ITensor *_output;
};
} // namespace arm_compute
#endif /*__ARM_COMPUTE_NEWEIGHTSRESHAPEKERNEL_H__ */
diff --git a/src/core/NEON/kernels/NEReorgLayerKernel.cpp b/src/core/NEON/kernels/NEReorgLayerKernel.cpp
index 8baea2b..ece5aa4 100644
--- a/src/core/NEON/kernels/NEReorgLayerKernel.cpp
+++ b/src/core/NEON/kernels/NEReorgLayerKernel.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2018 ARM Limited.
+ * Copyright (c) 2018-2019 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -67,9 +67,47 @@
}
} // namespace
-template <typename T>
-void NEReorgLayerKernel::run_reorg(const Window &window)
+NEReorgLayerKernel::NEReorgLayerKernel()
+ : _input(nullptr), _output(nullptr), _stride(1)
{
+}
+
+void NEReorgLayerKernel::configure(const ITensor *input, ITensor *output, int32_t stride)
+{
+ ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
+
+ // Output auto inizialitation if not yet initialized
+ const TensorShape output_shape = misc::shape_calculator::compute_reorg_output_shape(*input->info(), stride);
+ auto_init_if_empty(*output->info(), input->info()->clone()->set_tensor_shape(output_shape));
+
+ // Perform validation step
+ ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), stride));
+
+ _input = input;
+ _output = output;
+ _stride = stride;
+
+ // The NEReorgLayerKernel doesn't need padding so update_window_and_padding() can be skipped
+ output->info()->set_valid_region(ValidRegion(Coordinates(), output->info()->tensor_shape()));
+
+ // Configure kernel window
+ Window win = calculate_max_window(*output->info(), Steps());
+
+ ICPPKernel::configure(win);
+}
+
+Status NEReorgLayerKernel::validate(const ITensorInfo *input, const ITensorInfo *output, int32_t stride)
+{
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, stride));
+ return Status{};
+}
+
+void NEReorgLayerKernel::run(const Window &window, const ThreadInfo &info)
+{
+ ARM_COMPUTE_UNUSED(info);
+ ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
+ ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICPPKernel::window(), window);
+
const DataLayout data_layout = _input->info()->data_layout();
const size_t idx_w = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH);
const size_t idx_h = get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT);
@@ -101,72 +139,8 @@
map_coords.set(idx_c, c % out_c);
// Perform mapping
- *(reinterpret_cast<T *>(out.ptr())) = *(reinterpret_cast<const T *>(in_ptr + _input->info()->offset_element_in_bytes(map_coords)));
+ std::memcpy(out.ptr(), in_ptr + _input->info()->offset_element_in_bytes(map_coords), _input->info()->element_size());
},
out);
}
-
-NEReorgLayerKernel::NEReorgLayerKernel()
- : _func(nullptr), _input(nullptr), _output(nullptr), _stride(1)
-{
-}
-
-void NEReorgLayerKernel::configure(const ITensor *input, ITensor *output, int32_t stride)
-{
- ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
-
- // Output auto inizialitation if not yet initialized
- const TensorShape output_shape = misc::shape_calculator::compute_reorg_output_shape(*input->info(), stride);
- auto_init_if_empty(*output->info(), input->info()->clone()->set_tensor_shape(output_shape));
-
- // Perform validation step
- ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), stride));
-
- _func = nullptr;
- _input = input;
- _output = output;
- _stride = stride;
-
- switch(input->info()->element_size())
- {
- case 1:
- _func = &NEReorgLayerKernel::run_reorg<uint8_t>;
- break;
- case 2:
- _func = &NEReorgLayerKernel::run_reorg<uint16_t>;
- break;
- case 4:
- _func = &NEReorgLayerKernel::run_reorg<uint32_t>;
- break;
- default:
- ARM_COMPUTE_ERROR("Element size not supported");
- break;
- }
-
- // The NEReorgLayerKernel doesn't need padding so update_window_and_padding() can be skipped
- output->info()->set_valid_region(ValidRegion(Coordinates(), output->info()->tensor_shape()));
-
- // Configure kernel window
- Window win = calculate_max_window(*output->info(), Steps());
-
- ICPPKernel::configure(win);
-}
-
-Status NEReorgLayerKernel::validate(const ITensorInfo *input, const ITensorInfo *output, int32_t stride)
-{
- ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, stride));
- return Status{};
-}
-
-void NEReorgLayerKernel::run(const Window &window, const ThreadInfo &info)
-{
- ARM_COMPUTE_UNUSED(info);
- ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
- ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICPPKernel::window(), window);
-
- if(_func != nullptr)
- {
- (this->*_func)(window);
- }
-}
} // namespace arm_compute
diff --git a/src/core/NEON/kernels/NEReverseKernel.cpp b/src/core/NEON/kernels/NEReverseKernel.cpp
index 62e4882..36398cf 100644
--- a/src/core/NEON/kernels/NEReverseKernel.cpp
+++ b/src/core/NEON/kernels/NEReverseKernel.cpp
@@ -189,31 +189,21 @@
switch(_input->info()->data_type())
{
case DataType::F32:
- run_reverse<float>(window, _input, _axis, _output);
+ case DataType::U32:
+ case DataType::S32:
+ run_reverse<uint32_t>(window, _input, _axis, _output);
break;
#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
case DataType::F16:
- run_reverse<float16_t>(window, _input, _axis, _output);
- break;
#endif // __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
- case DataType::U32:
- run_reverse<uint32_t>(window, _input, _axis, _output);
- break;
- case DataType::S32:
- run_reverse<int32_t>(window, _input, _axis, _output);
- break;
case DataType::S16:
- run_reverse<int16_t>(window, _input, _axis, _output);
- break;
case DataType::U16:
run_reverse<uint16_t>(window, _input, _axis, _output);
break;
case DataType::QASYMM8:
case DataType::U8:
- run_reverse<uint8_t>(window, _input, _axis, _output);
- break;
case DataType::S8:
- run_reverse<int8_t>(window, _input, _axis, _output);
+ run_reverse<uint8_t>(window, _input, _axis, _output);
break;
default:
ARM_COMPUTE_ERROR("Data type not supported");
diff --git a/src/core/NEON/kernels/NEStackLayerKernel.cpp b/src/core/NEON/kernels/NEStackLayerKernel.cpp
index 0c33f36..3447d59 100644
--- a/src/core/NEON/kernels/NEStackLayerKernel.cpp
+++ b/src/core/NEON/kernels/NEStackLayerKernel.cpp
@@ -87,7 +87,7 @@
} // namespace
NEStackLayerKernel::NEStackLayerKernel()
- : _input(nullptr), _output(nullptr), _axis(), _idx_input(), _func(nullptr)
+ : _input(nullptr), _output(nullptr), _axis(), _idx_input()
{
}
@@ -101,22 +101,6 @@
_axis = axis;
_idx_input = idx_input;
- switch(input->info()->element_size())
- {
- case 1:
- _func = &NEStackLayerKernel::run_stack<uint8_t>;
- break;
- case 2:
- _func = &NEStackLayerKernel::run_stack<uint16_t>;
- break;
- case 4:
- _func = &NEStackLayerKernel::run_stack<uint32_t>;
- break;
- default:
- ARM_COMPUTE_ERROR("Element size not supported");
- break;
- }
-
// Configure kernel window
auto win_config = validate_and_configure_window(input->info(), axis, num_tensors, output->info());
@@ -137,15 +121,6 @@
ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(INEKernel::window(), window);
- if(_func != nullptr)
- {
- (this->*_func)(window);
- }
-}
-
-template <typename T>
-void NEStackLayerKernel::run_stack(const Window &window)
-{
Window window_out;
window_out.use_tensor_dimensions(_output->info()->tensor_shape());
@@ -160,9 +135,9 @@
execute_window_loop(window, [&](const Coordinates & id)
{
- Coordinates id_out = shift_from_axis_and_replace_coordinate(id, _axis, _idx_input);
- const int idx = id_out[0] * stride_x + id_out[1] * stride_y + id_out[2] * stride_z + id_out[3] * stride_w + id_out[4] * stride_k;
- *(reinterpret_cast<T *>(output.ptr() + idx)) = *(reinterpret_cast<const T *>(input.ptr()));
+ Coordinates id_out = shift_from_axis_and_replace_coordinate(id, _axis, _idx_input);
+ const int idx = id_out[0] * stride_x + id_out[1] * stride_y + id_out[2] * stride_z + id_out[3] * stride_w + id_out[4] * stride_k;
+ std::memcpy(output.ptr() + idx, input.ptr(), _input->info()->element_size());
},
input);
}
diff --git a/src/core/NEON/kernels/NEWeightsReshapeKernel.cpp b/src/core/NEON/kernels/NEWeightsReshapeKernel.cpp
index 4a0cf27..624833a 100644
--- a/src/core/NEON/kernels/NEWeightsReshapeKernel.cpp
+++ b/src/core/NEON/kernels/NEWeightsReshapeKernel.cpp
@@ -34,59 +34,6 @@
namespace
{
-template <typename T>
-void weights_reshape(const ITensor *input, const ITensor *bias, ITensor *output, const Window &window)
-{
- const unsigned int kernel_size_x = input->info()->dimension(0);
- const unsigned int kernel_size_y = input->info()->dimension(1);
- const unsigned int kernel_depth = input->info()->dimension(2);
- const unsigned int input_stride_x = input->info()->strides_in_bytes().x();
- const unsigned int input_stride_y = input->info()->strides_in_bytes().y();
- const unsigned int input_stride_z = input->info()->strides_in_bytes().z();
- const unsigned int output_stride_y = output->info()->strides_in_bytes().y();
-
- // Create iterators
- Iterator in(input, window);
- execute_window_loop(window, [&](const Coordinates & id)
- {
- // Get column index
- const int kernel_idx = id[3];
- const int kernel_idz = id[4];
-
- // Setup pointers
- const uint8_t *tmp_input_ptr = in.ptr();
- uint8_t *tmp_output_ptr = output->ptr_to_element(Coordinates(kernel_idx, 0, kernel_idz));
- const uint8_t *curr_input_row_ptr = tmp_input_ptr;
- const uint8_t *curr_input_depth_ptr = tmp_input_ptr;
-
- // Linearize volume
- for(unsigned int d = 0; d < kernel_depth; ++d)
- {
- for(unsigned int j = 0; j < kernel_size_y; ++j)
- {
- for(unsigned int i = 0; i < kernel_size_x; ++i)
- {
- *(reinterpret_cast<T *>(tmp_output_ptr)) = *(reinterpret_cast<const T *>(tmp_input_ptr));
- tmp_input_ptr += input_stride_x;
- tmp_output_ptr += output_stride_y;
- }
- curr_input_row_ptr += input_stride_y;
- tmp_input_ptr = curr_input_row_ptr;
- }
- curr_input_depth_ptr += input_stride_z;
- curr_input_row_ptr = curr_input_depth_ptr;
- tmp_input_ptr = curr_input_depth_ptr;
- }
-
- // Add bias
- if(bias != nullptr)
- {
- *(reinterpret_cast<T *>(tmp_output_ptr)) = *(reinterpret_cast<const T *>(bias->ptr_to_element(Coordinates(kernel_idx, kernel_idz))));
- }
- },
- in);
-}
-
TensorShape get_output_shape(const ITensorInfo *input, bool has_bias)
{
TensorShape output_shape{ input->tensor_shape() };
@@ -141,7 +88,7 @@
} // namespace
NEWeightsReshapeKernel::NEWeightsReshapeKernel()
- : _func(nullptr), _input(nullptr), _bias(nullptr), _output(nullptr)
+ : _input(nullptr), _bias(nullptr), _output(nullptr)
{
}
@@ -161,30 +108,6 @@
_bias = bias;
_output = output;
- switch(_input->info()->element_size())
- {
- case 4:
- {
- _func = &weights_reshape<uint32_t>;
- break;
- }
- case 2:
- {
- _func = &weights_reshape<uint16_t>;
- break;
- }
- case 1:
- {
- _func = &weights_reshape<uint8_t>;
- break;
- }
- default:
- {
- ARM_COMPUTE_ERROR_ON("Element size not supported");
- break;
- }
- }
-
// Configure kernel
auto win_config = validate_and_configure_window(input->info(), output->info());
ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
@@ -205,5 +128,52 @@
ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(INEKernel::window(), window);
- (*_func)(_input, _bias, _output, window);
+ const unsigned int kernel_size_x = _input->info()->dimension(0);
+ const unsigned int kernel_size_y = _input->info()->dimension(1);
+ const unsigned int kernel_depth = _input->info()->dimension(2);
+ const unsigned int input_stride_x = _input->info()->strides_in_bytes().x();
+ const unsigned int input_stride_y = _input->info()->strides_in_bytes().y();
+ const unsigned int input_stride_z = _input->info()->strides_in_bytes().z();
+ const unsigned int output_stride_y = _output->info()->strides_in_bytes().y();
+
+ // Create iterators
+ Iterator in(_input, window);
+ execute_window_loop(window, [&](const Coordinates & id)
+ {
+ // Get column index
+ const int kernel_idx = id[3];
+ const int kernel_idz = id[4];
+
+ // Setup pointers
+ const uint8_t *tmp_input_ptr = in.ptr();
+ uint8_t *tmp_output_ptr = _output->ptr_to_element(Coordinates(kernel_idx, 0, kernel_idz));
+ const uint8_t *curr_input_row_ptr = tmp_input_ptr;
+ const uint8_t *curr_input_depth_ptr = tmp_input_ptr;
+
+ // Linearize volume
+ for(unsigned int d = 0; d < kernel_depth; ++d)
+ {
+ for(unsigned int j = 0; j < kernel_size_y; ++j)
+ {
+ for(unsigned int i = 0; i < kernel_size_x; ++i)
+ {
+ std::memcpy(tmp_output_ptr, tmp_input_ptr, _input->info()->element_size());
+ tmp_input_ptr += input_stride_x;
+ tmp_output_ptr += output_stride_y;
+ }
+ curr_input_row_ptr += input_stride_y;
+ tmp_input_ptr = curr_input_row_ptr;
+ }
+ curr_input_depth_ptr += input_stride_z;
+ curr_input_row_ptr = curr_input_depth_ptr;
+ tmp_input_ptr = curr_input_depth_ptr;
+ }
+
+ // Add bias
+ if(_bias != nullptr)
+ {
+ std::memcpy(tmp_output_ptr, _bias->ptr_to_element(Coordinates(kernel_idx, kernel_idz)), _input->info()->element_size());
+ }
+ },
+ in);
}