aboutsummaryrefslogtreecommitdiff
path: root/arm_compute/core/Helpers.inl
diff options
context:
space:
mode:
Diffstat (limited to 'arm_compute/core/Helpers.inl')
-rw-r--r--arm_compute/core/Helpers.inl130
1 files changed, 50 insertions, 80 deletions
diff --git a/arm_compute/core/Helpers.inl b/arm_compute/core/Helpers.inl
index a960876074..60a21e9418 100644
--- a/arm_compute/core/Helpers.inl
+++ b/arm_compute/core/Helpers.inl
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2016-2020 Arm Limited.
+ * Copyright (c) 2016-2021, 2023 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -32,12 +32,9 @@ template <size_t dimension>
struct IncrementIterators
{
template <typename T, typename... Ts>
- static void unroll(T &&it, Ts &&... iterators)
+ static void unroll(T &&it, Ts &&...iterators)
{
- auto increment = [](T && it)
- {
- it.increment(dimension);
- };
+ auto increment = [](T &&it) { it.increment(dimension); };
utility::for_each(increment, std::forward<T>(it), std::forward<Ts>(iterators)...);
}
static void unroll()
@@ -50,14 +47,14 @@ template <size_t dim>
struct ForEachDimension
{
template <typename L, typename... Ts>
- static void unroll(const Window &w, Coordinates &id, L &&lambda_function, Ts &&... iterators)
+ static void unroll(const Window &w, Coordinates &id, L &&lambda_function, Ts &&...iterators)
{
const auto &d = w[dim - 1];
- for(auto v = d.start(); v < d.end(); v += d.step(), IncrementIterators < dim - 1 >::unroll(iterators...))
+ for (auto v = d.start(); v < d.end(); v += d.step(), IncrementIterators<dim - 1>::unroll(iterators...))
{
id.set(dim - 1, v);
- ForEachDimension < dim - 1 >::unroll(w, id, lambda_function, iterators...);
+ ForEachDimension<dim - 1>::unroll(w, id, lambda_function, iterators...);
}
}
};
@@ -66,7 +63,7 @@ template <>
struct ForEachDimension<0>
{
template <typename L, typename... Ts>
- static void unroll(const Window &w, Coordinates &id, L &&lambda_function, Ts &&... iterators)
+ static void unroll(const Window &w, Coordinates &id, L &&lambda_function, Ts &&...iterators)
{
ARM_COMPUTE_UNUSED(w, iterators...);
lambda_function(id);
@@ -74,49 +71,60 @@ struct ForEachDimension<0>
};
template <typename L, typename... Ts>
-inline void execute_window_loop(const Window &w, L &&lambda_function, Ts &&... iterators)
+inline void execute_window_loop(const Window &w, L &&lambda_function, Ts &&...iterators)
{
w.validate();
- for(unsigned int i = 0; i < Coordinates::num_max_dimensions; ++i)
+ for (unsigned int i = 0; i < Coordinates::num_max_dimensions; ++i)
{
ARM_COMPUTE_ERROR_ON(w[i].step() == 0);
}
Coordinates id;
- ForEachDimension<Coordinates::num_max_dimensions>::unroll(w, id, std::forward<L>(lambda_function), std::forward<Ts>(iterators)...);
+ ForEachDimension<Coordinates::num_max_dimensions>::unroll(w, id, std::forward<L>(lambda_function),
+ std::forward<Ts>(iterators)...);
}
-inline constexpr Iterator::Iterator()
- : _ptr(nullptr), _dims()
+inline constexpr Iterator::Iterator() : _ptr(nullptr), _dims()
{
}
-inline Iterator::Iterator(const ITensor *tensor, const Window &win)
- : Iterator()
+inline Iterator::Iterator(const ITensor *tensor, const Window &win) : Iterator()
{
ARM_COMPUTE_ERROR_ON(tensor == nullptr);
ARM_COMPUTE_ERROR_ON(tensor->info() == nullptr);
- const ITensorInfo *info = tensor->info();
- const Strides &strides = info->strides_in_bytes();
+ initialize(tensor->info()->num_dimensions(), tensor->info()->strides_in_bytes(), tensor->buffer(),
+ tensor->info()->offset_first_element_in_bytes(), win);
+}
+
+inline Iterator::Iterator(size_t num_dims, const Strides &strides, uint8_t *buffer, size_t offset, const Window &win)
+ : Iterator()
+{
+ initialize(num_dims, strides, buffer, offset, win);
+}
- _ptr = tensor->buffer() + info->offset_first_element_in_bytes();
+inline void
+Iterator::initialize(size_t num_dims, const Strides &strides, uint8_t *buffer, size_t offset, const Window &win)
+{
+ ARM_COMPUTE_ERROR_ON(buffer == nullptr);
+
+ _ptr = buffer + offset;
//Initialize the stride for each dimension and calculate the position of the first element of the iteration:
- for(unsigned int n = 0; n < info->num_dimensions(); ++n)
+ for (unsigned int n = 0; n < num_dims; ++n)
{
_dims[n]._stride = win[n].step() * strides[n];
std::get<0>(_dims)._dim_start += static_cast<size_t>(strides[n]) * win[n].start();
}
//Copy the starting point to all the dimensions:
- for(unsigned int n = 1; n < Coordinates::num_max_dimensions; ++n)
+ for (unsigned int n = 1; n < Coordinates::num_max_dimensions; ++n)
{
_dims[n]._dim_start = std::get<0>(_dims)._dim_start;
}
- ARM_COMPUTE_ERROR_ON_WINDOW_DIMENSIONS_GTE(win, info->num_dimensions());
+ ARM_COMPUTE_ERROR_ON_WINDOW_DIMENSIONS_GTE(win, num_dims);
}
inline void Iterator::increment(const size_t dimension)
@@ -125,7 +133,7 @@ inline void Iterator::increment(const size_t dimension)
_dims[dimension]._dim_start += _dims[dimension]._stride;
- for(unsigned int n = 0; n < dimension; ++n)
+ for (unsigned int n = 0; n < dimension; ++n)
{
_dims[n]._dim_start = _dims[dimension]._dim_start;
}
@@ -147,7 +155,7 @@ inline void Iterator::reset(const size_t dimension)
_dims[dimension]._dim_start = _dims[dimension + 1]._dim_start;
- for(unsigned int n = 0; n < dimension; ++n)
+ for (unsigned int n = 0; n < dimension; ++n)
{
_dims[n]._dim_start = _dims[dimension]._dim_start;
}
@@ -160,9 +168,9 @@ inline Coordinates index2coords(const TensorShape &shape, int index)
ARM_COMPUTE_ERROR_ON_MSG(index < 0 || index >= num_elements, "Index has to be in [0, num_elements]!");
ARM_COMPUTE_ERROR_ON_MSG(num_elements == 0, "Cannot create coordinate from empty shape!");
- Coordinates coord{ 0 };
+ Coordinates coord{0};
- for(int d = shape.num_dimensions() - 1; d >= 0; --d)
+ for (int d = shape.num_dimensions() - 1; d >= 0; --d)
{
num_elements /= shape[d];
coord.set(d, index / num_elements);
@@ -181,7 +189,7 @@ inline int coords2index(const TensorShape &shape, const Coordinates &coord)
int index = 0;
int stride = 1;
- for(unsigned int d = 0; d < coord.num_dimensions(); ++d)
+ for (unsigned int d = 0; d < coord.num_dimensions(); ++d)
{
index += coord[d] * stride;
stride *= shape[d];
@@ -190,61 +198,23 @@ inline int coords2index(const TensorShape &shape, const Coordinates &coord)
return index;
}
-inline size_t get_data_layout_dimension_index(const DataLayout data_layout, const DataLayoutDimension data_layout_dimension)
+inline size_t get_data_layout_dimension_index(const DataLayout &data_layout,
+ const DataLayoutDimension &data_layout_dimension)
{
- ARM_COMPUTE_ERROR_ON_MSG(data_layout == DataLayout::UNKNOWN, "Cannot retrieve the dimension index for an unknown layout!");
-
- /* Return the index based on the data layout
- * [N C H W]
- * [3 2 1 0]
- * [N H W C]
- */
- switch(data_layout_dimension)
- {
- case DataLayoutDimension::CHANNEL:
- return (data_layout == DataLayout::NCHW) ? 2 : 0;
- break;
- case DataLayoutDimension::HEIGHT:
- return (data_layout == DataLayout::NCHW) ? 1 : 2;
- break;
- case DataLayoutDimension::WIDTH:
- return (data_layout == DataLayout::NCHW) ? 0 : 1;
- break;
- case DataLayoutDimension::BATCHES:
- return 3;
- break;
- default:
- break;
- }
- ARM_COMPUTE_ERROR("Data layout index not supported!");
+ ARM_COMPUTE_ERROR_ON_MSG(data_layout == DataLayout::UNKNOWN,
+ "Cannot retrieve the dimension index for an unknown layout!");
+ const auto &dims = get_layout_map().at(data_layout);
+ const auto &it = std::find(dims.cbegin(), dims.cend(), data_layout_dimension);
+ ARM_COMPUTE_ERROR_ON_MSG(it == dims.cend(), "Invalid dimension for the given layout.");
+ return it - dims.cbegin();
}
-inline DataLayoutDimension get_index_data_layout_dimension(const DataLayout data_layout, const size_t index)
+inline DataLayoutDimension get_index_data_layout_dimension(const DataLayout &data_layout, const size_t index)
{
- ARM_COMPUTE_ERROR_ON_MSG(data_layout == DataLayout::UNKNOWN, "Cannot retrieve the dimension index for an unknown layout!");
-
- /* Return the index based on the data layout
- * [N C H W]
- * [3 2 1 0]
- * [N H W C]
- */
- switch(index)
- {
- case 0:
- return (data_layout == DataLayout::NCHW) ? DataLayoutDimension::WIDTH : DataLayoutDimension::CHANNEL;
- break;
- case 1:
- return (data_layout == DataLayout::NCHW) ? DataLayoutDimension::HEIGHT : DataLayoutDimension::WIDTH;
- break;
- case 2:
- return (data_layout == DataLayout::NCHW) ? DataLayoutDimension::CHANNEL : DataLayoutDimension::HEIGHT;
- break;
- case 3:
- return DataLayoutDimension::BATCHES;
- break;
- default:
- ARM_COMPUTE_ERROR("Index value not supported!");
- break;
- }
+ ARM_COMPUTE_ERROR_ON_MSG(data_layout == DataLayout::UNKNOWN,
+ "Cannot retrieve the layout dimension for an unknown layout!");
+ const auto &dims = get_layout_map().at(data_layout);
+ ARM_COMPUTE_ERROR_ON_MSG(index >= dims.size(), "Invalid index for the given layout.");
+ return dims[index];
}
} // namespace arm_compute
generated by cgit v1.2.1 (git 2.23.0) at 2024-05-04 04:26:49 +0000