| /* |
| * Copyright (c) 2016, 2017 ARM Limited. |
| * |
| * SPDX-License-Identifier: MIT |
| * |
| * Permission is hereby granted, free of charge, to any person obtaining a copy |
| * of this software and associated documentation files (the "Software"), to |
| * deal in the Software without restriction, including without limitation the |
| * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or |
| * sell copies of the Software, and to permit persons to whom the Software is |
| * furnished to do so, subject to the following conditions: |
| * |
| * The above copyright notice and this permission notice shall be included in all |
| * copies or substantial portions of the Software. |
| * |
| * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR |
| * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, |
| * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE |
| * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER |
| * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, |
| * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE |
| * SOFTWARE. |
| */ |
| #ifndef __ARM_COMPUTE_HELPERS_H__ |
| #define __ARM_COMPUTE_HELPERS_H__ |
| |
| #include "arm_compute/core/CL/CLTypes.h" |
| #include "arm_compute/core/Coordinates.h" |
| #include "arm_compute/core/Error.h" |
| #include "arm_compute/core/IAccessWindow.h" |
| #include "arm_compute/core/Steps.h" |
| #include "arm_compute/core/Strides.h" |
| #include "arm_compute/core/TensorShape.h" |
| #include "arm_compute/core/Types.h" |
| #include "arm_compute/core/Window.h" |
| #include "arm_compute/core/utils/misc/utility.h" |
| |
| #include <array> |
| #include <cstddef> |
| #include <cstdint> |
| #include <memory> |
| #include <tuple> |
| #include <type_traits> |
| #include <utility> |
| |
| namespace arm_compute |
| { |
| class IKernel; |
| class ITensor; |
| class ITensorInfo; |
| |
| template <typename T> |
| struct enable_bitwise_ops |
| { |
| static constexpr bool value = false; |
| }; |
| |
| template <typename T> |
| typename std::enable_if<enable_bitwise_ops<T>::value, T>::type operator&(T lhs, T rhs) |
| { |
| using underlying_type = typename std::underlying_type<T>::type; |
| return static_cast<T>(static_cast<underlying_type>(lhs) & static_cast<underlying_type>(rhs)); |
| } |
| |
| namespace traits |
| { |
| /** Check if a type T is contained in a tuple Tuple of types */ |
| template <typename T, typename Tuple> |
| struct is_contained; |
| |
| template <typename T> |
| struct is_contained<T, std::tuple<>> : std::false_type |
| { |
| }; |
| |
| template <typename T, typename... Ts> |
| struct is_contained<T, std::tuple<T, Ts...>> : std::true_type |
| { |
| }; |
| |
| template <typename T, typename U, typename... Ts> |
| struct is_contained<T, std::tuple<U, Ts...>> : is_contained<T, std::tuple<Ts...>> |
| { |
| }; |
| } |
| |
| /** Computes bilinear interpolation using the pointer to the top-left pixel and the pixel's distance between |
| * the real coordinates and the smallest following integer coordinates. Input must be in single channel format. |
| * |
| * @param[in] pixel_ptr Pointer to the top-left pixel value of a single channel input. |
| * @param[in] stride Stride to access the bottom-left and bottom-right pixel values |
| * @param[in] dx Pixel's distance between the X real coordinate and the smallest X following integer |
| * @param[in] dy Pixel's distance between the Y real coordinate and the smallest Y following integer |
| * |
| * @note dx and dy must be in the range [0, 1.0] |
| * |
| * @return The bilinear interpolated pixel value |
| */ |
| template <typename T> |
| inline T delta_bilinear_c1(const T *pixel_ptr, size_t stride, float dx, float dy) |
| { |
| ARM_COMPUTE_ERROR_ON(pixel_ptr == nullptr); |
| |
| const float dx1 = 1.0f - dx; |
| const float dy1 = 1.0f - dy; |
| |
| const T a00 = *pixel_ptr; |
| const T a01 = *(pixel_ptr + 1); |
| const T a10 = *(pixel_ptr + stride); |
| const T a11 = *(pixel_ptr + stride + 1); |
| |
| const float w1 = dx1 * dy1; |
| const float w2 = dx * dy1; |
| const float w3 = dx1 * dy; |
| const float w4 = dx * dy; |
| |
| return static_cast<T>(a00 * w1 + a01 * w2 + a10 * w3 + a11 * w4); |
| } |
| |
| /** Computes linear interpolation using the pointer to the top pixel and the pixel's distance between |
| * the real coordinates and the smallest following integer coordinates. Input must be in single channel format. |
| * |
| * @param[in] pixel_ptr Pointer to the top pixel value of a single channel input. |
| * @param[in] stride Stride to access the bottom pixel value |
| * @param[in] dy Pixel's distance between the Y real coordinate and the smallest Y following integer |
| * |
| * @note dy must be in the range [0, 1.0] |
| * |
| * @return The linear interpolated pixel value |
| */ |
| template <typename T> |
| inline T delta_linear_c1_y(const T *pixel_ptr, size_t stride, float dy) |
| { |
| ARM_COMPUTE_ERROR_ON(pixel_ptr == nullptr); |
| |
| const float dy1 = 1.0f - dy; |
| |
| const T a00 = *pixel_ptr; |
| const T a10 = *(pixel_ptr + stride); |
| |
| const float w1 = dy1; |
| const float w3 = dy; |
| |
| return static_cast<T>(a00 * w1 + a10 * w3); |
| } |
| /** Computes linear interpolation using the pointer to the left pixel and the pixel's distance between |
| * the real coordinates and the smallest following integer coordinates. Input must be in single channel format. |
| * |
| * @param[in] pixel_ptr Pointer to the left pixel value of a single channel input. |
| * @param[in] dx Pixel's distance between the X real coordinate and the smallest X following integer |
| * |
| * @note dx must be in the range [0, 1.0] |
| * |
| * @return The linear interpolated pixel value |
| */ |
| template <typename T> |
| inline T delta_linear_c1_x(const T *pixel_ptr, float dx) |
| { |
| ARM_COMPUTE_ERROR_ON(pixel_ptr == nullptr); |
| |
| const T a00 = *pixel_ptr; |
| const T a01 = *(pixel_ptr + 1); |
| |
| const float dx1 = 1.0f - dx; |
| |
| const float w1 = dx1; |
| const float w2 = dx; |
| |
| return static_cast<T>(a00 * w1 + a01 * w2); |
| } |
| /** Return the pixel at (x,y) using bilinear interpolation. |
| * |
| * @warning Only works if the iterator was created with an IImage |
| * |
| * @param[in] first_pixel_ptr Pointer to the first pixel of a single channel input. |
| * @param[in] stride Stride in bytes of the image; |
| * @param[in] x X position of the wanted pixel |
| * @param[in] y Y position of the wanted pixel |
| * |
| * @return The pixel at (x, y) using bilinear interpolation. |
| */ |
| template <typename T> |
| inline T pixel_bilinear_c1(const T *first_pixel_ptr, size_t stride, float x, float y) |
| { |
| ARM_COMPUTE_ERROR_ON(first_pixel_ptr == nullptr); |
| |
| const int32_t xi = std::floor(x); |
| const int32_t yi = std::floor(y); |
| |
| const float dx = x - xi; |
| const float dy = y - yi; |
| |
| return delta_bilinear_c1(first_pixel_ptr + xi + yi * stride, stride, dx, dy); |
| } |
| |
| /** Return the pixel at (x,y) using bilinear interpolation by clamping when out of borders. The image must be single channel input |
| * |
| * @warning Only works if the iterator was created with an IImage |
| * |
| * @param[in] first_pixel_ptr Pointer to the first pixel of a single channel image. |
| * @param[in] stride Stride in bytes of the image |
| * @param[in] width Width of the image |
| * @param[in] height Height of the image |
| * @param[in] x X position of the wanted pixel |
| * @param[in] y Y position of the wanted pixel |
| * |
| * @return The pixel at (x, y) using bilinear interpolation. |
| */ |
| template <typename T> |
| inline uint8_t pixel_bilinear_c1_clamp(const T *first_pixel_ptr, size_t stride, size_t width, size_t height, float x, float y) |
| { |
| ARM_COMPUTE_ERROR_ON(first_pixel_ptr == nullptr); |
| |
| x = std::max(-1.f, std::min(x, static_cast<float>(width))); |
| y = std::max(-1.f, std::min(y, static_cast<float>(height))); |
| |
| const float xi = std::floor(x); |
| const float yi = std::floor(y); |
| |
| const float dx = x - xi; |
| const float dy = y - yi; |
| |
| if(dx == 0.0f) |
| { |
| if(dy == 0.0f) |
| { |
| return static_cast<T>(first_pixel_ptr[static_cast<int32_t>(xi) + static_cast<int32_t>(yi) * stride]); |
| } |
| return delta_linear_c1_y(first_pixel_ptr + static_cast<int32_t>(xi) + static_cast<int32_t>(yi) * stride, stride, dy); |
| } |
| if(dy == 0.0f) |
| { |
| return delta_linear_c1_x(first_pixel_ptr + static_cast<int32_t>(xi) + static_cast<int32_t>(yi) * stride, dx); |
| } |
| return delta_bilinear_c1(first_pixel_ptr + static_cast<int32_t>(xi) + static_cast<int32_t>(yi) * stride, stride, dx, dy); |
| } |
| |
| /** Return the pixel at (x,y) using area interpolation by clamping when out of borders. The image must be single channel U8 |
| * |
| * @note The interpolation area depends on the width and height ration of the input and output images |
| * @note Currently average of the contributing pixels is calculated |
| * |
| * @param[in] first_pixel_ptr Pointer to the first pixel of a single channel U8 image. |
| * @param[in] stride Stride in bytes of the image |
| * @param[in] width Width of the image |
| * @param[in] height Height of the image |
| * @param[in] wr Width ratio among the input image width and output image width. |
| * @param[in] hr Height ratio among the input image height and output image height. |
| * @param[in] x X position of the wanted pixel |
| * @param[in] y Y position of the wanted pixel |
| * |
| * @return The pixel at (x, y) using area interpolation. |
| */ |
| inline uint8_t pixel_area_c1u8_clamp(const uint8_t *first_pixel_ptr, size_t stride, size_t width, size_t height, float wr, float hr, int x, int y); |
| |
| /** Iterator updated by @ref execute_window_loop for each window element */ |
| class Iterator |
| { |
| public: |
| /** Default constructor to create an empty iterator */ |
| constexpr Iterator(); |
| /** Create a container iterator for the metadata and allocation contained in the ITensor |
| * |
| * @param[in] tensor The tensor to associate to the iterator. |
| * @param[in] window The window which will be used to iterate over the tensor. |
| */ |
| Iterator(const ITensor *tensor, const Window &window); |
| |
| /** Increment the iterator along the specified dimension of the step value associated to the dimension. |
| * |
| * @warning It is the caller's responsibility to call increment(dimension+1) when reaching the end of a dimension, the iterator will not check for overflow. |
| * |
| * @note When incrementing a dimension 'n' the coordinates of all the dimensions in the range (0,n-1) are reset. For example if you iterate over a 2D image, everytime you change row (dimension 1), the iterator for the width (dimension 0) is reset to its start. |
| * |
| * @param[in] dimension Dimension to increment |
| */ |
| void increment(size_t dimension); |
| |
| /** Return the offset in bytes from the first element to the current position of the iterator |
| * |
| * @return The current position of the iterator in bytes relative to the first element. |
| */ |
| constexpr int offset() const; |
| |
| /** Return a pointer to the current pixel. |
| * |
| * @warning Only works if the iterator was created with an ITensor. |
| * |
| * @return equivalent to buffer() + offset() |
| */ |
| constexpr uint8_t *ptr() const; |
| |
| /** Move the iterator back to the beginning of the specified dimension. |
| * |
| * @param[in] dimension Dimension to reset |
| */ |
| void reset(size_t dimension); |
| |
| private: |
| uint8_t *_ptr; |
| |
| class Dimension |
| { |
| public: |
| constexpr Dimension() |
| : _dim_start(0), _stride(0) |
| { |
| } |
| |
| int _dim_start; |
| int _stride; |
| }; |
| |
| std::array<Dimension, Coordinates::num_max_dimensions> _dims; |
| }; |
| |
| /** Iterate through the passed window, automatically adjusting the iterators and calling the lambda_functino for each element. |
| * It passes the x and y positions to the lambda_function for each iteration |
| * |
| * @param[in] w Window to iterate through. |
| * @param[in] lambda_function The function of type void(function)( const Coordinates & id ) to call at each iteration. |
| * Where id represents the absolute coordinates of the item to process. |
| * @param[in,out] iterators Tensor iterators which will be updated by this function before calling lambda_function. |
| */ |
| template <typename L, typename... Ts> |
| inline void execute_window_loop(const Window &w, L &&lambda_function, Ts &&... iterators); |
| |
| /** Update window and padding size for each of the access patterns. |
| * |
| * First the window size is reduced based on all access patterns that are not |
| * allowed to modify the padding of the underlying tensor. Then the padding of |
| * the remaining tensors is increased to match the window. |
| * |
| * @param[in] win Window that is used by the kernel. |
| * @param[in] patterns Access patterns used to calculate the final window and padding. |
| * |
| * @return True if the window has been changed. Changes to the padding do not |
| * influence the returned value. |
| */ |
| template <typename... Ts> |
| bool update_window_and_padding(Window &win, Ts &&... patterns) |
| { |
| bool window_changed = false; |
| |
| utility::for_each([&](const IAccessWindow & w) |
| { |
| window_changed |= w.update_window_if_needed(win); |
| }, |
| patterns...); |
| |
| bool padding_changed = false; |
| |
| utility::for_each([&](const IAccessWindow & w) |
| { |
| padding_changed |= w.update_padding_if_needed(win); |
| }, |
| patterns...); |
| |
| return window_changed; |
| } |
| |
| /** Calculate the maximum window for a given tensor shape and border setting |
| * |
| * @param[in] info Tensor info object defining the shape of the object for which the window is created. |
| * @param[in] steps (Optional) Number of elements processed for each step. |
| * @param[in] skip_border (Optional) If true exclude the border region from the window. |
| * @param[in] border_size (Optional) Border size. |
| * |
| * @return The maximum window the kernel can be executed on. |
| */ |
| Window calculate_max_window(const ITensorInfo &info, const Steps &steps = Steps(), bool skip_border = false, BorderSize border_size = BorderSize()); |
| |
| /** Calculate the maximum window used by a horizontal kernel for a given tensor shape and border setting |
| * |
| * @param[in] info Tensor info object defining the shape of the object for which the window is created. |
| * @param[in] steps (Optional) Number of elements processed for each step. |
| * @param[in] skip_border (Optional) If true exclude the border region from the window. |
| * @param[in] border_size (Optional) Border size. The border region will be excluded from the window. |
| * |
| * @return The maximum window the kernel can be executed on. |
| */ |
| Window calculate_max_window_horizontal(const ITensorInfo &info, const Steps &steps = Steps(), bool skip_border = false, BorderSize border_size = BorderSize()); |
| |
| /** Calculate the maximum window for a given tensor shape and border setting. The window will also includes the border. |
| * |
| * @param[in] info Tensor info object defining the shape of the object for which the window is created. |
| * @param[in] steps (Optional) Number of elements processed for each step. |
| * @param[in] border_size (Optional) Border size. The border region will be included in the window. |
| * |
| * @return The maximum window the kernel can be executed on. |
| */ |
| Window calculate_max_enlarged_window(const ITensorInfo &info, const Steps &steps = Steps(), BorderSize border_size = BorderSize()); |
| |
| /** Intersect multiple valid regions. |
| * |
| * @param[in] regions Valid regions. |
| * |
| * @return Intersection of all regions. |
| */ |
| template <typename... Ts> |
| ValidRegion intersect_valid_regions(const Ts &... regions) |
| { |
| auto intersect = [](const ValidRegion & r1, const ValidRegion & r2) -> ValidRegion |
| { |
| ValidRegion region; |
| |
| for(size_t d = 0; d < std::min(r1.anchor.num_dimensions(), r2.anchor.num_dimensions()); ++d) |
| { |
| region.anchor.set(d, std::max(r1.anchor[d], r2.anchor[d])); |
| } |
| |
| for(size_t d = 0; d < std::min(r1.shape.num_dimensions(), r2.shape.num_dimensions()); ++d) |
| { |
| region.shape.set(d, std::min(r1.shape[d], r2.shape[d])); |
| } |
| |
| return region; |
| }; |
| |
| return utility::foldl(intersect, regions...); |
| } |
| |
| /** Create a strides object based on the provided strides and the tensor dimensions. |
| * |
| * @param[in] info Tensor info object providing the shape of the tensor for unspecified strides. |
| * @param[in] stride_x Stride to be used in X dimension (in bytes). |
| * @param[in] fixed_strides Strides to be used in higher dimensions starting at Y (in bytes). |
| * |
| * @return Strides object based on the specified strides. Missing strides are |
| * calculated based on the tensor shape and the strides of lower dimensions. |
| */ |
| template <typename T, typename... Ts> |
| inline Strides compute_strides(const ITensorInfo &info, T stride_x, Ts &&... fixed_strides) |
| { |
| const TensorShape &shape = info.tensor_shape(); |
| |
| // Create strides object |
| Strides strides(stride_x, fixed_strides...); |
| |
| for(size_t i = 1 + sizeof...(Ts); i < info.num_dimensions(); ++i) |
| { |
| strides.set(i, shape[i - 1] * strides[i - 1]); |
| } |
| |
| return strides; |
| } |
| |
| /** Create a strides object based on the tensor dimensions. |
| * |
| * @param[in] info Tensor info object used to compute the strides. |
| * |
| * @return Strides object based on element size and tensor shape. |
| */ |
| template <typename... Ts> |
| inline Strides compute_strides(const ITensorInfo &info) |
| { |
| return compute_strides(info, info.element_size()); |
| } |
| |
| /** Permutes given Dimensions according to a permutation vector |
| * |
| * @warning Validity of permutation is not checked |
| * |
| * @param[in, out] dimensions Dimensions to permute |
| * @param[in] perm Permutation vector |
| */ |
| template <typename T> |
| inline void permute(Dimensions<T> &dimensions, const PermutationVector &perm) |
| { |
| auto copy_dimensions = utility::make_array<Dimensions<T>::num_max_dimensions>(dimensions.begin(), dimensions.end()); |
| for(unsigned int i = 0; i < perm.num_dimensions(); ++i) |
| { |
| dimensions[i] = copy_dimensions[perm[i]]; |
| } |
| } |
| |
| /* Auto initialize the tensor info (shape, number of channels, data type and fixed point position) if the current assignment is empty. |
| * |
| * @param[in,out] info Tensor info used to check and assign. |
| * @param[in] shape New shape. |
| * @param[in] num_channels New number of channels. |
| * @param[in] data_type New data type |
| * @param[in] fixed_point_position New fixed point position |
| * @param[in] quantization_info (Optional) New quantization info |
| * |
| * @return True if the tensor info has been initialized |
| */ |
| bool auto_init_if_empty(ITensorInfo &info, |
| const TensorShape &shape, |
| int num_channels, DataType data_type, |
| int fixed_point_position, |
| QuantizationInfo quantization_info = QuantizationInfo()); |
| |
| /** Auto initialize the tensor info using another tensor info. |
| * |
| * @param info_sink Tensor info used to check and assign |
| * @param info_source Tensor info used to assign |
| * |
| * @return True if the tensor info has been initialized |
| */ |
| bool auto_init_if_empty(ITensorInfo &info_sink, const ITensorInfo &info_source); |
| |
| /* Set the shape to the specified value if the current assignment is empty. |
| * |
| * @param[in,out] info Tensor info used to check and assign. |
| * @param[in] shape New shape. |
| * |
| * @return True if the shape has been changed. |
| */ |
| bool set_shape_if_empty(ITensorInfo &info, const TensorShape &shape); |
| |
| /* Set the format, data type and number of channels to the specified value if |
| * the current data type is unknown. |
| * |
| * @param[in,out] info Tensor info used to check and assign. |
| * @param[in] format New format. |
| * |
| * @return True if the format has been changed. |
| */ |
| bool set_format_if_unknown(ITensorInfo &info, Format format); |
| |
| /* Set the data type and number of channels to the specified value if |
| * the current data type is unknown. |
| * |
| * @param[in,out] info Tensor info used to check and assign. |
| * @param[in] data_type New data type. |
| * |
| * @return True if the data type has been changed. |
| */ |
| bool set_data_type_if_unknown(ITensorInfo &info, DataType data_type); |
| |
| /* Set the fixed point position to the specified value if |
| * the current fixed point position is 0 and the data type is QS8 or QS16 |
| * |
| * @param[in,out] info Tensor info used to check and assign. |
| * @param[in] fixed_point_position New fixed point position |
| * |
| * @return True if the fixed point position has been changed. |
| */ |
| bool set_fixed_point_position_if_zero(ITensorInfo &info, int fixed_point_position); |
| |
| /* Set the quantization info to the specified value if |
| * the current quantization info is empty and the data type of asymmetric quantized type |
| * |
| * @param[in,out] info Tensor info used to check and assign. |
| * @param[in] quantization_info Quantization info |
| * |
| * @return True if the quantization info has been changed. |
| */ |
| bool set_quantization_info_if_empty(ITensorInfo &info, QuantizationInfo quantization_info); |
| |
| /** Helper function to calculate the Valid Region for Scale. |
| * |
| * @param[in] src_info Input tensor info used to check. |
| * @param[in] dst_shape Shape of the output. |
| * @param[in] policy Interpolation policy. |
| * @param[in] border_size Size of the border. |
| * @param[in] border_undefined True if the border is undefined. |
| * |
| * @return The corrispondent valid region |
| */ |
| ValidRegion calculate_valid_region_scale(const ITensorInfo &src_info, const TensorShape &dst_shape, InterpolationPolicy policy, BorderSize border_size, bool border_undefined); |
| |
| /** Convert a linear index into n-dimensional coordinates. |
| * |
| * @param[in] shape Shape of the n-dimensional tensor. |
| * @param[in] index Linear index specifying the i-th element. |
| * |
| * @return n-dimensional coordinates. |
| */ |
| inline Coordinates index2coords(const TensorShape &shape, int index); |
| |
| /** Convert n-dimensional coordinates into a linear index. |
| * |
| * @param[in] shape Shape of the n-dimensional tensor. |
| * @param[in] coord N-dimensional coordinates. |
| * |
| * @return linead index |
| */ |
| inline int coords2index(const TensorShape &shape, const Coordinates &coord); |
| } // namespace arm_compute |
| |
| #include "arm_compute/core/Helpers.inl" |
| #endif /*__ARM_COMPUTE_HELPERS_H__ */ |