diff options
author | Felix Thomasmathibalan <felixjohnny.thomasmathibalan@arm.com> | 2023-09-27 17:46:17 +0100 |
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committer | felixjohnny.thomasmathibalan <felixjohnny.thomasmathibalan@arm.com> | 2023-09-28 12:08:05 +0000 |
commit | afd38f0c617d6f89b2b4532c6c44f116617e2b6f (patch) | |
tree | 03bc7d5a762099989b16a656fa8d397b490ed70e /src/core/utils/helpers | |
parent | bdcb4c148ee2fdeaaddf4cf1e57bbb0de02bb894 (diff) | |
download | ComputeLibrary-afd38f0c617d6f89b2b4532c6c44f116617e2b6f.tar.gz |
Apply clang-format on repository
Code is formatted as per a revised clang format configuration
file(not part of this delivery). Version 14.0.6 is used.
Exclusion List:
- files with .cl extension
- files that are not strictly C/C++ (e.g. Android.bp, Sconscript ...)
And the following directories
- compute_kernel_writer/validation/
- tests/
- include/
- src/core/NEON/kernels/convolution/
- src/core/NEON/kernels/arm_gemm/
- src/core/NEON/kernels/arm_conv/
- data/
There will be a follow up for formatting of .cl files and the
files under tests/ and compute_kernel_writer/validation/.
Signed-off-by: Felix Thomasmathibalan <felixjohnny.thomasmathibalan@arm.com>
Change-Id: Ib7eb1fcf4e7537b9feaefcfc15098a804a3fde0a
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10391
Benchmark: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Gunes Bayir <gunes.bayir@arm.com>
Diffstat (limited to 'src/core/utils/helpers')
-rw-r--r-- | src/core/utils/helpers/fft.cpp | 19 | ||||
-rw-r--r-- | src/core/utils/helpers/float_ops.h | 3 | ||||
-rw-r--r-- | src/core/utils/helpers/tensor_info.h | 14 | ||||
-rw-r--r-- | src/core/utils/helpers/tensor_transform.cpp | 63 |
4 files changed, 58 insertions, 41 deletions
diff --git a/src/core/utils/helpers/fft.cpp b/src/core/utils/helpers/fft.cpp index 64633c643d..edc8d0eacc 100644 --- a/src/core/utils/helpers/fft.cpp +++ b/src/core/utils/helpers/fft.cpp @@ -37,7 +37,7 @@ std::vector<unsigned int> decompose_stages(unsigned int N, const std::set<unsign unsigned int res = N; // Early exit if no supported factors are provided - if(supported_factors.empty()) + if (supported_factors.empty()) { return stages; } @@ -46,10 +46,10 @@ std::vector<unsigned int> decompose_stages(unsigned int N, const std::set<unsign auto rfactor_it = supported_factors.rbegin(); // Decomposition step - while(res != 0) + while (res != 0) { const unsigned int factor = *rfactor_it; - if(0 == (res % factor) && res >= factor) + if (0 == (res % factor) && res >= factor) { stages.push_back(factor); res /= factor; @@ -57,9 +57,9 @@ std::vector<unsigned int> decompose_stages(unsigned int N, const std::set<unsign else { ++rfactor_it; - if(rfactor_it == supported_factors.rend()) + if (rfactor_it == supported_factors.rend()) { - if(res > 1) + if (res > 1) { // Couldn't decompose with given factors stages.clear(); @@ -81,8 +81,9 @@ std::vector<unsigned int> digit_reverse_indices(unsigned int N, const std::vecto std::vector<unsigned int> idx_digit_reverse; // Early exit in case N and fft stages do not match - const float stages_prod = std::accumulate(std::begin(fft_stages), std::end(fft_stages), 1, std::multiplies<unsigned int>()); - if(stages_prod != N) + const float stages_prod = + std::accumulate(std::begin(fft_stages), std::end(fft_stages), 1, std::multiplies<unsigned int>()); + if (stages_prod != N) { return idx_digit_reverse; } @@ -94,13 +95,13 @@ std::vector<unsigned int> digit_reverse_indices(unsigned int N, const std::vecto unsigned int n_stages = fft_stages.size(); // Scan elements - for(unsigned int n = 0; n < N; ++n) + for (unsigned int n = 0; n < N; ++n) { unsigned int k = n; unsigned int Nx = fft_stages[0]; // Scan stages - for(unsigned int s = 1; s < n_stages; ++s) + for (unsigned int s = 1; s < n_stages; ++s) { // radix of stage i-th unsigned int Ny = fft_stages[s]; diff --git a/src/core/utils/helpers/float_ops.h b/src/core/utils/helpers/float_ops.h index 99e1ea54ee..7f7fbd13bf 100644 --- a/src/core/utils/helpers/float_ops.h +++ b/src/core/utils/helpers/float_ops.h @@ -39,8 +39,7 @@ union RawFloat * * @param[in] val Floating-point value */ - explicit RawFloat(float val) - : f32(val) + explicit RawFloat(float val) : f32(val) { } /** Extract sign of floating point number diff --git a/src/core/utils/helpers/tensor_info.h b/src/core/utils/helpers/tensor_info.h index 9279532e2a..fd4745a453 100644 --- a/src/core/utils/helpers/tensor_info.h +++ b/src/core/utils/helpers/tensor_info.h @@ -41,15 +41,17 @@ namespace tensor_info * @return True if tensors have mismatching quantization info else false. */ template <typename... Ts> -inline bool tensors_have_different_quantization_info(const ITensorInfo *tensor_info_1, const ITensorInfo *tensor_info_2, Ts... tensor_infos) +inline bool tensors_have_different_quantization_info(const ITensorInfo *tensor_info_1, + const ITensorInfo *tensor_info_2, + Ts... tensor_infos) { const QuantizationInfo first_quantization_info = tensor_info_1->quantization_info(); - const std::array < const ITensorInfo *, 1 + sizeof...(Ts) > tensor_infos_array{ { tensor_info_2, std::forward<Ts>(tensor_infos)... } }; - return std::any_of(tensor_infos_array.begin(), tensor_infos_array.end(), [&](const ITensorInfo * tensor_info) - { - return tensor_info->quantization_info() != first_quantization_info; - }); + const std::array<const ITensorInfo *, 1 + sizeof...(Ts)> tensor_infos_array{ + {tensor_info_2, std::forward<Ts>(tensor_infos)...}}; + return std::any_of(tensor_infos_array.begin(), tensor_infos_array.end(), + [&](const ITensorInfo *tensor_info) + { return tensor_info->quantization_info() != first_quantization_info; }); } } // namespace tensor_info } // namespace helpers diff --git a/src/core/utils/helpers/tensor_transform.cpp b/src/core/utils/helpers/tensor_transform.cpp index f2216995a9..19d0badd74 100644 --- a/src/core/utils/helpers/tensor_transform.cpp +++ b/src/core/utils/helpers/tensor_transform.cpp @@ -36,10 +36,11 @@ int calculate_stride_on_index(int index, Coordinates strides) return index >= static_cast<int>(strides.num_dimensions()) ? 1 : strides[index]; } -int calculate_start_on_index(TensorShape input_shape, int index, Coordinates starts, Coordinates strides, int32_t begin_mask) +int calculate_start_on_index( + TensorShape input_shape, int index, Coordinates starts, Coordinates strides, int32_t begin_mask) { // Early exit - if(index >= static_cast<int>(starts.num_dimensions())) + if (index >= static_cast<int>(starts.num_dimensions())) { return 0; } @@ -51,14 +52,14 @@ int calculate_start_on_index(TensorShape input_shape, int index, Coordinates sta int start = starts[index]; // Reset in case of begin mask present - if(arm_compute::helpers::bit_ops::is_bit_set(begin_mask, index)) + if (arm_compute::helpers::bit_ops::is_bit_set(begin_mask, index)) { start = stride > 0 ? std::numeric_limits<int>::lowest() : std::numeric_limits<int>::max(); } // Account negative start points const int dim_size = input_shape[index]; - if(start < 0) + if (start < 0) { start += dim_size; } @@ -69,12 +70,16 @@ int calculate_start_on_index(TensorShape input_shape, int index, Coordinates sta return start; } -int calculate_end_on_index(TensorShape input_shape, int index, int start_on_index, - Coordinates ends, Coordinates strides, - int32_t end_mask, int32_t shrink_axis_mask) +int calculate_end_on_index(TensorShape input_shape, + int index, + int start_on_index, + Coordinates ends, + Coordinates strides, + int32_t end_mask, + int32_t shrink_axis_mask) { // Early exit - if(index >= static_cast<int>(ends.num_dimensions())) + if (index >= static_cast<int>(ends.num_dimensions())) { return input_shape[index]; } @@ -86,9 +91,9 @@ int calculate_end_on_index(TensorShape input_shape, int index, int start_on_inde int stop = ends[index]; // Shrink dimension - if(shrink_axis) + if (shrink_axis) { - if(start_on_index == std::numeric_limits<int>::max()) + if (start_on_index == std::numeric_limits<int>::max()) { stop = start_on_index; } @@ -99,14 +104,14 @@ int calculate_end_on_index(TensorShape input_shape, int index, int start_on_inde } // Reset in case of begin mask present - if(arm_compute::helpers::bit_ops::is_bit_set(end_mask, index) && !shrink_axis) + if (arm_compute::helpers::bit_ops::is_bit_set(end_mask, index) && !shrink_axis) { stop = (stride > 0) ? std::numeric_limits<int>::max() : std::numeric_limits<int>::lowest(); } // Account negative end points const int dim_size = input_shape[index]; - if(stop < 0) + if (stop < 0) { stop += dim_size; } @@ -118,14 +123,18 @@ int calculate_end_on_index(TensorShape input_shape, int index, int start_on_inde } std::tuple<Coordinates, Coordinates, Coordinates> calculate_strided_slice_coords(TensorShape input_shape, - Coordinates starts, Coordinates ends, Coordinates strides, - int32_t begin_mask, int32_t end_mask, int32_t shrink_axis_mask) + Coordinates starts, + Coordinates ends, + Coordinates strides, + int32_t begin_mask, + int32_t end_mask, + int32_t shrink_axis_mask) { Coordinates starts_abs{}; Coordinates ends_abs{}; Coordinates final_strides{}; - for(unsigned int i = 0; i < input_shape.num_dimensions(); ++i) + for (unsigned int i = 0; i < input_shape.num_dimensions(); ++i) { const int start_i = calculate_start_on_index(input_shape, i, starts, strides, begin_mask); starts_abs.set(i, start_i); @@ -136,13 +145,19 @@ std::tuple<Coordinates, Coordinates, Coordinates> calculate_strided_slice_coords return std::make_tuple(starts_abs, ends_abs, final_strides); } -TensorShape compute_strided_slice_output_shape(TensorShape input_shape, Coordinates starts, Coordinates ends, Coordinates strides, - int32_t begin_mask, int32_t end_mask, int32_t shrink_axis_mask, bool return_unshrinked) +TensorShape compute_strided_slice_output_shape(TensorShape input_shape, + Coordinates starts, + Coordinates ends, + Coordinates strides, + int32_t begin_mask, + int32_t end_mask, + int32_t shrink_axis_mask, + bool return_unshrinked) { unsigned int index = 0; TensorShape output_shape; - for(unsigned int i = 0; i < input_shape.num_dimensions(); ++i) + for (unsigned int i = 0; i < input_shape.num_dimensions(); ++i) { const int stride = calculate_stride_on_index(index, strides); const int start = calculate_start_on_index(input_shape, i, starts, strides, begin_mask); @@ -150,11 +165,11 @@ TensorShape compute_strided_slice_output_shape(TensorShape input_shape, Coordina const int range = end - start; const bool is_shrink = arm_compute::helpers::bit_ops::is_bit_set(shrink_axis_mask, i); - if(return_unshrinked || !is_shrink) + if (return_unshrinked || !is_shrink) { - if((range == 0) || // Zero range - (range < 0 && stride >= 0) || // Negative range with positive stride - (range > 0 && stride <= 0)) // Positive range with negative stride + if ((range == 0) || // Zero range + (range < 0 && stride >= 0) || // Negative range with positive stride + (range > 0 && stride <= 0)) // Positive range with negative stride { output_shape.set(index, 0); return output_shape; @@ -173,9 +188,9 @@ int32_t construct_slice_end_mask(Coordinates ends) { // Create end mask int32_t end_mask = 0; - for(unsigned int i = 0; i < ends.num_dimensions(); ++i) + for (unsigned int i = 0; i < ends.num_dimensions(); ++i) { - if(ends[i] < 0) + if (ends[i] < 0) { end_mask |= 1 << i; } |