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>
diff --git a/src/core/utils/helpers/tensor_transform.cpp b/src/core/utils/helpers/tensor_transform.cpp
index f221699..19d0bad 100644
--- a/src/core/utils/helpers/tensor_transform.cpp
+++ b/src/core/utils/helpers/tensor_transform.cpp
@@ -36,10 +36,11 @@
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 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 @@
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 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 @@
}
// 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 @@
}
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 @@
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 @@
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 @@
{
// 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;
}