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-rw-r--r--arm_compute/core/utils/FormatUtils.h4
-rw-r--r--arm_compute/core/utils/misc/ShapeCalculator.h12
2 files changed, 8 insertions, 8 deletions
diff --git a/arm_compute/core/utils/FormatUtils.h b/arm_compute/core/utils/FormatUtils.h
index 10e6f747f2..afb0f78255 100644
--- a/arm_compute/core/utils/FormatUtils.h
+++ b/arm_compute/core/utils/FormatUtils.h
@@ -24,7 +24,8 @@
#ifndef ARM_COMPUTE_CORE_UTILS_FORMATUTILS_H
#define ARM_COMPUTE_CORE_UTILS_FORMATUTILS_H
-#include "arm_compute/core/Types.h"
+#include "arm_compute/core/CoreTypes.h"
+#include "arm_compute/core/Error.h"
namespace arm_compute
{
@@ -339,6 +340,5 @@ inline size_t num_channels_from_format(Format format)
* @return The string describing the format.
*/
const std::string &string_from_format(Format format);
-
}
#endif /*ARM_COMPUTE_CORE_UTILS_FORMATUTILS_H */
diff --git a/arm_compute/core/utils/misc/ShapeCalculator.h b/arm_compute/core/utils/misc/ShapeCalculator.h
index 2a4aa4d7db..77ad33910b 100644
--- a/arm_compute/core/utils/misc/ShapeCalculator.h
+++ b/arm_compute/core/utils/misc/ShapeCalculator.h
@@ -24,11 +24,11 @@
#ifndef ACL_ARM_COMPUTE_CORE_UTILS_MISC_SHAPECALCULATOR
#define ACL_ARM_COMPUTE_CORE_UTILS_MISC_SHAPECALCULATOR
-#include "arm_compute/core/ConvolutionInfo.h"
#include "arm_compute/core/Helpers.h"
#include "arm_compute/core/ITensorInfo.h"
#include "arm_compute/core/KernelDescriptors.h"
#include "arm_compute/core/Utils.h"
+#include "arm_compute/function_info/ConvolutionInfo.h"
#include "arm_compute/runtime/FunctionDescriptors.h"
#include "arm_compute/core/utils/helpers/tensor_transform.h"
@@ -433,8 +433,8 @@ inline TensorShape compute_depthwise_convolution_shape(const ITensorInfo &input,
const int weights_width_idx = get_data_layout_dimension_index(weights_data_layout, DataLayoutDimension::WIDTH);
const int weights_height_idx = get_data_layout_dimension_index(weights_data_layout, DataLayoutDimension::HEIGHT);
- unsigned int output_width = 0;
- unsigned int output_height = 0;
+ unsigned int output_width = 0;
+ unsigned int output_height = 0;
std::tie(output_width, output_height) = scaled_dimensions(input_shape[width_idx], input_shape[height_idx],
weights_shape[weights_width_idx], weights_shape[weights_height_idx],
info.pad_stride_info, info.dilation);
@@ -684,8 +684,8 @@ inline TensorShape compute_winograd_output_transform_shape(const ITensorInfo &in
const DataLayout data_layout = winograd_info.output_data_layout;
// Compute output shape
- unsigned int output_width = 0;
- unsigned int output_height = 0;
+ unsigned int output_width = 0;
+ unsigned int output_height = 0;
std::tie(output_width, output_height) = scaled_dimensions(input_dimensions.width, input_dimensions.height,
kernel_size.width, kernel_size.height, conv_info);
@@ -725,7 +725,7 @@ inline TensorShape compute_deep_convolution_shape(const TensorShape &input_shape
const unsigned int weights_out_channel = weights_shape[3];
unsigned int output_width = 0;
unsigned int output_height = 0;
- std::tie(output_width, output_height) = scaled_dimensions(input_width, input_height, weights_width, weights_height, conv_info);
+ std::tie(output_width, output_height) = scaled_dimensions(input_width, input_height, weights_width, weights_height, conv_info);
TensorShape output_shape{ input_shape };
output_shape.set(idx_width, output_width);