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-rw-r--r--src/core/TensorInfo.cpp35
1 files changed, 0 insertions, 35 deletions
diff --git a/src/core/TensorInfo.cpp b/src/core/TensorInfo.cpp
index bedfe147b0..c471615ee8 100644
--- a/src/core/TensorInfo.cpp
+++ b/src/core/TensorInfo.cpp
@@ -24,7 +24,6 @@
#include "arm_compute/core/TensorInfo.h"
#include "arm_compute/core/Error.h"
-#include "arm_compute/core/HOGInfo.h"
#include "arm_compute/core/Helpers.h"
#include "arm_compute/core/TensorInfo.h"
#include "arm_compute/core/Validate.h"
@@ -100,12 +99,6 @@ TensorInfo::TensorInfo(const TensorShape &tensor_shape, size_t num_channels, Dat
_data_layout = data_layout;
}
-TensorInfo::TensorInfo(const HOGInfo &hog_info, unsigned int width, unsigned int height)
- : TensorInfo()
-{
- init(hog_info, width, height);
-}
-
void TensorInfo::init(Format format)
{
init(TensorShape(), format);
@@ -166,20 +159,6 @@ void TensorInfo::init(const TensorShape &tensor_shape, size_t num_channels, Data
_valid_region = ValidRegion{ Coordinates(), _tensor_shape };
}
-void TensorInfo::init(const HOGInfo &hog_info, unsigned int width, unsigned int height)
-{
- // Number of cells for each block
- const Size2D num_cells_per_block = hog_info.num_cells_per_block();
-
- // Tensor Size = (Number of horizontal block positions) * (Number of vertical block positions)
- const Size2D num_block_positions_per_img = hog_info.num_block_positions_per_image(Size2D(width, height));
-
- // Number of tensor channels = (Number of cells per block) * (Number of bins per cell)
- const size_t num_channels = num_cells_per_block.area() * hog_info.num_bins();
-
- init(TensorShape(num_block_positions_per_img.width, num_block_positions_per_img.height), num_channels, DataType::F32);
-}
-
size_t TensorInfo::init_auto_padding(const TensorShape &tensor_shape, Format format)
{
const size_t num_channels = num_channels_from_format(format);
@@ -207,20 +186,6 @@ size_t TensorInfo::init_auto_padding(const TensorShape &tensor_shape, size_t num
return _total_size;
}
-size_t TensorInfo::init_auto_padding(const HOGInfo &hog_info, unsigned int width, unsigned int height)
-{
- // Number of cells for each block
- const Size2D num_cells_per_block = hog_info.num_cells_per_block();
-
- // Tensor Size = (Number of horizontal block positions) * (Number of vertical block positions)
- const Size2D num_block_positions_per_img = hog_info.num_block_positions_per_image(Size2D(width, height));
-
- // Number of tensor channels = (Number of cells per block) * (Number of bins per cell)
- const size_t num_channels = num_cells_per_block.area() * hog_info.num_bins();
-
- return init_auto_padding(TensorShape(num_block_positions_per_img.width, num_block_positions_per_img.height), num_channels, DataType::F32);
-}
-
bool TensorInfo::auto_padding()
{
ARM_COMPUTE_ERROR_ON(!_is_resizable);