From 94450f1fc91a89778354c2e1c07a328ba86d9cfc Mon Sep 17 00:00:00 2001 From: Moritz Pflanzer Date: Fri, 30 Jun 2017 12:48:43 +0100 Subject: COMPMID-417: Use a common create_tensor function Change-Id: I6b0511484a5b433ebec3fd62d778e64dcb4f89b5 Reviewed-on: http://mpd-gerrit.cambridge.arm.com/79362 Reviewed-by: Georgios Pinitas Tested-by: Kaizen --- tests/NEON/Helper.h | 43 ++----------------------------------------- 1 file changed, 2 insertions(+), 41 deletions(-) (limited to 'tests/NEON') diff --git a/tests/NEON/Helper.h b/tests/NEON/Helper.h index e64ac27ef3..e77615406e 100644 --- a/tests/NEON/Helper.h +++ b/tests/NEON/Helper.h @@ -24,11 +24,9 @@ #ifndef __ARM_COMPUTE_TEST_NEON_HELPER_H__ #define __ARM_COMPUTE_TEST_NEON_HELPER_H__ -#include "Globals.h" -#include "TensorLibrary.h" - #include "arm_compute/runtime/Array.h" -#include "arm_compute/runtime/Tensor.h" + +#include namespace arm_compute { @@ -36,43 +34,6 @@ namespace test { namespace neon { -/** Helper to create an empty tensor. - * - * @param[in] shape Desired shape. - * @param[in] data_type Desired data type. - * @param[in] num_channels (Optional) It indicates the number of channels for each tensor element - * @param[in] fixed_point_position (Optional) Fixed point position that expresses the number of bits for the fractional part of the number when the tensor's data type is QS8 or QS16. - * - * @return Empty @ref Tensor with the specified shape and data type. - */ -inline Tensor create_tensor(const TensorShape &shape, DataType data_type, int num_channels = 1, int fixed_point_position = 0) -{ - Tensor tensor; - tensor.allocator()->init(TensorInfo(shape, num_channels, data_type, fixed_point_position)); - - return tensor; -} - -/** Helper to create an empty tensor. - * - * @param[in] name File name from which to get the dimensions. - * @param[in] data_type Desired data type. - * @param[in] fixed_point_position (Optional) Number of bits for the fractional part of the fixed point numbers - * - * @return Empty @ref Tensor with the specified shape and data type. - */ -inline Tensor create_tensor(const std::string &name, DataType data_type, int fixed_point_position = 0) -{ - constexpr unsigned int num_channels = 1; - - const RawTensor &raw = library->get(name); - - Tensor tensor; - tensor.allocator()->init(TensorInfo(raw.shape(), num_channels, data_type, fixed_point_position)); - - return tensor; -} - template Array create_array(const std::vector &v) { -- cgit v1.2.1