Remove unused yolo_layer OpenCL kernel

Change-Id: Ibab2095a1a5b525c8513f924cd5bcecd5172ed48
Signed-off-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/5467
Reviewed-by: Giorgio Arena <giorgio.arena@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>

2 files changed, 0 insertions, 178 deletions

diff --git a/src/core/CL/CLKernelLibrary.cpp b/src/core/CL/CLKernelLibrary.cpp
index 33b5ad0c6e..bb059bbc26 100644
--- a/src/core/CL/CLKernelLibrary.cpp
+++ b/src/core/CL/CLKernelLibrary.cpp
@@ -491,8 +491,6 @@ const std::map<std::string, std::string> CLKernelLibrary::_kernel_program_map =
     { "winograd_output_transform_2x2_7x7_nhwc", "winograd_output_transform.cl" },
     { "winograd_output_transform_2x1_7x1_nhwc", "winograd_output_transform.cl" },
     { "winograd_output_transform_1x2_1x7_nhwc", "winograd_output_transform.cl" },
-    { "yolo_layer_nchw", "yolo_layer.cl" },
-    { "yolo_layer_nhwc", "yolo_layer.cl" },
 };
 
 const std::map<std::string, std::string> CLKernelLibrary::_program_source_map =
@@ -854,10 +852,6 @@ const std::map<std::string, std::string> CLKernelLibrary::_program_source_map =
         "winograd_output_transform.cl",
 #include "./cl_kernels/winograd_output_transform.clembed"
     },
-    {
-        "yolo_layer.cl",
-#include "./cl_kernels/yolo_layer.clembed"
-    },
 #endif /* EMBEDDED_KERNELS */
 };
 
diff --git a/src/core/CL/cl_kernels/yolo_layer.cl b/src/core/CL/cl_kernels/yolo_layer.cl
deleted file mode 100644
index 9601dddf67..0000000000
--- a/src/core/CL/cl_kernels/yolo_layer.cl
+++ /dev/null
@@ -1,172 +0,0 @@
-/*
- * Copyright (c) 2018-2020 Arm Limited.
- *
- * SPDX-License-Identifier: MIT
- *
- * Permission is hereby granted, free of charge, to any person obtaining a copy
- * of this software and associated documentation files (the "Software"), to
- * deal in the Software without restriction, including without limitation the
- * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
- * sell copies of the Software, and to permit persons to whom the Software is
- * furnished to do so, subject to the following conditions:
- *
- * The above copyright notice and this permission notice shall be included in all
- * copies or substantial portions of the Software.
- *
- * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
- * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
- * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
- * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
- * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
- * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
- * SOFTWARE.
- */
-#if defined(DATA_TYPE) && defined(ACTIVATION_TYPE) && defined(NUM_CLASSES) && defined(VEC_SIZE)
-
-#include "activation_float_helpers.h"
-
-#define SELECT_TYPE SELECT_VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
-
-#if VEC_SIZE != 1
-#define TYPE VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
-
-/** This performs a YOLO partial activation function for NCHW data layout
- *
- * @note In order to perform the activation function "in-place", the pre-processor -DIN_PLACE must be passed at compile time
- *
- * @note Datatype should be given as a preprocessor argument using -DDATA_TYPE=type. e.g. -DDATA_TYPE=short
- * @note Vector size should be given as a preprocessor argument using -DVEC_SIZE=size. e.g. -DVEC_SIZE=16
- * @note Activation function should be given as a preprocessor argument using -DACTIVATION_TYPE=name. e.g. -DACTIVATION_TYPE=TANH
- * @note The number of classes should be given as a preprocessor argument using -DNUM_CLASSES=num. e.g. -DNUM_CLASSES=80
- * @note A, B variables required by some activation functions are set using -DA_VAL= and -DB_VAL= respectively.
- *
- * @param[in]  input_ptr                            Pointer to the source tensor. Supported data types: F16/F32
- * @param[in]  input_stride_x                       Stride of the source tensor in X dimension (in bytes)
- * @param[in]  input_step_x                         input_stride_x * number of elements along X processed per workitem(in bytes)
- * @param[in]  input_stride_y                       Stride of the source tensor in Y dimension (in bytes)
- * @param[in]  input_step_y                         input_stride_y * number of elements along Y processed per workitem(in bytes)
- * @param[in]  input_stride_z                       Stride of the source tensor in Z dimension (in bytes)
- * @param[in]  input_step_z                         input_stride_z * number of elements along Z processed per workitem(in bytes)
- * @param[in]  input_offset_first_element_in_bytes  The offset of the first element in the source tensor
- * @param[out] output_ptr                           (Optional) Pointer to the destination tensor. Supported data types: same as @p input_ptr
- * @param[in]  output_stride_x                      (Optional) Stride of the destination tensor in X dimension (in bytes)
- * @param[in]  output_step_x                        (Optional) output_stride_x * number of elements along X processed per workitem(in bytes)
- * @param[in]  output_stride_y                      (Optional) Stride of the destination tensor in Y dimension (in bytes)
- * @param[in]  output_step_y                        (Optional) output_stride_y * number of elements along Y processed per workitem(in bytes)
- * @param[in]  output_stride_z                      (Optional) Stride of the source tensor in Z dimension (in bytes)
- * @param[in]  output_step_z                        (Optional) output_stride_z * number of elements along Z processed per workitem(in bytes)
- * @param[in]  output_offset_first_element_in_bytes (Optional) The offset of the first element in the destination tensor
- */
-__kernel void yolo_layer_nchw(
-    TENSOR3D_DECLARATION(input)
-#ifndef IN_PLACE
-    ,
-    TENSOR3D_DECLARATION(output)
-#endif /* not IN_PLACE */
-)
-{
-    // Get pixels pointer
-    Tensor3D input = CONVERT_TO_TENSOR3D_STRUCT(input);
-#ifdef IN_PLACE
-    Tensor3D output = input;
-#else  /* IN_PLACE */
-    Tensor3D output = CONVERT_TO_TENSOR3D_STRUCT(output);
-#endif /* IN_PLACE */
-
-    const int  box_ch_id = get_global_id(2) % (NUM_CLASSES + 5);
-    const bool activate  = box_ch_id != 2 && box_ch_id != 3;
-
-    if(activate)
-    {
-        // Load data
-        TYPE data = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)input.ptr);
-        data      = ACTIVATION(ACTIVATION_TYPE, DATA_TYPE, VEC_SIZE, data, A_VAL, B_VAL); // select(1.0f, ACTIVATION_OP(ACTIVATION_TYPE, data), (SELECT_TYPE)activate);
-
-        // Store result
-        VSTORE(VEC_SIZE)
-        (data, 0, (__global DATA_TYPE *)output.ptr);
-    }
-#ifndef IN_PLACE
-    else
-    {
-        // Load data
-        TYPE data = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)input.ptr);
-
-        // Store result
-        VSTORE(VEC_SIZE)
-        (data, 0, (__global DATA_TYPE *)output.ptr);
-    }
-#endif // IN_PLACE
-}
-
-#else // VEC_SIZE != 1
-
-/** This performs a YOLO partial activation function for NCHW data layout
- *
- * @note In order to perform the activation function "in-place", the pre-processor -DIN_PLACE must be passed at compile time
- *
- * @note Datatype should be given as a preprocessor argument using -DDATA_TYPE=type. e.g. -DDATA_TYPE=short
- * @note Vector size should be given as a preprocessor argument using -DVEC_SIZE=size. e.g. -DVEC_SIZE=1
- * @note Activation function should be given as a preprocessor argument using -DACTIVATION_TYPE=name. e.g. -DACTIVATION_TYPE=TANH
- * @note The number of classes should be given as a preprocessor argument using -DNUM_CLASSES=num. e.g. -DNUM_CLASSES=80
- * @note A, B variables required by some activation functions are set using -DA_VAL= and -DB_VAL= respectively.
- *
- * @param[in]  input_ptr                            Pointer to the source tensor. Supported data types: F16/F32
- * @param[in]  input_stride_x                       Stride of the source tensor in X dimension (in bytes)
- * @param[in]  input_step_x                         input_stride_x * number of elements along X processed per workitem(in bytes)
- * @param[in]  input_stride_y                       Stride of the source tensor in Y dimension (in bytes)
- * @param[in]  input_step_y                         input_stride_y * number of elements along Y processed per workitem(in bytes)
- * @param[in]  input_stride_z                       Stride of the source tensor in Z dimension (in bytes)
- * @param[in]  input_step_z                         input_stride_z * number of elements along Z processed per workitem(in bytes)
- * @param[in]  input_offset_first_element_in_bytes  The offset of the first element in the source tensor
- * @param[out] output_ptr                           (Optional) Pointer to the destination tensor. Supported data types: same as @p input_ptr
- * @param[in]  output_stride_x                      (Optional) Stride of the destination tensor in X dimension (in bytes)
- * @param[in]  output_step_x                        (Optional) output_stride_x * number of elements along X processed per workitem(in bytes)
- * @param[in]  output_stride_y                      (Optional) Stride of the destination tensor in Y dimension (in bytes)
- * @param[in]  output_step_y                        (Optional) output_stride_y * number of elements along Y processed per workitem(in bytes)
- * @param[in]  output_stride_z                      (Optional) Stride of the source tensor in Z dimension (in bytes)
- * @param[in]  output_step_z                        (Optional) output_stride_z * number of elements along Z processed per workitem(in bytes)
- * @param[in]  output_offset_first_element_in_bytes (Optional) The offset of the first element in the destination tensor
- */
-__kernel void yolo_layer_nhwc(
-    TENSOR3D_DECLARATION(input)
-#ifndef IN_PLACE
-    ,
-    TENSOR3D_DECLARATION(output)
-#endif /* not IN_PLACE */
-)
-{
-    // Get pixels pointer
-    Tensor3D input  = CONVERT_TO_TENSOR3D_STRUCT(input);
-#ifdef IN_PLACE
-    Tensor3D output = input;
-#else  /* IN_PLACE */
-    Tensor3D output = CONVERT_TO_TENSOR3D_STRUCT(output);
-#endif /* IN_PLACE */
-
-    const int  box_ch_id = get_global_id(0) % (NUM_CLASSES + 5);
-    const bool activate  = box_ch_id != 2 && box_ch_id != 3;
-
-    if(activate)
-    {
-        // Load data
-        DATA_TYPE data = *((__global DATA_TYPE *)input.ptr);
-        data           = select(data, ACTIVATION(ACTIVATION_TYPE, DATA_TYPE, VEC_SIZE, data, A_VAL, B_VAL), (SELECT_TYPE)activate);
-
-        // Store result
-        *((__global DATA_TYPE *)output.ptr) = data;
-    }
-#ifndef IN_PLACE
-    else
-    {
-        // Load data
-        DATA_TYPE data = *((__global DATA_TYPE *)input.ptr);
-
-        // Store result
-        *((__global DATA_TYPE *)output.ptr) = data;
-    }
-#endif // IN_PLACE
-}
-
-#endif // VEC_SIZE != 1
-#endif // defined(DATA_TYPE) && defined(ACTIVATION_TYPE) && defined(NUM_CLASSES) && defined(VEC_SIZE)