src/core/CL/cl_kernels/yolo_layer.cl

/*
 * 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)