Compute Library
 22.08
normalize_planar_yuv_layer_quantized.cl
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1 /*
2  * Copyright (c) 2018-2021 Arm Limited.
3  *
4  * SPDX-License-Identifier: MIT
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24 #include "helpers.h"
25 
26 #if defined(DATA_TYPE) && defined(VEC_SIZE) && defined(OFFSET) && defined(SCALE)
27 
28 #define TYPE VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
29 #define OFFSET_FLT ((float)OFFSET)
30 #define SCALE_FLT ((float)SCALE)
31 
32 #if defined(NUM_CHANNELS)
33 
34 /** Apply normalize_planar_yuv layer on tensors with NCHW data layout.
35  *
36  * @note Data type should be given as a preprocessor argument using -DDATA_TYPE=type. e.g. -DDATA_TYPE=float
37  * @note Vector size should be given as a preprocessor argument using -DVEC_SIZE e.g. -DVEC_SIZE=8
38  * @note The depth of the input tensor should be given as a preprocessor argument using -DNUM_CHANNELS e.g. -DNUM_CHANNELS=8
39  * @note The quantization offset should be given as a preprocessor argument using -DOFFSET e.g. -DOFFSET=8
40  * @note The quantization scale should be given as a preprocessor argument using -DSCALE e.g. -DSCALE=8
41  *
42  * @param[in] src_ptr Pointer to the first source tensor. Supported data types: QASYMM8/QASYMM8_SIGNED
43  * @param[in] src_stride_x Stride of the first source tensor in X dimension (in bytes)
44  * @param[in] src_step_x input_stride_x * number of elements along X processed per workitem(in bytes)
45  * @param[in] src_stride_y Stride of the first source tensor in Y dimension (in bytes)
46  * @param[in] src_step_y input_stride_y * number of elements along Y processed per workitem(in bytes)
47  * @param[in] src_stride_z Stride of the first source tensor in Z dimension (in bytes)
48  * @param[in] src_step_z input_stride_z * number of elements along Z processed per workitem(in bytes)
49  * @param[in] src_offset_first_element_in_bytes The offset of the first element in the first source tensor
50  * @param[out] dst_ptr Pointer to the destination tensor. Supported data types: same as @p src_ptr
51  * @param[in] dst_stride_x Stride of the destination tensor in X dimension (in bytes)
52  * @param[in] dst_step_x output_stride_x * number of elements along X processed per workitem(in bytes)
53  * @param[in] dst_stride_y Stride of the destination tensor in Y dimension (in bytes)
54  * @param[in] dst_step_y output_stride_y * number of elements along Y processed per workitem(in bytes)
55  * @param[in] dst_stride_z Stride of the destination tensor in Z dimension (in bytes)
56  * @param[in] dst_step_z output_stride_z * number of elements along Z processed per workitem(in bytes)
57  * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination tensor
58  * @param[in] mean_ptr Pointer to the mean source tensor. Supported data types: same as @p src_ptr
59  * @param[in] mean_stride_x Stride of the mean source tensor in X dimension (in bytes)
60  * @param[in] mean_step_x mean_stride_x * number of elements along X processed per workitem(in bytes)
61  * @param[in] mean_offset_first_element_in_bytes The offset of the first element in the mean source tensor
62  * @param[in] std_ptr Pointer to the std tensor. Supported data types: same as @p src_ptr
63  * @param[in] std_stride_x Stride of the std tensor in X dimension (in bytes)
64  * @param[in] std_step_x std_stride_x * number of elements along X processed per workitem(in bytes)
65  * @param[in] std_offset_first_element_in_bytes The offset of the first element in the var source tensor
66  */
67 __kernel void normalize_planar_yuv_layer_q8_nchw(TENSOR3D_DECLARATION(src),
69  VECTOR_DECLARATION(mean),
71 {
74  Vector mean = CONVERT_TO_VECTOR_STRUCT(mean);
76 
77  const uint current_slice = get_global_id(2) % NUM_CHANNELS;
78 
79  VEC_DATA_TYPE(float, VEC_SIZE)
80  curr_mean_flt = (VEC_DATA_TYPE(float, VEC_SIZE))(*((__global DATA_TYPE *)(mean.ptr + current_slice * sizeof(DATA_TYPE))));
81  curr_mean_flt = round(curr_mean_flt - OFFSET_FLT) * SCALE_FLT;
82 
83  VEC_DATA_TYPE(float, VEC_SIZE)
84  curr_std_flt = (VEC_DATA_TYPE(float, VEC_SIZE))(*((__global DATA_TYPE *)(std.ptr + current_slice * sizeof(DATA_TYPE))));
85  curr_std_flt = round(curr_std_flt - OFFSET_FLT) * SCALE_FLT;
86 
87  VEC_DATA_TYPE(float, VEC_SIZE)
88  data_flt = CONVERT(VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)src.ptr), VEC_DATA_TYPE(float, VEC_SIZE));
89  data_flt = round(data_flt - OFFSET_FLT) * SCALE_FLT;
90 
91  // Perform normalization
92  VEC_DATA_TYPE(float, VEC_SIZE)
93  res_flt = (data_flt - curr_mean_flt) / curr_std_flt;
94 
95  const TYPE res_u8 = CONVERT_SAT(round(res_flt / SCALE_FLT) + OFFSET_FLT, TYPE);
97  (res_u8, 0, (__global DATA_TYPE *)dst.ptr);
98 }
99 
100 #endif // defined(NUM_CHANNELS)
101 #endif // defined(DATA_TYPE) && defined(VEC_SIZE) && defined(OFFSET) && defined(SCALE)
Structure to hold Vector information.
Definition: helpers.h:889
#define VEC_SIZE
#define CONVERT(x, type)
Definition: helpers.h:731
#define TYPE
Structure to hold 3D tensor information.
Definition: helpers.h:906
SimpleTensor< float > src
Definition: DFT.cpp:155
#define CONVERT_TO_VECTOR_STRUCT(name)
Definition: helpers.h:849
#define VECTOR_DECLARATION(name)
Definition: helpers.h:799
#define CONVERT_SAT(x, type)
Definition: helpers.h:734
__global uchar * ptr
Pointer to the starting postion of the buffer.
Definition: helpers.h:891
int round(float x, RoundingPolicy rounding_policy)
Return a rounded value of x.
Definition: Rounding.cpp:35
#define CONVERT_TO_TENSOR3D_STRUCT(name)
Definition: helpers.h:870
#define VSTORE(size)
Definition: helpers.h:458
__global uchar * ptr
Pointer to the starting postion of the buffer.
Definition: helpers.h:908
#define VLOAD(size)
Definition: helpers.h:204
#define TENSOR3D_DECLARATION(name)
Definition: helpers.h:813
#define VEC_DATA_TYPE(type, size)
Definition: helpers.h:728