Compute Library
 22.08
channel_shuffle.cl
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24 #include "helpers.h"
25 #include "tile_helpers.h"
26 
27 #if defined(DATA_TYPE) && defined(VEC_SIZE) && defined(NUM_GROUPS) && defined(K) && defined(SRC_DIM_Z)
28 
29 // Check valid VEC_SIZES
30 #if VEC_SIZE != 1 && VEC_SIZE != 2 && VEC_SIZE != 3 && VEC_SIZE != 4 && VEC_SIZE != 8 && VEC_SIZE != 16
31 #error "Only vector sizes 1, 2, 3, 4, 8 and 16 are supported"
32 #endif // VEC_SIZE != 1 && VEC_SIZE != 2 && VEC_SIZE != 3 && VEC_SIZE != 4 && VEC_SIZE != 8 && VEC_SIZE != 16
33 
34 #define DIV_MOD_UINT(x, y, div_res, mod_res) \
35  ({ \
36  div_res = (uint)((x)/(y)); \
37  uint r = div_res * (y); \
38  mod_res = (x)-r; \
39  })
40 
41 /** Performs channel shuffle when the data layout is NCHW. See https://arxiv.org/pdf/1707.01083.pdf for details.
42  *
43  * @note The vector size must be given as a preprocessor argument using -DVEC_SIZE=num. e.g. -DVEC_SIZE=4
44  * @note The depth of the tensor must be given as a preprocessor argument using -DSRC_DIM_Z=num. e.g. -DSRC_DIM_Z=64
45  * @note The number of groups must be given as a preprocessor argument using -DNUM_GROUPS=num_groups. e.g. -DNUM_GROUPS=2
46  * @note The number of channels in each group must be given as a preprocessor argument using -DK=num. e.g. -DK=1
47  * K is equal to num_channels / num_groups.
48  *
49  * @param[in] src_ptr Pointer to the source matrix. Supported data types: All
50  * @param[in] src_stride_x Stride of the first source tensor in X dimension (in bytes)
51  * @param[in] src_step_x src_stride_x * number of elements along X processed per workitem(in bytes)
52  * @param[in] src_stride_y Stride of the first source tensor in Y dimension (in bytes)
53  * @param[in] src_step_y src_stride_y * number of elements along Y processed per workitem(in bytes)
54  * @param[in] src_stride_z Stride of the first source tensor in Z dimension (in bytes)
55  * @param[in] src_step_z src_stride_z * number of elements along Z processed per workitem(in bytes)
56  * @param[in] src_stride_w Stride of the first source tensor in Z dimension (in bytes)
57  * @param[in] src_step_w src_stride_z * number of elements along Z processed per workitem(in bytes)
58  * @param[in] src_offset_first_element_in_bytes The offset of the first element in the first source tensor
59  * @param[out] dst_ptr Pointer to the destination tensor. Supported data types: same as @p src_ptr
60  * @param[in] dst_stride_x Stride of the destination tensor in X dimension (in bytes)
61  * @param[in] dst_step_x output_stride_x * number of elements along X processed per workitem(in bytes)
62  * @param[in] dst_stride_y Stride of the destination tensor in Y dimension (in bytes)
63  * @param[in] dst_step_y output_stride_y * number of elements along Y processed per workitem(in bytes)
64  * @param[in] dst_stride_z Stride of the destination tensor in Z dimension (in bytes)
65  * @param[in] dst_step_z output_stride_z * number of elements along Z processed per workitem(in bytes)
66  * @param[in] dst_stride_w Stride of the destination tensor in Z dimension (in bytes)
67  * @param[in] dst_step_w output_stride_z * number of elements along Z processed per workitem(in bytes)
68  * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination tensor
69  */
70 __kernel void channel_shuffle_nchw(TENSOR4D_DECLARATION(src),
72 {
73  uint curr_channel = 0; // channel id of input
74  uint batch_id = 0; // batch id
75  uint group_id = 0; // group id
76  uint channel_id = 0; // channel id within the group
77 
78  // Compute curr_channel and batch_id
79  DIV_MOD_UINT(get_global_id(2), SRC_DIM_Z, batch_id, curr_channel);
80 
81  // Compute group_id and channel_id
82  DIV_MOD_UINT(curr_channel, K, group_id, channel_id);
83 
84  const uint x = get_global_id(0) * VEC_SIZE;
85  const uint y = get_global_id(1) * 2;
86  const uint z = channel_id * NUM_GROUPS + group_id;
87 
88  // Load the Nx2 block
89  const __global uchar *input_ptr = src_ptr + src_offset_first_element_in_bytes + x * sizeof(DATA_TYPE) + y * src_stride_y + curr_channel * src_stride_z + batch_id * src_stride_w;
90  VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
91  u0 = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(input_ptr + 0 * src_stride_y));
92  VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
93  u1 = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(input_ptr + 1 * src_stride_y));
94 
95  // Store blocks
96  __global uchar *output_ptr = dst_ptr + dst_offset_first_element_in_bytes + x * sizeof(DATA_TYPE) + y * dst_stride_y + z * dst_stride_z + batch_id * dst_stride_w;
98  (u0, 0, (__global DATA_TYPE *)(output_ptr + 0 * dst_stride_y));
100  (u1, 0, (__global DATA_TYPE *)(output_ptr + 1 * dst_stride_y));
101 }
102 
103 #endif // defined(DATA_TYPE) && defined(VEC_SIZE) && defined(NUM_GROUPS) && defined(K) && defined(SRC_DIM_Z)
#define VEC_SIZE
SimpleTensor< float > src
Definition: DFT.cpp:155
#define VSTORE(size)
Definition: helpers.h:458
#define TENSOR4D_DECLARATION(name)
Definition: helpers.h:823
#define VLOAD(size)
Definition: helpers.h:204
#define VEC_DATA_TYPE(type, size)
Definition: helpers.h:728
unsigned int K