vec_trans_scatter
Description
Converts NCHW into NC1HWC0. If the data type is float32, int32, uint32, int16, unint16, or float16, then C0 is 16. If the data type is uint8 or int8, then C0 is 32.
Prototype
vec_trans_scatter (dst_high_half, src_high_half, dst_list, src_list, repeat_times, dst_rep_stride, src_rep_stride)
Parameters
|
Parameter |
Input/Output |
Description |
|---|---|---|
|
dst_high_half |
Input |
A bool specifying whether dst_list[*] stores data to the upper or lower half of the block. dst_list[*] stores data of type int8 or uint8 only. Selected from:
|
|
src_high_half |
Input |
A bool specifying whether to read the data of src_list[*] from the upper or lower half of the block. Only the int8 or uint8 data type is supported. Selected from:
|
|
dst_list |
Output |
A list for the destination Vector operand sequence. Each element marks the start of a destination operand. The supported data types are as follows: The scope of the tensor is the Unified Buffer. |
|
src_list |
Input |
A list for the source Vector operand sequence. Each element marks the start of a destination operand. Has the same data type as dst_list. The scope of the tensor is the Unified Buffer. |
|
repeat_times |
Input |
Repeat times (or iterations), in blocks. Must be in the range of [0, 255]. Must be a Scalar of type int16/int32/int64/uint16/uint32/uint64, an immediate of type int, or an Expr of type int16/int32/int64/uint16/uint32/uint64. Notes: 1. When repeat_times =1, the valid start of a destination or source operand is the start of dst_list or src_list plus dst_rep_stride or src_rep_stride. 2. When repeat_times > 1, the valid start of a destination or source operand in the first repeat is the start of dst_list or src_list. In the second repeat, dst_rep_stride or src_rep_stride needs to be added. This rule applies. |
|
dst_rep_stride |
Input |
Start address stride (in blocks) between iterations of the destination operand. Must be in the range of [0, 65535]. Must be a Scalar of type int16/int32/int64/uint16/uint32/uint64, an immediate of type int, or an Expr of type int16/int32/int64/uint16/uint32/uint64. |
|
src_rep_stride |
Input |
Start address stride (in blocks) between iterations of the source operand. Must be in the range of [0, 65535]. Must be a Scalar of type int16/int32/int64/uint16/uint32/uint64, an immediate of type int, or an Expr of type int16/int32/int64/uint16/uint32/uint64. |
Applicability
Restrictions
- Generally, each element in src_list or dst_list is configured as the start of each HW plane.
- For better performance, it is recommended that dstHighHalf and srcHighHalf be fixed when the data type is int8 or uint8, and be changed after the repeat in the H and W directions.
- The mask value does not affect the execution of the API.
- To save memory space, you can define a tensor reused by the source and destination operands (which means they have overlapped addresses). The general instruction restrictions are as follows.
- For a single repeat (repeat_times = 1), the source operand sequence and the target operand sequence must be completely the same. Partial overlapping is not supported. Instead, each block must be the same.
- In the event of multiple iteration repeats (repeat_times > 1), if there is a dependency between the source operand sequence and the destination operand sequence, that is, the destination operand of the Nth iteration is the source operand of the (N+1)th iteration, address overlapping is not allowed.
- For details about the alignment requirements of the operand address offset, see General Restrictions.
Returns
None
Example
Example 1
tik_instance = tik.Tik() shape = (3, 32, 16) dtype = "int8" # Number of iterations repeat_time = 3 # Address stride between two adjacent iterations, in 32 bytes. dst_rep_stride = 16 src_rep_stride = 16 src_gm = tik_instance.Tensor(dtype, shape, name="src_gm", scope=tik.scope_gm) src_ub = tik_instance.Tensor(dtype, shape, name="src_ub", scope=tik.scope_ubuf) dst0_gm = tik_instance.Tensor(dtype, shape, name="dst0_gm", scope=tik.scope_gm) dst_gm = tik_instance.Tensor(dtype, shape, name="dst_gm", scope=tik.scope_gm) dst_ub = tik_instance.Tensor(dtype, shape, name="dst_ub", scope=tik.scope_ubuf) # Specifies whether dst/src_list[*] stores data to the upper or lower half of the block. Only int8 and uint8 are supported. dstHighHalf = False srcHighHalf = True # Copy the user input to the source Unified Buffer. For details about data_move, see the corresponding section. tik_instance.data_move(src_ub, src_gm, 0, 1, 48, 0, 0) # vec_dup does not support int8. To facilitate observation, set the value to 0. tik_instance.data_move(dst_ub, dst0_gm, 0, 1, 48, 0, 0) dst_list = [dst_ub[32 * i] for i in range(16)] src_list = [src_ub[32 * i] for i in range(16)] tik_instance.vec_trans_scatter(dstHighHalf, srcHighHalf, dst_list, src_list, repeat_time, dst_rep_stride, src_rep_stride) # Copy the compute result to the destination Global Memory. For details about data_move, see the corresponding section. tik_instance.data_move(dst_gm, dst_ub, 0, 1, 48, 0, 0) tik_instance.BuildCCE(kernel_name="vec_trans_scatter", inputs=[src_gm, dst0_gm], outputs=[dst_gm])
Result example:
Input (src_gm): [[[ 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15] [ 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31] [ 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47] [ 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63] [ 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79] [ 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95] [ 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111] [112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127] [ 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15] [ 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31] [ 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47] [ 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63] [ 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79] [ 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95] [ 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111] [112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127] [ 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15] [ 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31] [ 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47] [ 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63] [ 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79] [ 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95] [ 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111] [112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127] [ 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15] [ 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31] [ 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47] [ 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63] [ 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79] [ 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95] [ 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111] [112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127]] [[ 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15] [ 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31] [ 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47] [ 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63] [ 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79] [ 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95] [ 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111] [112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127] [ 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15] [ 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31] [ 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47] [ 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63] [ 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79] [ 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95] [ 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111] [112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127] [ 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15] [ 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31] [ 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47] [ 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63] [ 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79] [ 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95] [ 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111] [112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127] [ 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15] [ 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31] [ 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47] [ 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63] [ 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79] [ 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95] [ 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111] [112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127]] [[ 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15] [ 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31] [ 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47] [ 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63] [ 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79] [ 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95] [ 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111] [112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127] [ 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15] [ 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31] [ 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47] [ 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63] [ 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79] [ 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95] [ 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111] [112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127] [ 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15] [ 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31] [ 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47] [ 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63] [ 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79] [ 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95] [ 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111] [112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127] [ 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15] [ 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31] [ 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47] [ 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63] [ 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79] [ 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95] [ 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111] [112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127]]] Output (dst_gm): [[[ 16 48 80 112 16 48 80 112 16 48 80 112 16 48 80 112] [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0] [ 17 49 81 113 17 49 81 113 17 49 81 113 17 49 81 113] [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0] [ 18 50 82 114 18 50 82 114 18 50 82 114 18 50 82 114] [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0] [ 19 51 83 115 19 51 83 115 19 51 83 115 19 51 83 115] [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0] [ 20 52 84 116 20 52 84 116 20 52 84 116 20 52 84 116] [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0] [ 21 53 85 117 21 53 85 117 21 53 85 117 21 53 85 117] [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0] [ 22 54 86 118 22 54 86 118 22 54 86 118 22 54 86 118] [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0] [ 23 55 87 119 23 55 87 119 23 55 87 119 23 55 87 119] [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0] [ 24 56 88 120 24 56 88 120 24 56 88 120 24 56 88 120] [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0] [ 25 57 89 121 25 57 89 121 25 57 89 121 25 57 89 121] [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0] [ 26 58 90 122 26 58 90 122 26 58 90 122 26 58 90 122] [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0] [ 27 59 91 123 27 59 91 123 27 59 91 123 27 59 91 123] [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0] [ 28 60 92 124 28 60 92 124 28 60 92 124 28 60 92 124] [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0] [ 29 61 93 125 29 61 93 125 29 61 93 125 29 61 93 125] [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0] [ 30 62 94 126 30 62 94 126 30 62 94 126 30 62 94 126] [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0] [ 31 63 95 127 31 63 95 127 31 63 95 127 31 63 95 127] [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]] [[ 16 48 80 112 16 48 80 112 16 48 80 112 16 48 80 112] [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0] [ 17 49 81 113 17 49 81 113 17 49 81 113 17 49 81 113] [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0] [ 18 50 82 114 18 50 82 114 18 50 82 114 18 50 82 114] [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0] [ 19 51 83 115 19 51 83 115 19 51 83 115 19 51 83 115] [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0] [ 20 52 84 116 20 52 84 116 20 52 84 116 20 52 84 116] [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0] [ 21 53 85 117 21 53 85 117 21 53 85 117 21 53 85 117] [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0] [ 22 54 86 118 22 54 86 118 22 54 86 118 22 54 86 118] [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0] [ 23 55 87 119 23 55 87 119 23 55 87 119 23 55 87 119] [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0] [ 24 56 88 120 24 56 88 120 24 56 88 120 24 56 88 120] [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0] [ 25 57 89 121 25 57 89 121 25 57 89 121 25 57 89 121] [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0] [ 26 58 90 122 26 58 90 122 26 58 90 122 26 58 90 122] [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0] [ 27 59 91 123 27 59 91 123 27 59 91 123 27 59 91 123] [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0] [ 28 60 92 124 28 60 92 124 28 60 92 124 28 60 92 124] [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0] [ 29 61 93 125 29 61 93 125 29 61 93 125 29 61 93 125] [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0] [ 30 62 94 126 30 62 94 126 30 62 94 126 30 62 94 126] [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0] [ 31 63 95 127 31 63 95 127 31 63 95 127 31 63 95 127] [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]] [[ 16 48 80 112 16 48 80 112 16 48 80 112 16 48 80 112] [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0] [ 17 49 81 113 17 49 81 113 17 49 81 113 17 49 81 113] [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0] [ 18 50 82 114 18 50 82 114 18 50 82 114 18 50 82 114] [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0] [ 19 51 83 115 19 51 83 115 19 51 83 115 19 51 83 115] [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0] [ 20 52 84 116 20 52 84 116 20 52 84 116 20 52 84 116] [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0] [ 21 53 85 117 21 53 85 117 21 53 85 117 21 53 85 117] [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0] [ 22 54 86 118 22 54 86 118 22 54 86 118 22 54 86 118] [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0] [ 23 55 87 119 23 55 87 119 23 55 87 119 23 55 87 119] [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0] [ 24 56 88 120 24 56 88 120 24 56 88 120 24 56 88 120] [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0] [ 25 57 89 121 25 57 89 121 25 57 89 121 25 57 89 121] [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0] [ 26 58 90 122 26 58 90 122 26 58 90 122 26 58 90 122] [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0] [ 27 59 91 123 27 59 91 123 27 59 91 123 27 59 91 123] [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0] [ 28 60 92 124 28 60 92 124 28 60 92 124 28 60 92 124] [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0] [ 29 61 93 125 29 61 93 125 29 61 93 125 29 61 93 125] [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0] [ 30 62 94 126 30 62 94 126 30 62 94 126 30 62 94 126] [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0] [ 31 63 95 127 31 63 95 127 31 63 95 127 31 63 95 127] [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]]]
Example 2
tik_instance = tik.Tik(disable_debug=False) shape = (3, 16, 16) dtype = "float16" # Number of iterations. repeat_time = 3 # Address stride between two adjacent iterations, in 32 bytes. dst_rep_stride = 16 src_rep_stride = 16 src_gm = tik_instance.Tensor(dtype, shape, name="src_gm", scope=tik.scope_gm) src_ub = tik_instance.Tensor(dtype, shape, name="src_ub", scope=tik.scope_ubuf) dst0_gm = tik_instance.Tensor(dtype, shape, name="dst0_gm", scope=tik.scope_gm) dst_gm = tik_instance.Tensor(dtype, shape, name="dst_gm", scope=tik.scope_gm) dst_ub = tik_instance.Tensor(dtype, shape, name="dst_ub", scope=tik.scope_ubuf) # Specifies whether dst/src_list[*] stores data to the upper or lower half of the block. Only int8 and uint8 are supported. dstHighHalf = False srcHighHalf = False # Copy the user input to the source Unified Buffer. For details about data_move, see the corresponding section. tik_instance.data_move(src_ub, src_gm, 0, 1, 48, 0, 0) dst_list = [dst_ub[16 * i] for i in range(16)] src_list = [src_ub[16 * i] for i in range(16)] tik_instance.vnchwconv(dstHighHalf, srcHighHalf, dst_list, src_list, repeat_time, dst_rep_stride, src_rep_stride) # Copy the compute result to the destination Global Memory. For details about data_move, see the corresponding section. tik_instance.data_move(dst_gm, dst_ub, 0, 1, 48, 0, 0) tik_instance.BuildCCE(kernel_name="vec_trans_scatter", inputs=[src_gm], outputs=[dst_gm])
Result example:
Input (src_gm):
[[[ 0. 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13.
14. 15.]
[ 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29.
30. 31.]
[ 32. 33. 34. 35. 36. 37. 38. 39. 40. 41. 42. 43. 44. 45.
46. 47.]
[ 48. 49. 50. 51. 52. 53. 54. 55. 56. 57. 58. 59. 60. 61.
62. 63.]
[ 64. 65. 66. 67. 68. 69. 70. 71. 72. 73. 74. 75. 76. 77.
78. 79.]
[ 80. 81. 82. 83. 84. 85. 86. 87. 88. 89. 90. 91. 92. 93.
94. 95.]
[ 96. 97. 98. 99. 100. 101. 102. 103. 104. 105. 106. 107. 108. 109.
110. 111.]
[112. 113. 114. 115. 116. 117. 118. 119. 120. 121. 122. 123. 124. 125.
126. 127.]
[128. 129. 130. 131. 132. 133. 134. 135. 136. 137. 138. 139. 140. 141.
142. 143.]
[144. 145. 146. 147. 148. 149. 150. 151. 152. 153. 154. 155. 156. 157.
158. 159.]
[160. 161. 162. 163. 164. 165. 166. 167. 168. 169. 170. 171. 172. 173.
174. 175.]
[176. 177. 178. 179. 180. 181. 182. 183. 184. 185. 186. 187. 188. 189.
190. 191.]
[192. 193. 194. 195. 196. 197. 198. 199. 200. 201. 202. 203. 204. 205.
206. 207.]
[208. 209. 210. 211. 212. 213. 214. 215. 216. 217. 218. 219. 220. 221.
222. 223.]
[224. 225. 226. 227. 228. 229. 230. 231. 232. 233. 234. 235. 236. 237.
238. 239.]
[240. 241. 242. 243. 244. 245. 246. 247. 248. 249. 250. 251. 252. 253.
254. 255.]]
[[256. 257. 258. 259. 260. 261. 262. 263. 264. 265. 266. 267. 268. 269.
270. 271.]
[272. 273. 274. 275. 276. 277. 278. 279. 280. 281. 282. 283. 284. 285.
286. 287.]
[288. 289. 290. 291. 292. 293. 294. 295. 296. 297. 298. 299. 300. 301.
302. 303.]
[304. 305. 306. 307. 308. 309. 310. 311. 312. 313. 314. 315. 316. 317.
318. 319.]
[320. 321. 322. 323. 324. 325. 326. 327. 328. 329. 330. 331. 332. 333.
334. 335.]
[336. 337. 338. 339. 340. 341. 342. 343. 344. 345. 346. 347. 348. 349.
350. 351.]
[352. 353. 354. 355. 356. 357. 358. 359. 360. 361. 362. 363. 364. 365.
366. 367.]
[368. 369. 370. 371. 372. 373. 374. 375. 376. 377. 378. 379. 380. 381.
382. 383.]
[384. 385. 386. 387. 388. 389. 390. 391. 392. 393. 394. 395. 396. 397.
398. 399.]
[400. 401. 402. 403. 404. 405. 406. 407. 408. 409. 410. 411. 412. 413.
414. 415.]
[416. 417. 418. 419. 420. 421. 422. 423. 424. 425. 426. 427. 428. 429.
430. 431.]
[432. 433. 434. 435. 436. 437. 438. 439. 440. 441. 442. 443. 444. 445.
446. 447.]
[448. 449. 450. 451. 452. 453. 454. 455. 456. 457. 458. 459. 460. 461.
462. 463.]
[464. 465. 466. 467. 468. 469. 470. 471. 472. 473. 474. 475. 476. 477.
478. 479.]
[480. 481. 482. 483. 484. 485. 486. 487. 488. 489. 490. 491. 492. 493.
494. 495.]
[496. 497. 498. 499. 500. 501. 502. 503. 504. 505. 506. 507. 508. 509.
510. 511.]]
[[512. 513. 514. 515. 516. 517. 518. 519. 520. 521. 522. 523. 524. 525.
526. 527.]
[528. 529. 530. 531. 532. 533. 534. 535. 536. 537. 538. 539. 540. 541.
542. 543.]
[544. 545. 546. 547. 548. 549. 550. 551. 552. 553. 554. 555. 556. 557.
558. 559.]
[560. 561. 562. 563. 564. 565. 566. 567. 568. 569. 570. 571. 572. 573.
574. 575.]
[576. 577. 578. 579. 580. 581. 582. 583. 584. 585. 586. 587. 588. 589.
590. 591.]
[592. 593. 594. 595. 596. 597. 598. 599. 600. 601. 602. 603. 604. 605.
606. 607.]
[608. 609. 610. 611. 612. 613. 614. 615. 616. 617. 618. 619. 620. 621.
622. 623.]
[624. 625. 626. 627. 628. 629. 630. 631. 632. 633. 634. 635. 636. 637.
638. 639.]
[640. 641. 642. 643. 644. 645. 646. 647. 648. 649. 650. 651. 652. 653.
654. 655.]
[656. 657. 658. 659. 660. 661. 662. 663. 664. 665. 666. 667. 668. 669.
670. 671.]
[672. 673. 674. 675. 676. 677. 678. 679. 680. 681. 682. 683. 684. 685.
686. 687.]
[688. 689. 690. 691. 692. 693. 694. 695. 696. 697. 698. 699. 700. 701.
702. 703.]
[704. 705. 706. 707. 708. 709. 710. 711. 712. 713. 714. 715. 716. 717.
718. 719.]
[720. 721. 722. 723. 724. 725. 726. 727. 728. 729. 730. 731. 732. 733.
734. 735.]
[736. 737. 738. 739. 740. 741. 742. 743. 744. 745. 746. 747. 748. 749.
750. 751.]
[752. 753. 754. 755. 756. 757. 758. 759. 760. 761. 762. 763. 764. 765.
766. 767.]]]
Output (dst_gm):
[[[ 0. 16. 32. 48. 64. 80. 96. 112. 128. 144. 160. 176. 192. 208.
224. 240.]
[ 1. 17. 33. 49. 65. 81. 97. 113. 129. 145. 161. 177. 193. 209.
225. 241.]
[ 2. 18. 34. 50. 66. 82. 98. 114. 130. 146. 162. 178. 194. 210.
226. 242.]
[ 3. 19. 35. 51. 67. 83. 99. 115. 131. 147. 163. 179. 195. 211.
227. 243.]
[ 4. 20. 36. 52. 68. 84. 100. 116. 132. 148. 164. 180. 196. 212.
228. 244.]
[ 5. 21. 37. 53. 69. 85. 101. 117. 133. 149. 165. 181. 197. 213.
229. 245.]
[ 6. 22. 38. 54. 70. 86. 102. 118. 134. 150. 166. 182. 198. 214.
230. 246.]
[ 7. 23. 39. 55. 71. 87. 103. 119. 135. 151. 167. 183. 199. 215.
231. 247.]
[ 8. 24. 40. 56. 72. 88. 104. 120. 136. 152. 168. 184. 200. 216.
232. 248.]
[ 9. 25. 41. 57. 73. 89. 105. 121. 137. 153. 169. 185. 201. 217.
233. 249.]
[ 10. 26. 42. 58. 74. 90. 106. 122. 138. 154. 170. 186. 202. 218.
234. 250.]
[ 11. 27. 43. 59. 75. 91. 107. 123. 139. 155. 171. 187. 203. 219.
235. 251.]
[ 12. 28. 44. 60. 76. 92. 108. 124. 140. 156. 172. 188. 204. 220.
236. 252.]
[ 13. 29. 45. 61. 77. 93. 109. 125. 141. 157. 173. 189. 205. 221.
237. 253.]
[ 14. 30. 46. 62. 78. 94. 110. 126. 142. 158. 174. 190. 206. 222.
238. 254.]
[ 15. 31. 47. 63. 79. 95. 111. 127. 143. 159. 175. 191. 207. 223.
239. 255.]]
[[256. 272. 288. 304. 320. 336. 352. 368. 384. 400. 416. 432. 448. 464.
480. 496.]
[257. 273. 289. 305. 321. 337. 353. 369. 385. 401. 417. 433. 449. 465.
481. 497.]
[258. 274. 290. 306. 322. 338. 354. 370. 386. 402. 418. 434. 450. 466.
482. 498.]
[259. 275. 291. 307. 323. 339. 355. 371. 387. 403. 419. 435. 451. 467.
483. 499.]
[260. 276. 292. 308. 324. 340. 356. 372. 388. 404. 420. 436. 452. 468.
484. 500.]
[261. 277. 293. 309. 325. 341. 357. 373. 389. 405. 421. 437. 453. 469.
485. 501.]
[262. 278. 294. 310. 326. 342. 358. 374. 390. 406. 422. 438. 454. 470.
486. 502.]
[263. 279. 295. 311. 327. 343. 359. 375. 391. 407. 423. 439. 455. 471.
487. 503.]
[264. 280. 296. 312. 328. 344. 360. 376. 392. 408. 424. 440. 456. 472.
488. 504.]
[265. 281. 297. 313. 329. 345. 361. 377. 393. 409. 425. 441. 457. 473.
489. 505.]
[266. 282. 298. 314. 330. 346. 362. 378. 394. 410. 426. 442. 458. 474.
490. 506.]
[267. 283. 299. 315. 331. 347. 363. 379. 395. 411. 427. 443. 459. 475.
491. 507.]
[268. 284. 300. 316. 332. 348. 364. 380. 396. 412. 428. 444. 460. 476.
492. 508.]
[269. 285. 301. 317. 333. 349. 365. 381. 397. 413. 429. 445. 461. 477.
493. 509.]
[270. 286. 302. 318. 334. 350. 366. 382. 398. 414. 430. 446. 462. 478.
494. 510.]
[271. 287. 303. 319. 335. 351. 367. 383. 399. 415. 431. 447. 463. 479.
495. 511.]]
[[512. 528. 544. 560. 576. 592. 608. 624. 640. 656. 672. 688. 704. 720.
736. 752.]
[513. 529. 545. 561. 577. 593. 609. 625. 641. 657. 673. 689. 705. 721.
737. 753.]
[514. 530. 546. 562. 578. 594. 610. 626. 642. 658. 674. 690. 706. 722.
738. 754.]
[515. 531. 547. 563. 579. 595. 611. 627. 643. 659. 675. 691. 707. 723.
739. 755.]
[516. 532. 548. 564. 580. 596. 612. 628. 644. 660. 676. 692. 708. 724.
740. 756.]
[517. 533. 549. 565. 581. 597. 613. 629. 645. 661. 677. 693. 709. 725.
741. 757.]
[518. 534. 550. 566. 582. 598. 614. 630. 646. 662. 678. 694. 710. 726.
742. 758.]
[519. 535. 551. 567. 583. 599. 615. 631. 647. 663. 679. 695. 711. 727.
743. 759.]
[520. 536. 552. 568. 584. 600. 616. 632. 648. 664. 680. 696. 712. 728.
744. 760.]
[521. 537. 553. 569. 585. 601. 617. 633. 649. 665. 681. 697. 713. 729.
745. 761.]
[522. 538. 554. 570. 586. 602. 618. 634. 650. 666. 682. 698. 714. 730.
746. 762.]
[523. 539. 555. 571. 587. 603. 619. 635. 651. 667. 683. 699. 715. 731.
747. 763.]
[524. 540. 556. 572. 588. 604. 620. 636. 652. 668. 684. 700. 716. 732.
748. 764.]
[525. 541. 557. 573. 589. 605. 621. 637. 653. 669. 685. 701. 717. 733.
749. 765.]
[526. 542. 558. 574. 590. 606. 622. 638. 654. 670. 686. 702. 718. 734.
750. 766.]
[527. 543. 559. 575. 591. 607. 623. 639. 655. 671. 687. 703. 719. 735.
751. 767.]]]
Parent topic: Data Conversion