Compute Library
 22.05
qlstm_layer_normalization.cl
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1 /*
2  * Copyright (c) 2020-2021 Arm Limited.
3  *
4  * SPDX-License-Identifier: MIT
5  *
6  * Permission is hereby granted, free of charge, to any person obtaining a copy
7  * of this software and associated documentation files (the "Software"), to
8  * deal in the Software without restriction, including without limitation the
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10  * sell copies of the Software, and to permit persons to whom the Software is
11  * furnished to do so, subject to the following conditions:
12  *
13  * The above copyright notice and this permission notice shall be included in all
14  * copies or substantial portions of the Software.
15  *
16  * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
17  * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
18  * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
19  * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
20  * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
21  * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
22  * SOFTWARE.
23  */
24 #include "helpers_asymm.h"
25 
26 #if VEC_SIZE == 2
27 #define multiply_by_quantized_multiplier(input, qmul, shift) MULTIPLY_BY_QUANTIZED_MULTIPLIER(input, qmul, shift, 2)
28 #define PERFORM_REDUCTION_IMPL(type) \
29  inline VEC_DATA_TYPE(type, 1) perform_reduction_##type(VEC_DATA_TYPE(type, 2) sum) \
30  { \
31  sum.s0 += sum.s1; \
32  return sum.s0; \
33  }
34 #elif VEC_SIZE == 4
35 #define multiply_by_quantized_multiplier(input, qmul, shift) MULTIPLY_BY_QUANTIZED_MULTIPLIER(input, qmul, shift, 4)
36 #define PERFORM_REDUCTION_IMPL(type) \
37  inline VEC_DATA_TYPE(type, 1) perform_reduction_##type(VEC_DATA_TYPE(type, 4) sum) \
38  { \
39  sum.s01 += sum.s23; \
40  sum.s0 += sum.s1; \
41  return sum.s0; \
42  }
43 #elif VEC_SIZE == 8
44 #define multiply_by_quantized_multiplier(input, qmul, shift) MULTIPLY_BY_QUANTIZED_MULTIPLIER(input, qmul, shift, 8)
45 #define PERFORM_REDUCTION_IMPL(type) \
46  inline VEC_DATA_TYPE(type, 1) perform_reduction_##type(VEC_DATA_TYPE(type, 8) sum) \
47  { \
48  sum.s0123 += sum.s4567; \
49  sum.s01 += sum.s23; \
50  sum.s0 += sum.s1; \
51  return sum.s0; \
52  }
53 #else /* VEC_SIZE DEFAULT */
54 #define VEC_SIZE 16
55 #define multiply_by_quantized_multiplier(input, qmul, shift) MULTIPLY_BY_QUANTIZED_MULTIPLIER(input, qmul, shift, 16)
56 #define PERFORM_REDUCTION_IMPL(type) \
57  inline VEC_DATA_TYPE(type, 1) perform_reduction_##type(VEC_DATA_TYPE(type, 16) sum) \
58  { \
59  sum.s01234567 += sum.s89abcdef; \
60  sum.s0123 += sum.s4567; \
61  sum.s01 += sum.s23; \
62  sum.s0 += sum.s1; \
63  return sum.s0; \
64  }
65 #endif /* VEC_SIZE END */
66 
67 #define PERFORM_REDUCTION_STR(input, type) perform_reduction_##type(input)
68 #define PERFORM_REDUCTION(input, type) PERFORM_REDUCTION_STR(input, type)
69 
72 
73 /** Compute quantized multiplier and shift for the inverse square root of input.
74  * Using 3-bit fixed point and 5 iteration of Newton-Raphson method.
75  *
76  * @param[in] in Input to use
77  * @param[in] reverse_shift -1 to reverse the shift direction
78  *
79  * @return:
80  * .s0 Quantized multiplier for inverse square root
81  * .s1 Shift for inverse square root
82  *
83  */
84 inline int2 get_invsqrt_quantized_multiplier_exp(int in, int reverse_shift)
85 {
86  int2 stddev_inv;
87  int stddev_inv_multiplier = INT_MAX;
88  int stddev_inv_shift = 0;
89  int input = in;
90  if(input <= 1)
91  {
92  stddev_inv.s0 = stddev_inv_multiplier;
93  stddev_inv.s1 = stddev_inv_shift;
94  return stddev_inv;
95  }
96 
97  stddev_inv_shift = 11;
98  while(input >= (1 << 29))
99  {
100  input /= 4;
101  ++stddev_inv_shift;
102  }
103 
104  const unsigned int max_left_shift_bits = clz(input) - 1;
105  const unsigned int max_left_shift_bits_pairs = max_left_shift_bits / 2;
106  const unsigned int left_shift_bit_pairs = max_left_shift_bits_pairs - 1;
107  stddev_inv_shift -= left_shift_bit_pairs;
108  input <<= 2 * left_shift_bit_pairs;
109 
110  typedef int FixedPointRawType;
111  const unsigned int fixedpoint_position = 3;
112  const unsigned int fixedpoint_int_position = sizeof(FixedPointRawType) * 8 - 1 - fixedpoint_position;
113  typedef FixedPointRawType FixedPoint3;
114  typedef FixedPointRawType FixedPoint0;
115 
116  const FixedPoint3 fixedpoint_input = (input >> 1);
117  const FixedPoint3 fixedpoint_half_input = ASYMM_ROUNDING_DIVIDE_BY_POW2(fixedpoint_input, 1, 1);
118  const FixedPoint3 fixedpoint_half_three = (0x1 << fixedpoint_int_position) + (0x1 << (fixedpoint_int_position - 1));
119  FixedPoint3 x = 0x1 << fixedpoint_int_position;
120 
121  const int num_iteration = 5;
122  for(int i = 0; i < num_iteration; i++)
123  {
124  int x3 = ASYMM_RESCALE(ASYMM_MULT(ASYMM_MULT(x, x, 1), x, 1), 9, fixedpoint_position, 1);
125  x = ASYMM_RESCALE(ASYMM_MULT(fixedpoint_half_three, x, 1) - ASYMM_MULT(fixedpoint_half_input, x3, 1), 6, fixedpoint_position, 1);
126  }
127  const FixedPoint0 fixedpoint_half_sqrt_2 = 1518500250;
128  x = ASYMM_MULT(fixedpoint_half_sqrt_2, x, 1);
129  stddev_inv_multiplier = x;
130  if(stddev_inv_shift < 0)
131  {
132  stddev_inv_multiplier <<= -stddev_inv_shift;
133  stddev_inv_shift = 0;
134  }
135  stddev_inv_shift *= reverse_shift;
136 
137  stddev_inv.s0 = stddev_inv_multiplier;
138  stddev_inv.s1 = stddev_inv_shift;
139  return stddev_inv;
140 }
141 
142 #if defined(VEC_SIZE) && defined(DATA_TYPE) && defined(WIDTH) && defined(OUTPUT_MULTIPLIER) && defined(OUTPUT_SHIFT)
143 /** This function implements QLSTM layer normalization.
144  *
145  * @attention Vector size should be given as a preprocessor argument using -DVEC_SIZE=size. e.g. -DVEC_SIZE=16
146  * @attention Data type should be passed using the -DDATA_TYPE compile flag, e.g. -DDATA_TYPE=float
147  * @attention Width of the input tensor should be passed using the -DWIDTH compile flag, e.g. -DWIDTH=16
148  *
149  * @param[in] input_ptr Pointer to the first source tensor. Supported data types: QSYMM16
150  * @param[in] input_stride_x Stride of the first source tensor in X dimension (in bytes)
151  * @param[in] input_step_x input_stride_x * number of elements along X processed per workitem(in bytes)
152  * @param[in] input_stride_y Stride of the first source tensor in Y dimension (in bytes)
153  * @param[in] input_step_y input_stride_y * number of elements along Y processed per workitem(in bytes)
154  * @param[in] input_offset_first_element_in_bytes The offset of the first element in the first source tensor
155  * @param[in] weight_ptr Pointer to the weight tensor. Supported data type: same as @p input_ptr
156  * @param[in] weight_stride_x Stride of the weight tensor in X dimension (in bytes)
157  * @param[in] weight_step_x weight_stride_x * number of elements along X processed per workitem(in bytes)
158  * @param[in] weight_offset_first_element_in_bytes The offset of the first element in the weight tensor
159  * @param[in] bias_ptr Pointer to the bias tensor. Supported data type: S32
160  * @param[in] bias_stride_x Stride of the bias tensor in X dimension (in bytes)
161  * @param[in] bias_step_x bias_stride_x * number of elements along X processed per workitem(in bytes)
162  * @param[in] bias_offset_first_element_in_bytes The offset of the first element in the biases tensor
163  * @param[out] output_ptr Pointer to the destination tensor. Supported data types: same as @p input_ptr
164  * @param[in] output_stride_x Stride of the destination tensor in X dimension (in bytes)
165  * @param[in] output_step_x output_stride_x * number of elements along X processed per workitem(in bytes)
166  * @param[in] output_stride_y Stride of the destination tensor in Y dimension (in bytes)
167  * @param[in] output_step_y output_stride_y * number of elements along Y processed per workitem(in bytes)
168  * @param[in] output_offset_first_element_in_bytes The offset of the first element in the destination tensor
169  */
170 __kernel void qlstm_layer_normalization(
172  VECTOR_DECLARATION(weight),
174  IMAGE_DECLARATION(output))
175 {
176  // Get pixels pointer
178  Vector weight = CONVERT_TO_VECTOR_STRUCT(weight);
180  Image output = CONVERT_TO_IMAGE_STRUCT(output);
181 
182  VEC_DATA_TYPE(int, VEC_SIZE)
183  sum = 0;
184  VEC_DATA_TYPE(long, VEC_SIZE)
185  sum_sq = 0;
186  // Calculate partial sum
187  int i = 0;
188  for(; i <= (WIDTH - VEC_SIZE); i += VEC_SIZE)
189  {
190  // Load data
191  VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
192  data = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)offset(&input, i, 0));
193 
194  sum += CONVERT(data, VEC_DATA_TYPE(int, VEC_SIZE));
195  sum_sq += CONVERT(data, VEC_DATA_TYPE(long, VEC_SIZE)) * CONVERT(data, VEC_DATA_TYPE(long, VEC_SIZE));
196  }
197  // Perform reduction
198  sum.s0 = PERFORM_REDUCTION(sum, int);
199  sum_sq.s0 = PERFORM_REDUCTION(sum_sq, long);
200 
201  // Left-overs loop
202  for(; i < WIDTH; ++i)
203  {
204  DATA_TYPE data = *((__global DATA_TYPE *)offset(&input, i, 0));
205 
206  sum.s0 += CONVERT(data, int);
207  sum_sq.s0 += CONVERT(data, long) * CONVERT(data, long);
208  }
209 
210  int temp = 0x100000 / WIDTH;
211  int mean = (int)(sum.s0 * 1024 / WIDTH);
212  int var2 = ((sum_sq.s0 * (long)temp) - ((long)mean * (long)mean)) / 0x100000;
213  int2 stddev_inv = get_invsqrt_quantized_multiplier_exp(var2, -1);
214 
215  i = 0;
216  for(; i <= (WIDTH - VEC_SIZE); i += VEC_SIZE)
217  {
218  VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
219  data = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)offset(&input, i, 0));
220  VEC_DATA_TYPE(int, VEC_SIZE)
221  res = CONVERT(data, VEC_DATA_TYPE(int, VEC_SIZE)) * 1024 - mean;
222  res = multiply_by_quantized_multiplier(res, stddev_inv.s0, stddev_inv.s1);
223  VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
224  w = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)vector_offset(&weight, i));
225  res = res * CONVERT(w, VEC_DATA_TYPE(int, VEC_SIZE));
226  res = res + VLOAD(VEC_SIZE)(0, (__global int *)vector_offset(&bias, i));
227  // Due to different rounding scheme, we might need to revisit in the future: res = select(res - 512, res + 512, res > 0) / 1024;
228  res = (res + 512) >> 10;
229  res = multiply_by_quantized_multiplier(res, OUTPUT_MULTIPLIER, OUTPUT_SHIFT + 12);
230 #if defined(MIN_BOUND)
231  res = max(res, (VEC_DATA_TYPE(int, VEC_SIZE))MIN_BOUND);
232 #endif // defined(MIN_BOUND)
233 #if defined(MAX_BOUND)
234  res = min(res, (VEC_DATA_TYPE(int, VEC_SIZE))MAX_BOUND);
235 #endif // defined(MAX_BOUND)
237  (CONVERT(res, VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)), 0, (__global DATA_TYPE *)offset(&output, i, 0));
238  }
239  for(; i < WIDTH; ++i)
240  {
241  DATA_TYPE data = *((__global DATA_TYPE *)offset(&input, i, 0));
242  int res = (int)data * 1024 - mean;
243  res = MULTIPLY_BY_QUANTIZED_MULTIPLIER(res, stddev_inv.s0, stddev_inv.s1, 1);
244  DATA_TYPE w = *((__global DATA_TYPE *)vector_offset(&weight, i));
245  res = res * (int)w;
246  int b = *((__global int *)vector_offset(&bias, i));
247  res = res + b;
248  // Due to different rounding scheme, we might need to revisit in the future: res = select(res - 512, res + 512, res > 0) / 1024;
249  res = (res + 512) >> 10;
250  res = MULTIPLY_BY_QUANTIZED_MULTIPLIER(res, OUTPUT_MULTIPLIER, OUTPUT_SHIFT + 12, 1);
251 #if defined(MIN_BOUND)
252  res = max(res, MIN_BOUND);
253 #endif // defined(MIN_BOUND)
254 #if defined(MAX_BOUND)
255  res = min(res, MAX_BOUND);
256 #endif // defined(MAX_BOUND)
257  *((__global DATA_TYPE *)offset(&output, i, 0)) = (DATA_TYPE)res;
258  }
259 }
260 #endif /* defined(VEC_SIZE) && defined(DATA_TYPE) && defined(WIDTH) && defined(OUTPUT_MULTIPLIER) && defined(OUTPUT_SHIFT) */
Structure to hold Vector information.
Definition: helpers.h:888
SimpleTensor< int16_t > qlstm_layer_normalization(const SimpleTensor< int16_t > &src, const SimpleTensor< int16_t > &weight, const SimpleTensor< int32_t > &bias)
__global uchar * offset(const Image *img, int x, int y)
Get the pointer position of a Image.
Definition: helpers.h:1083
#define VEC_SIZE
SimpleTensor< float > w
Definition: DFT.cpp:156
#define CONVERT(x, type)
Definition: helpers.h:730
#define CONVERT_TO_IMAGE_STRUCT(name)
Definition: helpers.h:854
SimpleTensor< float > b
Definition: DFT.cpp:157
#define ASYMM_MULT(a, b, size)
#define ASYMM_ROUNDING_DIVIDE_BY_POW2(x, exponent, size)
#define IMAGE_DECLARATION(name)
Definition: helpers.h:804
#define multiply_by_quantized_multiplier(input, qmul, shift)
#define PERFORM_REDUCTION_IMPL(type)
#define ASYMM_RESCALE(value, src_integer_bits, dst_integer_bits, size)
#define CONVERT_TO_VECTOR_STRUCT(name)
Definition: helpers.h:848
#define VECTOR_DECLARATION(name)
Definition: helpers.h:798
int2 get_invsqrt_quantized_multiplier_exp(int in, int reverse_shift)
Compute quantized multiplier and shift for the inverse square root of input.
Structure to hold Image information.
Definition: helpers.h:896
__global const uchar * vector_offset(const Vector *vec, int x)
Get the pointer position of a Vector.
Definition: helpers.h:1072
#define MULTIPLY_BY_QUANTIZED_MULTIPLIER(input, qmul, shift, size)
#define VSTORE(size)
Definition: helpers.h:457
#define VLOAD(size)
Definition: helpers.h:203
#define PERFORM_REDUCTION(input, type)
const int32_t * bias
#define VEC_DATA_TYPE(type, size)
Definition: helpers.h:727