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Anthony Barbier6ff3b192017-09-04 18:44:23 +01001/*
2 * Copyright (c) 2017 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
9 * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
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,
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23 */
24#ifndef __ARM_COMPUTE_TEST_REFERENCE_REFERENCE_H__
25#define __ARM_COMPUTE_TEST_REFERENCE_REFERENCE_H__
26
27#include "RawTensor.h"
28#include "Types.h"
Pablo Tello221f3812017-06-28 17:27:56 +010029#include <vector>
Anthony Barbier6ff3b192017-09-04 18:44:23 +010030
Georgios Pinitasd4f8c272017-06-30 16:16:19 +010031#include <vector>
32
Anthony Barbier6ff3b192017-09-04 18:44:23 +010033namespace arm_compute
34{
35namespace test
36{
37namespace validation
38{
39/** Interface for reference implementations. */
40class Reference
41{
42public:
Giorgio Arena50f9fd72017-06-19 17:05:30 +010043 /** Compute reference sobel 3x3.
44 *
45 * @param[in] shape Shape of the input and output tensors.
46 * @param[in] border_mode Border mode to use for input tensor
47 * @param[in] constant_border_value Constant value to use if @p border_mode is constant
48 *
49 * @return Computed raw tensors along x and y axis.
50 */
51 static std::pair<RawTensor, RawTensor> compute_reference_sobel_3x3(const TensorShape &shape, BorderMode border_mode, uint8_t constant_border_value);
52 /** Compute reference sobel 5x5.
53 *
54 * @param[in] shape Shape of the input and output tensors.
55 * @param[in] border_mode Border mode to use for input tensor
56 * @param[in] constant_border_value Constant value to use if @p border_mode is constant
57 *
58 * @return Computed raw tensors along x and y axis.
59 */
60 static std::pair<RawTensor, RawTensor> compute_reference_sobel_5x5(const TensorShape &shape, BorderMode border_mode, uint8_t constant_border_value);
Giorgio Arenaf7959862017-06-13 15:19:51 +010061 /** Compute reference mean and standard deviation.
62 *
63 * @param[in] shape Shape of the input tensors.
64 *
65 * @return Computed mean and standard deviation.
66 */
67 static std::pair<float, float> compute_reference_mean_and_standard_deviation(const TensorShape &shape);
Anthony Barbier6ff3b192017-09-04 18:44:23 +010068 /** Compute reference integral image.
69 *
70 * @param[in] shape Shape of the input and output tensors.
71 *
72 * @return Computed raw tensor.
73 */
74 static RawTensor compute_reference_integral_image(const TensorShape &shape);
75 /** Compute reference absolute difference.
76 *
77 * @param[in] shape Shape of the input and output tensors.
78 * @param[in] dt_in0 Data type of first input tensor.
79 * @param[in] dt_in1 Data type of second input tensor.
80 * @param[in] dt_out Data type of the output tensor.
81 *
82 * @return Computed raw tensor.
83 */
84 static RawTensor compute_reference_absolute_difference(const TensorShape &shape, DataType dt_in0, DataType dt_in1, DataType dt_out);
85 /** Compute reference accumulate.
86 *
87 * @param[in] shape Shape of the input and output tensors.
88 *
89 * @return Computed raw tensor.
90 */
91 static RawTensor compute_reference_accumulate(const TensorShape &shape);
92 /** Compute reference accumulate.
93 *
94 * @param[in] shape Shape of the input and output tensors.
95 * @param[in] shift A uint32_t value within the range of [0, 15]
96 *
97 * @return Computed raw tensor.
98 */
99 static RawTensor compute_reference_accumulate_squared(const TensorShape &shape, uint32_t shift);
100 /** Compute reference accumulate.
101 *
102 * @param[in] shape Shape of the input and output tensors.
103 * @param[in] alpha A float value within the range of [0, 1]
104 *
105 * @return Computed raw tensor.
106 */
107 static RawTensor compute_reference_accumulate_weighted(const TensorShape &shape, float alpha);
108 /** Compute reference arithmetic addition.
109 *
110 * @param[in] shape Shape of the input and output tensors.
111 * @param[in] dt_in0 Data type of first input tensor.
112 * @param[in] dt_in1 Data type of second input tensor.
113 * @param[in] dt_out Data type of the output tensor.
114 * @param[in] convert_policy Overflow policy of the operation.
115 *
116 * @return Computed raw tensor.
117 */
118 static RawTensor compute_reference_arithmetic_addition(const TensorShape &shape, DataType dt_in0, DataType dt_in1, DataType dt_out, ConvertPolicy convert_policy);
119 /** Compute reference arithmetic subtraction.
120 *
121 * @param[in] shape Shape of the input and output tensors.
122 * @param[in] dt_in0 Data type of first input tensor.
123 * @param[in] dt_in1 Data type of second input tensor.
124 * @param[in] dt_out Data type of the output tensor.
125 * @param[in] convert_policy Overflow policy of the operation.
126 *
127 * @return Computed raw tensor.
128 */
129 static RawTensor compute_reference_arithmetic_subtraction(const TensorShape &shape, DataType dt_in0, DataType dt_in1, DataType dt_out, ConvertPolicy convert_policy);
130 /** Compute reference bitwise and.
131 *
132 * @param[in] shape Shape of the input and output tensors.
133 *
134 * @return Computed raw tensor.
135 */
136 static RawTensor compute_reference_bitwise_and(const TensorShape &shape);
137 /** Compute reference bitwise or.
138 *
139 * @param[in] shape Shape of the input and output tensors.
140 *
141 * @return Computed raw tensor.
142 */
143 static RawTensor compute_reference_bitwise_or(const TensorShape &shape);
144 /** Compute reference bitwise xor.
145 *
146 * @param[in] shape Shape of the input and output tensors.
147 *
148 * @return Computed raw tensor.
149 */
150 static RawTensor compute_reference_bitwise_xor(const TensorShape &shape);
151 /** Compute reference bitwise not.
152 *
153 * @param[in] shape Shape of the input and output tensors.
154 *
155 * @return Computed raw tensor.
156 */
157 static RawTensor compute_reference_bitwise_not(const TensorShape &shape);
SiCong Libacaf9a2017-06-19 13:41:45 +0100158 /** Compute reference box3x3 filter.
Anthony Barbier6ff3b192017-09-04 18:44:23 +0100159 *
SiCong Libacaf9a2017-06-19 13:41:45 +0100160 * @param[in] shape Shape of the input and output tensors.
161 * @param[in] border_mode BorderMode used by the input tensor.
162 * @param[in] constant_border_value Constant to use if @p border_mode == CONSTANT.
Anthony Barbier6ff3b192017-09-04 18:44:23 +0100163 *
164 * @return Computed raw tensor.
165 */
SiCong Libacaf9a2017-06-19 13:41:45 +0100166 static RawTensor compute_reference_box3x3(const TensorShape &shape, BorderMode border_mode, uint8_t constant_border_value);
Anthony Barbier6ff3b192017-09-04 18:44:23 +0100167 /** Compute reference depth convert.
168 *
169 * @param[in] shape Shape of the input and output tensors.
170 * @param[in] dt_in Data type of input tensor.
171 * @param[in] dt_out Data type of the output tensor.
172 * @param[in] policy Overflow policy of the operation.
173 * @param[in] shift Value for down/up conversions. Must be 0 <= shift < 8.
174 * @param[in] fixed_point_position Fixed point position.
175 *
176 * @return Computed raw tensor.
177 */
178 static RawTensor compute_reference_depth_convert(const TensorShape &shape, DataType dt_in, DataType dt_out, ConvertPolicy policy, uint32_t shift, uint32_t fixed_point_position);
SiCong Li5a536642017-06-19 14:47:05 +0100179 /** Compute reference gaussian3x3 filter.
180 *
181 * @param[in] shape Shape of the input and output tensors.
182 * @param[in] border_mode BorderMode used by the input tensor
183 * @param[in] constant_border_value Constant to use if @p border_mode == CONSTANT
184 *
185 * @return Computed raw tensor.
186 */
187 static RawTensor compute_reference_gaussian3x3(const TensorShape &shape, BorderMode border_mode, uint8_t constant_border_value);
SiCong Li3eb263e2017-06-19 15:31:43 +0100188 /** Compute reference gaussian5x5 filter.
189 *
190 * @param[in] shape Shape of the input and output tensors.
191 * @param[in] border_mode BorderMode used by the input tensor.
192 * @param[in] constant_border_value Constant to use if @p border_mode == CONSTANT.
193 *
194 * @return Computed raw tensor.
195 */
196 static RawTensor compute_reference_gaussian5x5(const TensorShape &shape, BorderMode border_mode, uint8_t constant_border_value);
Anthony Barbier6ff3b192017-09-04 18:44:23 +0100197 /** Compute matrix multiply function.
198 *
199 * @param[in] src_shape1 First input tensor shape
200 * @param[in] src_shape2 Second input tensor shape
201 * @param[in] src_shape3 Third input tensor shape
202 * @param[out] dst_shape Output tensor.
203 * @param[in] alpha Weight of the matrix product
204 * @param[in] beta Weight of the third matrix
205 * @param[in] dt Tensor's data type
206 * @param[in] fixed_point_position (Optional) Number of bits for the fractional part of the fixed point numbers
207 *
208 * @return Computed output tensor.
209 */
210 static RawTensor compute_reference_gemm(const TensorShape &src_shape1, const TensorShape &src_shape2, const TensorShape &src_shape3,
211 const TensorShape &dst_shape, float alpha, float beta, DataType dt, int fixed_point_position = 0);
Isabella Gottardi3b77e9d2017-06-22 11:05:41 +0100212 /** Compute reference non linear filter function
213 *
214 * @param[in] shape Shape of the input and output tensors.Data type supported: U8
215 * @param[in] function Non linear function to perform
216 * @param[in] mask_size Mask size. Supported sizes: 3, 5
217 * @param[in] pattern Matrix pattern
218 * @param[in] mask The given mask. Will be used only if pattern is specified to PATTERN_OTHER
219 * @param[in] border_mode Strategy to use for borders.
220 * @param[in] constant_border_value (Optional) Constant value to use for borders if border_mode is set to CONSTANT.
221 *
222 * @return Computed raw tensor.
223 */
224 static RawTensor compute_reference_non_linear_filter(const TensorShape &shape, NonLinearFilterFunction function, unsigned int mask_size,
225 MatrixPattern pattern, const uint8_t *mask, BorderMode border_mode, uint8_t constant_border_value = 0);
Anthony Barbier6ff3b192017-09-04 18:44:23 +0100226 /** Compute reference pixel-wise multiplication
227 *
228 * @param[in] shape Shape of the input and output tensors.
229 * @param[in] dt_in0 Data type of first input tensor.
230 * @param[in] dt_in1 Data type of second input tensor.
231 * @param[in] dt_out Data type of the output tensor.
232 * @param[in] scale Non-negative scale.
233 * @param[in] convert_policy Overflow policy of the operation.
234 * @param[in] rounding_policy Rounding policy of the operation.
235 *
236 * @return Computed raw tensor.
237 */
238 static RawTensor compute_reference_pixel_wise_multiplication(const TensorShape &shape, DataType dt_in0, DataType dt_in1, DataType dt_out, float scale, ConvertPolicy convert_policy,
239 RoundingPolicy rounding_policy);
240 /** Compute reference pixel-wise multiplication.
241 *
242 * @param[in] shape Shape of the input and output tensors.
243 * @param[in] dt_in0 Data type of first input tensor.
244 * @param[in] dt_in1 Data type of second input tensor.
245 * @param[in] dt_out Data type of the output tensor.
246 * @param[in] scale Scale to apply after multiplication. Must be positive.
247 * @param[in] fixed_point_position Fixed point position that expresses the number of bits for the fractional part of the number.
248 * @param[in] convert_policy Overflow policy of the operation.
249 * @param[in] rounding_policy Rounding policy of the operation.
250 *
251 * @return Computed raw tensor.
252 */
253 static RawTensor compute_reference_fixed_point_pixel_wise_multiplication(const TensorShape &shape, DataType dt_in0, DataType dt_in1, DataType dt_out, float scale, int fixed_point_position,
254 ConvertPolicy convert_policy, RoundingPolicy rounding_policy);
255 /** Compute reference threshold.
256 *
257 * @param[in] shape Shape of the input and output tensors.
258 * @param[in] threshold Threshold. When the threshold type is RANGE, this is used as the lower threshold.
259 * @param[in] false_value value to set when the condition is not respected.
260 * @param[in] true_value value to set when the condition is respected.
261 * @param[in] type Thresholding type. Either RANGE or BINARY.
262 * @param[in] upper Upper threshold. Only used when the thresholding type is RANGE.
263 *
264 * @return Computed raw tensor.
265 */
266 static RawTensor compute_reference_threshold(const TensorShape &shape, uint8_t threshold, uint8_t false_value, uint8_t true_value, ThresholdType type, uint8_t upper);
267 /** Compute reference activation layer.
268 *
269 * @param[in] shape Shape of the input and output tensors.
270 * @param[in] dt Data type of the tensors.
271 * @param[in] act_info Activation layer information.
272 * @param[in] fixed_point_position (Optional)Number of bits for the fractional part of fixed point numbers.
273 *
274 * @return Computed raw tensor.
275 */
276 static RawTensor compute_reference_activation_layer(const TensorShape &shape, DataType dt, ActivationLayerInfo act_info, int fixed_point_position = 0);
277 /** Compute reference batch normalization layer.
278 *
279 * @param[in] shape0 Shape of the input and output tensors.
280 * @param[in] shape1 Shape of the vector tensors.
281 * @param[in] dt Data type of all input and output tensors.
282 * @param[in] epsilon Small value to avoid division with zero.
283 * @param[in] fixed_point_position Fixed point position.
284 *
285 * @return Computed raw tensor.
286 */
287 static RawTensor compute_reference_batch_normalization_layer(const TensorShape &shape0, const TensorShape &shape1, DataType dt, float epsilon, int fixed_point_position = 0);
288 /** Compute reference pixel-wise multiplication
289 *
290 * @param[in] input_shape Shape for the input tensor
291 * @param[in] weights_shape Shape for the weights tensor
292 * @param[in] bias_shape Shape for the bias tensor
293 * @param[in] output_shape Shape for the output tensor
294 * @param[in] dt Data type to use
295 * @param[in] conv_info Pads and strides information for the convolution layer
296 * @param[in] fixed_point_position Number of bits for the fractional part of the fixed point numbers
297 *
298 * @return Computed raw tensor.
299 */
300 static RawTensor compute_reference_convolution_layer(const TensorShape &input_shape, const TensorShape &weights_shape, const TensorShape &bias_shape, const TensorShape &output_shape, DataType dt,
301 const PadStrideInfo &conv_info, int fixed_point_position);
302 /** Compute reference for fully connected layer function
303 *
304 * @param[in] input_shape Shape for the input tensor
305 * @param[in] weights_shape Shape for the weights tensor
306 * @param[in] bias_shape Shape for the bias tensor
307 * @param[in] output_shape Shape for the output tensor
308 * @param[in] dt Data type to use
309 * @param[in] transpose_weights Transpose the weights if true
310 * @param[in] fixed_point_position Number of bits for the fractional part of the fixed point numbers
311 *
312 * @return Computed raw tensor.
313 */
314 static RawTensor compute_reference_fully_connected_layer(const TensorShape &input_shape, const TensorShape &weights_shape, const TensorShape &bias_shape, const TensorShape &output_shape, DataType dt,
315 bool transpose_weights, int fixed_point_position);
316 /** Compute reference normalization layer.
317 *
318 * @param[in] shape Shape of the input and output tensors.
319 * @param[in] dt Data type of input and output tensors.
320 * @param[in] norm_info Normalization Layer information.
321 * @param[in] fixed_point_position (Optional) Fixed point position that expresses the number of bits for the fractional part of the number when the tensor's data type is QS8 or QS16 (default = 0).
322 *
323 * @return Computed raw tensor.
324 */
325 static RawTensor compute_reference_normalization_layer(const TensorShape &shape, DataType dt, NormalizationLayerInfo norm_info, int fixed_point_position = 0);
326 /** Compute reference pooling layer.
327 *
328 * @param[in] shape_in Shape of the input tensor.
329 * @param[in] shape_out Shape of the output tensor.
330 * @param[in] dt Data type of input and output tensors.
331 * @param[in] pool_info Pooling Layer information.
332 * @param[in] fixed_point_position (Optional) Number of bits for the fractional part of the fixed point numbers.
333 *
334 * @return Computed raw tensor.
335 */
336 static RawTensor compute_reference_pooling_layer(const TensorShape &shape_in, const TensorShape &shape_out, DataType dt, PoolingLayerInfo pool_info, int fixed_point_position = 0);
Georgios Pinitas7b7858d2017-06-21 16:44:24 +0100337 /** Compute reference roi pooling layer.
338 *
339 * @param[in] shape Shape of the input tensor.
340 * @param[in] dt Data type of input and output tensors.
341 * @param[in] rois Region of interest vector.
342 * @param[in] pool_info ROI Pooling Layer information.
343 */
344 static RawTensor compute_reference_roi_pooling_layer(const TensorShape &shape, DataType dt, const std::vector<ROI> &rois, const ROIPoolingLayerInfo &pool_info);
Anthony Barbier6ff3b192017-09-04 18:44:23 +0100345 /** Compute reference softmax layer.
346 *
347 * @param[in] shape Shape of the input and output tensors.
348 * @param[in] dt Data type of input and output tensors.
349 * @param[in] fixed_point_position (Optional) Number of bits for the fractional part of the fixed point numbers
350 *
351 * @return Computed raw tensor.
352 */
353 static RawTensor compute_reference_softmax_layer(const TensorShape &shape, DataType dt, int fixed_point_position = 0);
354 /** Compute reference fixed point operation.
355 *
356 * @param[in] shape Shape of the input and output tensors.
357 * @param[in] dt_in Data type of the input tensor.
358 * @param[in] dt_out Data type of the output tensor.
359 * @param[in] op Fixed point operation to perform.
360 * @param[in] fixed_point_position Number of bits for the fractional part of the fixed point numbers
361 *
362 * @return Computed raw tensor.
363 */
364 static RawTensor compute_reference_fixed_point_operation(const TensorShape &shape, DataType dt_in, DataType dt_out, FixedPointOp op, int fixed_point_position);
365
366protected:
367 Reference() = default;
368 ~Reference() = default;
369};
370} // namespace validation
371} // namespace test
372} // namespace arm_compute
Anthony Barbierac69aa12017-07-03 17:39:37 +0100373#endif /* __ARM_COMPUTE_TEST_REFERENCE_REFERENCE_H__ */