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review.mlplatform.org / ml / ComputeLibrary / e8f28136a048829211d30208cdd6679f0f1c1632 / . / arm_compute / runtime / CL / functions / CLLSTMLayerQuantized.h
blob: 8c116b14826d6c999fe99d7332319c4a4736dcb5 [file] [log] [blame]
Manuel Bottini10c53f12019-07-17 16:11:53 +0100[diff] [blame]1/*
Teresa Charlin62687422021-04-28 10:58:49 +0100[diff] [blame]2 * Copyright (c) 2019-2021 Arm Limited.
Manuel Bottini10c53f12019-07-17 16:11:53 +0100[diff] [blame]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,
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 */
Michalis Spyrouf4643372019-11-29 16:17:13 +0000[diff] [blame]24#ifndef ARM_COMPUTE_CLLSTMLAYERQUANTIZED_H
25#define ARM_COMPUTE_CLLSTMLAYERQUANTIZED_H
Manuel Bottini10c53f12019-07-17 16:11:53 +0100[diff] [blame]26
27#include "arm_compute/core/Types.h"
28#include "arm_compute/runtime/CL/functions/CLActivationLayer.h"
29#include "arm_compute/runtime/CL/functions/CLConcatenateLayer.h"
30#include "arm_compute/runtime/CL/functions/CLDequantizationLayer.h"
31#include "arm_compute/runtime/CL/functions/CLElementwiseOperations.h"
32#include "arm_compute/runtime/CL/functions/CLGEMMLowpMatrixMultiplyCore.h"
33#include "arm_compute/runtime/CL/functions/CLGEMMLowpOutputStage.h"
34#include "arm_compute/runtime/CL/functions/CLPixelWiseMultiplication.h"
35#include "arm_compute/runtime/CL/functions/CLQuantizationLayer.h"
36#include "arm_compute/runtime/CL/functions/CLSlice.h"
37#include "arm_compute/runtime/CL/functions/CLTranspose.h"
Manuel Bottini10c53f12019-07-17 16:11:53 +0100[diff] [blame]38#include "arm_compute/runtime/common/LSTMParams.h"
39
40namespace arm_compute
41{
42// Forward declarations
43class ICLTensor;
44
45/** Basic function to run @ref CLLSTMLayerQuantized
46 *
47 * This function calls the following CL functions/kernels:
48 *
Georgios Pinitas4a578b92021-06-25 12:13:49 +0100[diff] [blame]49 * -# @ref CLGEMMLowpMatrixMultiplyCore Quantized matrix multiplication core. Accumulators are 32-bit integers
50 * -# @ref CLGEMMLowpOutputStage Convert 32-bit integers into QSYMM16
51 * -# @ref CLTranspose Matrix transpose
52 * -# @ref CLConcatenateLayer Tensor concatenation
53 * -# @ref CLActivationLayer Activation functions (tanh and logistic)
54 * -# @ref CLArithmeticAddition Elementwise addition
55 * -# @ref CLPixelWiseMultiplication Elementwise multiplication
56 * -# @ref CLSlice Tensor slicing
57 * -# @ref CLDequantizationLayer Dequantize into float
58 * -# @ref CLQuantizationLayer Quantize from float
Manuel Bottini10c53f12019-07-17 16:11:53 +0100[diff] [blame]59 * */
60class CLLSTMLayerQuantized : public IFunction
61{
62public:
63 /** Default constructor */
64 CLLSTMLayerQuantized(std::shared_ptr<IMemoryManager> memory_manager = nullptr);
65 /** Prevent instances of this class from being copied (As this class contains pointers) */
66 CLLSTMLayerQuantized(const CLLSTMLayerQuantized &) = delete;
67 /** Default move constructor */
68 CLLSTMLayerQuantized(CLLSTMLayerQuantized &&) = default;
69 /** Prevent instances of this class from being copied (As this class contains pointers) */
70 CLLSTMLayerQuantized &operator=(const CLLSTMLayerQuantized &) = delete;
71 /** Default move assignment operator */
72 CLLSTMLayerQuantized &operator=(CLLSTMLayerQuantized &&) = default;
73 /** Initialize function's tensors.
74 *
Teresa Charlin62687422021-04-28 10:58:49 +0100[diff] [blame]75 * Valid data layouts:
76 * - All
77 *
78 * Valid data type configurations:
79 * |src0 - src8 |src9 - src12 |src13 |src14 |dst0 |dst1 |
80 * |:-----------|:------------|:-------|:------|:------|:------|
81 * |QASYMM8 |S32 |QSYMM16 |QASYMM8|QSYMM16|QASYMM8|
82 *
Manuel Bottini10c53f12019-07-17 16:11:53 +0100[diff] [blame]83 * @param[in] input Source tensor. Input is a 2D tensor with dimensions [input_size, batch_size]. Data types supported: QASYMM8.
84 * @param[in] input_to_input_weights 2D weights tensor with dimensions [input_size, output_size]. Data type supported: Same as @p input.
85 * @param[in] input_to_forget_weights 2D weights tensor with dimensions [input_size, output_size]. Data type supported: Same as @p input.
86 * @param[in] input_to_cell_weights 2D weights tensor with dimensions [input_size, output_size]. Data type supported: Same as @p input.
87 * @param[in] input_to_output_weights 2D weights tensor with dimensions [input_size, output_size]. Data type supported: Same as @p input.
88 * @param[in] recurrent_to_input_weights 2D weights tensor with dimensions [output_size, output_size]. Data type supported: Same as @p input.
89 * @param[in] recurrent_to_forget_weights 2D weights tensor with dimensions [output_size, output_size]. Data type supported: Same as @p input.
90 * @param[in] recurrent_to_cell_weights 2D weights tensor with dimensions [output_size, output_size]. Data type supported: Same as @p input.
91 * @param[in] recurrent_to_output_weights 2D weights tensor with dimensions [output_size, output_size]. Data type supported: Same as @p input.
92 * @param[in] input_gate_bias 1D weights tensor with dimensions [output_size]. Data type supported: S32.
93 * @param[in] forget_gate_bias 1D weights tensor with dimensions [output_size]. Data type supported: S32.
94 * @param[in] cell_bias 1D weights tensor with dimensions [output_size]. Data type supported: S32.
95 * @param[in] output_gate_bias 1D weights tensor with dimensions [output_size]. Data type supported: S32.
96 * @param[in] cell_state_in 2D tensor with dimensions [output_size, batch_size]. Data type supported: QSYMM16.
97 * @param[in] output_state_in 2D tensor with dimensions [output_size, batch_size]. Data type supported: Same as @p input.
98 * @param[out] cell_state_out Destination tensor. Output is a 2D tensor with dimensions [output_size, batch_size]. Data type supported: QSYMM16.
99 * @param[out] output_state_out Destination tensor. Output is a 2D tensor with dimensions [output_size, batch_size].Data types supported: Same as @p input.
100 */
101 void configure(const ICLTensor *input,
Felix Thomasmathibalanafd38f02023-09-27 17:46:17 +0100[diff] [blame]102 const ICLTensor *input_to_input_weights,
103 const ICLTensor *input_to_forget_weights,
104 const ICLTensor *input_to_cell_weights,
105 const ICLTensor *input_to_output_weights,
106 const ICLTensor *recurrent_to_input_weights,
107 const ICLTensor *recurrent_to_forget_weights,
108 const ICLTensor *recurrent_to_cell_weights,
109 const ICLTensor *recurrent_to_output_weights,
110 const ICLTensor *input_gate_bias,
111 const ICLTensor *forget_gate_bias,
112 const ICLTensor *cell_bias,
113 const ICLTensor *output_gate_bias,
114 ICLTensor *cell_state_in,
115 const ICLTensor *output_state_in,
116 ICLTensor *cell_state_out,
117 ICLTensor *output_state_out);
Manuel Bottini2b84be52020-04-08 10:15:51 +0100[diff] [blame]118 /** Initialize function's tensors.
119 *
120 * @param[in] compile_context The compile context to be used.
121 * @param[in] input Source tensor. Input is a 2D tensor with dimensions [input_size, batch_size]. Data types supported: QASYMM8.
122 * @param[in] input_to_input_weights 2D weights tensor with dimensions [input_size, output_size]. Data type supported: Same as @p input.
123 * @param[in] input_to_forget_weights 2D weights tensor with dimensions [input_size, output_size]. Data type supported: Same as @p input.
124 * @param[in] input_to_cell_weights 2D weights tensor with dimensions [input_size, output_size]. Data type supported: Same as @p input.
125 * @param[in] input_to_output_weights 2D weights tensor with dimensions [input_size, output_size]. Data type supported: Same as @p input.
126 * @param[in] recurrent_to_input_weights 2D weights tensor with dimensions [output_size, output_size]. Data type supported: Same as @p input.
127 * @param[in] recurrent_to_forget_weights 2D weights tensor with dimensions [output_size, output_size]. Data type supported: Same as @p input.
128 * @param[in] recurrent_to_cell_weights 2D weights tensor with dimensions [output_size, output_size]. Data type supported: Same as @p input.
129 * @param[in] recurrent_to_output_weights 2D weights tensor with dimensions [output_size, output_size]. Data type supported: Same as @p input.
130 * @param[in] input_gate_bias 1D weights tensor with dimensions [output_size]. Data type supported: S32.
131 * @param[in] forget_gate_bias 1D weights tensor with dimensions [output_size]. Data type supported: S32.
132 * @param[in] cell_bias 1D weights tensor with dimensions [output_size]. Data type supported: S32.
133 * @param[in] output_gate_bias 1D weights tensor with dimensions [output_size]. Data type supported: S32.
134 * @param[in] cell_state_in 2D tensor with dimensions [output_size, batch_size]. Data type supported: QSYMM16.
135 * @param[in] output_state_in 2D tensor with dimensions [output_size, batch_size]. Data type supported: Same as @p input.
136 * @param[out] cell_state_out Destination tensor. Output is a 2D tensor with dimensions [output_size, batch_size]. Data type supported: QSYMM16.
137 * @param[out] output_state_out Destination tensor. Output is a 2D tensor with dimensions [output_size, batch_size].Data types supported: Same as @p input.
138 */
Felix Thomasmathibalanafd38f02023-09-27 17:46:17 +0100[diff] [blame]139 void configure(const CLCompileContext &compile_context,
140 const ICLTensor *input,
141 const ICLTensor *input_to_input_weights,
142 const ICLTensor *input_to_forget_weights,
143 const ICLTensor *input_to_cell_weights,
144 const ICLTensor *input_to_output_weights,
145 const ICLTensor *recurrent_to_input_weights,
146 const ICLTensor *recurrent_to_forget_weights,
147 const ICLTensor *recurrent_to_cell_weights,
148 const ICLTensor *recurrent_to_output_weights,
149 const ICLTensor *input_gate_bias,
150 const ICLTensor *forget_gate_bias,
151 const ICLTensor *cell_bias,
152 const ICLTensor *output_gate_bias,
153 ICLTensor *cell_state_in,
154 const ICLTensor *output_state_in,
155 ICLTensor *cell_state_out,
156 ICLTensor *output_state_out);
Manuel Bottini10c53f12019-07-17 16:11:53 +0100[diff] [blame]157
158 /** Static function to check if given info will lead to a valid configuration of @ref CLLSTMLayerQuantized
159 *
160 * @param[in] input Source tensor info. Input is a 2D tensor info with dimensions [input_size, batch_size]. Data types supported: QASYMM8.
161 * @param[in] input_to_input_weights 2D weights tensor info with dimensions [input_size, output_size]. Data type supported: Same as @p input.
162 * @param[in] input_to_forget_weights 2D weights tensor info with dimensions [input_size, output_size]. Data type supported: Same as @p input.
163 * @param[in] input_to_cell_weights 2D weights tensor info with dimensions [input_size, output_size]. Data type supported: Same as @p input.
164 * @param[in] input_to_output_weights 2D weights tensor info with dimensions [input_size, output_size]. Data type supported: Same as @p input.
165 * @param[in] recurrent_to_input_weights 2D weights tensor info with dimensions [output_size, output_size]. Data type supported: Same as @p input.
166 * @param[in] recurrent_to_forget_weights 2D weights tensor info with dimensions [output_size, output_size]. Data type supported: Same as @p input.
167 * @param[in] recurrent_to_cell_weights 2D weights tensor info with dimensions [output_size, output_size]. Data type supported: Same as @p input.
168 * @param[in] recurrent_to_output_weights 2D weights tensor info with dimensions [output_size, output_size]. Data type supported: Same as @p input.
169 * @param[in] input_gate_bias 1D weights tensor info with dimensions [output_size]. Data type supported: S32.
170 * @param[in] forget_gate_bias 1D weights tensor info with dimensions [output_size]. Data type supported: S32.
171 * @param[in] cell_bias 1D weights tensor info with dimensions [output_size]. Data type supported: S32.
172 * @param[in] output_gate_bias 1D weights tensor info with dimensions [output_size]. Data type supported: S32.
173 * @param[in] cell_state_in 2D tensor info with dimensions [output_size, batch_size]. Data type supported: QSYMM16.
174 * @param[in] output_state_in 2D tensor info with dimensions [output_size, batch_size]. Data type supported: Same as @p input.
175 * @param[out] cell_state_out Destination tensor info. Output is a 2D tensor info with dimensions [output_size, batch_size]. Data type supported: QSYMM16.
176 * @param[out] output_state_out Destination tensor info. Output is a 2D tensor info with dimensions [output_size, batch_size].Data types supported: Same as @p input.
177 *
178 * @return a status
179 */
180 static Status validate(const ITensorInfo *input,
Felix Thomasmathibalanafd38f02023-09-27 17:46:17 +0100[diff] [blame]181 const ITensorInfo *input_to_input_weights,
182 const ITensorInfo *input_to_forget_weights,
183 const ITensorInfo *input_to_cell_weights,
184 const ITensorInfo *input_to_output_weights,
185 const ITensorInfo *recurrent_to_input_weights,
186 const ITensorInfo *recurrent_to_forget_weights,
187 const ITensorInfo *recurrent_to_cell_weights,
188 const ITensorInfo *recurrent_to_output_weights,
189 const ITensorInfo *input_gate_bias,
190 const ITensorInfo *forget_gate_bias,
191 const ITensorInfo *cell_bias,
192 const ITensorInfo *output_gate_bias,
193 const ITensorInfo *cell_state_in,
194 const ITensorInfo *output_state_in,
195 const ITensorInfo *cell_state_out,
196 const ITensorInfo *output_state_out);
Manuel Bottini10c53f12019-07-17 16:11:53 +0100[diff] [blame]197
198 // Inherited methods overridden:
199 void run() override;
200 void prepare() override;
201
202private:
Georgios Pinitas26014cf2019-09-09 19:00:57 +0100[diff] [blame]203 MemoryGroup _memory_group;
Manuel Bottini10c53f12019-07-17 16:11:53 +0100[diff] [blame]204
205 // Functions used
Georgios Pinitas4a578b92021-06-25 12:13:49 +0100[diff] [blame]206 CLGEMMLowpMatrixMultiplyCore _gemmlowp;
207 CLGEMMLowpOutputStage _output_stage;
208 CLTranspose _transpose_weights;
209 CLConcatenateLayer _concat_input_weights;
210 CLConcatenateLayer _concat_recurrent_weights;
211 CLConcatenateLayer _concat_weights;
212 CLConcatenateLayer _concat_inputs;
213 CLConcatenateLayer _concat_bias;
214 CLActivationLayer _sigmoid_forget_gate;
215 CLActivationLayer _sigmoid_input_gate;
216 CLActivationLayer _sigmoid_output_gate;
217 CLActivationLayer _tanh_modulation_gate;
218 CLActivationLayer _tanh_output_state;
219 CLArithmeticAddition _add_cell_state_tmps;
220 CLArithmeticAddition _add2;
221 CLPixelWiseMultiplication _mul_forget_gate_cell_state;
222 CLPixelWiseMultiplication _mul_input_gate_input_mod_gate;
223 CLPixelWiseMultiplication _mul_output_state_tmp_output_gate;
224 CLSlice _slice_input_tensor;
225 CLSlice _slice_forget_tensor;
226 CLSlice _slice_cell_tensor;
227 CLSlice _slice_output_tensor;
228 CLDequantizationLayer _dequantize;
229 CLQuantizationLayer _quantize;
Manuel Bottini10c53f12019-07-17 16:11:53 +0100[diff] [blame]230
231 // Tensor pointers
232 const ICLTensor *_input_to_input_weights;
233 const ICLTensor *_input_to_forget_weights;
234 const ICLTensor *_input_to_cell_weights;
235 const ICLTensor *_input_to_output_weights;
236 const ICLTensor *_recurrent_to_input_weights;
237 const ICLTensor *_recurrent_to_forget_weights;
238 const ICLTensor *_recurrent_to_cell_weights;
239 const ICLTensor *_recurrent_to_output_weights;
240 const ICLTensor *_input_gate_bias;
241 const ICLTensor *_forget_gate_bias;
242 const ICLTensor *_cell_bias;
243 const ICLTensor *_output_gate_bias;
244
245 // Temporary tensors
246 CLTensor _recurrent_weights;
247 CLTensor _input_weights;
248 CLTensor _weights;
249 CLTensor _input;
250 CLTensor _weights_transposed;
251 CLTensor _output_highp;
252 CLTensor _output_lowp;
253 CLTensor _bias;
254 CLTensor _forget_gate_input;
255 CLTensor _input_gate_input;
256 CLTensor _output_gate_input;
257 CLTensor _input_modulation_gate_input;
258 CLTensor _forget_gate_output;
259 CLTensor _input_gate_output;
260 CLTensor _output_gate_output;
261 CLTensor _input_modulation_gate_output;
262 CLTensor _cell_state_tmp1;
263 CLTensor _cell_state_tmp2;
264 CLTensor _output_state_tmp;
265 CLTensor _output_state_out_symm;
266 CLTensor _output_state_out_f32;
267
268 bool _is_prepared;
269};
270} // namespace arm_compute
Michalis Spyrouf4643372019-11-29 16:17:13 +0000[diff] [blame]271#endif /* ARM_COMPUTE_CLLSTMLAYERQUANTIZED_H */