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review.mlplatform.org / ml / ComputeLibrary / bec9b032ddcff449c7ad40febbcab24c23ee58a0 / . / arm_compute / runtime / NEON / functions / NELSTMLayer.h
blob: 4272215486725eab4325988c88726c8f9b6e901b [file] [log] [blame]
Michalis Spyrou25f45a42018-08-08 12:53:05 +0100[diff] [blame]1/*
Teresa Charlin62687422021-04-28 10:58:49 +0100[diff] [blame]2 * Copyright (c) 2018-2021 Arm Limited.
Michalis Spyrou25f45a42018-08-08 12:53:05 +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_NELSTMLAYER_H
25#define ARM_COMPUTE_NELSTMLAYER_H
Michalis Spyrou25f45a42018-08-08 12:53:05 +0100[diff] [blame]26
Michalis Spyrou25f45a42018-08-08 12:53:05 +0100[diff] [blame]27#include "arm_compute/core/Types.h"
Michele Di Giorgio93b75e02021-06-21 12:00:43 +0100[diff] [blame]28#include "arm_compute/runtime/NEON/functions/NEActivationLayer.h"
Michalis Spyrou173ba9b2020-06-23 17:25:43 +0100[diff] [blame]29#include "arm_compute/runtime/NEON/functions/NEArithmeticAddition.h"
30#include "arm_compute/runtime/NEON/functions/NEArithmeticSubtraction.h"
Georgios Pinitas09f24972019-05-17 18:14:40 +0100[diff] [blame]31#include "arm_compute/runtime/NEON/functions/NEConcatenateLayer.h"
Michalis Spyrouebcebf12020-10-21 00:04:14 +0100[diff] [blame]32#include "arm_compute/runtime/NEON/functions/NECopy.h"
Michalis Spyrou25f45a42018-08-08 12:53:05 +0100[diff] [blame]33#include "arm_compute/runtime/NEON/functions/NEFullyConnectedLayer.h"
34#include "arm_compute/runtime/NEON/functions/NEGEMM.h"
Michele Di Giorgio0cbfda62019-06-13 17:01:29 +0100[diff] [blame]35#include "arm_compute/runtime/NEON/functions/NEMeanStdDevNormalizationLayer.h"
Michalis Spyrou6eb73452020-07-02 17:39:25 +0100[diff] [blame]36#include "arm_compute/runtime/NEON/functions/NEPixelWiseMultiplication.h"
Michalis Spyrouebcebf12020-10-21 00:04:14 +0100[diff] [blame]37#include "arm_compute/runtime/NEON/functions/NETranspose.h"
Michalis Spyrou25f45a42018-08-08 12:53:05 +0100[diff] [blame]38#include "arm_compute/runtime/common/LSTMParams.h"
39
40namespace arm_compute
41{
42// Forward declarations
43class ITensor;
44
45/** Basic function to run @ref NELSTMLayer */
46class NELSTMLayer : public IFunction
47{
48public:
49 /** Default constructor */
50 NELSTMLayer(std::shared_ptr<IMemoryManager> memory_manager = nullptr);
Michalis Spyrouebcebf12020-10-21 00:04:14 +0100[diff] [blame]51 /** Prevent instances of this class from being copied (As this class contains pointers) */
52 NELSTMLayer(const NELSTMLayer &) = delete;
53 /** Prevent instances of this class from being copied (As this class contains pointers) */
54 NELSTMLayer &operator=(const NELSTMLayer &) = delete;
55 /** Prevent instances of this class from being moved (As this class contains non movable objects) */
56 NELSTMLayer(NELSTMLayer &&) = delete;
57 /** Prevent instances of this class from being moved (As this class contains non movable objects) */
58 NELSTMLayer &operator=(NELSTMLayer &&) = delete;
59 /** Default destructor */
60 ~NELSTMLayer();
Michalis Spyrou25f45a42018-08-08 12:53:05 +0100[diff] [blame]61 /** Initialize function's tensors.
62 *
Teresa Charlin62687422021-04-28 10:58:49 +0100[diff] [blame]63 * Valid data layouts:
64 * - All
65 *
66 * Valid data type configurations:
67 * |src0 - src13 | dst0 - dst3 |
68 * |:------------|:------------|
69 * |F16 |F16 |
70 * |F32 |F32 |
71 *
Michalis Spyrou25f45a42018-08-08 12:53:05 +0100[diff] [blame]72 * @param[in] input Source tensor. Input is a 2D tensor with dimensions [input_size, batch_size]. Data types supported: F16/F32.
73 * @param[in] input_to_forget_weights 2D weights tensor with dimensions [input_size, num_units]. Data type supported: Same as @p input.
74 * @param[in] input_to_cell_weights 2D weights tensor with dimensions [input_size, num_units]. Data type supported: Same as @p input.
75 * @param[in] input_to_output_weights 2D weights tensor with dimensions [input_size, num_units]. Data type supported: Same as @p input.
76 * @param[in] recurrent_to_forget_weights 2D weights tensor with dimensions [output_size, num_units]. Data type supported: Same as @p input.
77 * @param[in] recurrent_to_cell_weights 2D weights tensor with dimensions [output_size, num_units]. Data type supported: Same as @p input.
78 * @param[in] recurrent_to_output_weights 2D weights tensor with dimensions [output_size, num_units]. Data type supported: Same as @p input.
79 * @param[in] forget_gate_bias 1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input.
80 * @param[in] cell_bias 1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input.
81 * @param[in] output_gate_bias 1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input.
82 * @param[in] output_state_in 2D weights tensor with dimensions [output_size, batch_size]. Data type supported: Same as @p input.
83 * @param[in] cell_state_in 2D tensor with dimensions [num_units, batch_size]. Data type supported: Same as @p input.
84 * @param[out] scratch_buffer 2D tensor with dimensions [num_units * 4, batch_size] with CIFG or [num_units * 3, batch_size] without CIGF. Data type supported: Same as @p input.
85 * @param[out] output_state_out 2D weights tensor with dimensions [output_size, batch_size]. Data type supported: Same as @p input.
86 * @param[out] cell_state_out 2D tensor with dimensions [num_units, batch_size]. Data type supported: Same as @p input.
87 * @param[out] output Destination tensor. Output is a 2D tensor with dimensions [output_size, batch_size].
88 * Data types supported: Same as @p input.
Michele Di Giorgio47a89902020-03-09 19:32:33 +0000[diff] [blame]89 * @param[in] lstm_params Weights tensors used in peephole optimization:
90 * input_to_input_weights (Optional) 2D weights tensor with dimensions [input_size, num_units]. Data type supported: Same as @p input.
91 * recurrent_to_input_weights (Optional) 2D weights tensor with dimensions [output_size, num_units]. Data type supported: Same as @p input.
92 * cell_to_input_weights (Optional) 1D weights tensor with dimensions [num_units]. Can be nullptr. Data type supported: Same as @p input.
93 * cell_to_forget_weights (Optional) 1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input.
94 * cell_to_output_weights (Optional) 1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input.
95 * input_gate_bias (Optional) 1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input
96 * projection_weights (Optional) 2D weights tensor with dimensions [output_size, num_units]. Data type supported: Same as @p input.
97 * projection_bias (Optional) 1D weights tensor with dimensions [output_size]. Data type supported: Same as @p input.
98 * input_layer_norm_weights (Optional) 1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input.
99 * forget_layer_norm_weights (Optional) 1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input.
100 * cell_layer_norm_weights (Optional) 1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input.
101 * output_layer_norm_weights (Optional) 1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input.
Michalis Spyrou25f45a42018-08-08 12:53:05 +0100[diff] [blame]102 * @param[in] activation_info Contains activation information described in @ref ActivationLayerInfo.
103 * @param[in] cell_threshold The clipping threshold for the cell state, such that values are bound within [-cell_clip, cell_clip]. If set to 0.0 then clipping is disabled.
Michele Di Giorgio47a89902020-03-09 19:32:33 +0000[diff] [blame]104 * @param[in] projection_threshold The clipping threshold for the output from the projection layer, such that values are bound within [-proj_clip, proj_clip].
105 * If set to 0.0 then clipping is disabled.
Michalis Spyrou25f45a42018-08-08 12:53:05 +0100[diff] [blame]106 */
107 void configure(const ITensor *input,
108 const ITensor *input_to_forget_weights, const ITensor *input_to_cell_weights, const ITensor *input_to_output_weights,
109 const ITensor *recurrent_to_forget_weights, const ITensor *recurrent_to_cell_weights, const ITensor *recurrent_to_output_weights,
110 const ITensor *forget_gate_bias, const ITensor *cell_bias, const ITensor *output_gate_bias,
111 const ITensor *output_state_in, const ITensor *cell_state_in,
112 ITensor *scratch_buffer, ITensor *output_state_out, ITensor *cell_state_out, ITensor *output,
113 const LSTMParams<ITensor> &lstm_params, const ActivationLayerInfo &activation_info, float cell_threshold = 0.f, float projection_threshold = 0.f);
114
115 /** Static function to check if given info will lead to a valid configuration of @ref NELSTMLayer
116 *
117 * @param[in] input Source tensor. Input is a 2D tensor with dimensions [input_size, batch_size]. Data types supported: F16/F32.
118 * @param[in] input_to_forget_weights 2D weights tensor with dimensions [input_size, num_units]. Data type supported: Same as @p input.
119 * @param[in] input_to_cell_weights 2D weights tensor with dimensions [input_size, num_units]. Data type supported: Same as @p input.
120 * @param[in] input_to_output_weights 2D weights tensor with dimensions [input_size, num_units]. Data type supported: Same as @p input.
121 * @param[in] recurrent_to_forget_weights 2D weights tensor with dimensions [output_size, num_units]. Data type supported: Same as @p input.
122 * @param[in] recurrent_to_cell_weights 2D weights tensor with dimensions [output_size, num_units]. Data type supported: Same as @p input.
123 * @param[in] recurrent_to_output_weights 2D weights tensor with dimensions [output_size, num_units]. Data type supported: Same as @p input.
124 * @param[in] forget_gate_bias 1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input.
125 * @param[in] cell_bias 1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input.
126 * @param[in] output_gate_bias 1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input.
127 * @param[in] output_state_in 2D weights tensor with dimensions [output_size, batch_size]. Data type supported: Same as @p input.
128 * @param[in] cell_state_in 2D tensor with dimensions [num_units, batch_size]. Data type supported: Same as @p input.
129 * @param[in] scratch_buffer 2D tensor with dimensions [num_units * 4, batch_size] with CIFG or [num_units * 3, batch_size] without CIGF. Data type supported: Same as @p input.
130 * @param[in] output_state_out 2D weights tensor with dimensions [output_size, batch_size]. Data type supported: Same as @p input.
131 * @param[in] cell_state_out 2D tensor with dimensions [num_units, batch_size]. Data type supported: Same as @p input.
132 * @param[in] output Destination tensor. Output is a 2D tensor with dimensions [output_size, batch_size].
133 * Data types supported: Same as @p input.
Michele Di Giorgio47a89902020-03-09 19:32:33 +0000[diff] [blame]134 * @param[in] lstm_params Weights tensors used in peephole optimization:
135 * input_to_input_weights (Optional) 2D weights tensor with dimensions [input_size, num_units]. Data type supported: Same as @p input.
136 * recurrent_to_input_weights (Optional) 2D weights tensor with dimensions [output_size, num_units]. Data type supported: Same as @p input.
137 * cell_to_input_weights (Optional) 1D weights tensor with dimensions [num_units]. Can be nullptr. Data type supported: Same as @p input.
138 * cell_to_forget_weights (Optional) 1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input.
139 * cell_to_output_weights (Optional) 1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input.
140 * input_gate_bias (Optional) 1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input
141 * projection_weights (Optional) 2D weights tensor with dimensions [output_size, num_units]. Data type supported: Same as @p input.
142 * projection_bias (Optional) 1D weights tensor with dimensions [output_size]. Data type supported: Same as @p input.
143 * input_layer_norm_weights (Optional) 1D weights tensor info with dimensions [num_units]. Data type supported: Same as @p input.
144 * forget_layer_norm_weights (Optional) 1D weights tensor info with dimensions [num_units]. Data type supported: Same as @p input.
145 * cell_layer_norm_weights (Optional) 1D weights tensor info with dimensions [num_units]. Data type supported: Same as @p input.
146 * output_layer_norm_weights (Optional) 1D weights tensor info with dimensions [num_units]. Data type supported: Same as @p input.
Michalis Spyrou25f45a42018-08-08 12:53:05 +0100[diff] [blame]147 * @param[in] activation_info Contains activation information described in @ref ActivationLayerInfo.
148 * @param[in] cell_threshold The clipping threshold for the cell state, such that values are bound within [-cell_clip, cell_clip]. If set to 0.0 then clipping is disabled.
Michele Di Giorgio47a89902020-03-09 19:32:33 +0000[diff] [blame]149 * @param[in] projection_threshold The clipping threshold for the output from the projection layer, such that values are bound within [-proj_clip, proj_clip].
150 * If set to 0.0 then clipping is disabled.
Michalis Spyrou25f45a42018-08-08 12:53:05 +0100[diff] [blame]151 *
152 * @return a status
153 */
154 static Status validate(const ITensorInfo *input,
155 const ITensorInfo *input_to_forget_weights, const ITensorInfo *input_to_cell_weights, const ITensorInfo *input_to_output_weights,
156 const ITensorInfo *recurrent_to_forget_weights, const ITensorInfo *recurrent_to_cell_weights, const ITensorInfo *recurrent_to_output_weights,
157 const ITensorInfo *forget_gate_bias, const ITensorInfo *cell_bias, const ITensorInfo *output_gate_bias,
158 const ITensorInfo *output_state_in, const ITensorInfo *cell_state_in,
159 const ITensorInfo *scratch_buffer, const ITensorInfo *output_state_out, const ITensorInfo *cell_state_out, const ITensorInfo *output,
160 const LSTMParams<ITensorInfo> &lstm_params, const ActivationLayerInfo &activation_info, float cell_threshold = 0.f, float projection_threshold = 0.f);
161
162 // Inherited methods overridden:
163 void run() override;
John Kesapides917959c2019-02-04 12:37:29 +0000[diff] [blame]164 void prepare() override;
Michalis Spyrou25f45a42018-08-08 12:53:05 +0100[diff] [blame]165
166private:
Michalis Spyrou6eb73452020-07-02 17:39:25 +0100[diff] [blame]167 MemoryGroup _memory_group;
168 NEFullyConnectedLayer _fully_connected_input_gate;
169 NEArithmeticAddition _accum_input_gate1;
170 NEArithmeticSubtraction _subtract_input_gate;
171 NEPixelWiseMultiplication _pixelwise_mul_input_gate;
172 NEActivationLayer _activation_input_gate;
173 NEFullyConnectedLayer _fully_connected_forget_gate;
174 NEArithmeticAddition _accum_forget_gate1;
175 NEPixelWiseMultiplication _pixelwise_mul_forget_gate;
176 NEActivationLayer _activation_forget_gate;
177 NEFullyConnectedLayer _fully_connected_cell_state;
178 NEGEMM _gemm_cell_state1;
Michalis Spyrouebcebf12020-10-21 00:04:14 +0100[diff] [blame]179 NETranspose _transpose_cell_state;
Michalis Spyrou6eb73452020-07-02 17:39:25 +0100[diff] [blame]180 NEArithmeticAddition _accum_cell_state1;
181 NEArithmeticAddition _accum_cell_state2;
182 NEPixelWiseMultiplication _pixelwise_mul_cell_state1;
183 NEActivationLayer _activation_cell_state;
184 NEActivationLayer _cell_clip;
185 NEPixelWiseMultiplication _pixelwise_mul_cell_state2;
186 NEFullyConnectedLayer _fully_connected_output;
187 NEPixelWiseMultiplication _pixelwise_mul_output_state1;
188 NEArithmeticAddition _accum_output1;
189 NEActivationLayer _activation_output;
190 NEActivationLayer _activation_output_state;
191 NEPixelWiseMultiplication _pixelwise_mul_output_state2;
192 NEFullyConnectedLayer _fully_connected_output_state;
193 NEActivationLayer _projection_clip;
Michalis Spyrouebcebf12020-10-21 00:04:14 +0100[diff] [blame]194 NECopy _copy_cell_state;
195 NECopy _copy_output;
Michalis Spyrou6eb73452020-07-02 17:39:25 +0100[diff] [blame]196 NEConcatenateLayer _concat_scratch_buffer;
197 NEConcatenateLayer _concat_inputs_forget_gate;
198 NEConcatenateLayer _concat_weights_forget_gate;
199 NEConcatenateLayer _concat_weights_input_gate;
200 NEConcatenateLayer _concat_weights_output;
201 NEMeanStdDevNormalizationLayer _mean_std_norm_input_gate;
202 NEPixelWiseMultiplication _pixelwise_mul_input_gate_coeff;
203 NEArithmeticAddition _accum_input_gate_bias;
204 NEMeanStdDevNormalizationLayer _mean_std_norm_forget_gate;
205 NEPixelWiseMultiplication _pixelwise_mul_forget_gate_coeff;
206 NEArithmeticAddition _accum_forget_gate_bias;
207 NEMeanStdDevNormalizationLayer _mean_std_norm_cell_gate;
208 NEPixelWiseMultiplication _pixelwise_mul_cell_gate_coeff;
209 NEArithmeticAddition _accum_cell_gate_bias;
210 NEMeanStdDevNormalizationLayer _mean_std_norm_output_gate;
211 NEPixelWiseMultiplication _pixelwise_mul_output_gate_coeff;
212 NEArithmeticAddition _accum_output_gate_bias;
213 Tensor _input_gate_out1;
214 Tensor _input_gate_out2;
215 Tensor _input_gate_out3;
216 Tensor _input_gate_out4;
217 Tensor _forget_gate_out1;
218 Tensor _forget_gate_out2;
219 Tensor _forget_gate_out3;
220 Tensor _forget_gate_out4;
221 Tensor _forget_gate_out5;
222 Tensor _forget_gate_out6;
223 Tensor _cell_state_out1;
224 Tensor _cell_state_out2;
225 Tensor _cell_state_out3;
226 Tensor _cell_state_out4;
227 Tensor _cell_state_out5;
228 Tensor _output1;
229 Tensor _output2;
230 Tensor _output3;
231 Tensor _output4;
232 Tensor _cell_state_activation;
233 Tensor _output_state1;
234 Tensor _ones;
235 Tensor _input_layer_norm_out1;
236 Tensor _input_layer_norm_out2;
237 Tensor _forget_layer_norm_out1;
238 Tensor _forget_layer_norm_out2;
239 Tensor _cell_layer_norm_out1;
240 Tensor _cell_layer_norm_out2;
241 Tensor _output_layer_norm_out1;
242 Tensor _output_layer_norm_out2;
243 bool _run_peephole_opt;
244 bool _run_cifg_opt;
245 bool _perform_cell_clipping;
246 bool _has_projection_weights;
247 bool _perform_projection_clipping;
248 bool _is_prepared;
249 bool _is_layer_norm_lstm;
Michalis Spyrou25f45a42018-08-08 12:53:05 +0100[diff] [blame]250};
251} // namespace arm_compute
Michalis Spyrouf4643372019-11-29 16:17:13 +0000[diff] [blame]252#endif /* ARM_COMPUTE_NELSTMLAYER_H */