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review.mlplatform.org / ml / ComputeLibrary / d9eaf614975afad18fd13b9e8c7a7dd21ff6a1dd / . / arm_compute / runtime / CL / functions / CLLSTMLayer.h
blob: 2e44eed6f679a546403655616ac7ba98a50e7688 [file] [log] [blame]
Michalis Spyroubcedf512018-03-22 14:55:08 +0000[diff] [blame]1/*
Michele Di Giorgiod9eaf612020-07-08 11:12:57 +0100[diff] [blame^]2 * Copyright (c) 2018-2020 Arm Limited.
Michalis Spyroubcedf512018-03-22 14:55:08 +0000[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_CLLSTMLAYER_H
25#define ARM_COMPUTE_CLLSTMLAYER_H
Michalis Spyroubcedf512018-03-22 14:55:08 +0000[diff] [blame]26
27#include "arm_compute/runtime/IFunction.h"
28
Michalis Spyroubcedf512018-03-22 14:55:08 +0000[diff] [blame]29#include "arm_compute/core/CL/kernels/CLCopyKernel.h"
giuros01164a2722018-11-20 18:34:46 +0000[diff] [blame]30#include "arm_compute/core/CL/kernels/CLElementwiseOperationKernel.h"
Georgios Pinitasdbfc2dc2019-04-02 12:51:21 +0100[diff] [blame]31#include "arm_compute/core/CL/kernels/CLMemsetKernel.h"
Michalis Spyroubcedf512018-03-22 14:55:08 +0000[diff] [blame]32#include "arm_compute/core/CL/kernels/CLPixelWiseMultiplicationKernel.h"
John Kesapidescafec8f2019-02-19 15:53:59 +0000[diff] [blame]33#include "arm_compute/core/CL/kernels/CLWidthConcatenate2TensorsKernel.h"
Michalis Spyroubcedf512018-03-22 14:55:08 +0000[diff] [blame]34#include "arm_compute/core/Types.h"
Michalis Spyroubcedf512018-03-22 14:55:08 +0000[diff] [blame]35#include "arm_compute/runtime/CL/CLTensor.h"
Georgios Pinitasab23dd02020-07-06 14:57:36 +0100[diff] [blame]36#include "arm_compute/runtime/CL/functions/CLActivationLayer.h"
Georgios Pinitas09f24972019-05-17 18:14:40 +0100[diff] [blame]37#include "arm_compute/runtime/CL/functions/CLConcatenateLayer.h"
giuros01164a2722018-11-20 18:34:46 +0000[diff] [blame]38#include "arm_compute/runtime/CL/functions/CLElementwiseOperations.h"
Michalis Spyroubcedf512018-03-22 14:55:08 +0000[diff] [blame]39#include "arm_compute/runtime/CL/functions/CLFullyConnectedLayer.h"
40#include "arm_compute/runtime/CL/functions/CLGEMM.h"
Michele Di Giorgio39438b42019-06-04 12:41:45 +0100[diff] [blame]41#include "arm_compute/runtime/CL/functions/CLMeanStdDevNormalizationLayer.h"
Michalis Spyroubcedf512018-03-22 14:55:08 +0000[diff] [blame]42#include "arm_compute/runtime/IMemoryManager.h"
Georgios Pinitas26014cf2019-09-09 19:00:57 +0100[diff] [blame]43#include "arm_compute/runtime/MemoryGroup.h"
Michalis Spyrou25f45a42018-08-08 12:53:05 +0100[diff] [blame]44#include "arm_compute/runtime/common/LSTMParams.h"
Michalis Spyroubcedf512018-03-22 14:55:08 +0000[diff] [blame]45
46#include <memory>
47
48namespace arm_compute
49{
50class ICLTensor;
51
Michalis Spyroubcedf512018-03-22 14:55:08 +0000[diff] [blame]52/** This function performs a single time step in a Long Short-Term Memory (LSTM) layer.
53 *
54 */
55class CLLSTMLayer : public IFunction
56{
57public:
58 /** Default constructor */
59 CLLSTMLayer(std::shared_ptr<IMemoryManager> memory_manager = nullptr);
60 /** Initialize function's tensors.
61 *
Georgios Pinitas8bc745d2018-07-18 19:51:24 +0100[diff] [blame]62 * @param[in] input Source tensor. Input is a 2D tensor with dimensions [input_size, batch_size]. Data types supported: F16/F32.
63 * @param[in] input_to_forget_weights 2D weights tensor with dimensions [input_size, num_units]. Data type supported: Same as @p input.
64 * @param[in] input_to_cell_weights 2D weights tensor with dimensions [input_size, num_units]. Data type supported: Same as @p input.
65 * @param[in] input_to_output_weights 2D weights tensor with dimensions [input_size, num_units]. Data type supported: Same as @p input.
66 * @param[in] recurrent_to_forget_weights 2D weights tensor with dimensions [output_size, num_units]. Data type supported: Same as @p input.
67 * @param[in] recurrent_to_cell_weights 2D weights tensor with dimensions [output_size, num_units]. Data type supported: Same as @p input.
68 * @param[in] recurrent_to_output_weights 2D weights tensor with dimensions [output_size, num_units]. Data type supported: Same as @p input.
69 * @param[in] forget_gate_bias 1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input.
70 * @param[in] cell_bias 1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input.
71 * @param[in] output_gate_bias 1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input.
72 * @param[in] output_state_in 2D weights tensor with dimensions [output_size, batch_size]. Data type supported: Same as @p input.
73 * @param[in] cell_state_in 2D tensor with dimensions [num_units, batch_size]. Data type supported: Same as @p input.
74 * @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.
75 * @param[out] output_state_out 2D weights tensor with dimensions [output_size, batch_size]. Data type supported: Same as @p input.
76 * @param[out] cell_state_out 2D tensor with dimensions [num_units, batch_size]. Data type supported: Same as @p input.
77 * @param[out] output Destination tensor. Output is a 2D tensor with dimensions [output_size, batch_size].
78 * Data types supported: Same as @p input.
Michele Di Giorgio25d97752020-03-04 18:08:47 +0000[diff] [blame]79 * @param[in] lstm_params Weights tensors used in peephole optimization:
80 * input_to_input_weights 2D weights tensor with dimensions [input_size, num_units]. Data type supported: Same as @p input.
81 * recurrent_to_input_weights 2D weights tensor with dimensions [output_size, num_units]. Data type supported: Same as @p input.
82 * cell_to_input_weights 1D weights tensor with dimensions [num_units]. Can be nullptr. Data type supported: Same as @p input.
83 * cell_to_forget_weights 1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input.
84 * cell_to_output_weights 1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input.
85 * input_gate_bias 1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input
86 * projection_weights 2D weights tensor with dimensions [output_size, num_units]. Data type supported: Same as @p input.
87 * projection_bias 1D weights tensor with dimensions [output_size]. Data type supported: Same as @p input.
88 * input_layer_norm_weights 1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input.
89 * forget_layer_norm_weights 1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input.
90 * cell_layer_norm_weights 1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input.
91 * output_layer_norm_weights 1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input.
Georgios Pinitas8bc745d2018-07-18 19:51:24 +0100[diff] [blame]92 * @param[in] activation_info Contains activation information described in @ref ActivationLayerInfo.
Michele Di Giorgio25d97752020-03-04 18:08:47 +0000[diff] [blame]93 * @param[in] cell_threshold (Optional) The clipping threshold for the cell state, such that values are bound within [-cell_clip, cell_clip].
94 * If set to 0.0f then clipping is disabled.
95 * @param[in] projection_threshold (Optional) The clipping threshold for the output from the projection layer, such that values are bound within [-proj_clip, proj_clip].
Michele Di Giorgio39438b42019-06-04 12:41:45 +0100[diff] [blame]96 * If set to 0.0f then clipping is disabled.
Michalis Spyroubcedf512018-03-22 14:55:08 +0000[diff] [blame]97 */
Georgios Pinitas8bc745d2018-07-18 19:51:24 +0100[diff] [blame]98 void configure(const ICLTensor *input,
99 const ICLTensor *input_to_forget_weights, const ICLTensor *input_to_cell_weights, const ICLTensor *input_to_output_weights,
Michalis Spyroubcedf512018-03-22 14:55:08 +0000[diff] [blame]100 const ICLTensor *recurrent_to_forget_weights, const ICLTensor *recurrent_to_cell_weights, const ICLTensor *recurrent_to_output_weights,
Georgios Pinitas8bc745d2018-07-18 19:51:24 +0100[diff] [blame]101 const ICLTensor *forget_gate_bias, const ICLTensor *cell_bias, const ICLTensor *output_gate_bias,
102 const ICLTensor *output_state_in, const ICLTensor *cell_state_in,
103 ICLTensor *scratch_buffer, ICLTensor *output_state_out, ICLTensor *cell_state_out, ICLTensor *output,
Michalis Spyroubcedf512018-03-22 14:55:08 +0000[diff] [blame]104 const LSTMParams<ICLTensor> &lstm_params, const ActivationLayerInfo &activation_info, float cell_threshold = 0.f, float projection_threshold = 0.f);
Manuel Bottini2b84be52020-04-08 10:15:51 +0100[diff] [blame]105 /** Initialize function's tensors.
106 *
107 * @param[in] compile_context The compile context to be used.
108 * @param[in] input Source tensor. Input is a 2D tensor with dimensions [input_size, batch_size]. Data types supported: F16/F32.
109 * @param[in] input_to_forget_weights 2D weights tensor with dimensions [input_size, num_units]. Data type supported: Same as @p input.
110 * @param[in] input_to_cell_weights 2D weights tensor with dimensions [input_size, num_units]. Data type supported: Same as @p input.
111 * @param[in] input_to_output_weights 2D weights tensor with dimensions [input_size, num_units]. Data type supported: Same as @p input.
112 * @param[in] recurrent_to_forget_weights 2D weights tensor with dimensions [output_size, num_units]. Data type supported: Same as @p input.
113 * @param[in] recurrent_to_cell_weights 2D weights tensor with dimensions [output_size, num_units]. Data type supported: Same as @p input.
114 * @param[in] recurrent_to_output_weights 2D weights tensor with dimensions [output_size, num_units]. Data type supported: Same as @p input.
115 * @param[in] forget_gate_bias 1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input.
116 * @param[in] cell_bias 1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input.
117 * @param[in] output_gate_bias 1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input.
118 * @param[in] output_state_in 2D weights tensor with dimensions [output_size, batch_size]. Data type supported: Same as @p input.
119 * @param[in] cell_state_in 2D tensor with dimensions [num_units, batch_size]. Data type supported: Same as @p input.
120 * @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.
121 * @param[out] output_state_out 2D weights tensor with dimensions [output_size, batch_size]. Data type supported: Same as @p input.
122 * @param[out] cell_state_out 2D tensor with dimensions [num_units, batch_size]. Data type supported: Same as @p input.
123 * @param[out] output Destination tensor. Output is a 2D tensor with dimensions [output_size, batch_size].
124 * Data types supported: Same as @p input.
125 * @param[in] lstm_params Weights tensors used in peephole optimization:
126 * input_to_input_weights 2D weights tensor with dimensions [input_size, num_units]. Data type supported: Same as @p input.
127 * recurrent_to_input_weights 2D weights tensor with dimensions [output_size, num_units]. Data type supported: Same as @p input.
128 * cell_to_input_weights 1D weights tensor with dimensions [num_units]. Can be nullptr. Data type supported: Same as @p input.
129 * cell_to_forget_weights 1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input.
130 * cell_to_output_weights 1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input.
131 * input_gate_bias 1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input
132 * projection_weights 2D weights tensor with dimensions [output_size, num_units]. Data type supported: Same as @p input.
133 * projection_bias 1D weights tensor with dimensions [output_size]. Data type supported: Same as @p input.
134 * input_layer_norm_weights 1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input.
135 * forget_layer_norm_weights 1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input.
136 * cell_layer_norm_weights 1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input.
137 * output_layer_norm_weights 1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input.
138 * @param[in] activation_info Contains activation information described in @ref ActivationLayerInfo.
139 * @param[in] cell_threshold (Optional) The clipping threshold for the cell state, such that values are bound within [-cell_clip, cell_clip].
140 * If set to 0.0f then clipping is disabled.
141 * @param[in] projection_threshold (Optional) The clipping threshold for the output from the projection layer, such that values are bound within [-proj_clip, proj_clip].
142 * If set to 0.0f then clipping is disabled.
143 */
144 void configure(const CLCompileContext &compile_context, const ICLTensor *input,
145 const ICLTensor *input_to_forget_weights, const ICLTensor *input_to_cell_weights, const ICLTensor *input_to_output_weights,
146 const ICLTensor *recurrent_to_forget_weights, const ICLTensor *recurrent_to_cell_weights, const ICLTensor *recurrent_to_output_weights,
147 const ICLTensor *forget_gate_bias, const ICLTensor *cell_bias, const ICLTensor *output_gate_bias,
148 const ICLTensor *output_state_in, const ICLTensor *cell_state_in,
149 ICLTensor *scratch_buffer, ICLTensor *output_state_out, ICLTensor *cell_state_out, ICLTensor *output,
150 const LSTMParams<ICLTensor> &lstm_params, const ActivationLayerInfo &activation_info, float cell_threshold = 0.f, float projection_threshold = 0.f);
Michalis Spyroubcedf512018-03-22 14:55:08 +0000[diff] [blame]151
152 /** Static function to check if given info will lead to a valid configuration of @ref CLLSTMLayer
153 *
Michele Di Giorgio39438b42019-06-04 12:41:45 +0100[diff] [blame]154 * @param[in] input Source tensor info. Input is a 2D tensor with dimensions [input_size, batch_size]. Data types supported: F16/F32.
155 * @param[in] input_to_forget_weights 2D weights tensor info with dimensions [input_size, num_units]. Data type supported: Same as @p input.
156 * @param[in] input_to_cell_weights 2D weights tensor info with dimensions [input_size, num_units]. Data type supported: Same as @p input.
157 * @param[in] input_to_output_weights 2D weights tensor info with dimensions [input_size, num_units]. Data type supported: Same as @p input.
158 * @param[in] recurrent_to_forget_weights 2D weights tensor info with dimensions [output_size, num_units]. Data type supported: Same as @p input.
159 * @param[in] recurrent_to_cell_weights 2D weights tensor info with dimensions [output_size, num_units]. Data type supported: Same as @p input.
160 * @param[in] recurrent_to_output_weights 2D weights tensor info with dimensions [output_size, num_units]. Data type supported: Same as @p input.
161 * @param[in] forget_gate_bias 1D weights tensor info with dimensions [num_units]. Data type supported: Same as @p input.
162 * @param[in] cell_bias 1D weights tensor info with dimensions [num_units]. Data type supported: Same as @p input.
163 * @param[in] output_gate_bias 1D weights tensor info with dimensions [num_units]. Data type supported: Same as @p input.
164 * @param[in] output_state_in 2D weights tensor info with dimensions [output_size, batch_size]. Data type supported: Same as @p input.
165 * @param[in] cell_state_in 2D tensor info with dimensions [num_units, batch_size]. Data type supported: Same as @p input.
166 * @param[in] scratch_buffer 2D tensor info with dimensions [num_units * 4, batch_size] with CIFG or [num_units * 3, batch_size] without CIGF.
167 * Data type supported: Same as @p input.
168 * @param[in] output_state_out 2D weights tensor info with dimensions [output_size, batch_size]. Data type supported: Same as @p input.
169 * @param[in] cell_state_out 2D tensor info with dimensions [num_units, batch_size]. Data type supported: Same as @p input.
170 * @param[in] output Destination tensor info. Output is a 2D tensor with dimensions [output_size, batch_size]. Data types supported: Same as @p input.
Michele Di Giorgio25d97752020-03-04 18:08:47 +0000[diff] [blame]171 * @param[in] lstm_params Weights tensors info used in peephole optimization:
172 * input_to_input_weights 2D weights tensor info with dimensions [input_size, num_units]. Data type supported: Same as @p input.
173 * recurrent_to_input_weights 2D weights tensor info with dimensions [output_size, num_units]. Data type supported: Same as @p input.
174 * cell_to_input_weights 1D weights tensor info with dimensions [num_units]. Can be nullptr. Data type supported: Same as @p input.
175 * cell_to_forget_weights 1D weights tensor info with dimensions [num_units]. Data type supported: Same as @p input.
176 * cell_to_output_weights 1D weights tensor info with dimensions [num_units]. Data type supported: Same as @p input.
177 * input_gate_bias 1D weights tensor info with dimensions [num_units]. Data type supported: Same as @p input
178 * projection_weights 2D weights tensor info with dimensions [output_size, num_units]. Data type supported: Same as @p input.
179 * projection_bias 1D weights tensor info with dimensions [output_size]. Data type supported: Same as @p input.
180 * input_layer_norm_weights 1D weights tensor info with dimensions [num_units]. Data type supported: Same as @p input.
181 * forget_layer_norm_weights 1D weights tensor info with dimensions [num_units]. Data type supported: Same as @p input.
182 * cell_layer_norm_weights 1D weights tensor info with dimensions [num_units]. Data type supported: Same as @p input.
183 * output_layer_norm_weights 1D weights tensor info with dimensions [num_units]. Data type supported: Same as @p input.
Michalis Spyroubcedf512018-03-22 14:55:08 +0000[diff] [blame]184 * @param[in] activation_info Contains activation information described in @ref ActivationLayerInfo.
Michele Di Giorgio25d97752020-03-04 18:08:47 +0000[diff] [blame]185 * @param[in] cell_threshold (Optional) The clipping threshold for the cell state, such that values are bound within [-cell_clip, cell_clip].
186 * If set to 0.0f then clipping is disabled.
187 * @param[in] projection_threshold (Optional) The clipping threshold for the output from the projection layer, such that values are bound within [-proj_clip, proj_clip].
Michele Di Giorgio39438b42019-06-04 12:41:45 +0100[diff] [blame]188 * If set to 0.0f then clipping is disabled.
Michalis Spyroubcedf512018-03-22 14:55:08 +0000[diff] [blame]189 *
190 * @return a status
191 */
Georgios Pinitas8bc745d2018-07-18 19:51:24 +0100[diff] [blame]192 static Status validate(const ITensorInfo *input,
193 const ITensorInfo *input_to_forget_weights, const ITensorInfo *input_to_cell_weights, const ITensorInfo *input_to_output_weights,
Michalis Spyroubcedf512018-03-22 14:55:08 +0000[diff] [blame]194 const ITensorInfo *recurrent_to_forget_weights, const ITensorInfo *recurrent_to_cell_weights, const ITensorInfo *recurrent_to_output_weights,
195 const ITensorInfo *forget_gate_bias, const ITensorInfo *cell_bias, const ITensorInfo *output_gate_bias,
Georgios Pinitas8bc745d2018-07-18 19:51:24 +0100[diff] [blame]196 const ITensorInfo *output_state_in, const ITensorInfo *cell_state_in,
197 const ITensorInfo *scratch_buffer, const ITensorInfo *output_state_out, const ITensorInfo *cell_state_out, const ITensorInfo *output,
Michalis Spyroubcedf512018-03-22 14:55:08 +0000[diff] [blame]198 const LSTMParams<ITensorInfo> &lstm_params, const ActivationLayerInfo &activation_info, float cell_threshold = 0.f, float projection_threshold = 0.f);
199
200 // Inherited methods overridden:
201 void run() override;
John Kesapidescafec8f2019-02-19 15:53:59 +0000[diff] [blame]202 void prepare() override;
Michalis Spyroubcedf512018-03-22 14:55:08 +0000[diff] [blame]203
204private:
Georgios Pinitas26014cf2019-09-09 19:00:57 +0100[diff] [blame]205 MemoryGroup _memory_group;
giuros01164a2722018-11-20 18:34:46 +0000[diff] [blame]206 CLFullyConnectedLayer _fully_connected_input_gate;
Michele Di Giorgio39438b42019-06-04 12:41:45 +0100[diff] [blame]207 CLArithmeticAddition _accum_input_gate1;
giuros01164a2722018-11-20 18:34:46 +0000[diff] [blame]208 CLSaturatedArithmeticOperationKernel _subtract_input_gate;
209 CLPixelWiseMultiplicationKernel _pixelwise_mul_input_gate;
Georgios Pinitasab23dd02020-07-06 14:57:36 +0100[diff] [blame]210 CLActivationLayer _activation_input_gate;
giuros01164a2722018-11-20 18:34:46 +0000[diff] [blame]211 CLFullyConnectedLayer _fully_connected_forget_gate;
Michele Di Giorgio39438b42019-06-04 12:41:45 +0100[diff] [blame]212 CLArithmeticAddition _accum_forget_gate1;
giuros01164a2722018-11-20 18:34:46 +0000[diff] [blame]213 CLPixelWiseMultiplicationKernel _pixelwise_mul_forget_gate;
Georgios Pinitasab23dd02020-07-06 14:57:36 +0100[diff] [blame]214 CLActivationLayer _activation_forget_gate;
giuros01164a2722018-11-20 18:34:46 +0000[diff] [blame]215 CLFullyConnectedLayer _fully_connected_cell_state;
216 CLGEMM _gemm_cell_state1;
giuros01164a2722018-11-20 18:34:46 +0000[diff] [blame]217 CLTransposeKernel _transpose_cell_state;
218 CLSaturatedArithmeticOperationKernel _accum_cell_state1;
219 CLSaturatedArithmeticOperationKernel _accum_cell_state2;
220 CLPixelWiseMultiplicationKernel _pixelwise_mul_cell_state1;
Georgios Pinitasab23dd02020-07-06 14:57:36 +0100[diff] [blame]221 CLActivationLayer _activation_cell_state;
222 CLActivationLayer _cell_clip;
giuros01164a2722018-11-20 18:34:46 +0000[diff] [blame]223 CLPixelWiseMultiplicationKernel _pixelwise_mul_cell_state2;
224 CLFullyConnectedLayer _fully_connected_output;
giuros01164a2722018-11-20 18:34:46 +0000[diff] [blame]225 CLPixelWiseMultiplicationKernel _pixelwise_mul_output_state1;
Michele Di Giorgio39438b42019-06-04 12:41:45 +0100[diff] [blame]226 CLArithmeticAddition _accum_output1;
Georgios Pinitasab23dd02020-07-06 14:57:36 +0100[diff] [blame]227 CLActivationLayer _activation_output;
228 CLActivationLayer _activation_output_state;
giuros01164a2722018-11-20 18:34:46 +0000[diff] [blame]229 CLPixelWiseMultiplicationKernel _pixelwise_mul_output_state2;
230 CLFullyConnectedLayer _fully_connected_output_state;
Georgios Pinitasab23dd02020-07-06 14:57:36 +0100[diff] [blame]231 CLActivationLayer _projection_clip;
giuros01164a2722018-11-20 18:34:46 +0000[diff] [blame]232 CLCopyKernel _copy_cell_state;
233 CLCopyKernel _copy_output;
Georgios Pinitas09f24972019-05-17 18:14:40 +0100[diff] [blame]234 CLConcatenateLayer _concat_scratch_buffer;
John Kesapidescafec8f2019-02-19 15:53:59 +0000[diff] [blame]235 CLWidthConcatenate2TensorsKernel _concat_inputs_forget_gate;
236 CLWidthConcatenate2TensorsKernel _concat_weights_forget_gate;
237 CLWidthConcatenate2TensorsKernel _concat_weights_input_gate;
238 CLWidthConcatenate2TensorsKernel _concat_weights_output;
Georgios Pinitasdbfc2dc2019-04-02 12:51:21 +0100[diff] [blame]239 CLMemsetKernel _ones_memset_kernel;
Michele Di Giorgio39438b42019-06-04 12:41:45 +0100[diff] [blame]240 CLMeanStdDevNormalizationLayer _mean_std_norm_input_gate;
241 CLPixelWiseMultiplicationKernel _pixelwise_mul_input_gate_coeff;
242 CLSaturatedArithmeticOperationKernel _accum_input_gate_bias;
243 CLMeanStdDevNormalizationLayer _mean_std_norm_forget_gate;
244 CLPixelWiseMultiplicationKernel _pixelwise_mul_forget_gate_coeff;
245 CLSaturatedArithmeticOperationKernel _accum_forget_gate_bias;
246 CLMeanStdDevNormalizationLayer _mean_std_norm_cell_gate;
247 CLPixelWiseMultiplicationKernel _pixelwise_mul_cell_gate_coeff;
248 CLSaturatedArithmeticOperationKernel _accum_cell_gate_bias;
249 CLMeanStdDevNormalizationLayer _mean_std_norm_output_gate;
250 CLPixelWiseMultiplicationKernel _pixelwise_mul_output_gate_coeff;
251 CLSaturatedArithmeticOperationKernel _accum_output_gate_bias;
giuros01164a2722018-11-20 18:34:46 +0000[diff] [blame]252 CLTensor _input_gate_out1;
253 CLTensor _input_gate_out2;
254 CLTensor _input_gate_out3;
255 CLTensor _input_gate_out4;
giuros01164a2722018-11-20 18:34:46 +0000[diff] [blame]256 CLTensor _forget_gate_out1;
257 CLTensor _forget_gate_out2;
258 CLTensor _forget_gate_out3;
259 CLTensor _forget_gate_out4;
260 CLTensor _forget_gate_out5;
John Kesapidescafec8f2019-02-19 15:53:59 +0000[diff] [blame]261 CLTensor _forget_gate_out6;
giuros01164a2722018-11-20 18:34:46 +0000[diff] [blame]262 CLTensor _cell_state_out1;
263 CLTensor _cell_state_out2;
264 CLTensor _cell_state_out3;
265 CLTensor _cell_state_out4;
266 CLTensor _cell_state_out5;
267 CLTensor _output1;
268 CLTensor _output2;
269 CLTensor _output3;
270 CLTensor _output4;
giuros01164a2722018-11-20 18:34:46 +0000[diff] [blame]271 CLTensor _cell_state_activation;
272 CLTensor _output_state1;
273 CLTensor _ones;
Michele Di Giorgio39438b42019-06-04 12:41:45 +0100[diff] [blame]274 CLTensor _input_layer_norm_out1;
275 CLTensor _input_layer_norm_out2;
276 CLTensor _forget_layer_norm_out1;
277 CLTensor _forget_layer_norm_out2;
278 CLTensor _cell_layer_norm_out1;
279 CLTensor _cell_layer_norm_out2;
280 CLTensor _output_layer_norm_out1;
281 CLTensor _output_layer_norm_out2;
giuros01164a2722018-11-20 18:34:46 +0000[diff] [blame]282 bool _run_peephole_opt;
283 bool _run_cifg_opt;
284 bool _perform_cell_clipping;
285 bool _has_projection_weights;
286 bool _perform_projection_clipping;
John Kesapidescafec8f2019-02-19 15:53:59 +0000[diff] [blame]287 bool _is_prepared;
Michele Di Giorgio39438b42019-06-04 12:41:45 +0100[diff] [blame]288 bool _is_layer_norm_lstm;
Michalis Spyroubcedf512018-03-22 14:55:08 +0000[diff] [blame]289};
John Kesapidescafec8f2019-02-19 15:53:59 +0000[diff] [blame]290} // namespace arm_compute
Michalis Spyrouf4643372019-11-29 16:17:13 +0000[diff] [blame]291#endif /* ARM_COMPUTE_CLLSTMLAYER_H */