| /* |
| * Copyright (c) 2018 ARM Limited. |
| * |
| * SPDX-License-Identifier: MIT |
| * |
| * Permission is hereby granted, free of charge, to any person obtaining a copy |
| * of this software and associated documentation files (the "Software"), to |
| * deal in the Software without restriction, including without limitation the |
| * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or |
| * sell copies of the Software, and to permit persons to whom the Software is |
| * furnished to do so, subject to the following conditions: |
| * |
| * The above copyright notice and this permission notice shall be included in all |
| * copies or substantial portions of the Software. |
| * |
| * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR |
| * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, |
| * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE |
| * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER |
| * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, |
| * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE |
| * SOFTWARE. |
| */ |
| #ifndef __ARM_COMPUTE_CLLSTMLAYER_H__ |
| #define __ARM_COMPUTE_CLLSTMLAYER_H__ |
| |
| #include "arm_compute/runtime/IFunction.h" |
| |
| #include "arm_compute/core/CL/kernels/CLActivationLayerKernel.h" |
| #include "arm_compute/core/CL/kernels/CLArithmeticAdditionKernel.h" |
| #include "arm_compute/core/CL/kernels/CLArithmeticSubtractionKernel.h" |
| #include "arm_compute/core/CL/kernels/CLCopyKernel.h" |
| #include "arm_compute/core/CL/kernels/CLPixelWiseMultiplicationKernel.h" |
| #include "arm_compute/core/Types.h" |
| #include "arm_compute/runtime/CL/CLMemoryGroup.h" |
| #include "arm_compute/runtime/CL/CLTensor.h" |
| #include "arm_compute/runtime/CL/functions/CLArithmeticAddition.h" |
| #include "arm_compute/runtime/CL/functions/CLFullyConnectedLayer.h" |
| #include "arm_compute/runtime/CL/functions/CLGEMM.h" |
| #include "arm_compute/runtime/CL/functions/CLWidthConcatenateLayer.h" |
| #include "arm_compute/runtime/IMemoryManager.h" |
| |
| #include <memory> |
| |
| namespace arm_compute |
| { |
| class ICLTensor; |
| |
| template <typename T> |
| class LSTMParams |
| { |
| public: |
| /** Constructor */ |
| LSTMParams() |
| : _input_to_input_weights(nullptr), _recurrent_to_input_weights(nullptr), _cell_to_input_weights(nullptr), _input_gate_bias(nullptr), _cell_to_forget_weights(nullptr), |
| _cell_to_output_weights(nullptr), _projection_weights(nullptr), _projection_bias(nullptr), _has_peephole_opt(false), _has_projection(false), _has_cifg_opt(true) |
| { |
| } |
| /** Prevent instances of this class from being copied (As this class contains pointers) */ |
| LSTMParams(const LSTMParams &) = delete; |
| /** Prevent instances of this class from being copied (As this class contains pointers) */ |
| LSTMParams &operator=(const LSTMParams &) = delete; |
| /** Default destructor */ |
| ~LSTMParams() = default; |
| /** Set CIFG tensor parameters. |
| * |
| * @param[in] input_to_input_weights 2D weights tensor with dimensions [input_size, num_units]. Data types supported: F16/F32. |
| * @param[in] recurrent_to_input_weights 2D weights tensor with dimensions [output_size, num_units]. Data type supported: Same as @p input_to_input_weights. |
| * @param[in] cell_to_input_weights 1D weights tensor with dimensions [num_units]. Can be nullptr. Data type supported: Same as @p input_to_input_weights. |
| * @param[in] input_gate_bias 1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input_to_input_weights |
| * |
| * @return Reference to this LSTMParams object |
| */ |
| LSTMParams &set_cifg_params(const T *input_to_input_weights, const T *recurrent_to_input_weights, const T *cell_to_input_weights, const T *input_gate_bias) |
| { |
| _input_to_input_weights = input_to_input_weights; |
| _recurrent_to_input_weights = recurrent_to_input_weights; |
| _cell_to_input_weights = cell_to_input_weights; |
| _input_gate_bias = input_gate_bias; |
| _has_cifg_opt = false; |
| return *this; |
| } |
| /** Set projection tensor parameters. |
| * |
| * @param[in] projection_weights 2D weights tensor with dimensions [output_size, num_units]. Data type supported: Data types supported: F16/F32. |
| * @param[in] projection_bias 1D weights tensor with dimensions [output_size]. Data type supported: Same as @p projection_weights. |
| * |
| * @return Reference to this LSTMParams object |
| */ |
| LSTMParams &set_projection_params(const T *projection_weights, const T *projection_bias) |
| { |
| _projection_weights = projection_weights; |
| _projection_bias = projection_bias; |
| _has_projection = true; |
| return *this; |
| } |
| /** Set peephole tensor parameters. |
| * |
| * @param[in] cell_to_input_weights 1D weights tensor with dimensions [num_units]. Data type supported: Data types supported: F16/F32. |
| * @param[in] cell_to_forget_weights 1D weights tensor with dimensions [num_units]. Data type supported: Same as @p cell_to_input_weights. |
| * @param[in] cell_to_output_weights 1D weights tensor with dimensions [num_units]. Data type supported: Same as @p cell_to_input_weights. |
| * |
| * @return Reference to this LSTMParams object |
| */ |
| LSTMParams &set_peephole_params(const T *cell_to_input_weights, const T *cell_to_forget_weights, const T *cell_to_output_weights) |
| { |
| _cell_to_input_weights = cell_to_input_weights; |
| _cell_to_forget_weights = cell_to_forget_weights; |
| _cell_to_output_weights = cell_to_output_weights; |
| _has_peephole_opt = true; |
| return *this; |
| } |
| |
| const T *input_to_input_weights() const |
| { |
| return _input_to_input_weights; |
| } |
| |
| const T *recurrent_to_input_weights() const |
| { |
| return _recurrent_to_input_weights; |
| } |
| |
| const T *cell_to_input_weights() const |
| { |
| return _cell_to_input_weights; |
| } |
| |
| const T *input_gate_bias() const |
| { |
| return _input_gate_bias; |
| } |
| |
| const T *cell_to_forget_weights() const |
| { |
| return _cell_to_forget_weights; |
| } |
| |
| const T *cell_to_output_weights() const |
| { |
| return _cell_to_output_weights; |
| } |
| |
| const T *projection_weights() const |
| { |
| return _projection_weights; |
| } |
| |
| const T *projection_bias() const |
| { |
| return _projection_bias; |
| } |
| |
| bool has_peephole_opt() const |
| { |
| return _has_peephole_opt; |
| } |
| |
| bool has_projection() const |
| { |
| return _has_projection; |
| } |
| |
| bool has_cifg_opt() const |
| { |
| return _has_cifg_opt; |
| } |
| |
| private: |
| const T *_input_to_input_weights; |
| const T *_recurrent_to_input_weights; |
| const T *_cell_to_input_weights; |
| const T *_input_gate_bias; |
| const T *_cell_to_forget_weights; |
| const T *_cell_to_output_weights; |
| const T *_projection_weights; |
| const T *_projection_bias; |
| bool _has_peephole_opt; |
| bool _has_projection; |
| bool _has_cifg_opt; |
| }; |
| |
| /** This function performs a single time step in a Long Short-Term Memory (LSTM) layer. |
| * |
| */ |
| class CLLSTMLayer : public IFunction |
| { |
| public: |
| /** Default constructor */ |
| CLLSTMLayer(std::shared_ptr<IMemoryManager> memory_manager = nullptr); |
| /** Initialize function's tensors. |
| * |
| * @param[in] input Source tensor. Input is a 2D tensor with dimensions [input_size, batch_size]. Data types supported: F16/F32. |
| * @param[in] input_to_forget_weights 2D weights tensor with dimensions [input_size, num_units]. Data type supported: Same as @p input. |
| * @param[in] input_to_cell_weights 2D weights tensor with dimensions [input_size, num_units]. Data type supported: Same as @p input. |
| * @param[in] input_to_output_weights 2D weights tensor with dimensions [input_size, num_units]. Data type supported: Same as @p input. |
| * @param[in] recurrent_to_forget_weights 2D weights tensor with dimensions [output_size, num_units]. Data type supported: Same as @p input. |
| * @param[in] recurrent_to_cell_weights 2D weights tensor with dimensions [output_size, num_units]. Data type supported: Same as @p input. |
| * @param[in] recurrent_to_output_weights 2D weights tensor with dimensions [output_size, num_units]. Data type supported: Same as @p input. |
| * @param[in] forget_gate_bias 1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input. |
| * @param[in] cell_bias 1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input. |
| * @param[in] output_gate_bias 1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input. |
| * @param[in, out] output_state 2D weights tensor with dimensions [output_size, batch_size]. Data type supported: Same as @p input. |
| * @param[in, out] cell_state 2D tensor with dimensions [num_units, batch_size]. Data type supported: Same as @p input. |
| * @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. |
| * @param[out] output Destination tensor. Output is a 2D tensor with dimensions [output_size, batch_size]. |
| * Data types supported: Same as @p input. |
| * @param[in] lstm_params (Optional) Weights tensors used in peephole optimization: |
| * input_to_input_weights 2D weights tensor with dimensions [input_size, num_units]. Data type supported: Same as @p input. |
| * recurrent_to_input_weights 2D weights tensor with dimensions [output_size, num_units]. Data type supported: Same as @p input. |
| * cell_to_input_weights 1D weights tensor with dimensions [num_units]. Can be nullptr. Data type supported: Same as @p input. |
| * cell_to_forget_weights 1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input. |
| * cell_to_output_weights 1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input. |
| * input_gate_bias 1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input |
| * projection_weights 2D weights tensor with dimensions [output_size, num_units]. Data type supported: Same as @p input. |
| * projection_bias 1D weights tensor with dimensions [output_size]. Data type supported: Same as @p input. |
| * @param[in] activation_info Contains activation information described in @ref ActivationLayerInfo. |
| * @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. |
| * @param[in] projection_threshold The clipping threshold for the output from the projection layer, such that values are bound within [-proj_clip, proj_clip]. If set to 0.0 then clipping is disabled. |
| */ |
| void configure(const ICLTensor *input, const ICLTensor *input_to_forget_weights, const ICLTensor *input_to_cell_weights, const ICLTensor *input_to_output_weights, |
| const ICLTensor *recurrent_to_forget_weights, const ICLTensor *recurrent_to_cell_weights, const ICLTensor *recurrent_to_output_weights, |
| const ICLTensor *forget_gate_bias, const ICLTensor *cell_bias, const ICLTensor *output_gate_bias, ICLTensor *output_state, ICLTensor *cell_state, ICLTensor *scratch_buffer, ICLTensor *output, |
| const LSTMParams<ICLTensor> &lstm_params, const ActivationLayerInfo &activation_info, float cell_threshold = 0.f, float projection_threshold = 0.f); |
| |
| /** Static function to check if given info will lead to a valid configuration of @ref CLLSTMLayer |
| * |
| * @param[in] input Source tensor info. Input is a 2D tensor info with dimensions [input_size, batch_size]. Data types supported: F16/F32. |
| * @param[in] input_to_forget_weights 2D weights tensor info with dimensions [input_size, num_units]. Data type supported: Same as @p input. |
| * @param[in] input_to_cell_weights 2D weights tensor info with dimensions [input_size, num_units]. Data type supported: Same as @p input. |
| * @param[in] input_to_output_weights 2D weights tensor info with dimensions [input_size, num_units]. Data type supported: Same as @p input. |
| * @param[in] recurrent_to_forget_weights 2D weights tensor info with dimensions [output_size, num_units]. Data type supported: Same as @p input. |
| * @param[in] recurrent_to_cell_weights 2D weights tensor info with dimensions [output_size, num_units]. Data type supported: Same as @p input. |
| * @param[in] recurrent_to_output_weights 2D weights tensor info with dimensions [output_size, num_units]. Data type supported: Same as @p input. |
| * @param[in] forget_gate_bias 1D weights tensor info with dimensions [num_units]. Data type supported: Same as @p input. |
| * @param[in] cell_bias 1D weights tensor info with dimensions [num_units]. Data type supported: Same as @p input. |
| * @param[in] output_gate_bias 1D weights tensor info with dimensions [num_units]. Data type supported: Same as @p input. |
| * @param[in] output_state 2D weights tensor info with dimensions [output_size, batch_size]. Data type supported: Same as @p input. |
| * @param[in] cell_state 2D tensor info with dimensions [num_units, batch_size]. Data type supported: Same as @p input. |
| * @param[in] scratch_buffer 2D tensor info with dimensions [num_units * 4, batch_size] with CIFG or [num_units * 3, batch_size] without CIGF. Data type supported: Same as @p input. |
| * @param[in] output Destination tensor info. Output is a 2D tensor with dimensions [output_size, batch_size]. |
| * Data types supported: Same as @p input. |
| * @param[in] lstm_params (Optional) Weights tensors used in peephole optimization: |
| * input_to_input_weights 2D weights tensor with dimensions [input_size, num_units]. Data type supported: Same as @p input. |
| * recurrent_to_input_weights 2D weights tensor with dimensions [output_size, num_units]. Data type supported: Same as @p input. |
| * cell_to_input_weights 1D weights tensor with dimensions [num_units]. Can be nullptr. Data type supported: Same as @p input. |
| * cell_to_forget_weights 1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input. |
| * cell_to_output_weights 1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input. |
| * input_gate_bias 1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input |
| * projection_weights 2D weights tensor with dimensions [output_size, num_units]. Data type supported: Same as @p input. |
| * projection_bias 1D weights tensor with dimensions [output_size]. Data type supported: Same as @p input. |
| * @param[in] activation_info Contains activation information described in @ref ActivationLayerInfo. |
| * @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. |
| * @param[in] projection_threshold The clipping threshold for the output from the projection layer, such that values are bound within [-proj_clip, proj_clip]. If set to 0.0 then clipping is disabled. |
| * |
| * @return a status |
| */ |
| static Status validate(const ITensorInfo *input, const ITensorInfo *input_to_forget_weights, const ITensorInfo *input_to_cell_weights, const ITensorInfo *input_to_output_weights, |
| const ITensorInfo *recurrent_to_forget_weights, const ITensorInfo *recurrent_to_cell_weights, const ITensorInfo *recurrent_to_output_weights, |
| const ITensorInfo *forget_gate_bias, const ITensorInfo *cell_bias, const ITensorInfo *output_gate_bias, |
| const ITensorInfo *output_state, const ITensorInfo *cell_state, const ITensorInfo *scratch_buffer, const ITensorInfo *output, |
| const LSTMParams<ITensorInfo> &lstm_params, const ActivationLayerInfo &activation_info, float cell_threshold = 0.f, float projection_threshold = 0.f); |
| |
| // Inherited methods overridden: |
| void run() override; |
| |
| private: |
| CLMemoryGroup _memory_group; |
| CLFullyConnectedLayer _fully_connected_input_gate; |
| CLGEMM _gemm_input_gate1; |
| CLGEMM _gemm_input_gate2; |
| CLTransposeKernel _transpose_input_gate1; |
| CLTransposeKernel _transpose_input_gate2; |
| CLArithmeticAdditionKernel _accum_input_gate1; |
| CLArithmeticAddition _accum_input_gate2; |
| CLArithmeticSubtractionKernel _subtract_input_gate; |
| CLActivationLayerKernel _activation_input_gate; |
| CLFullyConnectedLayer _fully_connected_forget_gate; |
| CLGEMM _gemm_forget_gate1; |
| CLGEMM _gemm_forget_gate2; |
| CLTransposeKernel _transpose_forget_gate1; |
| CLTransposeKernel _transpose_forget_gate2; |
| CLArithmeticAdditionKernel _accum_forget_gate1; |
| CLArithmeticAddition _accum_forget_gate2; |
| CLActivationLayerKernel _activation_forget_gate; |
| CLFullyConnectedLayer _fully_connected_cell_state; |
| CLGEMM _gemm_cell_state1; |
| CLGEMM _gemm_cell_state2; |
| CLTransposeKernel _transpose_cell_state1; |
| CLArithmeticAdditionKernel _accum_cell_state1; |
| CLArithmeticAdditionKernel _accum_cell_state2; |
| CLPixelWiseMultiplicationKernel _pixelwise_mul_cell_state1; |
| CLActivationLayerKernel _activation_cell_state; |
| CLActivationLayerKernel _cell_clip; |
| CLPixelWiseMultiplicationKernel _pixelwise_mul_cell_state2; |
| CLFullyConnectedLayer _fully_connected_output; |
| CLGEMM _gemm_output1; |
| CLGEMM _gemm_output2; |
| CLTransposeKernel _transpose_output1; |
| CLTransposeKernel _transpose_output2; |
| CLArithmeticAdditionKernel _accum_output1; |
| CLArithmeticAddition _accum_output2; |
| CLActivationLayerKernel _activation_output; |
| CLActivationLayerKernel _activation_output_state; |
| CLPixelWiseMultiplicationKernel _pixelwise_mul_output_state; |
| CLFullyConnectedLayer _fully_connected_output_state; |
| CLGEMM _gemm_output_state; |
| CLArithmeticAdditionKernel _accum_output_state; |
| CLActivationLayerKernel _projection_clip; |
| CLCopyKernel _copy_cell_state; |
| CLCopyKernel _copy_output; |
| CLWidthConcatenateLayer _concat_scratch_buffer; |
| CLTensor _input_gate_out1; |
| CLTensor _input_gate_out2; |
| CLTensor _input_gate_out3; |
| CLTensor _input_gate_out4; |
| CLTensor _input_gate_out5; |
| CLTensor _input_gate_out6; |
| CLTensor _forget_gate_out1; |
| CLTensor _forget_gate_out2; |
| CLTensor _forget_gate_out3; |
| CLTensor _forget_gate_out4; |
| CLTensor _forget_gate_out5; |
| CLTensor _forget_gate_out6; |
| CLTensor _cell_state_out1; |
| CLTensor _cell_state_out2; |
| CLTensor _cell_state_out3; |
| CLTensor _cell_state_out4; |
| CLTensor _cell_state_out5; |
| CLTensor _output1; |
| CLTensor _output2; |
| CLTensor _output3; |
| CLTensor _output4; |
| CLTensor _output5; |
| CLTensor _output6; |
| CLTensor _cell_state_activation; |
| CLTensor _output_projection1; |
| CLTensor _ones; |
| bool _run_peephole_opt; |
| bool _run_cifg_opt; |
| bool _perform_cell_clipping; |
| bool _has_projection_weights; |
| bool _perform_projection_clipping; |
| }; |
| } |
| #endif /* __ARM_COMPUTE_CLLSTMLAYER_H__ */ |