From bcedf513938fca9e33331bdef975f0488288bad4 Mon Sep 17 00:00:00 2001 From: Michalis Spyrou Date: Thu, 22 Mar 2018 14:55:08 +0000 Subject: COMPMID-993 Implement CL LSTM function Change-Id: Iee4ad387c41dd8ccfe31b3044d797f2d7448e552 Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/126655 Tested-by: Jenkins Reviewed-by: Anthony Barbier --- arm_compute/runtime/CL/functions/CLLSTMLayer.h | 346 +++++++++++++++++++++++++ 1 file changed, 346 insertions(+) create mode 100644 arm_compute/runtime/CL/functions/CLLSTMLayer.h (limited to 'arm_compute/runtime/CL/functions/CLLSTMLayer.h') diff --git a/arm_compute/runtime/CL/functions/CLLSTMLayer.h b/arm_compute/runtime/CL/functions/CLLSTMLayer.h new file mode 100644 index 0000000000..cf47f34290 --- /dev/null +++ b/arm_compute/runtime/CL/functions/CLLSTMLayer.h @@ -0,0 +1,346 @@ +/* + * 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 + +namespace arm_compute +{ +class ICLTensor; + +template +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 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 &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 &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__ */ -- cgit v1.2.1