From 25f45a4a0158a709d28a5207a867a9b5ce390621 Mon Sep 17 00:00:00 2001 From: Michalis Spyrou Date: Wed, 8 Aug 2018 12:53:05 +0100 Subject: COMPMID-1060 LSTM FP32 NEON Change-Id: I0bdf874e61917903c26f713ec41a7ffc29e07233 Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/143892 Tested-by: Jenkins Reviewed-by: Georgios Pinitas --- arm_compute/runtime/NEON/functions/NELSTMLayer.h | 210 +++++++++++++++++++++++ 1 file changed, 210 insertions(+) create mode 100644 arm_compute/runtime/NEON/functions/NELSTMLayer.h (limited to 'arm_compute/runtime/NEON/functions/NELSTMLayer.h') diff --git a/arm_compute/runtime/NEON/functions/NELSTMLayer.h b/arm_compute/runtime/NEON/functions/NELSTMLayer.h new file mode 100644 index 0000000000..9c4ab2b068 --- /dev/null +++ b/arm_compute/runtime/NEON/functions/NELSTMLayer.h @@ -0,0 +1,210 @@ +/* + * 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_NELSTMLAYER_H__ +#define __ARM_COMPUTE_NELSTMLAYER_H__ + +#include "arm_compute/core/NEON/kernels/NEActivationLayerKernel.h" +#include "arm_compute/core/NEON/kernels/NEArithmeticAdditionKernel.h" +#include "arm_compute/core/NEON/kernels/NEArithmeticSubtractionKernel.h" +#include "arm_compute/core/NEON/kernels/NECopyKernel.h" +#include "arm_compute/core/NEON/kernels/NEPixelWiseMultiplicationKernel.h" + +#include "arm_compute/core/Types.h" +#include "arm_compute/runtime/NEON/INESimpleFunction.h" +#include "arm_compute/runtime/NEON/functions/NEArithmeticAddition.h" +#include "arm_compute/runtime/NEON/functions/NEFullyConnectedLayer.h" +#include "arm_compute/runtime/NEON/functions/NEGEMM.h" +#include "arm_compute/runtime/NEON/functions/NEWidthConcatenateLayer.h" +#include "arm_compute/runtime/common/LSTMParams.h" + +namespace arm_compute +{ +// Forward declarations +class ITensor; + +/** Basic function to run @ref NELSTMLayer */ +class NELSTMLayer : public IFunction +{ +public: + /** Default constructor */ + NELSTMLayer(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] output_state_in 2D weights tensor with dimensions [output_size, batch_size]. Data type supported: Same as @p input. + * @param[in] cell_state_in 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_state_out 2D weights tensor with dimensions [output_size, batch_size]. Data type supported: Same as @p input. + * @param[out] cell_state_out 2D tensor with dimensions [num_units, batch_size]. 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 ITensor *input, + const ITensor *input_to_forget_weights, const ITensor *input_to_cell_weights, const ITensor *input_to_output_weights, + const ITensor *recurrent_to_forget_weights, const ITensor *recurrent_to_cell_weights, const ITensor *recurrent_to_output_weights, + const ITensor *forget_gate_bias, const ITensor *cell_bias, const ITensor *output_gate_bias, + const ITensor *output_state_in, const ITensor *cell_state_in, + ITensor *scratch_buffer, ITensor *output_state_out, ITensor *cell_state_out, ITensor *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 NELSTMLayer + * + * @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] output_state_in 2D weights tensor with dimensions [output_size, batch_size]. Data type supported: Same as @p input. + * @param[in] cell_state_in 2D tensor with dimensions [num_units, batch_size]. Data type supported: Same as @p input. + * @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. + * @param[in] output_state_out 2D weights tensor with dimensions [output_size, batch_size]. Data type supported: Same as @p input. + * @param[in] cell_state_out 2D tensor with dimensions [num_units, batch_size]. Data type supported: Same as @p input. + * @param[in] 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. + * + * @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_in, const ITensorInfo *cell_state_in, + const ITensorInfo *scratch_buffer, const ITensorInfo *output_state_out, const ITensorInfo *cell_state_out, 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: + MemoryGroup _memory_group; + NEFullyConnectedLayer _fully_connected_input_gate; + NEGEMM _gemm_input_gate; + NETransposeKernel _transpose_input_gate; + NEArithmeticAdditionKernel _accum_input_gate1; + NEArithmeticAddition _accum_input_gate2; + NEArithmeticSubtractionKernel _subtract_input_gate; + NEPixelWiseMultiplicationKernel _pixelwise_mul_input_gate; + NEActivationLayerKernel _activation_input_gate; + NEFullyConnectedLayer _fully_connected_forget_gate; + NEGEMM _gemm_forget_gate; + NETransposeKernel _transpose_forget_gate; + NEArithmeticAdditionKernel _accum_forget_gate1; + NEArithmeticAddition _accum_forget_gate2; + NEPixelWiseMultiplicationKernel _pixelwise_mul_forget_gate; + NEActivationLayerKernel _activation_forget_gate; + NEFullyConnectedLayer _fully_connected_cell_state; + NEGEMM _gemm_cell_state1; + NEGEMM _gemm_cell_state2; + NETransposeKernel _transpose_cell_state; + NEArithmeticAdditionKernel _accum_cell_state1; + NEArithmeticAdditionKernel _accum_cell_state2; + NEPixelWiseMultiplicationKernel _pixelwise_mul_cell_state1; + NEActivationLayerKernel _activation_cell_state; + NEActivationLayerKernel _cell_clip; + NEPixelWiseMultiplicationKernel _pixelwise_mul_cell_state2; + NEFullyConnectedLayer _fully_connected_output; + NEGEMM _gemm_output; + NEPixelWiseMultiplicationKernel _pixelwise_mul_output_state1; + NETransposeKernel _transpose_output; + NEArithmeticAdditionKernel _accum_output1; + NEArithmeticAddition _accum_output2; + NEActivationLayerKernel _activation_output; + NEActivationLayerKernel _activation_output_state; + NEPixelWiseMultiplicationKernel _pixelwise_mul_output_state2; + NEFullyConnectedLayer _fully_connected_output_state; + NEGEMM _gemm_output_state; + NEArithmeticAdditionKernel _accum_output_state; + NEActivationLayerKernel _projection_clip; + NECopyKernel _copy_cell_state; + NECopyKernel _copy_output; + NEWidthConcatenateLayer _concat_scratch_buffer; + Tensor _input_gate_out1; + Tensor _input_gate_out2; + Tensor _input_gate_out3; + Tensor _input_gate_out4; + Tensor _input_gate_out5; + Tensor _forget_gate_out1; + Tensor _forget_gate_out2; + Tensor _forget_gate_out3; + Tensor _forget_gate_out4; + Tensor _forget_gate_out5; + Tensor _cell_state_out1; + Tensor _cell_state_out2; + Tensor _cell_state_out3; + Tensor _cell_state_out4; + Tensor _cell_state_out5; + Tensor _output1; + Tensor _output2; + Tensor _output3; + Tensor _output4; + Tensor _output5; + Tensor _cell_state_activation; + Tensor _output_state1; + Tensor _ones; + bool _run_peephole_opt; + bool _run_cifg_opt; + bool _perform_cell_clipping; + bool _has_projection_weights; + bool _perform_projection_clipping; +}; +} // namespace arm_compute +#endif /* __ARM_COMPUTE_NELSTMLAYER_H__ */ -- cgit v1.2.1