From 39438b427b293c6d2e7066c68d3c3d3cb6d98a15 Mon Sep 17 00:00:00 2001 From: Michele Di Giorgio Date: Tue, 4 Jun 2019 12:41:45 +0100 Subject: COMPMID-2342: Add layer normalization support in CLLSTMLayer Change-Id: I25d974aa94e69c5f79a0bd99d5869a351d6d954d Signed-off-by: Michele Di Giorgio Reviewed-on: https://review.mlplatform.org/c/1324 Reviewed-by: Manuel Bottini Comments-Addressed: Arm Jenkins Tested-by: Arm Jenkins Reviewed-by: Michalis Spyrou --- arm_compute/runtime/CL/functions/CLLSTMLayer.h | 126 ++++++++++++++----------- arm_compute/runtime/common/LSTMParams.h | 54 ++++++++++- 2 files changed, 125 insertions(+), 55 deletions(-) (limited to 'arm_compute/runtime') diff --git a/arm_compute/runtime/CL/functions/CLLSTMLayer.h b/arm_compute/runtime/CL/functions/CLLSTMLayer.h index 3add152878..44b3baf81b 100644 --- a/arm_compute/runtime/CL/functions/CLLSTMLayer.h +++ b/arm_compute/runtime/CL/functions/CLLSTMLayer.h @@ -39,6 +39,7 @@ #include "arm_compute/runtime/CL/functions/CLElementwiseOperations.h" #include "arm_compute/runtime/CL/functions/CLFullyConnectedLayer.h" #include "arm_compute/runtime/CL/functions/CLGEMM.h" +#include "arm_compute/runtime/CL/functions/CLMeanStdDevNormalizationLayer.h" #include "arm_compute/runtime/IMemoryManager.h" #include "arm_compute/runtime/common/LSTMParams.h" @@ -76,17 +77,22 @@ public: * @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. + * 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. + * input_layer_norm_coefficients 1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input. + * forget_layer_norm_coefficients 1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input. + * cell_layer_norm_coefficients 1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input. + * output_layer_norm_coefficients 1D weights tensor with dimensions [num_units]. 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. + * @param[in] cell_threshold The clipping threshold for the cell state, such that values are bound within [-cell_clip, cell_clip]. If set to 0.0f 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 0.0f 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, @@ -98,35 +104,40 @@ public: /** Static function to check if given info will lead to a valid configuration of @ref CLLSTMLayer * - * @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] input Source tensor info. 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 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_in 2D weights tensor info with dimensions [output_size, batch_size]. Data type supported: Same as @p input. + * @param[in] cell_state_in 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_state_out 2D weights tensor info with dimensions [output_size, batch_size]. Data type supported: Same as @p input. + * @param[in] cell_state_out 2D tensor info with dimensions [num_units, batch_size]. 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 info used in peephole optimization: + * input_to_input_weights 2D weights tensor info with dimensions [input_size, num_units]. Data type supported: Same as @p input. + * recurrent_to_input_weights 2D weights tensor info with dimensions [output_size, num_units]. Data type supported: Same as @p input. + * cell_to_input_weights 1D weights tensor info with dimensions [num_units]. Can be nullptr. Data type supported: Same as @p input. + * cell_to_forget_weights 1D weights tensor info with dimensions [num_units]. Data type supported: Same as @p input. + * cell_to_output_weights 1D weights tensor info with dimensions [num_units]. Data type supported: Same as @p input. + * input_gate_bias 1D weights tensor info with dimensions [num_units]. Data type supported: Same as @p input + * projection_weights 2D weights tensor info with dimensions [output_size, num_units]. Data type supported: Same as @p input. + * projection_bias 1D weights tensor info with dimensions [output_size]. Data type supported: Same as @p input. + * input_layer_norm_coefficients 1D weights tensor info with dimensions [num_units]. Data type supported: Same as @p input. + * forget_layer_norm_coefficients 1D weights tensor info with dimensions [num_units]. Data type supported: Same as @p input. + * cell_layer_norm_coefficients 1D weights tensor info with dimensions [num_units]. Data type supported: Same as @p input. + * output_layer_norm_coefficients 1D weights tensor info with dimensions [num_units]. 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. + * @param[in] cell_threshold The clipping threshold for the cell state, such that values are bound within [-cell_clip, cell_clip]. If set to 0.0f 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 0.0f then clipping is disabled. * * @return a status */ @@ -145,23 +156,16 @@ public: private: CLMemoryGroup _memory_group; CLFullyConnectedLayer _fully_connected_input_gate; - CLGEMM _gemm_input_gate; - CLTransposeKernel _transpose_input_gate; - CLSaturatedArithmeticOperationKernel _accum_input_gate1; - CLArithmeticAddition _accum_input_gate2; + CLArithmeticAddition _accum_input_gate1; CLSaturatedArithmeticOperationKernel _subtract_input_gate; CLPixelWiseMultiplicationKernel _pixelwise_mul_input_gate; CLActivationLayerKernel _activation_input_gate; CLFullyConnectedLayer _fully_connected_forget_gate; - CLGEMM _gemm_forget_gate; - CLTransposeKernel _transpose_forget_gate; - CLSaturatedArithmeticOperationKernel _accum_forget_gate1; - CLArithmeticAddition _accum_forget_gate2; + CLArithmeticAddition _accum_forget_gate1; CLPixelWiseMultiplicationKernel _pixelwise_mul_forget_gate; CLActivationLayerKernel _activation_forget_gate; CLFullyConnectedLayer _fully_connected_cell_state; CLGEMM _gemm_cell_state1; - CLGEMM _gemm_cell_state2; CLTransposeKernel _transpose_cell_state; CLSaturatedArithmeticOperationKernel _accum_cell_state1; CLSaturatedArithmeticOperationKernel _accum_cell_state2; @@ -170,17 +174,12 @@ private: CLActivationLayerKernel _cell_clip; CLPixelWiseMultiplicationKernel _pixelwise_mul_cell_state2; CLFullyConnectedLayer _fully_connected_output; - CLGEMM _gemm_output; CLPixelWiseMultiplicationKernel _pixelwise_mul_output_state1; - CLTransposeKernel _transpose_output; - CLSaturatedArithmeticOperationKernel _accum_output1; - CLArithmeticAddition _accum_output2; + CLArithmeticAddition _accum_output1; CLActivationLayerKernel _activation_output; CLActivationLayerKernel _activation_output_state; CLPixelWiseMultiplicationKernel _pixelwise_mul_output_state2; CLFullyConnectedLayer _fully_connected_output_state; - CLGEMM _gemm_output_state; - CLSaturatedArithmeticOperationKernel _accum_output_state; CLActivationLayerKernel _projection_clip; CLCopyKernel _copy_cell_state; CLCopyKernel _copy_output; @@ -190,6 +189,18 @@ private: CLWidthConcatenate2TensorsKernel _concat_weights_input_gate; CLWidthConcatenate2TensorsKernel _concat_weights_output; CLMemsetKernel _ones_memset_kernel; + CLMeanStdDevNormalizationLayer _mean_std_norm_input_gate; + CLPixelWiseMultiplicationKernel _pixelwise_mul_input_gate_coeff; + CLSaturatedArithmeticOperationKernel _accum_input_gate_bias; + CLMeanStdDevNormalizationLayer _mean_std_norm_forget_gate; + CLPixelWiseMultiplicationKernel _pixelwise_mul_forget_gate_coeff; + CLSaturatedArithmeticOperationKernel _accum_forget_gate_bias; + CLMeanStdDevNormalizationLayer _mean_std_norm_cell_gate; + CLPixelWiseMultiplicationKernel _pixelwise_mul_cell_gate_coeff; + CLSaturatedArithmeticOperationKernel _accum_cell_gate_bias; + CLMeanStdDevNormalizationLayer _mean_std_norm_output_gate; + CLPixelWiseMultiplicationKernel _pixelwise_mul_output_gate_coeff; + CLSaturatedArithmeticOperationKernel _accum_output_gate_bias; CLTensor _input_gate_out1; CLTensor _input_gate_out2; CLTensor _input_gate_out3; @@ -212,12 +223,21 @@ private: CLTensor _cell_state_activation; CLTensor _output_state1; CLTensor _ones; + CLTensor _input_layer_norm_out1; + CLTensor _input_layer_norm_out2; + CLTensor _forget_layer_norm_out1; + CLTensor _forget_layer_norm_out2; + CLTensor _cell_layer_norm_out1; + CLTensor _cell_layer_norm_out2; + CLTensor _output_layer_norm_out1; + CLTensor _output_layer_norm_out2; bool _run_peephole_opt; bool _run_cifg_opt; bool _perform_cell_clipping; bool _has_projection_weights; bool _perform_projection_clipping; bool _is_prepared; + bool _is_layer_norm_lstm; }; } // namespace arm_compute #endif /* __ARM_COMPUTE_CLLSTMLAYER_H__ */ diff --git a/arm_compute/runtime/common/LSTMParams.h b/arm_compute/runtime/common/LSTMParams.h index 5b33e2e937..6979f90721 100644 --- a/arm_compute/runtime/common/LSTMParams.h +++ b/arm_compute/runtime/common/LSTMParams.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2018 ARM Limited. + * Copyright (c) 2018-2019 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -41,7 +41,8 @@ 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) + _cell_to_output_weights(nullptr), _projection_weights(nullptr), _projection_bias(nullptr), _input_layer_norm_weights(nullptr), _forget_layer_norm_weights(nullptr), _cell_layer_norm_weights(nullptr), + _output_layer_norm_weights(nullptr), _has_peephole_opt(false), _has_projection(false), _has_cifg_opt(true), _use_layer_norm(false) { } /** Prevent instances of this class from being copied (As this class contains pointers) */ @@ -96,6 +97,25 @@ public: _has_peephole_opt = true; return *this; } + /** Set layer normalization tensor parameters. + * + * @param[in] input_layer_norm_weights 1D weights tensor with dimensions [num_units]. Data type supported: Data types supported: F16/F32. + * @param[in] forget_layer_norm_weights 1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input_layer_norm_weights. + * @param[in] cell_layer_norm_weights 1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input_layer_norm_weights. + * @param[in] output_layer_norm_weights 1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input_layer_norm_weights. + * + * @return Reference to this LSTMParams object + */ + LSTMParams &set_layer_normalization_params(const T *input_layer_norm_weights, const T *forget_layer_norm_weights, + const T *cell_layer_norm_weights, const T *output_layer_norm_weights) + { + _input_layer_norm_weights = input_layer_norm_weights; + _forget_layer_norm_weights = forget_layer_norm_weights; + _cell_layer_norm_weights = cell_layer_norm_weights; + _output_layer_norm_weights = output_layer_norm_weights; + _use_layer_norm = true; + return *this; + } const T *input_to_input_weights() const { @@ -137,6 +157,26 @@ public: return _projection_bias; } + const T *input_layer_norm_weights() const + { + return _input_layer_norm_weights; + } + + const T *forget_layer_norm_weights() const + { + return _forget_layer_norm_weights; + } + + const T *cell_layer_norm_weights() const + { + return _cell_layer_norm_weights; + } + + const T *output_layer_norm_weights() const + { + return _output_layer_norm_weights; + } + bool has_peephole_opt() const { return _has_peephole_opt; @@ -152,6 +192,11 @@ public: return _has_cifg_opt; } + bool use_layer_norm() const + { + return _use_layer_norm; + } + private: const T *_input_to_input_weights; const T *_recurrent_to_input_weights; @@ -161,9 +206,14 @@ private: const T *_cell_to_output_weights; const T *_projection_weights; const T *_projection_bias; + const T *_input_layer_norm_weights; + const T *_forget_layer_norm_weights; + const T *_cell_layer_norm_weights; + const T *_output_layer_norm_weights; bool _has_peephole_opt; bool _has_projection; bool _has_cifg_opt; + bool _use_layer_norm; }; } #endif /*__ARM_COMPUTE_LSTMPARAMS_H__ */ -- cgit v1.2.1