diff options
Diffstat (limited to 'arm_compute/runtime/NEON/functions/NEQLSTMLayer.h')
| -rw-r--r-- | arm_compute/runtime/NEON/functions/NEQLSTMLayer.h | 186 |
1 files changed, 87 insertions, 99 deletions
diff --git a/arm_compute/runtime/NEON/functions/NEQLSTMLayer.h b/arm_compute/runtime/NEON/functions/NEQLSTMLayer.h index 7c572de874..17ad5a354b 100644 --- a/arm_compute/runtime/NEON/functions/NEQLSTMLayer.h +++ b/arm_compute/runtime/NEON/functions/NEQLSTMLayer.h @@ -24,24 +24,27 @@ #ifndef ARM_COMPUTE_NEQLSTMLAYER_H #define ARM_COMPUTE_NEQLSTMLAYER_H -#include "arm_compute/core/NEON/kernels/NECopyKernel.h" -#include "arm_compute/core/NEON/kernels/NEGEMMLowpReductionKernel.h" -#include "arm_compute/core/NEON/kernels/NEQLSTMLayerNormalizationKernel.h" #include "arm_compute/core/Types.h" #include "arm_compute/runtime/NEON/functions/NEActivationLayer.h" #include "arm_compute/runtime/NEON/functions/NEArithmeticAddition.h" #include "arm_compute/runtime/NEON/functions/NEArithmeticSubtraction.h" +#include "arm_compute/runtime/NEON/functions/NECopy.h" #include "arm_compute/runtime/NEON/functions/NEGEMMLowpMatrixMultiplyCore.h" #include "arm_compute/runtime/NEON/functions/NEGEMMLowpOutputStage.h" #include "arm_compute/runtime/NEON/functions/NEPixelWiseMultiplication.h" #include "arm_compute/runtime/NEON/functions/NETranspose.h" +#include "support/MemorySupport.h" #include "arm_compute/runtime/common/LSTMParams.h" +#include <memory> namespace arm_compute { // Forward declarations class ITensor; +class ITensorInfo; +class NEQLSTMLayerNormalizationKernel; +class NEGEMMLowpMatrixAReductionKernel; /** Basic function to run @ref NEQLSTMLayer * @@ -70,6 +73,8 @@ public: NEQLSTMLayer &operator=(const NEQLSTMLayer &) = delete; /** Default move assignment operator */ NEQLSTMLayer &operator=(NEQLSTMLayer &&) = default; + /** Default destructor */ + ~NEQLSTMLayer(); /** Initialize function's tensors. * * @param[in] input Source tensor. Input is a 2D tensor with dimensions [input_size, batch_size]. Data types supported: QASYMM8_SIGNED. @@ -204,7 +209,7 @@ private: Tensor *outstage_res, float gemmlowp_scale, const TensorInfo &mm_res_info, const TensorInfo &outstage_tensor_info); - MemoryGroup _memory_group{}; + MemoryGroup _memory_group; /** A small internel kernel do the copy between two tensors */ class TensorCopyKernel @@ -217,6 +222,8 @@ private: Window _window{}; public: + /** Destructor */ + ~TensorCopyKernel(); /** Static function to check if given info will lead to a valid configuration of @ref NEQLSTMLayer::TensorCopyKernel * * @param[in] src Source tensor info. @@ -236,79 +243,79 @@ private: }; // Functions used - NETranspose _transpose_input_to_forget_weights{}; - NETranspose _transpose_input_to_cell_weights{}; - NETranspose _transpose_input_to_output_weights{}; - NETranspose _transpose_input_to_input_weights{}; - NETranspose _transpose_recurrent_to_forget_weights{}; - NETranspose _transpose_recurrent_to_cell_weights{}; - NETranspose _transpose_recurrent_to_output_weights{}; - NETranspose _transpose_recurrent_to_input_weights{}; - NETranspose _transpose_projection_weights{}; - NEGEMMLowpMatrixAReductionKernel _input_to_input_reduction{}; - NEGEMMLowpMatrixAReductionKernel _recurrent_to_input_reduction{}; - NEGEMMLowpMatrixAReductionKernel _input_to_forget_reduction{}; - NEGEMMLowpMatrixAReductionKernel _recurrent_to_forget_reduction{}; - NEGEMMLowpMatrixAReductionKernel _input_to_cell_reduction{}; - NEGEMMLowpMatrixAReductionKernel _recurrent_to_cell_reduction{}; - NEGEMMLowpMatrixAReductionKernel _input_to_output_reduction{}; - NEGEMMLowpMatrixAReductionKernel _recurrent_to_output_reduction{}; - NEGEMMLowpMatrixAReductionKernel _projection_reduction{}; - NEArithmeticAddition _projection_bias_add{}; - NEGEMMLowpMatrixMultiplyCore _mm_input_to_forget{}; - NEGEMMLowpMatrixMultiplyCore _mm_recurrent_to_forget{}; - NEPixelWiseMultiplication _pixelwise_mul_cell_to_forget{}; - NEGEMMLowpOutputStage _input_to_forget_outstage{}; - NEGEMMLowpOutputStage _recurrent_to_forget_outstage{}; - NEGEMMLowpOutputStage _cell_to_forget_outstage{}; - NEArithmeticAddition _accumulate_input_recurrent_forget{}; - NEArithmeticAddition _accumulate_cell_forget{}; - NEActivationLayer _forget_gate_sigmoid{}; - NEGEMMLowpMatrixMultiplyCore _mm_input_to_cell{}; - NEGEMMLowpOutputStage _input_to_cell_outstage{}; - NEGEMMLowpMatrixMultiplyCore _mm_recurrent_to_cell{}; - NEGEMMLowpOutputStage _recurrent_to_cell_outstage{}; - NEArithmeticAddition _accumulate_input_recurrent_modulation{}; - NEActivationLayer _cell_gate_tanh{}; - NEArithmeticSubtraction _input_gate_sub{}; - NEGEMMLowpMatrixMultiplyCore _mm_input_to_input{}; - NEGEMMLowpOutputStage _input_to_input_outstage{}; - NEGEMMLowpMatrixMultiplyCore _mm_recurrent_to_input{}; - NEGEMMLowpOutputStage _recurrent_to_input_outstage{}; - NEArithmeticAddition _accumulate_input_recurrent_input{}; - NEPixelWiseMultiplication _pixelwise_mul_cell_to_input{}; - NEGEMMLowpOutputStage _cell_to_input_outstage{}; - NEArithmeticAddition _accumulate_cell_input{}; - NEActivationLayer _input_gate_sigmoid{}; - NEPixelWiseMultiplication _pixelwise_mul_forget_cell{}; - NEPixelWiseMultiplication _pixelwise_mul_input_cell{}; - NEArithmeticAddition _add_forget_cell{}; - NEActivationLayer _cell_clip{}; - NEGEMMLowpMatrixMultiplyCore _mm_input_to_output{}; - NEGEMMLowpOutputStage _input_to_output_outstage{}; - NEGEMMLowpMatrixMultiplyCore _mm_recurrent_to_output{}; - NEGEMMLowpOutputStage _recurrent_to_output_outstage{}; - NEArithmeticAddition _accumulate_input_recurrent_output{}; - NEPixelWiseMultiplication _pixelwise_mul_cell_to_output{}; - NEGEMMLowpOutputStage _cell_to_output_outstage{}; - NEArithmeticAddition _accumulate_cell_to_output{}; - NEActivationLayer _output_gate_sigmoid{}; - NEActivationLayer _hidden_tanh{}; - NEPixelWiseMultiplication _pixelwise_mul_hidden{}; - NEGEMMLowpOutputStage _hidden_outstage{}; - NEGEMMLowpMatrixMultiplyCore _mm_projection{}; - NEGEMMLowpOutputStage _projection_outstage{}; - NEArithmeticAddition _accumulate_projection{}; - NEActivationLayer _projection_clip{}; + NETranspose _transpose_input_to_forget_weights; + NETranspose _transpose_input_to_cell_weights; + NETranspose _transpose_input_to_output_weights; + NETranspose _transpose_input_to_input_weights; + NETranspose _transpose_recurrent_to_forget_weights; + NETranspose _transpose_recurrent_to_cell_weights; + NETranspose _transpose_recurrent_to_output_weights; + NETranspose _transpose_recurrent_to_input_weights; + NETranspose _transpose_projection_weights; + std::unique_ptr<NEGEMMLowpMatrixAReductionKernel> _input_to_input_reduction; + std::unique_ptr<NEGEMMLowpMatrixAReductionKernel> _recurrent_to_input_reduction; + std::unique_ptr<NEGEMMLowpMatrixAReductionKernel> _input_to_forget_reduction; + std::unique_ptr<NEGEMMLowpMatrixAReductionKernel> _recurrent_to_forget_reduction; + std::unique_ptr<NEGEMMLowpMatrixAReductionKernel> _input_to_cell_reduction; + std::unique_ptr<NEGEMMLowpMatrixAReductionKernel> _recurrent_to_cell_reduction; + std::unique_ptr<NEGEMMLowpMatrixAReductionKernel> _input_to_output_reduction; + std::unique_ptr<NEGEMMLowpMatrixAReductionKernel> _recurrent_to_output_reduction; + std::unique_ptr<NEGEMMLowpMatrixAReductionKernel> _projection_reduction; + NEArithmeticAddition _projection_bias_add; + NEGEMMLowpMatrixMultiplyCore _mm_input_to_forget; + NEGEMMLowpMatrixMultiplyCore _mm_recurrent_to_forget; + NEPixelWiseMultiplication _pixelwise_mul_cell_to_forget; + NEGEMMLowpOutputStage _input_to_forget_outstage; + NEGEMMLowpOutputStage _recurrent_to_forget_outstage; + NEGEMMLowpOutputStage _cell_to_forget_outstage; + NEArithmeticAddition _accumulate_input_recurrent_forget; + NEArithmeticAddition _accumulate_cell_forget; + NEActivationLayer _forget_gate_sigmoid; + NEGEMMLowpMatrixMultiplyCore _mm_input_to_cell; + NEGEMMLowpOutputStage _input_to_cell_outstage; + NEGEMMLowpMatrixMultiplyCore _mm_recurrent_to_cell; + NEGEMMLowpOutputStage _recurrent_to_cell_outstage; + NEArithmeticAddition _accumulate_input_recurrent_modulation; + NEActivationLayer _cell_gate_tanh; + NEArithmeticSubtraction _input_gate_sub; + NEGEMMLowpMatrixMultiplyCore _mm_input_to_input; + NEGEMMLowpOutputStage _input_to_input_outstage; + NEGEMMLowpMatrixMultiplyCore _mm_recurrent_to_input; + NEGEMMLowpOutputStage _recurrent_to_input_outstage; + NEArithmeticAddition _accumulate_input_recurrent_input; + NEPixelWiseMultiplication _pixelwise_mul_cell_to_input; + NEGEMMLowpOutputStage _cell_to_input_outstage; + NEArithmeticAddition _accumulate_cell_input; + NEActivationLayer _input_gate_sigmoid; + NEPixelWiseMultiplication _pixelwise_mul_forget_cell; + NEPixelWiseMultiplication _pixelwise_mul_input_cell; + NEArithmeticAddition _add_forget_cell; + NEActivationLayer _cell_clip; + NEGEMMLowpMatrixMultiplyCore _mm_input_to_output; + NEGEMMLowpOutputStage _input_to_output_outstage; + NEGEMMLowpMatrixMultiplyCore _mm_recurrent_to_output; + NEGEMMLowpOutputStage _recurrent_to_output_outstage; + NEArithmeticAddition _accumulate_input_recurrent_output; + NEPixelWiseMultiplication _pixelwise_mul_cell_to_output; + NEGEMMLowpOutputStage _cell_to_output_outstage; + NEArithmeticAddition _accumulate_cell_to_output; + NEActivationLayer _output_gate_sigmoid; + NEActivationLayer _hidden_tanh; + NEPixelWiseMultiplication _pixelwise_mul_hidden; + NEGEMMLowpOutputStage _hidden_outstage; + NEGEMMLowpMatrixMultiplyCore _mm_projection; + NEGEMMLowpOutputStage _projection_outstage; + NEArithmeticAddition _accumulate_projection; + NEActivationLayer _projection_clip; - TensorCopyKernel _projection_bias_copy{}; - TensorCopyKernel _projection_output_to_accumulate_copy{}; - TensorCopyKernel _projection_accumulate_to_output_copy{}; - TensorCopyKernel _hidden_to_output_copy{}; + TensorCopyKernel _projection_bias_copy; + TensorCopyKernel _projection_output_to_accumulate_copy; + TensorCopyKernel _projection_accumulate_to_output_copy; + TensorCopyKernel _hidden_to_output_copy; - std::array<NEQLSTMLayerNormalizationKernel, _layer_norm_count> _layer_norms{ {} }; + std::array<std::unique_ptr<NEQLSTMLayerNormalizationKernel>, _layer_norm_count> _layer_norms; - NECopyKernel _copy_output{}; + NECopy _copy_output; // Tensor pointers const ITensor *_input_to_input_weights @@ -324,8 +331,8 @@ private: const ITensor *_recurrent_to_cell_weights{ nullptr }; const ITensor *_recurrent_to_output_weights{ nullptr }; const ITensor *_projection_weights{ nullptr }; - std::array<const ITensor *, _layer_norm_count> _layer_norm_weights{ {} }; - std::array<const ITensor *, _layer_norm_count> _layer_norm_bias{ {} }; + std::array<const ITensor *, _layer_norm_count> _layer_norm_weights{}; + std::array<const ITensor *, _layer_norm_count> _layer_norm_bias{}; using LayerNormIndexType = typename std::underlying_type<LayerNormGate>::type; inline LayerNormIndexType getGateIndex(LayerNormGate g) @@ -353,32 +360,13 @@ private: return _layer_norm_bias[getGateIndex(g)]; } - inline NEQLSTMLayerNormalizationKernel &get_layer_norm(LayerNormGate g) + inline std::unique_ptr<NEQLSTMLayerNormalizationKernel> &get_layer_norm(LayerNormGate g) { return _layer_norms[getGateIndex(g)]; } - inline void configure_layer_norm(LayerNormGate g, const ITensor *in) - { - ARM_COMPUTE_ERROR_ON(!_has_layer_norm); - - Tensor &out = get_layer_norm_output(g); - _memory_group.manage(&out); - out.allocator()->init(*(in->info())); - - get_layer_norm(g).configure(in, &out, get_layer_norm_weight(g), get_layer_norm_bias(g)); - } - - inline static Status validate_layer_norm(const ITensorInfo &in, const ITensorInfo &weight, const ITensorInfo &bias) - { - // Output quantization scale will be different, but ignored here - // since it will be configured at configure() stage. - const TensorInfo out - { - in - }; - return NEQLSTMLayerNormalizationKernel::validate(&in, &out, &weight, &bias); - } + void configure_layer_norm(LayerNormGate g, const ITensor *in); + static Status validate_layer_norm(const ITensorInfo &in, const ITensorInfo &weight, const ITensorInfo &bias); // Temporary tensors Tensor _input_to_forget_weights_transposed{ nullptr }; @@ -434,7 +422,7 @@ private: Tensor _projection_out_res{ nullptr }; Tensor _projection_accumulate_res{ nullptr }; Tensor _ones{ nullptr }; - std::array<Tensor, _layer_norm_count> _layer_norm_output{ {} }; + std::array<Tensor, _layer_norm_count> _layer_norm_output{}; inline Tensor &get_layer_norm_output(LayerNormGate g) { |