| /* |
| * Copyright (c) 2018-2019 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/functions/NEArithmeticAddition.h" |
| #include "arm_compute/runtime/NEON/functions/NEConcatenateLayer.h" |
| #include "arm_compute/runtime/NEON/functions/NEFullyConnectedLayer.h" |
| #include "arm_compute/runtime/NEON/functions/NEGEMM.h" |
| #include "arm_compute/runtime/NEON/functions/NEMeanStdDevNormalizationLayer.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<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] 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. |
| * 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. |
| */ |
| 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<ITensor> &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. |
| * 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. |
| * |
| * @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<ITensorInfo> &lstm_params, const ActivationLayerInfo &activation_info, float cell_threshold = 0.f, float projection_threshold = 0.f); |
| |
| // Inherited methods overridden: |
| void run() override; |
| void prepare() override; |
| |
| private: |
| MemoryGroup _memory_group; |
| NEFullyConnectedLayer _fully_connected_input_gate; |
| NEArithmeticAddition _accum_input_gate1; |
| NEArithmeticSubtractionKernel _subtract_input_gate; |
| NEPixelWiseMultiplicationKernel _pixelwise_mul_input_gate; |
| NEActivationLayerKernel _activation_input_gate; |
| NEFullyConnectedLayer _fully_connected_forget_gate; |
| NEArithmeticAddition _accum_forget_gate1; |
| NEPixelWiseMultiplicationKernel _pixelwise_mul_forget_gate; |
| NEActivationLayerKernel _activation_forget_gate; |
| NEFullyConnectedLayer _fully_connected_cell_state; |
| NEGEMM _gemm_cell_state1; |
| 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; |
| NEPixelWiseMultiplicationKernel _pixelwise_mul_output_state1; |
| NEArithmeticAddition _accum_output1; |
| NEActivationLayerKernel _activation_output; |
| NEActivationLayerKernel _activation_output_state; |
| NEPixelWiseMultiplicationKernel _pixelwise_mul_output_state2; |
| NEFullyConnectedLayer _fully_connected_output_state; |
| NEActivationLayerKernel _projection_clip; |
| NECopyKernel _copy_cell_state; |
| NECopyKernel _copy_output; |
| NEConcatenateLayer _concat_scratch_buffer; |
| NEConcatenateLayer _concat_inputs_forget_gate; |
| NEConcatenateLayer _concat_weights_forget_gate; |
| NEConcatenateLayer _concat_weights_input_gate; |
| NEConcatenateLayer _concat_weights_output; |
| NEMeanStdDevNormalizationLayer _mean_std_norm_input_gate; |
| NEPixelWiseMultiplicationKernel _pixelwise_mul_input_gate_coeff; |
| NEArithmeticAdditionKernel _accum_input_gate_bias; |
| NEMeanStdDevNormalizationLayer _mean_std_norm_forget_gate; |
| NEPixelWiseMultiplicationKernel _pixelwise_mul_forget_gate_coeff; |
| NEArithmeticAdditionKernel _accum_forget_gate_bias; |
| NEMeanStdDevNormalizationLayer _mean_std_norm_cell_gate; |
| NEPixelWiseMultiplicationKernel _pixelwise_mul_cell_gate_coeff; |
| NEArithmeticAdditionKernel _accum_cell_gate_bias; |
| NEMeanStdDevNormalizationLayer _mean_std_norm_output_gate; |
| NEPixelWiseMultiplicationKernel _pixelwise_mul_output_gate_coeff; |
| NEArithmeticAdditionKernel _accum_output_gate_bias; |
| Tensor _input_gate_out1; |
| Tensor _input_gate_out2; |
| Tensor _input_gate_out3; |
| Tensor _input_gate_out4; |
| Tensor _forget_gate_out1; |
| Tensor _forget_gate_out2; |
| Tensor _forget_gate_out3; |
| Tensor _forget_gate_out4; |
| Tensor _forget_gate_out5; |
| Tensor _forget_gate_out6; |
| 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 _cell_state_activation; |
| Tensor _output_state1; |
| Tensor _ones; |
| Tensor _input_layer_norm_out1; |
| Tensor _input_layer_norm_out2; |
| Tensor _forget_layer_norm_out1; |
| Tensor _forget_layer_norm_out2; |
| Tensor _cell_layer_norm_out1; |
| Tensor _cell_layer_norm_out2; |
| Tensor _output_layer_norm_out1; |
| Tensor _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_NELSTMLAYER_H__ */ |
