| /* |
| * Copyright (c) 2019-2020 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_CLLSTMLAYERQUANTIZED_H |
| #define ARM_COMPUTE_CLLSTMLAYERQUANTIZED_H |
| |
| #include "arm_compute/core/Types.h" |
| #include "arm_compute/runtime/CL/functions/CLActivationLayer.h" |
| #include "arm_compute/runtime/CL/functions/CLConcatenateLayer.h" |
| #include "arm_compute/runtime/CL/functions/CLDequantizationLayer.h" |
| #include "arm_compute/runtime/CL/functions/CLElementwiseOperations.h" |
| #include "arm_compute/runtime/CL/functions/CLGEMMLowpMatrixMultiplyCore.h" |
| #include "arm_compute/runtime/CL/functions/CLGEMMLowpOutputStage.h" |
| #include "arm_compute/runtime/CL/functions/CLPixelWiseMultiplication.h" |
| #include "arm_compute/runtime/CL/functions/CLQuantizationLayer.h" |
| #include "arm_compute/runtime/CL/functions/CLSlice.h" |
| #include "arm_compute/runtime/CL/functions/CLTranspose.h" |
| |
| #include "arm_compute/runtime/common/LSTMParams.h" |
| |
| namespace arm_compute |
| { |
| // Forward declarations |
| class ICLTensor; |
| |
| /** Basic function to run @ref CLLSTMLayerQuantized |
| * |
| * This function calls the following CL functions/kernels: |
| * |
| * -# @ref CLGEMMLowpMatrixMultiplyCore Quantized matrix multiplication core. Accumulators are 32-bit integers |
| * -# @ref CLGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPoint Convert 32-bit integers into QSYMM16 |
| * -# @ref CLTranspose Matrix transpose |
| * -# @ref CLConcatenateLayer Tensor concatenation |
| * -# @ref CLActivationLayer Activation functions (tanh and logistic) |
| * -# @ref CLArithmeticAddition Elementwise addition |
| * -# @ref CLPixelWiseMultiplication Elementwise multiplication |
| * -# @ref CLSlice Tensor slicing |
| * -# @ref CLDequantizationLayer Dequantize into float |
| * -# @ref CLQuantizationLayer Quantize from float |
| * */ |
| class CLLSTMLayerQuantized : public IFunction |
| { |
| public: |
| /** Default constructor */ |
| CLLSTMLayerQuantized(std::shared_ptr<IMemoryManager> memory_manager = nullptr); |
| /** Prevent instances of this class from being copied (As this class contains pointers) */ |
| CLLSTMLayerQuantized(const CLLSTMLayerQuantized &) = delete; |
| /** Default move constructor */ |
| CLLSTMLayerQuantized(CLLSTMLayerQuantized &&) = default; |
| /** Prevent instances of this class from being copied (As this class contains pointers) */ |
| CLLSTMLayerQuantized &operator=(const CLLSTMLayerQuantized &) = delete; |
| /** Default move assignment operator */ |
| CLLSTMLayerQuantized &operator=(CLLSTMLayerQuantized &&) = default; |
| /** Initialize function's tensors. |
| * |
| * @param[in] input Source tensor. Input is a 2D tensor with dimensions [input_size, batch_size]. Data types supported: QASYMM8. |
| * @param[in] input_to_input_weights 2D weights tensor with dimensions [input_size, output_size]. Data type supported: Same as @p input. |
| * @param[in] input_to_forget_weights 2D weights tensor with dimensions [input_size, output_size]. Data type supported: Same as @p input. |
| * @param[in] input_to_cell_weights 2D weights tensor with dimensions [input_size, output_size]. Data type supported: Same as @p input. |
| * @param[in] input_to_output_weights 2D weights tensor with dimensions [input_size, output_size]. Data type supported: Same as @p input. |
| * @param[in] recurrent_to_input_weights 2D weights tensor with dimensions [output_size, output_size]. Data type supported: Same as @p input. |
| * @param[in] recurrent_to_forget_weights 2D weights tensor with dimensions [output_size, output_size]. Data type supported: Same as @p input. |
| * @param[in] recurrent_to_cell_weights 2D weights tensor with dimensions [output_size, output_size]. Data type supported: Same as @p input. |
| * @param[in] recurrent_to_output_weights 2D weights tensor with dimensions [output_size, output_size]. Data type supported: Same as @p input. |
| * @param[in] input_gate_bias 1D weights tensor with dimensions [output_size]. Data type supported: S32. |
| * @param[in] forget_gate_bias 1D weights tensor with dimensions [output_size]. Data type supported: S32. |
| * @param[in] cell_bias 1D weights tensor with dimensions [output_size]. Data type supported: S32. |
| * @param[in] output_gate_bias 1D weights tensor with dimensions [output_size]. Data type supported: S32. |
| * @param[in] cell_state_in 2D tensor with dimensions [output_size, batch_size]. Data type supported: QSYMM16. |
| * @param[in] output_state_in 2D tensor with dimensions [output_size, batch_size]. Data type supported: Same as @p input. |
| * @param[out] cell_state_out Destination tensor. Output is a 2D tensor with dimensions [output_size, batch_size]. Data type supported: QSYMM16. |
| * @param[out] output_state_out Destination tensor. Output is a 2D tensor with dimensions [output_size, batch_size].Data types supported: Same as @p input. |
| */ |
| void configure(const ICLTensor *input, |
| const ICLTensor *input_to_input_weights, const ICLTensor *input_to_forget_weights, const ICLTensor *input_to_cell_weights, const ICLTensor *input_to_output_weights, |
| const ICLTensor *recurrent_to_input_weights, const ICLTensor *recurrent_to_forget_weights, const ICLTensor *recurrent_to_cell_weights, const ICLTensor *recurrent_to_output_weights, |
| const ICLTensor *input_gate_bias, const ICLTensor *forget_gate_bias, const ICLTensor *cell_bias, const ICLTensor *output_gate_bias, |
| ICLTensor *cell_state_in, const ICLTensor *output_state_in, |
| ICLTensor *cell_state_out, ICLTensor *output_state_out); |
| /** Initialize function's tensors. |
| * |
| * @param[in] compile_context The compile context to be used. |
| * @param[in] input Source tensor. Input is a 2D tensor with dimensions [input_size, batch_size]. Data types supported: QASYMM8. |
| * @param[in] input_to_input_weights 2D weights tensor with dimensions [input_size, output_size]. Data type supported: Same as @p input. |
| * @param[in] input_to_forget_weights 2D weights tensor with dimensions [input_size, output_size]. Data type supported: Same as @p input. |
| * @param[in] input_to_cell_weights 2D weights tensor with dimensions [input_size, output_size]. Data type supported: Same as @p input. |
| * @param[in] input_to_output_weights 2D weights tensor with dimensions [input_size, output_size]. Data type supported: Same as @p input. |
| * @param[in] recurrent_to_input_weights 2D weights tensor with dimensions [output_size, output_size]. Data type supported: Same as @p input. |
| * @param[in] recurrent_to_forget_weights 2D weights tensor with dimensions [output_size, output_size]. Data type supported: Same as @p input. |
| * @param[in] recurrent_to_cell_weights 2D weights tensor with dimensions [output_size, output_size]. Data type supported: Same as @p input. |
| * @param[in] recurrent_to_output_weights 2D weights tensor with dimensions [output_size, output_size]. Data type supported: Same as @p input. |
| * @param[in] input_gate_bias 1D weights tensor with dimensions [output_size]. Data type supported: S32. |
| * @param[in] forget_gate_bias 1D weights tensor with dimensions [output_size]. Data type supported: S32. |
| * @param[in] cell_bias 1D weights tensor with dimensions [output_size]. Data type supported: S32. |
| * @param[in] output_gate_bias 1D weights tensor with dimensions [output_size]. Data type supported: S32. |
| * @param[in] cell_state_in 2D tensor with dimensions [output_size, batch_size]. Data type supported: QSYMM16. |
| * @param[in] output_state_in 2D tensor with dimensions [output_size, batch_size]. Data type supported: Same as @p input. |
| * @param[out] cell_state_out Destination tensor. Output is a 2D tensor with dimensions [output_size, batch_size]. Data type supported: QSYMM16. |
| * @param[out] output_state_out Destination tensor. Output is a 2D tensor with dimensions [output_size, batch_size].Data types supported: Same as @p input. |
| */ |
| void configure(const CLCompileContext &compile_context, const ICLTensor *input, |
| const ICLTensor *input_to_input_weights, const ICLTensor *input_to_forget_weights, const ICLTensor *input_to_cell_weights, const ICLTensor *input_to_output_weights, |
| const ICLTensor *recurrent_to_input_weights, const ICLTensor *recurrent_to_forget_weights, const ICLTensor *recurrent_to_cell_weights, const ICLTensor *recurrent_to_output_weights, |
| const ICLTensor *input_gate_bias, const ICLTensor *forget_gate_bias, const ICLTensor *cell_bias, const ICLTensor *output_gate_bias, |
| ICLTensor *cell_state_in, const ICLTensor *output_state_in, |
| ICLTensor *cell_state_out, ICLTensor *output_state_out); |
| |
| /** Static function to check if given info will lead to a valid configuration of @ref CLLSTMLayerQuantized |
| * |
| * @param[in] input Source tensor info. Input is a 2D tensor info with dimensions [input_size, batch_size]. Data types supported: QASYMM8. |
| * @param[in] input_to_input_weights 2D weights tensor info with dimensions [input_size, output_size]. Data type supported: Same as @p input. |
| * @param[in] input_to_forget_weights 2D weights tensor info with dimensions [input_size, output_size]. Data type supported: Same as @p input. |
| * @param[in] input_to_cell_weights 2D weights tensor info with dimensions [input_size, output_size]. Data type supported: Same as @p input. |
| * @param[in] input_to_output_weights 2D weights tensor info with dimensions [input_size, output_size]. Data type supported: Same as @p input. |
| * @param[in] recurrent_to_input_weights 2D weights tensor info with dimensions [output_size, output_size]. Data type supported: Same as @p input. |
| * @param[in] recurrent_to_forget_weights 2D weights tensor info with dimensions [output_size, output_size]. Data type supported: Same as @p input. |
| * @param[in] recurrent_to_cell_weights 2D weights tensor info with dimensions [output_size, output_size]. Data type supported: Same as @p input. |
| * @param[in] recurrent_to_output_weights 2D weights tensor info with dimensions [output_size, output_size]. Data type supported: Same as @p input. |
| * @param[in] input_gate_bias 1D weights tensor info with dimensions [output_size]. Data type supported: S32. |
| * @param[in] forget_gate_bias 1D weights tensor info with dimensions [output_size]. Data type supported: S32. |
| * @param[in] cell_bias 1D weights tensor info with dimensions [output_size]. Data type supported: S32. |
| * @param[in] output_gate_bias 1D weights tensor info with dimensions [output_size]. Data type supported: S32. |
| * @param[in] cell_state_in 2D tensor info with dimensions [output_size, batch_size]. Data type supported: QSYMM16. |
| * @param[in] output_state_in 2D tensor info with dimensions [output_size, batch_size]. Data type supported: Same as @p input. |
| * @param[out] cell_state_out Destination tensor info. Output is a 2D tensor info with dimensions [output_size, batch_size]. Data type supported: QSYMM16. |
| * @param[out] output_state_out Destination tensor info. Output is a 2D tensor info with dimensions [output_size, batch_size].Data types supported: Same as @p input. |
| * |
| * @return a status |
| */ |
| static Status validate(const ITensorInfo *input, |
| const ITensorInfo *input_to_input_weights, const ITensorInfo *input_to_forget_weights, const ITensorInfo *input_to_cell_weights, const ITensorInfo *input_to_output_weights, |
| const ITensorInfo *recurrent_to_input_weights, const ITensorInfo *recurrent_to_forget_weights, const ITensorInfo *recurrent_to_cell_weights, const ITensorInfo *recurrent_to_output_weights, |
| const ITensorInfo *input_gate_bias, const ITensorInfo *forget_gate_bias, const ITensorInfo *cell_bias, const ITensorInfo *output_gate_bias, |
| const ITensorInfo *cell_state_in, const ITensorInfo *output_state_in, |
| const ITensorInfo *cell_state_out, const ITensorInfo *output_state_out); |
| |
| // Inherited methods overridden: |
| void run() override; |
| void prepare() override; |
| |
| private: |
| MemoryGroup _memory_group; |
| |
| // Functions used |
| CLGEMMLowpMatrixMultiplyCore _gemmlowp; |
| CLGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPoint _output_stage; |
| CLTranspose _transpose_weights; |
| CLConcatenateLayer _concat_input_weights; |
| CLConcatenateLayer _concat_recurrent_weights; |
| CLConcatenateLayer _concat_weights; |
| CLConcatenateLayer _concat_inputs; |
| CLConcatenateLayer _concat_bias; |
| CLActivationLayer _sigmoid_forget_gate; |
| CLActivationLayer _sigmoid_input_gate; |
| CLActivationLayer _sigmoid_output_gate; |
| CLActivationLayer _tanh_modulation_gate; |
| CLActivationLayer _tanh_output_state; |
| CLArithmeticAddition _add_cell_state_tmps; |
| CLArithmeticAddition _add2; |
| CLPixelWiseMultiplication _mul_forget_gate_cell_state; |
| CLPixelWiseMultiplication _mul_input_gate_input_mod_gate; |
| CLPixelWiseMultiplication _mul_output_state_tmp_output_gate; |
| CLSlice _slice_input_tensor; |
| CLSlice _slice_forget_tensor; |
| CLSlice _slice_cell_tensor; |
| CLSlice _slice_output_tensor; |
| CLDequantizationLayer _dequantize; |
| CLQuantizationLayer _quantize; |
| |
| // Tensor pointers |
| const ICLTensor *_input_to_input_weights; |
| const ICLTensor *_input_to_forget_weights; |
| const ICLTensor *_input_to_cell_weights; |
| const ICLTensor *_input_to_output_weights; |
| const ICLTensor *_recurrent_to_input_weights; |
| const ICLTensor *_recurrent_to_forget_weights; |
| const ICLTensor *_recurrent_to_cell_weights; |
| const ICLTensor *_recurrent_to_output_weights; |
| const ICLTensor *_input_gate_bias; |
| const ICLTensor *_forget_gate_bias; |
| const ICLTensor *_cell_bias; |
| const ICLTensor *_output_gate_bias; |
| |
| // Temporary tensors |
| CLTensor _recurrent_weights; |
| CLTensor _input_weights; |
| CLTensor _weights; |
| CLTensor _input; |
| CLTensor _weights_transposed; |
| CLTensor _output_highp; |
| CLTensor _output_lowp; |
| CLTensor _bias; |
| CLTensor _forget_gate_input; |
| CLTensor _input_gate_input; |
| CLTensor _output_gate_input; |
| CLTensor _input_modulation_gate_input; |
| CLTensor _forget_gate_output; |
| CLTensor _input_gate_output; |
| CLTensor _output_gate_output; |
| CLTensor _input_modulation_gate_output; |
| CLTensor _cell_state_tmp1; |
| CLTensor _cell_state_tmp2; |
| CLTensor _output_state_tmp; |
| CLTensor _output_state_out_symm; |
| CLTensor _output_state_out_f32; |
| |
| bool _is_prepared; |
| }; |
| } // namespace arm_compute |
| #endif /* ARM_COMPUTE_CLLSTMLAYERQUANTIZED_H */ |