/* * Copyright (c) 2019-2021 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 CLGEMMLowpOutputStage 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 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. * * Valid data layouts: * - All * * Valid data type configurations: * |src0 - src8 |src9 - src12 |src13 |src14 |dst0 |dst1 | * |:-----------|:------------|:-------|:------|:------|:------| * |QASYMM8 |S32 |QSYMM16 |QASYMM8|QSYMM16|QASYMM8| * * @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; CLGEMMLowpOutputStage _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 */