From 10c53f1ef317095ddcd9143bf759cc68ecb0e721 Mon Sep 17 00:00:00 2001 From: Manuel Bottini Date: Wed, 17 Jul 2019 16:11:53 +0100 Subject: COMPMID-2307: QUANTIZED_16BIT_LSTM operator for CL Change-Id: I1b52df359f1a368d585fac43a08496544dd2f86f Signed-off-by: Manuel Bottini Reviewed-on: https://review.mlplatform.org/c/1568 Tested-by: Arm Jenkins Reviewed-by: Giuseppe Rossini Comments-Addressed: Arm Jenkins --- .../runtime/CL/functions/CLLSTMLayerQuantized.h | 203 +++++++++++++++++++++ 1 file changed, 203 insertions(+) create mode 100644 arm_compute/runtime/CL/functions/CLLSTMLayerQuantized.h (limited to 'arm_compute/runtime/CL/functions/CLLSTMLayerQuantized.h') diff --git a/arm_compute/runtime/CL/functions/CLLSTMLayerQuantized.h b/arm_compute/runtime/CL/functions/CLLSTMLayerQuantized.h new file mode 100644 index 0000000000..e2d164c395 --- /dev/null +++ b/arm_compute/runtime/CL/functions/CLLSTMLayerQuantized.h @@ -0,0 +1,203 @@ +/* + * Copyright (c) 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_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 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); + + /** 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: + CLMemoryGroup _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__ */ -- cgit v1.2.1