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/*
* 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<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.
*
* 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 */
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