COMPMID-2307: QUANTIZED_16BIT_LSTM operator for CL
Change-Id: I1b52df359f1a368d585fac43a08496544dd2f86f
Signed-off-by: Manuel Bottini <manuel.bottini@arm.com>
Reviewed-on: https://review.mlplatform.org/c/1568
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Giuseppe Rossini <giuseppe.rossini@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
diff --git a/arm_compute/runtime/CL/functions/CLLSTMLayerQuantized.h b/arm_compute/runtime/CL/functions/CLLSTMLayerQuantized.h
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+++ b/arm_compute/runtime/CL/functions/CLLSTMLayerQuantized.h
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+/*
+ * 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<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);
+
+ /** 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__ */