COMPMID-993 Implement CL LSTM function

Change-Id: Iee4ad387c41dd8ccfe31b3044d797f2d7448e552
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/126655
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>

1 files changed, 346 insertions, 0 deletions

diff --git a/arm_compute/runtime/CL/functions/CLLSTMLayer.h b/arm_compute/runtime/CL/functions/CLLSTMLayer.h
new file mode 100644
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+++ b/arm_compute/runtime/CL/functions/CLLSTMLayer.h
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+/*
+ * Copyright (c) 2018 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_CLLSTMLAYER_H__
+#define __ARM_COMPUTE_CLLSTMLAYER_H__
+
+#include "arm_compute/runtime/IFunction.h"
+
+#include "arm_compute/core/CL/kernels/CLActivationLayerKernel.h"
+#include "arm_compute/core/CL/kernels/CLArithmeticAdditionKernel.h"
+#include "arm_compute/core/CL/kernels/CLArithmeticSubtractionKernel.h"
+#include "arm_compute/core/CL/kernels/CLCopyKernel.h"
+#include "arm_compute/core/CL/kernels/CLPixelWiseMultiplicationKernel.h"
+#include "arm_compute/core/Types.h"
+#include "arm_compute/runtime/CL/CLMemoryGroup.h"
+#include "arm_compute/runtime/CL/CLTensor.h"
+#include "arm_compute/runtime/CL/functions/CLArithmeticAddition.h"
+#include "arm_compute/runtime/CL/functions/CLFullyConnectedLayer.h"
+#include "arm_compute/runtime/CL/functions/CLGEMM.h"
+#include "arm_compute/runtime/CL/functions/CLWidthConcatenateLayer.h"
+#include "arm_compute/runtime/IMemoryManager.h"
+
+#include <memory>
+
+namespace arm_compute
+{
+class ICLTensor;
+
+template <typename T>
+class LSTMParams
+{
+public:
+    /** Constructor */
+    LSTMParams()
+        : _input_to_input_weights(nullptr), _recurrent_to_input_weights(nullptr), _cell_to_input_weights(nullptr), _input_gate_bias(nullptr), _cell_to_forget_weights(nullptr),
+          _cell_to_output_weights(nullptr), _projection_weights(nullptr), _projection_bias(nullptr), _has_peephole_opt(false), _has_projection(false), _has_cifg_opt(true)
+    {
+    }
+    /** Prevent instances of this class from being copied (As this class contains pointers) */
+    LSTMParams(const LSTMParams &) = delete;
+    /** Prevent instances of this class from being copied (As this class contains pointers) */
+    LSTMParams &operator=(const LSTMParams &) = delete;
+    /** Default destructor */
+    ~LSTMParams() = default;
+    /** Set CIFG tensor parameters.
+     *
+     * @param[in] input_to_input_weights     2D weights tensor with dimensions [input_size, num_units]. Data types supported: F16/F32.
+     * @param[in] recurrent_to_input_weights 2D weights tensor with dimensions [output_size, num_units]. Data type supported: Same as @p input_to_input_weights.
+     * @param[in] cell_to_input_weights      1D weights tensor with dimensions [num_units]. Can be nullptr. Data type supported: Same as @p input_to_input_weights.
+     * @param[in] input_gate_bias            1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input_to_input_weights
+     *
+     * @return Reference to this LSTMParams object
+     */
+    LSTMParams &set_cifg_params(const T *input_to_input_weights, const T *recurrent_to_input_weights, const T *cell_to_input_weights, const T *input_gate_bias)
+    {
+        _input_to_input_weights     = input_to_input_weights;
+        _recurrent_to_input_weights = recurrent_to_input_weights;
+        _cell_to_input_weights      = cell_to_input_weights;
+        _input_gate_bias            = input_gate_bias;
+        _has_cifg_opt               = false;
+        return *this;
+    }
+    /** Set projection tensor parameters.
+     *
+     * @param[in] projection_weights 2D weights tensor with dimensions [output_size, num_units]. Data type supported: Data types supported: F16/F32.
+     * @param[in] projection_bias    1D weights tensor with dimensions [output_size]. Data type supported: Same as @p projection_weights.
+     *
+     * @return Reference to this LSTMParams object
+     */
+    LSTMParams &set_projection_params(const T *projection_weights, const T *projection_bias)
+    {
+        _projection_weights = projection_weights;
+        _projection_bias    = projection_bias;
+        _has_projection     = true;
+        return *this;
+    }
+    /** Set peephole tensor parameters.
+     *
+     * @param[in] cell_to_input_weights  1D weights tensor with dimensions [num_units]. Data type supported: Data types supported: F16/F32.
+     * @param[in] cell_to_forget_weights 1D weights tensor with dimensions [num_units]. Data type supported: Same as @p cell_to_input_weights.
+     * @param[in] cell_to_output_weights 1D weights tensor with dimensions [num_units]. Data type supported: Same as @p cell_to_input_weights.
+     *
+     * @return Reference to this LSTMParams object
+     */
+    LSTMParams &set_peephole_params(const T *cell_to_input_weights, const T *cell_to_forget_weights, const T *cell_to_output_weights)
+    {
+        _cell_to_input_weights  = cell_to_input_weights;
+        _cell_to_forget_weights = cell_to_forget_weights;
+        _cell_to_output_weights = cell_to_output_weights;
+        _has_peephole_opt       = true;
+        return *this;
+    }
+
+    const T *input_to_input_weights() const
+    {
+        return _input_to_input_weights;
+    }
+
+    const T *recurrent_to_input_weights() const
+    {
+        return _recurrent_to_input_weights;
+    }
+
+    const T *cell_to_input_weights() const
+    {
+        return _cell_to_input_weights;
+    }
+
+    const T *input_gate_bias() const
+    {
+        return _input_gate_bias;
+    }
+
+    const T *cell_to_forget_weights() const
+    {
+        return _cell_to_forget_weights;
+    }
+
+    const T *cell_to_output_weights() const
+    {
+        return _cell_to_output_weights;
+    }
+
+    const T *projection_weights() const
+    {
+        return _projection_weights;
+    }
+
+    const T *projection_bias() const
+    {
+        return _projection_bias;
+    }
+
+    bool has_peephole_opt() const
+    {
+        return _has_peephole_opt;
+    }
+
+    bool has_projection() const
+    {
+        return _has_projection;
+    }
+
+    bool has_cifg_opt() const
+    {
+        return _has_cifg_opt;
+    }
+
+private:
+    const T *_input_to_input_weights;
+    const T *_recurrent_to_input_weights;
+    const T *_cell_to_input_weights;
+    const T *_input_gate_bias;
+    const T *_cell_to_forget_weights;
+    const T *_cell_to_output_weights;
+    const T *_projection_weights;
+    const T *_projection_bias;
+    bool     _has_peephole_opt;
+    bool     _has_projection;
+    bool     _has_cifg_opt;
+};
+
+/** This function performs a single time step in a Long Short-Term Memory (LSTM) layer.
+ *
+ */
+class CLLSTMLayer : public IFunction
+{
+public:
+    /** Default constructor */
+    CLLSTMLayer(std::shared_ptr<IMemoryManager> memory_manager = nullptr);
+    /** Initialize function's tensors.
+     *
+     * @param[in]      input                       Source tensor. Input is a 2D tensor with dimensions [input_size, batch_size]. Data types supported: F16/F32.
+     * @param[in]      input_to_forget_weights     2D weights tensor with dimensions [input_size, num_units]. Data type supported: Same as @p input.
+     * @param[in]      input_to_cell_weights       2D weights tensor with dimensions [input_size, num_units]. Data type supported: Same as @p input.
+     * @param[in]      input_to_output_weights     2D weights tensor with dimensions [input_size, num_units]. Data type supported: Same as @p input.
+     * @param[in]      recurrent_to_forget_weights 2D weights tensor with dimensions [output_size, num_units]. Data type supported: Same as @p input.
+     * @param[in]      recurrent_to_cell_weights   2D weights tensor with dimensions [output_size, num_units]. Data type supported: Same as @p input.
+     * @param[in]      recurrent_to_output_weights 2D weights tensor with dimensions [output_size, num_units]. Data type supported: Same as @p input.
+     * @param[in]      forget_gate_bias            1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input.
+     * @param[in]      cell_bias                   1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input.
+     * @param[in]      output_gate_bias            1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input.
+     * @param[in, out] output_state                2D weights tensor with dimensions [output_size, batch_size]. Data type supported: Same as @p input.
+     * @param[in, out] cell_state                  2D tensor with dimensions [num_units, batch_size]. Data type supported: Same as @p input.
+     * @param[out]     scratch_buffer              2D tensor with dimensions [num_units * 4, batch_size] with CIFG or [num_units * 3, batch_size] without CIGF. Data type supported: Same as @p input.
+     * @param[out]     output                      Destination tensor. Output is a 2D tensor with dimensions [output_size, batch_size].
+     *                                             Data types supported: Same as @p input.
+     * @param[in]      lstm_params                 (Optional) Weights tensors used in peephole optimization:
+     *                                             input_to_input_weights       2D weights tensor with dimensions [input_size, num_units]. Data type supported: Same as @p input.
+     *                                             recurrent_to_input_weights   2D weights tensor with dimensions [output_size, num_units]. Data type supported: Same as @p input.
+     *                                             cell_to_input_weights        1D weights tensor with dimensions [num_units]. Can be nullptr. Data type supported: Same as @p input.
+     *                                             cell_to_forget_weights       1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input.
+     *                                             cell_to_output_weights       1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input.
+     *                                             input_gate_bias              1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input
+     *                                             projection_weights           2D weights tensor with dimensions [output_size, num_units]. Data type supported: Same as @p input.
+     *                                             projection_bias              1D weights tensor with dimensions [output_size]. Data type supported: Same as @p input.
+     * @param[in]      activation_info             Contains activation information described in @ref ActivationLayerInfo.
+     * @param[in]      cell_threshold              The clipping threshold for the cell state, such that values are bound within [-cell_clip, cell_clip]. If set to 0.0 then clipping is disabled.
+     * @param[in]      projection_threshold        The clipping threshold for the output from the projection layer, such that values are bound within [-proj_clip, proj_clip]. If set to 0.0 then clipping is disabled.
+     */
+    void configure(const ICLTensor *input, const ICLTensor *input_to_forget_weights, const ICLTensor *input_to_cell_weights, const ICLTensor *input_to_output_weights,
+                   const ICLTensor *recurrent_to_forget_weights, const ICLTensor *recurrent_to_cell_weights, const ICLTensor *recurrent_to_output_weights,
+                   const ICLTensor *forget_gate_bias, const ICLTensor *cell_bias, const ICLTensor *output_gate_bias, ICLTensor *output_state, ICLTensor *cell_state, ICLTensor *scratch_buffer, ICLTensor *output,
+                   const LSTMParams<ICLTensor> &lstm_params, const ActivationLayerInfo &activation_info, float cell_threshold = 0.f, float projection_threshold = 0.f);
+
+    /** Static function to check if given info will lead to a valid configuration of @ref CLLSTMLayer
+     *
+     * @param[in] input                       Source tensor info. Input is a 2D tensor info with dimensions [input_size, batch_size]. Data types supported: F16/F32.
+     * @param[in] input_to_forget_weights     2D weights tensor info with dimensions [input_size, num_units]. Data type supported: Same as @p input.
+     * @param[in] input_to_cell_weights       2D weights tensor info with dimensions [input_size, num_units]. Data type supported: Same as @p input.
+     * @param[in] input_to_output_weights     2D weights tensor info with dimensions [input_size, num_units]. Data type supported: Same as @p input.
+     * @param[in] recurrent_to_forget_weights 2D weights tensor info with dimensions [output_size, num_units]. Data type supported: Same as @p input.
+     * @param[in] recurrent_to_cell_weights   2D weights tensor info with dimensions [output_size, num_units]. Data type supported: Same as @p input.
+     * @param[in] recurrent_to_output_weights 2D weights tensor info with dimensions [output_size, num_units]. Data type supported: Same as @p input.
+     * @param[in] forget_gate_bias            1D weights tensor info with dimensions [num_units]. Data type supported: Same as @p input.
+     * @param[in] cell_bias                   1D weights tensor info with dimensions [num_units]. Data type supported: Same as @p input.
+     * @param[in] output_gate_bias            1D weights tensor info with dimensions [num_units]. Data type supported: Same as @p input.
+     * @param[in] output_state                2D weights tensor info with dimensions [output_size, batch_size]. Data type supported: Same as @p input.
+     * @param[in] cell_state                  2D tensor info with dimensions [num_units, batch_size]. Data type supported: Same as @p input.
+     * @param[in] scratch_buffer              2D tensor info with dimensions [num_units * 4, batch_size] with CIFG or [num_units * 3, batch_size] without CIGF. Data type supported: Same as @p input.
+     * @param[in] output                      Destination tensor info. Output is a 2D tensor with dimensions [output_size, batch_size].
+     *                                        Data types supported: Same as @p input.
+     * @param[in] lstm_params                 (Optional) Weights tensors used in peephole optimization:
+     *                                        input_to_input_weights       2D weights tensor with dimensions [input_size, num_units]. Data type supported: Same as @p input.
+     *                                        recurrent_to_input_weights   2D weights tensor with dimensions [output_size, num_units]. Data type supported: Same as @p input.
+     *                                        cell_to_input_weights        1D weights tensor with dimensions [num_units]. Can be nullptr. Data type supported: Same as @p input.
+     *                                        cell_to_forget_weights       1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input.
+     *                                        cell_to_output_weights       1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input.
+     *                                        input_gate_bias              1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input
+     *                                        projection_weights           2D weights tensor with dimensions [output_size, num_units]. Data type supported: Same as @p input.
+     *                                        projection_bias              1D weights tensor with dimensions [output_size]. Data type supported: Same as @p input.
+     * @param[in] activation_info             Contains activation information described in @ref ActivationLayerInfo.
+     * @param[in] cell_threshold              The clipping threshold for the cell state, such that values are bound within [-cell_clip, cell_clip]. If set to 0.0 then clipping is disabled.
+     * @param[in] projection_threshold        The clipping threshold for the output from the projection layer, such that values are bound within [-proj_clip, proj_clip]. If set to 0.0 then clipping is disabled.
+     *
+     * @return a status
+     */
+    static Status validate(const ITensorInfo *input, const ITensorInfo *input_to_forget_weights, const ITensorInfo *input_to_cell_weights, const ITensorInfo *input_to_output_weights,
+                           const ITensorInfo *recurrent_to_forget_weights, const ITensorInfo *recurrent_to_cell_weights, const ITensorInfo *recurrent_to_output_weights,
+                           const ITensorInfo *forget_gate_bias, const ITensorInfo *cell_bias, const ITensorInfo *output_gate_bias,
+                           const ITensorInfo *output_state, const ITensorInfo *cell_state, const ITensorInfo *scratch_buffer, const ITensorInfo *output,
+                           const LSTMParams<ITensorInfo> &lstm_params, const ActivationLayerInfo &activation_info, float cell_threshold = 0.f, float projection_threshold = 0.f);
+
+    // Inherited methods overridden:
+    void run() override;
+
+private:
+    CLMemoryGroup                   _memory_group;
+    CLFullyConnectedLayer           _fully_connected_input_gate;
+    CLGEMM                          _gemm_input_gate1;
+    CLGEMM                          _gemm_input_gate2;
+    CLTransposeKernel               _transpose_input_gate1;
+    CLTransposeKernel               _transpose_input_gate2;
+    CLArithmeticAdditionKernel      _accum_input_gate1;
+    CLArithmeticAddition            _accum_input_gate2;
+    CLArithmeticSubtractionKernel   _subtract_input_gate;
+    CLActivationLayerKernel         _activation_input_gate;
+    CLFullyConnectedLayer           _fully_connected_forget_gate;
+    CLGEMM                          _gemm_forget_gate1;
+    CLGEMM                          _gemm_forget_gate2;
+    CLTransposeKernel               _transpose_forget_gate1;
+    CLTransposeKernel               _transpose_forget_gate2;
+    CLArithmeticAdditionKernel      _accum_forget_gate1;
+    CLArithmeticAddition            _accum_forget_gate2;
+    CLActivationLayerKernel         _activation_forget_gate;
+    CLFullyConnectedLayer           _fully_connected_cell_state;
+    CLGEMM                          _gemm_cell_state1;
+    CLGEMM                          _gemm_cell_state2;
+    CLTransposeKernel               _transpose_cell_state1;
+    CLArithmeticAdditionKernel      _accum_cell_state1;
+    CLArithmeticAdditionKernel      _accum_cell_state2;
+    CLPixelWiseMultiplicationKernel _pixelwise_mul_cell_state1;
+    CLActivationLayerKernel         _activation_cell_state;
+    CLActivationLayerKernel         _cell_clip;
+    CLPixelWiseMultiplicationKernel _pixelwise_mul_cell_state2;
+    CLFullyConnectedLayer           _fully_connected_output;
+    CLGEMM                          _gemm_output1;
+    CLGEMM                          _gemm_output2;
+    CLTransposeKernel               _transpose_output1;
+    CLTransposeKernel               _transpose_output2;
+    CLArithmeticAdditionKernel      _accum_output1;
+    CLArithmeticAddition            _accum_output2;
+    CLActivationLayerKernel         _activation_output;
+    CLActivationLayerKernel         _activation_output_state;
+    CLPixelWiseMultiplicationKernel _pixelwise_mul_output_state;
+    CLFullyConnectedLayer           _fully_connected_output_state;
+    CLGEMM                          _gemm_output_state;
+    CLArithmeticAdditionKernel      _accum_output_state;
+    CLActivationLayerKernel         _projection_clip;
+    CLCopyKernel                    _copy_cell_state;
+    CLCopyKernel                    _copy_output;
+    CLWidthConcatenateLayer         _concat_scratch_buffer;
+    CLTensor                        _input_gate_out1;
+    CLTensor                        _input_gate_out2;
+    CLTensor                        _input_gate_out3;
+    CLTensor                        _input_gate_out4;
+    CLTensor                        _input_gate_out5;
+    CLTensor                        _input_gate_out6;
+    CLTensor                        _forget_gate_out1;
+    CLTensor                        _forget_gate_out2;
+    CLTensor                        _forget_gate_out3;
+    CLTensor                        _forget_gate_out4;
+    CLTensor                        _forget_gate_out5;
+    CLTensor                        _forget_gate_out6;
+    CLTensor                        _cell_state_out1;
+    CLTensor                        _cell_state_out2;
+    CLTensor                        _cell_state_out3;
+    CLTensor                        _cell_state_out4;
+    CLTensor                        _cell_state_out5;
+    CLTensor                        _output1;
+    CLTensor                        _output2;
+    CLTensor                        _output3;
+    CLTensor                        _output4;
+    CLTensor                        _output5;
+    CLTensor                        _output6;
+    CLTensor                        _cell_state_activation;
+    CLTensor                        _output_projection1;
+    CLTensor                        _ones;
+    bool                            _run_peephole_opt;
+    bool                            _run_cifg_opt;
+    bool                            _perform_cell_clipping;
+    bool                            _has_projection_weights;
+    bool                            _perform_projection_clipping;
+};
+}
+#endif /* __ARM_COMPUTE_CLLSTMLAYER_H__ */