COMPMID-1060 LSTM FP32 NEON

Change-Id: I0bdf874e61917903c26f713ec41a7ffc29e07233
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/143892
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>

1 files changed, 210 insertions, 0 deletions

diff --git a/arm_compute/runtime/NEON/functions/NELSTMLayer.h b/arm_compute/runtime/NEON/functions/NELSTMLayer.h
new file mode 100644
index 0000000000..9c4ab2b068
--- /dev/null
+++ b/arm_compute/runtime/NEON/functions/NELSTMLayer.h
@@ -0,0 +1,210 @@
+/*
+ * 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_NELSTMLAYER_H__
+#define __ARM_COMPUTE_NELSTMLAYER_H__
+
+#include "arm_compute/core/NEON/kernels/NEActivationLayerKernel.h"
+#include "arm_compute/core/NEON/kernels/NEArithmeticAdditionKernel.h"
+#include "arm_compute/core/NEON/kernels/NEArithmeticSubtractionKernel.h"
+#include "arm_compute/core/NEON/kernels/NECopyKernel.h"
+#include "arm_compute/core/NEON/kernels/NEPixelWiseMultiplicationKernel.h"
+
+#include "arm_compute/core/Types.h"
+#include "arm_compute/runtime/NEON/INESimpleFunction.h"
+#include "arm_compute/runtime/NEON/functions/NEArithmeticAddition.h"
+#include "arm_compute/runtime/NEON/functions/NEFullyConnectedLayer.h"
+#include "arm_compute/runtime/NEON/functions/NEGEMM.h"
+#include "arm_compute/runtime/NEON/functions/NEWidthConcatenateLayer.h"
+#include "arm_compute/runtime/common/LSTMParams.h"
+
+namespace arm_compute
+{
+// Forward declarations
+class ITensor;
+
+/** Basic function to run @ref NELSTMLayer */
+class NELSTMLayer : public IFunction
+{
+public:
+    /** Default constructor */
+    NELSTMLayer(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]  output_state_in             2D weights tensor with dimensions [output_size, batch_size]. Data type supported: Same as @p input.
+     * @param[in]  cell_state_in               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_state_out            2D weights tensor with dimensions [output_size, batch_size]. Data type supported: Same as @p input.
+     * @param[out] cell_state_out              2D tensor with dimensions [num_units, batch_size]. 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 ITensor *input,
+                   const ITensor *input_to_forget_weights, const ITensor *input_to_cell_weights, const ITensor *input_to_output_weights,
+                   const ITensor *recurrent_to_forget_weights, const ITensor *recurrent_to_cell_weights, const ITensor *recurrent_to_output_weights,
+                   const ITensor *forget_gate_bias, const ITensor *cell_bias, const ITensor *output_gate_bias,
+                   const ITensor *output_state_in, const ITensor *cell_state_in,
+                   ITensor *scratch_buffer, ITensor *output_state_out, ITensor *cell_state_out, ITensor *output,
+                   const LSTMParams<ITensor> &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 NELSTMLayer
+     *
+     * @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] output_state_in             2D weights tensor with dimensions [output_size, batch_size]. Data type supported: Same as @p input.
+     * @param[in] cell_state_in               2D tensor with dimensions [num_units, batch_size]. Data type supported: Same as @p input.
+     * @param[in] 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[in] output_state_out            2D weights tensor with dimensions [output_size, batch_size]. Data type supported: Same as @p input.
+     * @param[in] cell_state_out              2D tensor with dimensions [num_units, batch_size]. Data type supported: Same as @p input.
+     * @param[in] 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.
+     *
+     * @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_in, const ITensorInfo *cell_state_in,
+                           const ITensorInfo *scratch_buffer, const ITensorInfo *output_state_out, const ITensorInfo *cell_state_out, 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:
+    MemoryGroup                     _memory_group;
+    NEFullyConnectedLayer           _fully_connected_input_gate;
+    NEGEMM                          _gemm_input_gate;
+    NETransposeKernel               _transpose_input_gate;
+    NEArithmeticAdditionKernel      _accum_input_gate1;
+    NEArithmeticAddition            _accum_input_gate2;
+    NEArithmeticSubtractionKernel   _subtract_input_gate;
+    NEPixelWiseMultiplicationKernel _pixelwise_mul_input_gate;
+    NEActivationLayerKernel         _activation_input_gate;
+    NEFullyConnectedLayer           _fully_connected_forget_gate;
+    NEGEMM                          _gemm_forget_gate;
+    NETransposeKernel               _transpose_forget_gate;
+    NEArithmeticAdditionKernel      _accum_forget_gate1;
+    NEArithmeticAddition            _accum_forget_gate2;
+    NEPixelWiseMultiplicationKernel _pixelwise_mul_forget_gate;
+    NEActivationLayerKernel         _activation_forget_gate;
+    NEFullyConnectedLayer           _fully_connected_cell_state;
+    NEGEMM                          _gemm_cell_state1;
+    NEGEMM                          _gemm_cell_state2;
+    NETransposeKernel               _transpose_cell_state;
+    NEArithmeticAdditionKernel      _accum_cell_state1;
+    NEArithmeticAdditionKernel      _accum_cell_state2;
+    NEPixelWiseMultiplicationKernel _pixelwise_mul_cell_state1;
+    NEActivationLayerKernel         _activation_cell_state;
+    NEActivationLayerKernel         _cell_clip;
+    NEPixelWiseMultiplicationKernel _pixelwise_mul_cell_state2;
+    NEFullyConnectedLayer           _fully_connected_output;
+    NEGEMM                          _gemm_output;
+    NEPixelWiseMultiplicationKernel _pixelwise_mul_output_state1;
+    NETransposeKernel               _transpose_output;
+    NEArithmeticAdditionKernel      _accum_output1;
+    NEArithmeticAddition            _accum_output2;
+    NEActivationLayerKernel         _activation_output;
+    NEActivationLayerKernel         _activation_output_state;
+    NEPixelWiseMultiplicationKernel _pixelwise_mul_output_state2;
+    NEFullyConnectedLayer           _fully_connected_output_state;
+    NEGEMM                          _gemm_output_state;
+    NEArithmeticAdditionKernel      _accum_output_state;
+    NEActivationLayerKernel         _projection_clip;
+    NECopyKernel                    _copy_cell_state;
+    NECopyKernel                    _copy_output;
+    NEWidthConcatenateLayer         _concat_scratch_buffer;
+    Tensor                          _input_gate_out1;
+    Tensor                          _input_gate_out2;
+    Tensor                          _input_gate_out3;
+    Tensor                          _input_gate_out4;
+    Tensor                          _input_gate_out5;
+    Tensor                          _forget_gate_out1;
+    Tensor                          _forget_gate_out2;
+    Tensor                          _forget_gate_out3;
+    Tensor                          _forget_gate_out4;
+    Tensor                          _forget_gate_out5;
+    Tensor                          _cell_state_out1;
+    Tensor                          _cell_state_out2;
+    Tensor                          _cell_state_out3;
+    Tensor                          _cell_state_out4;
+    Tensor                          _cell_state_out5;
+    Tensor                          _output1;
+    Tensor                          _output2;
+    Tensor                          _output3;
+    Tensor                          _output4;
+    Tensor                          _output5;
+    Tensor                          _cell_state_activation;
+    Tensor                          _output_state1;
+    Tensor                          _ones;
+    bool                            _run_peephole_opt;
+    bool                            _run_cifg_opt;
+    bool                            _perform_cell_clipping;
+    bool                            _has_projection_weights;
+    bool                            _perform_projection_clipping;
+};
+} // namespace arm_compute
+#endif /* __ARM_COMPUTE_NELSTMLAYER_H__ */