1 /* 2 * Copyright (c) 2018-2020 Arm Limited. 3 * 4 * SPDX-License-Identifier: MIT 5 * 6 * Permission is hereby granted, free of charge, to any person obtaining a copy 7 * of this software and associated documentation files (the "Software"), to 8 * deal in the Software without restriction, including without limitation the 9 * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or 10 * sell copies of the Software, and to permit persons to whom the Software is 11 * furnished to do so, subject to the following conditions: 12 * 13 * The above copyright notice and this permission notice shall be included in all 14 * copies or substantial portions of the Software. 15 * 16 * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR 17 * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, 18 * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE 19 * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER 20 * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, 21 * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE 22 * SOFTWARE. 23 */ 24 #ifndef ARM_COMPUTE_NERNNLAYER_H 25 #define ARM_COMPUTE_NERNNLAYER_H 26 27 #include "arm_compute/core/Types.h" 28 #include "arm_compute/runtime/NEON/functions/NEActivationLayer.h" 29 #include "arm_compute/runtime/NEON/functions/NEArithmeticAddition.h" 30 #include "arm_compute/runtime/NEON/functions/NEFullyConnectedLayer.h" 31 #include "arm_compute/runtime/NEON/functions/NEGEMM.h" 32 33 namespace arm_compute 34 { 35 // Forward declarations 36 class ITensor; 37 class NECopyKernel; 38 39 /** Basic function to run @ref NERNNLayer */ 40 class NERNNLayer : public IFunction 41 { 42 public: 43 /** Default constructor */ 44 NERNNLayer(std::shared_ptr<IMemoryManager> memory_manager = nullptr); 45 /** Prevent instances of this class from being copied (As this class contains pointers) */ 46 NERNNLayer(const NERNNLayer &) = delete; 47 /** Prevent instances of this class from being moved (As this class contains pointers) */ 48 NERNNLayer(NERNNLayer &&) = delete; 49 /** Prevent instances of this class from being copied (As this class contains pointers) */ 50 NERNNLayer &operator=(const NERNNLayer &) = delete; 51 /** Prevent instances of this class from being moved (As this class contains pointers) */ 52 NERNNLayer &operator=(NERNNLayer &&) = delete; 53 /** Default destructor */ 54 ~NERNNLayer(); 55 /** Initialize the function 56 * 57 * @param[in] input Input is a 2-D tensor of shape [input_size, batch_size]. Data types supported: F16/F32 58 * @param[in] weights Weights tensor of shape [input_size, num_units] that multiplies the input. Data types supported: Same as @p input 59 * @param[in] recurrent_weights Weights tensor of shape [num_units, num_units] that multiplies the current 'state'. Data types supported: Same as @p input 60 * @param[in] bias Bias vector of shape [num_units]. Data types supported: Same as @p input 61 * @param[out] output Output tensor of shape [num_units, batch_size]. Data types supported: Same as @p input 62 * @param[in,out] hidden_state Output tensor of shape [num_units, batch_size]. Data types supported: Same as @p input 63 * @param[in] info Activation layer parameter. 64 */ 65 void configure(const ITensor *input, const ITensor *weights, const ITensor *recurrent_weights, const ITensor *bias, ITensor *hidden_state, ITensor *output, ActivationLayerInfo &info); 66 /** Initialize the function 67 * 68 * @param[in] input Input is a 2-D tensor of shape [input_size, batch_size]. Data types supported: F16/F32 69 * @param[in] weights Weights tensor of shape [input_size, num_units] that multiplies the input. Data types supported: Same as @p input 70 * @param[in] recurrent_weights Weights tensor of shape [num_units, num_units] that multiplies the current 'state'. Data types supported: Same as @p input 71 * @param[in] bias Bias vector of shape [num_units]. Data types supported: Same as @p input 72 * @param[in] output Output tensor of shape [num_units, batch_size]. Data types supported: Same as @p input 73 * @param[in] hidden_state Output tensor of shape [num_units, batch_size]. Data types supported: Same as @p input 74 * @param[in] info Activation layer parameter. 75 * 76 * @return a status 77 */ 78 static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *recurrent_weights, const ITensorInfo *bias, const ITensorInfo *hidden_state, const ITensorInfo *output, 79 const ActivationLayerInfo &info); 80 81 // Inherited methods overridden: 82 void run() override; 83 void prepare() override; 84 85 private: 86 MemoryGroup _memory_group; 87 NEGEMM _gemm_state_f; 88 NEArithmeticAddition _add_f; 89 NEActivationLayer _activation; 90 NEFullyConnectedLayer _fully_connected; 91 std::unique_ptr<NECopyKernel> _copy_kernel; 92 Tensor _fully_connected_out; 93 Tensor _gemm_output; 94 Tensor _add_output; 95 bool _is_prepared; 96 }; 97 } // namespace arm_compute 98 #endif /* ARM_COMPUTE_NERNNLAYER_H */ 99