1 /* 2 * Copyright (c) 2018-2021 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/NECopy.h" 31 #include "arm_compute/runtime/NEON/functions/NEFullyConnectedLayer.h" 32 #include "arm_compute/runtime/NEON/functions/NEGEMM.h" 33 34 namespace arm_compute 35 { 36 // Forward declarations 37 class ITensor; 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 * Valid data layouts: 58 * - NHWC 59 * - NCHW 60 * 61 * Valid data type configurations: 62 * |src0 |src1 |src2 |src3 |dst0 |dst1 | 63 * |:------|:------|:------|:------|:------|:------| 64 * |F16 |F16 |F16 |F16 |F16 |F16 | 65 * |F32 |F32 |F32 |F32 |F32 |F32 | 66 * 67 * @param[in] input Input is a 2-D tensor of shape [input_size, batch_size]. Data types supported: F16/F32 68 * @param[in] weights Weights tensor of shape [input_size, num_units] that multiplies the input. Data types supported: Same as @p input 69 * @param[in] recurrent_weights Weights tensor of shape [num_units, num_units] that multiplies the current 'state'. Data types supported: Same as @p input 70 * @param[in] bias Bias vector of shape [num_units]. Data types supported: Same as @p input 71 * @param[out] output Output tensor of shape [num_units, batch_size]. Data types supported: Same as @p input 72 * @param[in,out] hidden_state Output tensor of shape [num_units, batch_size]. Data types supported: Same as @p input 73 * @param[in] info Activation layer parameter. 74 */ 75 void configure(const ITensor *input, const ITensor *weights, const ITensor *recurrent_weights, const ITensor *bias, ITensor *hidden_state, ITensor *output, ActivationLayerInfo &info); 76 /** Initialize the function 77 * 78 * @param[in] input Input is a 2-D tensor of shape [input_size, batch_size]. Data types supported: F16/F32 79 * @param[in] weights Weights tensor of shape [input_size, num_units] that multiplies the input. Data types supported: Same as @p input 80 * @param[in] recurrent_weights Weights tensor of shape [num_units, num_units] that multiplies the current 'state'. Data types supported: Same as @p input 81 * @param[in] bias Bias vector of shape [num_units]. Data types supported: Same as @p input 82 * @param[in] output Output tensor of shape [num_units, batch_size]. Data types supported: Same as @p input 83 * @param[in] hidden_state Output tensor of shape [num_units, batch_size]. Data types supported: Same as @p input 84 * @param[in] info Activation layer parameter. 85 * 86 * @return a status 87 */ 88 static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *recurrent_weights, const ITensorInfo *bias, const ITensorInfo *hidden_state, const ITensorInfo *output, 89 const ActivationLayerInfo &info); 90 91 // Inherited methods overridden: 92 void run() override; 93 void prepare() override; 94 95 private: 96 MemoryGroup _memory_group; 97 NEGEMM _gemm_state_f; 98 NEArithmeticAddition _add_f; 99 NEActivationLayer _activation; 100 NEFullyConnectedLayer _fully_connected; 101 NECopy _copy_f; 102 Tensor _fully_connected_out; 103 Tensor _gemm_output; 104 Tensor _add_output; 105 bool _is_prepared; 106 }; 107 } // namespace arm_compute 108 #endif /* ARM_COMPUTE_NERNNLAYER_H */ 109