1 /* 2 * Copyright (c) 2017-2020 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_CLSOFTMAXLAYER_H 25 #define ARM_COMPUTE_CLSOFTMAXLAYER_H 26 27 #include "arm_compute/runtime/CL/CLTensor.h" 28 #include "arm_compute/runtime/CL/functions/CLPermute.h" 29 #include "arm_compute/runtime/IFunction.h" 30 #include "arm_compute/runtime/IMemoryManager.h" 31 #include "arm_compute/runtime/MemoryGroup.h" 32 33 #include <memory> 34 35 namespace arm_compute 36 { 37 class CLCompileContext; 38 class CLLogits1DMaxShiftExpSumKernel; 39 class CLLogits1DNormKernel; 40 class ICLTensor; 41 class ITensorInfo; 42 43 /** Basic function to compute a SoftmaxLayer. 44 * 45 * Softmax is calculated by : 46 * @f[ out = exp((x - max(x)) * beta) / sum(exp((x - max(x)) * beta)) @f] 47 * 48 * Log Softmax is calculated by : 49 * @f[ out = (x - max(x) * beta) - log(\sum{e^{x - max(x) * beta}}) @f] 50 * 51 * This function runs the following kernels: 52 * -# If axis is not 0: 53 * -# @ref CLPermute 54 * -# @ref CLLogits1DNormKernel 55 * -# @ref CLLogits1DMaxShiftExpSumKernel 56 */ 57 template <bool IS_LOG = false> 58 class CLSoftmaxLayerGeneric : public IFunction 59 { 60 public: 61 /** Constructor */ 62 CLSoftmaxLayerGeneric(std::shared_ptr<IMemoryManager> memory_manager = nullptr); 63 /** Prevent instances of this class from being copied */ 64 CLSoftmaxLayerGeneric(const CLSoftmaxLayerGeneric &) = delete; 65 /** Prevent instances of this class from being copied */ 66 CLSoftmaxLayerGeneric &operator=(const CLSoftmaxLayerGeneric &) = delete; 67 /** Prevent instances of this class to be moved */ 68 CLSoftmaxLayerGeneric(CLSoftmaxLayerGeneric &&) = delete; 69 /** Prevent instances of this class to be moved */ 70 CLSoftmaxLayerGeneric &operator=(CLSoftmaxLayerGeneric &&) = delete; 71 /** Default destructor */ 72 ~CLSoftmaxLayerGeneric(); 73 /** Set the input and output tensors. 74 * 75 * @param[in] input Source tensor. Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32 for Softmax and F16/F32 for Log Softmax 76 * @param[out] output Destination tensor. Data types supported: same as @p input 77 * @param[in] beta (Optional) A scaling factor for the exponent. Defaults to 1.f 78 * @param[in] axis (Optional) The dimension in which to apply the function. E.g. for input of shape 4x5x6 and 79 * axis=1, softmax will be applied to 4x6=24 vectors of size 5. Defaults to 0 80 */ 81 void configure(const ICLTensor *input, ICLTensor *output, float beta = 1.0f, int32_t axis = 0); 82 /** Set the input and output tensors. 83 * 84 * @param[in] compile_context The compile context to be used. 85 * @param[in] input Source tensor. Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32 for Softmax and F16/F32 for Log Softmax 86 * @param[out] output Destination tensor. Data types supported: same as @p input 87 * @param[in] beta (Optional) A scaling factor for the exponent. Defaults to 1.f 88 * @param[in] axis (Optional) The dimension in which to apply the function. E.g. for input of shape 4x5x6 and 89 * axis=1, softmax will be applied to 4x6=24 vectors of size 5. Defaults to 0 90 */ 91 void configure(const CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, float beta = 1.0f, int32_t axis = 0); 92 /** Static function to check if given info will lead to a valid configuration of @ref CLSoftmaxLayer 93 * 94 * @param[in] input Source tensor. Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32 for Softmax and F16/F32 for Log Softmax 95 * @param[in] output Destination tensor. Data types supported: same as @p input 96 * @param[in] beta (Optional) A scaling factor for the exponent. Defaults to 1.f 97 * @param[in] axis (Optional) The dimension in which to apply the function. E.g. for input of shape 4x5x6 and 98 * axis=1, softmax will be applied to 4x6=24 vectors of size 5. Defaults to 0 99 * 100 * @return a status 101 */ 102 static Status validate(const ITensorInfo *input, const ITensorInfo *output, float beta = 1.0f, int32_t axis = 0); 103 104 // Inherited methods overridden: 105 void run() override; 106 107 private: 108 MemoryGroup _memory_group; 109 CLPermute _permute_input; 110 CLPermute _permute_output; 111 std::unique_ptr<CLLogits1DMaxShiftExpSumKernel> _max_shift_exp_sum_kernel; 112 std::unique_ptr<CLLogits1DNormKernel> _norm_kernel; 113 CLTensor _max; 114 CLTensor _sum; 115 CLTensor _tmp; 116 CLTensor _input_permuted; 117 CLTensor _output_permuted; 118 bool _needs_permute; 119 }; 120 121 using CLSoftmaxLayer = CLSoftmaxLayerGeneric<false>; 122 using CLLogSoftmaxLayer = CLSoftmaxLayerGeneric<true>; 123 } // namespace arm_compute 124 #endif /* ARM_COMPUTE_CLSOFTMAXLAYER_H */ 125