1 // Copyright 2022 Google LLC 2 // 3 // This source code is licensed under the BSD-style license found in the 4 // LICENSE file in the root directory of this source tree. 5 // 6 // Auto-generated file. Do not edit! 7 // Specification: src/operator-strings.yaml 8 // Generator: tools/generate-enum.py 9 10 #pragma once 11 12 enum xnn_operator_type { 13 xnn_operator_type_invalid = 0, 14 xnn_operator_type_abs_nc_f16, 15 xnn_operator_type_abs_nc_f32, 16 xnn_operator_type_add_nd_f16, 17 xnn_operator_type_add_nd_f32, 18 xnn_operator_type_add_nd_qs8, 19 xnn_operator_type_add_nd_qu8, 20 xnn_operator_type_argmax_pooling_nhwc_f32, 21 xnn_operator_type_average_pooling_nhwc_f16, 22 xnn_operator_type_average_pooling_nhwc_f32, 23 xnn_operator_type_average_pooling_nhwc_qu8, 24 xnn_operator_type_bankers_rounding_nc_f16, 25 xnn_operator_type_bankers_rounding_nc_f32, 26 xnn_operator_type_ceiling_nc_f16, 27 xnn_operator_type_ceiling_nc_f32, 28 xnn_operator_type_channel_shuffle_nc_x8, 29 xnn_operator_type_channel_shuffle_nc_x32, 30 xnn_operator_type_clamp_nc_f16, 31 xnn_operator_type_clamp_nc_f32, 32 xnn_operator_type_clamp_nc_s8, 33 xnn_operator_type_clamp_nc_u8, 34 xnn_operator_type_constant_pad_nd_x8, 35 xnn_operator_type_constant_pad_nd_x16, 36 xnn_operator_type_constant_pad_nd_x32, 37 xnn_operator_type_convert_nc_f16_f32, 38 xnn_operator_type_convert_nc_f32_f16, 39 xnn_operator_type_convert_nc_f32_qs8, 40 xnn_operator_type_convert_nc_f32_qu8, 41 xnn_operator_type_convert_nc_qs8, 42 xnn_operator_type_convert_nc_qs8_f32, 43 xnn_operator_type_convert_nc_qu8, 44 xnn_operator_type_convert_nc_qu8_f32, 45 xnn_operator_type_convolution_nhwc_f16, 46 xnn_operator_type_convolution_nhwc_f32, 47 xnn_operator_type_convolution_nhwc_qc8, 48 xnn_operator_type_convolution_nhwc_qs8, 49 xnn_operator_type_convolution_nhwc_qu8, 50 xnn_operator_type_convolution_nchw_f32, 51 xnn_operator_type_copy_nc_x8, 52 xnn_operator_type_copy_nc_x16, 53 xnn_operator_type_copy_nc_x32, 54 xnn_operator_type_deconvolution_nhwc_f16, 55 xnn_operator_type_deconvolution_nhwc_f32, 56 xnn_operator_type_deconvolution_nhwc_qs8, 57 xnn_operator_type_deconvolution_nhwc_qu8, 58 xnn_operator_type_depth_to_space_nchw2nhwc_x32, 59 xnn_operator_type_depth_to_space_nhwc_x8, 60 xnn_operator_type_depth_to_space_nhwc_x16, 61 xnn_operator_type_depth_to_space_nhwc_x32, 62 xnn_operator_type_divide_nd_f16, 63 xnn_operator_type_divide_nd_f32, 64 xnn_operator_type_elu_nc_f16, 65 xnn_operator_type_elu_nc_f32, 66 xnn_operator_type_elu_nc_qs8, 67 xnn_operator_type_floor_nc_f16, 68 xnn_operator_type_floor_nc_f32, 69 xnn_operator_type_fully_connected_nc_f16, 70 xnn_operator_type_fully_connected_nc_f32, 71 xnn_operator_type_fully_connected_nc_qs8, 72 xnn_operator_type_fully_connected_nc_qu8, 73 xnn_operator_type_global_average_pooling_nwc_f16, 74 xnn_operator_type_global_average_pooling_nwc_f32, 75 xnn_operator_type_global_average_pooling_nwc_qs8, 76 xnn_operator_type_global_average_pooling_nwc_qu8, 77 xnn_operator_type_global_average_pooling_ncw_f32, 78 xnn_operator_type_hardswish_nc_f16, 79 xnn_operator_type_hardswish_nc_f32, 80 xnn_operator_type_leaky_relu_nc_f16, 81 xnn_operator_type_leaky_relu_nc_f32, 82 xnn_operator_type_leaky_relu_nc_qs8, 83 xnn_operator_type_leaky_relu_nc_qu8, 84 xnn_operator_type_max_pooling_nhwc_f16, 85 xnn_operator_type_max_pooling_nhwc_f32, 86 xnn_operator_type_max_pooling_nhwc_s8, 87 xnn_operator_type_max_pooling_nhwc_u8, 88 xnn_operator_type_maximum_nd_f16, 89 xnn_operator_type_maximum_nd_f32, 90 xnn_operator_type_minimum_nd_f16, 91 xnn_operator_type_minimum_nd_f32, 92 xnn_operator_type_multiply_nd_f16, 93 xnn_operator_type_multiply_nd_f32, 94 xnn_operator_type_multiply_nd_qs8, 95 xnn_operator_type_multiply_nd_qu8, 96 xnn_operator_type_negate_nc_f16, 97 xnn_operator_type_negate_nc_f32, 98 xnn_operator_type_prelu_nc_f16, 99 xnn_operator_type_prelu_nc_f32, 100 xnn_operator_type_resize_bilinear_nhwc_f16, 101 xnn_operator_type_resize_bilinear_nhwc_f32, 102 xnn_operator_type_resize_bilinear_nhwc_s8, 103 xnn_operator_type_resize_bilinear_nhwc_u8, 104 xnn_operator_type_resize_bilinear_nchw_f32, 105 xnn_operator_type_sigmoid_nc_f16, 106 xnn_operator_type_sigmoid_nc_f32, 107 xnn_operator_type_sigmoid_nc_qs8, 108 xnn_operator_type_sigmoid_nc_qu8, 109 xnn_operator_type_softmax_nc_f16, 110 xnn_operator_type_softmax_nc_f32, 111 xnn_operator_type_softmax_nc_qu8, 112 xnn_operator_type_space_to_depth_nhwc_x8, 113 xnn_operator_type_space_to_depth_nhwc_x16, 114 xnn_operator_type_space_to_depth_nhwc_x32, 115 xnn_operator_type_square_nc_f16, 116 xnn_operator_type_square_nc_f32, 117 xnn_operator_type_square_root_nc_f16, 118 xnn_operator_type_square_root_nc_f32, 119 xnn_operator_type_squared_difference_nd_f16, 120 xnn_operator_type_squared_difference_nd_f32, 121 xnn_operator_type_subtract_nd_f16, 122 xnn_operator_type_subtract_nd_f32, 123 xnn_operator_type_subtract_nd_qs8, 124 xnn_operator_type_subtract_nd_qu8, 125 xnn_operator_type_tanh_nc_qs8, 126 xnn_operator_type_tanh_nc_qu8, 127 xnn_operator_type_truncation_nc_f16, 128 xnn_operator_type_truncation_nc_f32, 129 xnn_operator_type_transpose_nd_x8, 130 xnn_operator_type_transpose_nd_x16, 131 xnn_operator_type_transpose_nd_x32, 132 xnn_operator_type_unpooling_nhwc_x32, 133 };