1 // Copyright 2020 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 #include <math.h>
7 #include <stddef.h>
8 #include <stdint.h>
9
10 #include <xnnpack/common.h>
11 #include <xnnpack/log.h>
12 #include <xnnpack/subgraph.h>
13
14
15 // This function is defined inline when logging is disabled
16 #if XNN_LOG_LEVEL > 0
xnn_operator_type_to_string(enum xnn_operator_type type)17 const char* xnn_operator_type_to_string(enum xnn_operator_type type) {
18 switch (type) {
19 case xnn_operator_type_invalid:
20 return "Invalid";
21 case xnn_operator_type_abs_nc_f32:
22 return "Abs (NC, F32)";
23 case xnn_operator_type_add_nd_f16:
24 return "Add (ND, F16)";
25 case xnn_operator_type_add_nd_f32:
26 return "Add (ND, F32)";
27 case xnn_operator_type_add_nd_qs8:
28 return "Add (ND, QS8)";
29 case xnn_operator_type_argmax_pooling_nhwc_f32:
30 return "ArgMax Pooling (NHWC, F32)";
31 case xnn_operator_type_average_pooling_nhwc_f32:
32 return "Average Pooling (NHWC, F32)";
33 case xnn_operator_type_average_pooling_nhwc_qu8:
34 return "Average Pooling (NHWC, QU8)";
35 case xnn_operator_type_bankers_rounding_nc_f32:
36 return "Bankers Rounding (NC, F32)";
37 case xnn_operator_type_ceiling_nc_f32:
38 return "Ceiling (NC, F32)";
39 case xnn_operator_type_channel_shuffle_nc_x32:
40 return "Channel Shuffle (NC, X32)";
41 case xnn_operator_type_channel_shuffle_nc_x8:
42 return "Channel Shuffle (NC, X8)";
43 case xnn_operator_type_clamp_nc_f32:
44 return "Clamp (NC, F32)";
45 case xnn_operator_type_clamp_nc_u8:
46 return "Clamp (NC, U8)";
47 case xnn_operator_type_constant_pad_nd_x32:
48 return "Constant Pad (ND, X32)";
49 case xnn_operator_type_convolution_nhwc_f16:
50 return "Convolution (NHWC, F16)";
51 case xnn_operator_type_convolution_nhwc_f32:
52 return "Convolution (NHWC, F32)";
53 case xnn_operator_type_convolution_nhwc_qs8:
54 return "Convolution (NHWC, QS8)";
55 case xnn_operator_type_convolution_nhwc_qu8:
56 return "Convolution (NHWC, QU8)";
57 case xnn_operator_type_convolution_nchw_f32:
58 return "Convolution (NCHW, F32)";
59 case xnn_operator_type_copy_nc_x32:
60 return "Copy (NC, X32)";
61 case xnn_operator_type_deconvolution_nhwc_f32:
62 return "Deconvolution (NHWC, F32)";
63 case xnn_operator_type_deconvolution_nhwc_qu8:
64 return "Deconvolution (NHWC, QU8)";
65 case xnn_operator_type_depth_to_space_nchw2nhwc_x32:
66 return "Depth To Space (NCHW2NHWC, X32)";
67 case xnn_operator_type_depth_to_space_nhwc_x32:
68 return "Depth To Space (NHWC, X32)";
69 case xnn_operator_type_divide_nd_f32:
70 return "Divide (ND, F32)";
71 case xnn_operator_type_elu_nc_f32:
72 return "ELU (NC, F32)";
73 case xnn_operator_type_floor_nc_f32:
74 return "Floor (NC, F32)";
75 case xnn_operator_type_fully_connected_nc_f32:
76 return "Fully Connected (NC, F32)";
77 case xnn_operator_type_fully_connected_nc_qu8:
78 return "Fully Connected (NC, QU8)";
79 case xnn_operator_type_global_average_pooling_nwc_f16:
80 return "Global Average Pooling (NWC, F16)";
81 case xnn_operator_type_global_average_pooling_nwc_f32:
82 return "Global Average Pooling (NWC, F32)";
83 case xnn_operator_type_global_average_pooling_nwc_qs8:
84 return "Global Average Pooling (NWC, QS8)";
85 case xnn_operator_type_global_average_pooling_nwc_qu8:
86 return "Global Average Pooling (NWC, QU8)";
87 case xnn_operator_type_global_average_pooling_ncw_f32:
88 return "Global Average Pooling (NCW, F32)";
89 case xnn_operator_type_hardswish_nc_f16:
90 return "HardSwish (NC, F16)";
91 case xnn_operator_type_hardswish_nc_f32:
92 return "HardSwish (NC, F32)";
93 case xnn_operator_type_leaky_relu_nc_f32:
94 return "Leaky ReLU (NC, F32)";
95 case xnn_operator_type_leaky_relu_nc_qu8:
96 return "Leaky ReLU (NC, QU8)";
97 case xnn_operator_type_max_pooling_nhwc_f32:
98 return "Max Pooling (NHWC, F32)";
99 case xnn_operator_type_max_pooling_nhwc_u8:
100 return "Max Pooling (NHWC, U8)";
101 case xnn_operator_type_maximum_nd_f32:
102 return "Maximum (ND, F32)";
103 case xnn_operator_type_minimum_nd_f32:
104 return "Minimum (ND, F32)";
105 case xnn_operator_type_multiply_nd_f16:
106 return "Multiply (ND, F16)";
107 case xnn_operator_type_multiply_nd_f32:
108 return "Multiply (ND, F32)";
109 case xnn_operator_type_negate_nc_f32:
110 return "Negate (NC, F32)";
111 case xnn_operator_type_prelu_nc_f32:
112 return "PReLU (NC, F32)";
113 case xnn_operator_type_resize_bilinear_nhwc_f32:
114 return "Resize Bilinear (NHWC, F32)";
115 case xnn_operator_type_resize_bilinear_nchw_f32:
116 return "Resize Bilinear (NCHW, F32)";
117 case xnn_operator_type_sigmoid_nc_f32:
118 return "Sigmoid (NC, F32)";
119 case xnn_operator_type_sigmoid_nc_qu8:
120 return "Sigmoid (NC, QU8)";
121 case xnn_operator_type_softmax_nc_f32:
122 return "Softmax (NC, F32)";
123 case xnn_operator_type_softmax_nc_qu8:
124 return "Softmax (NC, QU8)";
125 case xnn_operator_type_square_nc_f32:
126 return "Square (NC, F32)";
127 case xnn_operator_type_square_root_nc_f32:
128 return "Square Root (NC, F32)";
129 case xnn_operator_type_squared_difference_nd_f32:
130 return "Squared Difference (NC, F32)";
131 case xnn_operator_type_subtract_nd_f32:
132 return "Subtract (ND, F32)";
133 case xnn_operator_type_truncation_nc_f32:
134 return "Truncation (NC, F32)";
135 case xnn_operator_type_unpooling_nhwc_x32:
136 return "Unpooling (NHWC, X32)";
137 }
138 XNN_UNREACHABLE;
139 return NULL;
140 }
141 #endif // XNN_LOG_LEVEL > 0
142