forked from tensorflow/tensorflow
/
saved_model.pb.go
177 lines (159 loc) · 7.45 KB
/
saved_model.pb.go
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
// Code generated by protoc-gen-go. DO NOT EDIT.
// versions:
// protoc-gen-go v1.28.0
// protoc v3.19.4
// source: tensorflow/core/protobuf/saved_model.proto
package for_core_protos_go_proto
import (
protoreflect "google.golang.org/protobuf/reflect/protoreflect"
protoimpl "google.golang.org/protobuf/runtime/protoimpl"
reflect "reflect"
sync "sync"
)
const (
// Verify that this generated code is sufficiently up-to-date.
_ = protoimpl.EnforceVersion(20 - protoimpl.MinVersion)
// Verify that runtime/protoimpl is sufficiently up-to-date.
_ = protoimpl.EnforceVersion(protoimpl.MaxVersion - 20)
)
// SavedModel is the high level serialization format for TensorFlow Models.
// See [todo: doc links, similar to session_bundle] for more information.
type SavedModel struct {
state protoimpl.MessageState
sizeCache protoimpl.SizeCache
unknownFields protoimpl.UnknownFields
// The schema version of the SavedModel instance. Used for versioning when
// making future changes to the specification/implementation. Initial value
// at release will be 1.
SavedModelSchemaVersion int64 `protobuf:"varint,1,opt,name=saved_model_schema_version,json=savedModelSchemaVersion,proto3" json:"saved_model_schema_version,omitempty"`
// One or more MetaGraphs.
MetaGraphs []*MetaGraphDef `protobuf:"bytes,2,rep,name=meta_graphs,json=metaGraphs,proto3" json:"meta_graphs,omitempty"`
}
func (x *SavedModel) Reset() {
*x = SavedModel{}
if protoimpl.UnsafeEnabled {
mi := &file_tensorflow_core_protobuf_saved_model_proto_msgTypes[0]
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
ms.StoreMessageInfo(mi)
}
}
func (x *SavedModel) String() string {
return protoimpl.X.MessageStringOf(x)
}
func (*SavedModel) ProtoMessage() {}
func (x *SavedModel) ProtoReflect() protoreflect.Message {
mi := &file_tensorflow_core_protobuf_saved_model_proto_msgTypes[0]
if protoimpl.UnsafeEnabled && x != nil {
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
if ms.LoadMessageInfo() == nil {
ms.StoreMessageInfo(mi)
}
return ms
}
return mi.MessageOf(x)
}
// Deprecated: Use SavedModel.ProtoReflect.Descriptor instead.
func (*SavedModel) Descriptor() ([]byte, []int) {
return file_tensorflow_core_protobuf_saved_model_proto_rawDescGZIP(), []int{0}
}
func (x *SavedModel) GetSavedModelSchemaVersion() int64 {
if x != nil {
return x.SavedModelSchemaVersion
}
return 0
}
func (x *SavedModel) GetMetaGraphs() []*MetaGraphDef {
if x != nil {
return x.MetaGraphs
}
return nil
}
var File_tensorflow_core_protobuf_saved_model_proto protoreflect.FileDescriptor
var file_tensorflow_core_protobuf_saved_model_proto_rawDesc = []byte{
0x0a, 0x2a, 0x74, 0x65, 0x6e, 0x73, 0x6f, 0x72, 0x66, 0x6c, 0x6f, 0x77, 0x2f, 0x63, 0x6f, 0x72,
0x65, 0x2f, 0x70, 0x72, 0x6f, 0x74, 0x6f, 0x62, 0x75, 0x66, 0x2f, 0x73, 0x61, 0x76, 0x65, 0x64,
0x5f, 0x6d, 0x6f, 0x64, 0x65, 0x6c, 0x2e, 0x70, 0x72, 0x6f, 0x74, 0x6f, 0x12, 0x0a, 0x74, 0x65,
0x6e, 0x73, 0x6f, 0x72, 0x66, 0x6c, 0x6f, 0x77, 0x1a, 0x29, 0x74, 0x65, 0x6e, 0x73, 0x6f, 0x72,
0x66, 0x6c, 0x6f, 0x77, 0x2f, 0x63, 0x6f, 0x72, 0x65, 0x2f, 0x70, 0x72, 0x6f, 0x74, 0x6f, 0x62,
0x75, 0x66, 0x2f, 0x6d, 0x65, 0x74, 0x61, 0x5f, 0x67, 0x72, 0x61, 0x70, 0x68, 0x2e, 0x70, 0x72,
0x6f, 0x74, 0x6f, 0x22, 0x84, 0x01, 0x0a, 0x0a, 0x53, 0x61, 0x76, 0x65, 0x64, 0x4d, 0x6f, 0x64,
0x65, 0x6c, 0x12, 0x3b, 0x0a, 0x1a, 0x73, 0x61, 0x76, 0x65, 0x64, 0x5f, 0x6d, 0x6f, 0x64, 0x65,
0x6c, 0x5f, 0x73, 0x63, 0x68, 0x65, 0x6d, 0x61, 0x5f, 0x76, 0x65, 0x72, 0x73, 0x69, 0x6f, 0x6e,
0x18, 0x01, 0x20, 0x01, 0x28, 0x03, 0x52, 0x17, 0x73, 0x61, 0x76, 0x65, 0x64, 0x4d, 0x6f, 0x64,
0x65, 0x6c, 0x53, 0x63, 0x68, 0x65, 0x6d, 0x61, 0x56, 0x65, 0x72, 0x73, 0x69, 0x6f, 0x6e, 0x12,
0x39, 0x0a, 0x0b, 0x6d, 0x65, 0x74, 0x61, 0x5f, 0x67, 0x72, 0x61, 0x70, 0x68, 0x73, 0x18, 0x02,
0x20, 0x03, 0x28, 0x0b, 0x32, 0x18, 0x2e, 0x74, 0x65, 0x6e, 0x73, 0x6f, 0x72, 0x66, 0x6c, 0x6f,
0x77, 0x2e, 0x4d, 0x65, 0x74, 0x61, 0x47, 0x72, 0x61, 0x70, 0x68, 0x44, 0x65, 0x66, 0x52, 0x0a,
0x6d, 0x65, 0x74, 0x61, 0x47, 0x72, 0x61, 0x70, 0x68, 0x73, 0x42, 0x88, 0x01, 0x0a, 0x18, 0x6f,
0x72, 0x67, 0x2e, 0x74, 0x65, 0x6e, 0x73, 0x6f, 0x72, 0x66, 0x6c, 0x6f, 0x77, 0x2e, 0x66, 0x72,
0x61, 0x6d, 0x65, 0x77, 0x6f, 0x72, 0x6b, 0x42, 0x10, 0x53, 0x61, 0x76, 0x65, 0x64, 0x4d, 0x6f,
0x64, 0x65, 0x6c, 0x50, 0x72, 0x6f, 0x74, 0x6f, 0x73, 0x50, 0x01, 0x5a, 0x55, 0x67, 0x69, 0x74,
0x68, 0x75, 0x62, 0x2e, 0x63, 0x6f, 0x6d, 0x2f, 0x74, 0x65, 0x6e, 0x73, 0x6f, 0x72, 0x66, 0x6c,
0x6f, 0x77, 0x2f, 0x74, 0x65, 0x6e, 0x73, 0x6f, 0x72, 0x66, 0x6c, 0x6f, 0x77, 0x2f, 0x74, 0x65,
0x6e, 0x73, 0x6f, 0x72, 0x66, 0x6c, 0x6f, 0x77, 0x2f, 0x67, 0x6f, 0x2f, 0x63, 0x6f, 0x72, 0x65,
0x2f, 0x70, 0x72, 0x6f, 0x74, 0x6f, 0x62, 0x75, 0x66, 0x2f, 0x66, 0x6f, 0x72, 0x5f, 0x63, 0x6f,
0x72, 0x65, 0x5f, 0x70, 0x72, 0x6f, 0x74, 0x6f, 0x73, 0x5f, 0x67, 0x6f, 0x5f, 0x70, 0x72, 0x6f,
0x74, 0x6f, 0xf8, 0x01, 0x01, 0x62, 0x06, 0x70, 0x72, 0x6f, 0x74, 0x6f, 0x33,
}
var (
file_tensorflow_core_protobuf_saved_model_proto_rawDescOnce sync.Once
file_tensorflow_core_protobuf_saved_model_proto_rawDescData = file_tensorflow_core_protobuf_saved_model_proto_rawDesc
)
func file_tensorflow_core_protobuf_saved_model_proto_rawDescGZIP() []byte {
file_tensorflow_core_protobuf_saved_model_proto_rawDescOnce.Do(func() {
file_tensorflow_core_protobuf_saved_model_proto_rawDescData = protoimpl.X.CompressGZIP(file_tensorflow_core_protobuf_saved_model_proto_rawDescData)
})
return file_tensorflow_core_protobuf_saved_model_proto_rawDescData
}
var file_tensorflow_core_protobuf_saved_model_proto_msgTypes = make([]protoimpl.MessageInfo, 1)
var file_tensorflow_core_protobuf_saved_model_proto_goTypes = []interface{}{
(*SavedModel)(nil), // 0: tensorflow.SavedModel
(*MetaGraphDef)(nil), // 1: tensorflow.MetaGraphDef
}
var file_tensorflow_core_protobuf_saved_model_proto_depIdxs = []int32{
1, // 0: tensorflow.SavedModel.meta_graphs:type_name -> tensorflow.MetaGraphDef
1, // [1:1] is the sub-list for method output_type
1, // [1:1] is the sub-list for method input_type
1, // [1:1] is the sub-list for extension type_name
1, // [1:1] is the sub-list for extension extendee
0, // [0:1] is the sub-list for field type_name
}
func init() { file_tensorflow_core_protobuf_saved_model_proto_init() }
func file_tensorflow_core_protobuf_saved_model_proto_init() {
if File_tensorflow_core_protobuf_saved_model_proto != nil {
return
}
file_tensorflow_core_protobuf_meta_graph_proto_init()
if !protoimpl.UnsafeEnabled {
file_tensorflow_core_protobuf_saved_model_proto_msgTypes[0].Exporter = func(v interface{}, i int) interface{} {
switch v := v.(*SavedModel); i {
case 0:
return &v.state
case 1:
return &v.sizeCache
case 2:
return &v.unknownFields
default:
return nil
}
}
}
type x struct{}
out := protoimpl.TypeBuilder{
File: protoimpl.DescBuilder{
GoPackagePath: reflect.TypeOf(x{}).PkgPath(),
RawDescriptor: file_tensorflow_core_protobuf_saved_model_proto_rawDesc,
NumEnums: 0,
NumMessages: 1,
NumExtensions: 0,
NumServices: 0,
},
GoTypes: file_tensorflow_core_protobuf_saved_model_proto_goTypes,
DependencyIndexes: file_tensorflow_core_protobuf_saved_model_proto_depIdxs,
MessageInfos: file_tensorflow_core_protobuf_saved_model_proto_msgTypes,
}.Build()
File_tensorflow_core_protobuf_saved_model_proto = out.File
file_tensorflow_core_protobuf_saved_model_proto_rawDesc = nil
file_tensorflow_core_protobuf_saved_model_proto_goTypes = nil
file_tensorflow_core_protobuf_saved_model_proto_depIdxs = nil
}