forked from tensorflow/tensorflow
/
meta_graph.pb.go
1647 lines (1487 loc) · 65.6 KB
/
meta_graph.pb.go
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// Code generated by protoc-gen-go. DO NOT EDIT.
// versions:
// protoc-gen-go v1.28.1
// protoc v3.21.7
// source: tensorflow/core/protobuf/meta_graph.proto
package for_core_protos_go_proto
import (
graph_go_proto "github.com/galeone/tensorflow/tensorflow/go/core/framework/graph_go_proto"
op_def_go_proto "github.com/galeone/tensorflow/tensorflow/go/core/framework/op_def_go_proto"
tensor_shape_go_proto "github.com/galeone/tensorflow/tensorflow/go/core/framework/tensor_shape_go_proto"
types_go_proto "github.com/galeone/tensorflow/tensorflow/go/core/framework/types_go_proto"
protoreflect "google.golang.org/protobuf/reflect/protoreflect"
protoimpl "google.golang.org/protobuf/runtime/protoimpl"
anypb "google.golang.org/protobuf/types/known/anypb"
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)
)
// Protocol buffer containing the following which are necessary to restart
// training, run inference. It can be used to serialize/de-serialize memory
// objects necessary for running computation in a graph when crossing the
// process boundary. It can be used for long term storage of graphs,
// cross-language execution of graphs, etc.
//
// MetaInfoDef
// GraphDef
// SaverDef
// CollectionDef
// TensorInfo
// SignatureDef
type MetaGraphDef struct {
state protoimpl.MessageState
sizeCache protoimpl.SizeCache
unknownFields protoimpl.UnknownFields
MetaInfoDef *MetaGraphDef_MetaInfoDef `protobuf:"bytes,1,opt,name=meta_info_def,json=metaInfoDef,proto3" json:"meta_info_def,omitempty"`
// GraphDef.
GraphDef *graph_go_proto.GraphDef `protobuf:"bytes,2,opt,name=graph_def,json=graphDef,proto3" json:"graph_def,omitempty"`
// SaverDef.
SaverDef *SaverDef `protobuf:"bytes,3,opt,name=saver_def,json=saverDef,proto3" json:"saver_def,omitempty"`
// collection_def: Map from collection name to collections.
// See CollectionDef section for details.
CollectionDef map[string]*CollectionDef `protobuf:"bytes,4,rep,name=collection_def,json=collectionDef,proto3" json:"collection_def,omitempty" protobuf_key:"bytes,1,opt,name=key,proto3" protobuf_val:"bytes,2,opt,name=value,proto3"`
// signature_def: Map from user supplied key for a signature to a single
// SignatureDef.
SignatureDef map[string]*SignatureDef `protobuf:"bytes,5,rep,name=signature_def,json=signatureDef,proto3" json:"signature_def,omitempty" protobuf_key:"bytes,1,opt,name=key,proto3" protobuf_val:"bytes,2,opt,name=value,proto3"`
// Asset file def to be used with the defined graph.
AssetFileDef []*AssetFileDef `protobuf:"bytes,6,rep,name=asset_file_def,json=assetFileDef,proto3" json:"asset_file_def,omitempty"`
// Extra information about the structure of functions and stateful objects.
ObjectGraphDef *SavedObjectGraph `protobuf:"bytes,7,opt,name=object_graph_def,json=objectGraphDef,proto3" json:"object_graph_def,omitempty"`
}
func (x *MetaGraphDef) Reset() {
*x = MetaGraphDef{}
if protoimpl.UnsafeEnabled {
mi := &file_tensorflow_core_protobuf_meta_graph_proto_msgTypes[0]
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
ms.StoreMessageInfo(mi)
}
}
func (x *MetaGraphDef) String() string {
return protoimpl.X.MessageStringOf(x)
}
func (*MetaGraphDef) ProtoMessage() {}
func (x *MetaGraphDef) ProtoReflect() protoreflect.Message {
mi := &file_tensorflow_core_protobuf_meta_graph_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 MetaGraphDef.ProtoReflect.Descriptor instead.
func (*MetaGraphDef) Descriptor() ([]byte, []int) {
return file_tensorflow_core_protobuf_meta_graph_proto_rawDescGZIP(), []int{0}
}
func (x *MetaGraphDef) GetMetaInfoDef() *MetaGraphDef_MetaInfoDef {
if x != nil {
return x.MetaInfoDef
}
return nil
}
func (x *MetaGraphDef) GetGraphDef() *graph_go_proto.GraphDef {
if x != nil {
return x.GraphDef
}
return nil
}
func (x *MetaGraphDef) GetSaverDef() *SaverDef {
if x != nil {
return x.SaverDef
}
return nil
}
func (x *MetaGraphDef) GetCollectionDef() map[string]*CollectionDef {
if x != nil {
return x.CollectionDef
}
return nil
}
func (x *MetaGraphDef) GetSignatureDef() map[string]*SignatureDef {
if x != nil {
return x.SignatureDef
}
return nil
}
func (x *MetaGraphDef) GetAssetFileDef() []*AssetFileDef {
if x != nil {
return x.AssetFileDef
}
return nil
}
func (x *MetaGraphDef) GetObjectGraphDef() *SavedObjectGraph {
if x != nil {
return x.ObjectGraphDef
}
return nil
}
// CollectionDef should cover most collections.
// To add a user-defined collection, do one of the following:
// 1. For simple data types, such as string, int, float:
// tf.add_to_collection("your_collection_name", your_simple_value)
// strings will be stored as bytes_list.
//
// 2. For Protobuf types, there are three ways to add them:
//
// 1. tf.add_to_collection("your_collection_name",
// your_proto.SerializeToString())
//
// collection_def {
// key: "user_defined_bytes_collection"
// value {
// bytes_list {
// value: "queue_name: \"test_queue\"\n"
// }
// }
// }
//
// or
//
// 2. tf.add_to_collection("your_collection_name", str(your_proto))
//
// collection_def {
// key: "user_defined_string_collection"
// value {
// bytes_list {
// value: "\n\ntest_queue"
// }
// }
// }
//
// or
//
// 3. any_buf = any_pb2.Any()
// tf.add_to_collection("your_collection_name",
// any_buf.Pack(your_proto))
//
// collection_def {
// key: "user_defined_any_collection"
// value {
// any_list {
// value {
// type_url: "type.googleapis.com/tensorflow.QueueRunnerDef"
// value: "\n\ntest_queue"
// }
// }
// }
// }
//
// 3. For Python objects, implement to_proto() and from_proto(), and register
// them in the following manner:
// ops.register_proto_function("your_collection_name",
// proto_type,
// to_proto=YourPythonObject.to_proto,
// from_proto=YourPythonObject.from_proto)
// These functions will be invoked to serialize and de-serialize the
// collection. For example,
// ops.register_proto_function(ops.GraphKeys.GLOBAL_VARIABLES,
// proto_type=variable_pb2.VariableDef,
// to_proto=Variable.to_proto,
// from_proto=Variable.from_proto)
type CollectionDef struct {
state protoimpl.MessageState
sizeCache protoimpl.SizeCache
unknownFields protoimpl.UnknownFields
// Types that are assignable to Kind:
//
// *CollectionDef_NodeList_
// *CollectionDef_BytesList_
// *CollectionDef_Int64List_
// *CollectionDef_FloatList_
// *CollectionDef_AnyList_
Kind isCollectionDef_Kind `protobuf_oneof:"kind"`
}
func (x *CollectionDef) Reset() {
*x = CollectionDef{}
if protoimpl.UnsafeEnabled {
mi := &file_tensorflow_core_protobuf_meta_graph_proto_msgTypes[1]
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
ms.StoreMessageInfo(mi)
}
}
func (x *CollectionDef) String() string {
return protoimpl.X.MessageStringOf(x)
}
func (*CollectionDef) ProtoMessage() {}
func (x *CollectionDef) ProtoReflect() protoreflect.Message {
mi := &file_tensorflow_core_protobuf_meta_graph_proto_msgTypes[1]
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 CollectionDef.ProtoReflect.Descriptor instead.
func (*CollectionDef) Descriptor() ([]byte, []int) {
return file_tensorflow_core_protobuf_meta_graph_proto_rawDescGZIP(), []int{1}
}
func (m *CollectionDef) GetKind() isCollectionDef_Kind {
if m != nil {
return m.Kind
}
return nil
}
func (x *CollectionDef) GetNodeList() *CollectionDef_NodeList {
if x, ok := x.GetKind().(*CollectionDef_NodeList_); ok {
return x.NodeList
}
return nil
}
func (x *CollectionDef) GetBytesList() *CollectionDef_BytesList {
if x, ok := x.GetKind().(*CollectionDef_BytesList_); ok {
return x.BytesList
}
return nil
}
func (x *CollectionDef) GetInt64List() *CollectionDef_Int64List {
if x, ok := x.GetKind().(*CollectionDef_Int64List_); ok {
return x.Int64List
}
return nil
}
func (x *CollectionDef) GetFloatList() *CollectionDef_FloatList {
if x, ok := x.GetKind().(*CollectionDef_FloatList_); ok {
return x.FloatList
}
return nil
}
func (x *CollectionDef) GetAnyList() *CollectionDef_AnyList {
if x, ok := x.GetKind().(*CollectionDef_AnyList_); ok {
return x.AnyList
}
return nil
}
type isCollectionDef_Kind interface {
isCollectionDef_Kind()
}
type CollectionDef_NodeList_ struct {
NodeList *CollectionDef_NodeList `protobuf:"bytes,1,opt,name=node_list,json=nodeList,proto3,oneof"`
}
type CollectionDef_BytesList_ struct {
BytesList *CollectionDef_BytesList `protobuf:"bytes,2,opt,name=bytes_list,json=bytesList,proto3,oneof"`
}
type CollectionDef_Int64List_ struct {
Int64List *CollectionDef_Int64List `protobuf:"bytes,3,opt,name=int64_list,json=int64List,proto3,oneof"`
}
type CollectionDef_FloatList_ struct {
FloatList *CollectionDef_FloatList `protobuf:"bytes,4,opt,name=float_list,json=floatList,proto3,oneof"`
}
type CollectionDef_AnyList_ struct {
AnyList *CollectionDef_AnyList `protobuf:"bytes,5,opt,name=any_list,json=anyList,proto3,oneof"`
}
func (*CollectionDef_NodeList_) isCollectionDef_Kind() {}
func (*CollectionDef_BytesList_) isCollectionDef_Kind() {}
func (*CollectionDef_Int64List_) isCollectionDef_Kind() {}
func (*CollectionDef_FloatList_) isCollectionDef_Kind() {}
func (*CollectionDef_AnyList_) isCollectionDef_Kind() {}
// Information about a Tensor necessary for feeding or retrieval.
type TensorInfo struct {
state protoimpl.MessageState
sizeCache protoimpl.SizeCache
unknownFields protoimpl.UnknownFields
// Types that are assignable to Encoding:
//
// *TensorInfo_Name
// *TensorInfo_CooSparse_
// *TensorInfo_CompositeTensor_
Encoding isTensorInfo_Encoding `protobuf_oneof:"encoding"`
Dtype types_go_proto.DataType `protobuf:"varint,2,opt,name=dtype,proto3,enum=tensorflow.DataType" json:"dtype,omitempty"`
// The static shape should be recorded here, to the extent that it can
// be known in advance. In the case of a SparseTensor, this field describes
// the logical shape of the represented tensor (aka dense_shape).
TensorShape *tensor_shape_go_proto.TensorShapeProto `protobuf:"bytes,3,opt,name=tensor_shape,json=tensorShape,proto3" json:"tensor_shape,omitempty"`
}
func (x *TensorInfo) Reset() {
*x = TensorInfo{}
if protoimpl.UnsafeEnabled {
mi := &file_tensorflow_core_protobuf_meta_graph_proto_msgTypes[2]
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
ms.StoreMessageInfo(mi)
}
}
func (x *TensorInfo) String() string {
return protoimpl.X.MessageStringOf(x)
}
func (*TensorInfo) ProtoMessage() {}
func (x *TensorInfo) ProtoReflect() protoreflect.Message {
mi := &file_tensorflow_core_protobuf_meta_graph_proto_msgTypes[2]
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 TensorInfo.ProtoReflect.Descriptor instead.
func (*TensorInfo) Descriptor() ([]byte, []int) {
return file_tensorflow_core_protobuf_meta_graph_proto_rawDescGZIP(), []int{2}
}
func (m *TensorInfo) GetEncoding() isTensorInfo_Encoding {
if m != nil {
return m.Encoding
}
return nil
}
func (x *TensorInfo) GetName() string {
if x, ok := x.GetEncoding().(*TensorInfo_Name); ok {
return x.Name
}
return ""
}
func (x *TensorInfo) GetCooSparse() *TensorInfo_CooSparse {
if x, ok := x.GetEncoding().(*TensorInfo_CooSparse_); ok {
return x.CooSparse
}
return nil
}
func (x *TensorInfo) GetCompositeTensor() *TensorInfo_CompositeTensor {
if x, ok := x.GetEncoding().(*TensorInfo_CompositeTensor_); ok {
return x.CompositeTensor
}
return nil
}
func (x *TensorInfo) GetDtype() types_go_proto.DataType {
if x != nil {
return x.Dtype
}
return types_go_proto.DataType(0)
}
func (x *TensorInfo) GetTensorShape() *tensor_shape_go_proto.TensorShapeProto {
if x != nil {
return x.TensorShape
}
return nil
}
type isTensorInfo_Encoding interface {
isTensorInfo_Encoding()
}
type TensorInfo_Name struct {
// For dense `Tensor`s, the name of the tensor in the graph.
Name string `protobuf:"bytes,1,opt,name=name,proto3,oneof"`
}
type TensorInfo_CooSparse_ struct {
// There are many possible encodings of sparse matrices
// (https://en.wikipedia.org/wiki/Sparse_matrix). Currently, TensorFlow
// uses only the COO encoding. This is supported and documented in the
// SparseTensor Python class.
CooSparse *TensorInfo_CooSparse `protobuf:"bytes,4,opt,name=coo_sparse,json=cooSparse,proto3,oneof"`
}
type TensorInfo_CompositeTensor_ struct {
// Generic encoding for CompositeTensors.
CompositeTensor *TensorInfo_CompositeTensor `protobuf:"bytes,5,opt,name=composite_tensor,json=compositeTensor,proto3,oneof"`
}
func (*TensorInfo_Name) isTensorInfo_Encoding() {}
func (*TensorInfo_CooSparse_) isTensorInfo_Encoding() {}
func (*TensorInfo_CompositeTensor_) isTensorInfo_Encoding() {}
// SignatureDef defines the signature of a computation supported by a TensorFlow
// graph.
//
// For example, a model with two loss computations, sharing a single input,
// might have the following signature_def map, in a MetaGraphDef message.
//
// Note that across the two SignatureDefs "loss_A" and "loss_B", the input key,
// output key, and method_name are identical, and will be used by system(s) that
// implement or rely upon this particular loss method. The output tensor names
// differ, demonstrating how different outputs can exist for the same method.
//
// signature_def {
// key: "loss_A"
// value {
// inputs {
// key: "input"
// value {
// name: "input:0"
// dtype: DT_STRING
// tensor_shape: ...
// }
// }
// outputs {
// key: "loss_output"
// value {
// name: "loss_output_A:0"
// dtype: DT_FLOAT
// tensor_shape: ...
// }
// }
// method_name: "some/package/compute_loss"
// }
// ...
// }
//
// signature_def {
// key: "loss_B"
// value {
// inputs {
// key: "input"
// value {
// name: "input:0"
// dtype: DT_STRING
// tensor_shape: ...
// }
// }
// outputs {
// key: "loss_output"
// value {
// name: "loss_output_B:0"
// dtype: DT_FLOAT
// tensor_shape: ...
// }
// }
// method_name: "some/package/compute_loss"
// }
// ...
// }
type SignatureDef struct {
state protoimpl.MessageState
sizeCache protoimpl.SizeCache
unknownFields protoimpl.UnknownFields
// Named input parameters.
Inputs map[string]*TensorInfo `protobuf:"bytes,1,rep,name=inputs,proto3" json:"inputs,omitempty" protobuf_key:"bytes,1,opt,name=key,proto3" protobuf_val:"bytes,2,opt,name=value,proto3"`
// Named output parameters.
Outputs map[string]*TensorInfo `protobuf:"bytes,2,rep,name=outputs,proto3" json:"outputs,omitempty" protobuf_key:"bytes,1,opt,name=key,proto3" protobuf_val:"bytes,2,opt,name=value,proto3"`
// Extensible method_name information enabling third-party users to mark a
// SignatureDef as supporting a particular method. This enables producers and
// consumers of SignatureDefs, e.g. a model definition library and a serving
// library to have a clear hand-off regarding the semantics of a computation.
//
// Note that multiple SignatureDefs in a single MetaGraphDef may have the same
// method_name. This is commonly used to support multi-headed computation,
// where a single graph computation may return multiple results.
MethodName string `protobuf:"bytes,3,opt,name=method_name,json=methodName,proto3" json:"method_name,omitempty"`
}
func (x *SignatureDef) Reset() {
*x = SignatureDef{}
if protoimpl.UnsafeEnabled {
mi := &file_tensorflow_core_protobuf_meta_graph_proto_msgTypes[3]
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
ms.StoreMessageInfo(mi)
}
}
func (x *SignatureDef) String() string {
return protoimpl.X.MessageStringOf(x)
}
func (*SignatureDef) ProtoMessage() {}
func (x *SignatureDef) ProtoReflect() protoreflect.Message {
mi := &file_tensorflow_core_protobuf_meta_graph_proto_msgTypes[3]
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 SignatureDef.ProtoReflect.Descriptor instead.
func (*SignatureDef) Descriptor() ([]byte, []int) {
return file_tensorflow_core_protobuf_meta_graph_proto_rawDescGZIP(), []int{3}
}
func (x *SignatureDef) GetInputs() map[string]*TensorInfo {
if x != nil {
return x.Inputs
}
return nil
}
func (x *SignatureDef) GetOutputs() map[string]*TensorInfo {
if x != nil {
return x.Outputs
}
return nil
}
func (x *SignatureDef) GetMethodName() string {
if x != nil {
return x.MethodName
}
return ""
}
// An asset file def for a single file or a set of sharded files with the same
// name.
type AssetFileDef struct {
state protoimpl.MessageState
sizeCache protoimpl.SizeCache
unknownFields protoimpl.UnknownFields
// The tensor to bind the asset filename to.
TensorInfo *TensorInfo `protobuf:"bytes,1,opt,name=tensor_info,json=tensorInfo,proto3" json:"tensor_info,omitempty"`
// The filename within an assets directory. Note: does not include the path
// prefix, i.e. directories. For an asset at /tmp/path/vocab.txt, the filename
// would be "vocab.txt".
Filename string `protobuf:"bytes,2,opt,name=filename,proto3" json:"filename,omitempty"`
}
func (x *AssetFileDef) Reset() {
*x = AssetFileDef{}
if protoimpl.UnsafeEnabled {
mi := &file_tensorflow_core_protobuf_meta_graph_proto_msgTypes[4]
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
ms.StoreMessageInfo(mi)
}
}
func (x *AssetFileDef) String() string {
return protoimpl.X.MessageStringOf(x)
}
func (*AssetFileDef) ProtoMessage() {}
func (x *AssetFileDef) ProtoReflect() protoreflect.Message {
mi := &file_tensorflow_core_protobuf_meta_graph_proto_msgTypes[4]
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 AssetFileDef.ProtoReflect.Descriptor instead.
func (*AssetFileDef) Descriptor() ([]byte, []int) {
return file_tensorflow_core_protobuf_meta_graph_proto_rawDescGZIP(), []int{4}
}
func (x *AssetFileDef) GetTensorInfo() *TensorInfo {
if x != nil {
return x.TensorInfo
}
return nil
}
func (x *AssetFileDef) GetFilename() string {
if x != nil {
return x.Filename
}
return ""
}
// Meta information regarding the graph to be exported. To be used by users
// of this protocol buffer to encode information regarding their meta graph.
type MetaGraphDef_MetaInfoDef struct {
state protoimpl.MessageState
sizeCache protoimpl.SizeCache
unknownFields protoimpl.UnknownFields
// User specified Version string. Can be the name of the model and revision,
// steps this model has been trained to, etc.
MetaGraphVersion string `protobuf:"bytes,1,opt,name=meta_graph_version,json=metaGraphVersion,proto3" json:"meta_graph_version,omitempty"`
// A copy of the OpDefs used by the producer of this graph_def.
// Descriptions and Ops not used in graph_def are stripped out.
StrippedOpList *op_def_go_proto.OpList `protobuf:"bytes,2,opt,name=stripped_op_list,json=strippedOpList,proto3" json:"stripped_op_list,omitempty"`
// A serialized protobuf. Can be the time this meta graph is created, or
// modified, or name of the model.
AnyInfo *anypb.Any `protobuf:"bytes,3,opt,name=any_info,json=anyInfo,proto3" json:"any_info,omitempty"`
// User supplied tag(s) on the meta_graph and included graph_def.
//
// MetaGraphDefs should be tagged with their capabilities or use-cases.
// Examples: "train", "serve", "gpu", "tpu", etc.
// These tags enable loaders to access the MetaGraph(s) appropriate for a
// specific use-case or runtime environment.
Tags []string `protobuf:"bytes,4,rep,name=tags,proto3" json:"tags,omitempty"`
// The __version__ string of the tensorflow build used to write this graph.
// This will be populated by the framework, which will overwrite any user
// supplied value.
TensorflowVersion string `protobuf:"bytes,5,opt,name=tensorflow_version,json=tensorflowVersion,proto3" json:"tensorflow_version,omitempty"`
// The __git_version__ string of the tensorflow build used to write this
// graph. This will be populated by the framework, which will overwrite any
// user supplied value.
TensorflowGitVersion string `protobuf:"bytes,6,opt,name=tensorflow_git_version,json=tensorflowGitVersion,proto3" json:"tensorflow_git_version,omitempty"`
// A flag to denote whether default-valued attrs have been stripped from
// the nodes in this graph_def.
StrippedDefaultAttrs bool `protobuf:"varint,7,opt,name=stripped_default_attrs,json=strippedDefaultAttrs,proto3" json:"stripped_default_attrs,omitempty"`
// FunctionDef name to aliases mapping.
FunctionAliases map[string]string `protobuf:"bytes,8,rep,name=function_aliases,json=functionAliases,proto3" json:"function_aliases,omitempty" protobuf_key:"bytes,1,opt,name=key,proto3" protobuf_val:"bytes,2,opt,name=value,proto3"`
}
func (x *MetaGraphDef_MetaInfoDef) Reset() {
*x = MetaGraphDef_MetaInfoDef{}
if protoimpl.UnsafeEnabled {
mi := &file_tensorflow_core_protobuf_meta_graph_proto_msgTypes[5]
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
ms.StoreMessageInfo(mi)
}
}
func (x *MetaGraphDef_MetaInfoDef) String() string {
return protoimpl.X.MessageStringOf(x)
}
func (*MetaGraphDef_MetaInfoDef) ProtoMessage() {}
func (x *MetaGraphDef_MetaInfoDef) ProtoReflect() protoreflect.Message {
mi := &file_tensorflow_core_protobuf_meta_graph_proto_msgTypes[5]
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 MetaGraphDef_MetaInfoDef.ProtoReflect.Descriptor instead.
func (*MetaGraphDef_MetaInfoDef) Descriptor() ([]byte, []int) {
return file_tensorflow_core_protobuf_meta_graph_proto_rawDescGZIP(), []int{0, 0}
}
func (x *MetaGraphDef_MetaInfoDef) GetMetaGraphVersion() string {
if x != nil {
return x.MetaGraphVersion
}
return ""
}
func (x *MetaGraphDef_MetaInfoDef) GetStrippedOpList() *op_def_go_proto.OpList {
if x != nil {
return x.StrippedOpList
}
return nil
}
func (x *MetaGraphDef_MetaInfoDef) GetAnyInfo() *anypb.Any {
if x != nil {
return x.AnyInfo
}
return nil
}
func (x *MetaGraphDef_MetaInfoDef) GetTags() []string {
if x != nil {
return x.Tags
}
return nil
}
func (x *MetaGraphDef_MetaInfoDef) GetTensorflowVersion() string {
if x != nil {
return x.TensorflowVersion
}
return ""
}
func (x *MetaGraphDef_MetaInfoDef) GetTensorflowGitVersion() string {
if x != nil {
return x.TensorflowGitVersion
}
return ""
}
func (x *MetaGraphDef_MetaInfoDef) GetStrippedDefaultAttrs() bool {
if x != nil {
return x.StrippedDefaultAttrs
}
return false
}
func (x *MetaGraphDef_MetaInfoDef) GetFunctionAliases() map[string]string {
if x != nil {
return x.FunctionAliases
}
return nil
}
// NodeList is used for collecting nodes in graph. For example
//
// collection_def {
// key: "summaries"
// value {
// node_list {
// value: "input_producer/ScalarSummary:0"
// value: "shuffle_batch/ScalarSummary:0"
// value: "ImageSummary:0"
// }
// }
type CollectionDef_NodeList struct {
state protoimpl.MessageState
sizeCache protoimpl.SizeCache
unknownFields protoimpl.UnknownFields
Value []string `protobuf:"bytes,1,rep,name=value,proto3" json:"value,omitempty"`
}
func (x *CollectionDef_NodeList) Reset() {
*x = CollectionDef_NodeList{}
if protoimpl.UnsafeEnabled {
mi := &file_tensorflow_core_protobuf_meta_graph_proto_msgTypes[9]
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
ms.StoreMessageInfo(mi)
}
}
func (x *CollectionDef_NodeList) String() string {
return protoimpl.X.MessageStringOf(x)
}
func (*CollectionDef_NodeList) ProtoMessage() {}
func (x *CollectionDef_NodeList) ProtoReflect() protoreflect.Message {
mi := &file_tensorflow_core_protobuf_meta_graph_proto_msgTypes[9]
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 CollectionDef_NodeList.ProtoReflect.Descriptor instead.
func (*CollectionDef_NodeList) Descriptor() ([]byte, []int) {
return file_tensorflow_core_protobuf_meta_graph_proto_rawDescGZIP(), []int{1, 0}
}
func (x *CollectionDef_NodeList) GetValue() []string {
if x != nil {
return x.Value
}
return nil
}
// BytesList is used for collecting strings and serialized protobufs. For
// example:
//
// collection_def {
// key: "trainable_variables"
// value {
// bytes_list {
// value: "\n\017conv1/weights:0\022\024conv1/weights/Assign
// \032\024conv1/weights/read:0"
// value: "\n\016conv1/biases:0\022\023conv1/biases/Assign\032
// \023conv1/biases/read:0"
// }
// }
// }
type CollectionDef_BytesList struct {
state protoimpl.MessageState
sizeCache protoimpl.SizeCache
unknownFields protoimpl.UnknownFields
Value [][]byte `protobuf:"bytes,1,rep,name=value,proto3" json:"value,omitempty"`
}
func (x *CollectionDef_BytesList) Reset() {
*x = CollectionDef_BytesList{}
if protoimpl.UnsafeEnabled {
mi := &file_tensorflow_core_protobuf_meta_graph_proto_msgTypes[10]
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
ms.StoreMessageInfo(mi)
}
}
func (x *CollectionDef_BytesList) String() string {
return protoimpl.X.MessageStringOf(x)
}
func (*CollectionDef_BytesList) ProtoMessage() {}
func (x *CollectionDef_BytesList) ProtoReflect() protoreflect.Message {
mi := &file_tensorflow_core_protobuf_meta_graph_proto_msgTypes[10]
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 CollectionDef_BytesList.ProtoReflect.Descriptor instead.
func (*CollectionDef_BytesList) Descriptor() ([]byte, []int) {
return file_tensorflow_core_protobuf_meta_graph_proto_rawDescGZIP(), []int{1, 1}
}
func (x *CollectionDef_BytesList) GetValue() [][]byte {
if x != nil {
return x.Value
}
return nil
}
// Int64List is used for collecting int, int64 and long values.
type CollectionDef_Int64List struct {
state protoimpl.MessageState
sizeCache protoimpl.SizeCache
unknownFields protoimpl.UnknownFields
Value []int64 `protobuf:"varint,1,rep,packed,name=value,proto3" json:"value,omitempty"`
}
func (x *CollectionDef_Int64List) Reset() {
*x = CollectionDef_Int64List{}
if protoimpl.UnsafeEnabled {
mi := &file_tensorflow_core_protobuf_meta_graph_proto_msgTypes[11]
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
ms.StoreMessageInfo(mi)
}
}
func (x *CollectionDef_Int64List) String() string {
return protoimpl.X.MessageStringOf(x)
}
func (*CollectionDef_Int64List) ProtoMessage() {}
func (x *CollectionDef_Int64List) ProtoReflect() protoreflect.Message {
mi := &file_tensorflow_core_protobuf_meta_graph_proto_msgTypes[11]
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 CollectionDef_Int64List.ProtoReflect.Descriptor instead.
func (*CollectionDef_Int64List) Descriptor() ([]byte, []int) {
return file_tensorflow_core_protobuf_meta_graph_proto_rawDescGZIP(), []int{1, 2}
}
func (x *CollectionDef_Int64List) GetValue() []int64 {
if x != nil {
return x.Value
}
return nil
}
// FloatList is used for collecting float values.
type CollectionDef_FloatList struct {
state protoimpl.MessageState
sizeCache protoimpl.SizeCache
unknownFields protoimpl.UnknownFields
Value []float32 `protobuf:"fixed32,1,rep,packed,name=value,proto3" json:"value,omitempty"`
}
func (x *CollectionDef_FloatList) Reset() {
*x = CollectionDef_FloatList{}
if protoimpl.UnsafeEnabled {
mi := &file_tensorflow_core_protobuf_meta_graph_proto_msgTypes[12]
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
ms.StoreMessageInfo(mi)
}
}
func (x *CollectionDef_FloatList) String() string {
return protoimpl.X.MessageStringOf(x)
}
func (*CollectionDef_FloatList) ProtoMessage() {}
func (x *CollectionDef_FloatList) ProtoReflect() protoreflect.Message {
mi := &file_tensorflow_core_protobuf_meta_graph_proto_msgTypes[12]
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 CollectionDef_FloatList.ProtoReflect.Descriptor instead.
func (*CollectionDef_FloatList) Descriptor() ([]byte, []int) {
return file_tensorflow_core_protobuf_meta_graph_proto_rawDescGZIP(), []int{1, 3}
}
func (x *CollectionDef_FloatList) GetValue() []float32 {
if x != nil {
return x.Value
}
return nil
}
// AnyList is used for collecting Any protos.
type CollectionDef_AnyList struct {
state protoimpl.MessageState
sizeCache protoimpl.SizeCache
unknownFields protoimpl.UnknownFields
Value []*anypb.Any `protobuf:"bytes,1,rep,name=value,proto3" json:"value,omitempty"`
}
func (x *CollectionDef_AnyList) Reset() {
*x = CollectionDef_AnyList{}
if protoimpl.UnsafeEnabled {
mi := &file_tensorflow_core_protobuf_meta_graph_proto_msgTypes[13]
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
ms.StoreMessageInfo(mi)
}
}