forked from galeone/tensorflow
/
tensor_shape.pb.go
262 lines (234 loc) · 9.82 KB
/
tensor_shape.pb.go
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// Protocol buffer representing the shape of tensors.
// Code generated by protoc-gen-go. DO NOT EDIT.
// versions:
// protoc-gen-go v1.28.1
// protoc v3.21.7
// source: tensorflow/core/framework/tensor_shape.proto
package tensor_shape_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)
)
// Dimensions of a tensor.
type TensorShapeProto struct {
state protoimpl.MessageState
sizeCache protoimpl.SizeCache
unknownFields protoimpl.UnknownFields
// Dimensions of the tensor, such as {"input", 30}, {"output", 40}
// for a 30 x 40 2D tensor. If an entry has size -1, this
// corresponds to a dimension of unknown size. The names are
// optional.
//
// The order of entries in "dim" matters: It indicates the layout of the
// values in the tensor in-memory representation.
//
// The first entry in "dim" is the outermost dimension used to layout the
// values, the last entry is the innermost dimension. This matches the
// in-memory layout of RowMajor Eigen tensors.
//
// If "dim.size()" > 0, "unknown_rank" must be false.
Dim []*TensorShapeProto_Dim `protobuf:"bytes,2,rep,name=dim,proto3" json:"dim,omitempty"`
// If true, the number of dimensions in the shape is unknown.
//
// If true, "dim.size()" must be 0.
UnknownRank bool `protobuf:"varint,3,opt,name=unknown_rank,json=unknownRank,proto3" json:"unknown_rank,omitempty"`
}
func (x *TensorShapeProto) Reset() {
*x = TensorShapeProto{}
if protoimpl.UnsafeEnabled {
mi := &file_tensorflow_core_framework_tensor_shape_proto_msgTypes[0]
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
ms.StoreMessageInfo(mi)
}
}
func (x *TensorShapeProto) String() string {
return protoimpl.X.MessageStringOf(x)
}
func (*TensorShapeProto) ProtoMessage() {}
func (x *TensorShapeProto) ProtoReflect() protoreflect.Message {
mi := &file_tensorflow_core_framework_tensor_shape_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 TensorShapeProto.ProtoReflect.Descriptor instead.
func (*TensorShapeProto) Descriptor() ([]byte, []int) {
return file_tensorflow_core_framework_tensor_shape_proto_rawDescGZIP(), []int{0}
}
func (x *TensorShapeProto) GetDim() []*TensorShapeProto_Dim {
if x != nil {
return x.Dim
}
return nil
}
func (x *TensorShapeProto) GetUnknownRank() bool {
if x != nil {
return x.UnknownRank
}
return false
}
// One dimension of the tensor.
type TensorShapeProto_Dim struct {
state protoimpl.MessageState
sizeCache protoimpl.SizeCache
unknownFields protoimpl.UnknownFields
// Size of the tensor in that dimension.
// This value must be >= -1, but values of -1 are reserved for "unknown"
// shapes (values of -1 mean "unknown" dimension). Certain wrappers
// that work with TensorShapeProto may fail at runtime when deserializing
// a TensorShapeProto containing a dim value of -1.
Size int64 `protobuf:"varint,1,opt,name=size,proto3" json:"size,omitempty"`
// Optional name of the tensor dimension.
Name string `protobuf:"bytes,2,opt,name=name,proto3" json:"name,omitempty"`
}
func (x *TensorShapeProto_Dim) Reset() {
*x = TensorShapeProto_Dim{}
if protoimpl.UnsafeEnabled {
mi := &file_tensorflow_core_framework_tensor_shape_proto_msgTypes[1]
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
ms.StoreMessageInfo(mi)
}
}
func (x *TensorShapeProto_Dim) String() string {
return protoimpl.X.MessageStringOf(x)
}
func (*TensorShapeProto_Dim) ProtoMessage() {}
func (x *TensorShapeProto_Dim) ProtoReflect() protoreflect.Message {
mi := &file_tensorflow_core_framework_tensor_shape_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 TensorShapeProto_Dim.ProtoReflect.Descriptor instead.
func (*TensorShapeProto_Dim) Descriptor() ([]byte, []int) {
return file_tensorflow_core_framework_tensor_shape_proto_rawDescGZIP(), []int{0, 0}
}
func (x *TensorShapeProto_Dim) GetSize() int64 {
if x != nil {
return x.Size
}
return 0
}
func (x *TensorShapeProto_Dim) GetName() string {
if x != nil {
return x.Name
}
return ""
}
var File_tensorflow_core_framework_tensor_shape_proto protoreflect.FileDescriptor
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var (
file_tensorflow_core_framework_tensor_shape_proto_rawDescOnce sync.Once
file_tensorflow_core_framework_tensor_shape_proto_rawDescData = file_tensorflow_core_framework_tensor_shape_proto_rawDesc
)
func file_tensorflow_core_framework_tensor_shape_proto_rawDescGZIP() []byte {
file_tensorflow_core_framework_tensor_shape_proto_rawDescOnce.Do(func() {
file_tensorflow_core_framework_tensor_shape_proto_rawDescData = protoimpl.X.CompressGZIP(file_tensorflow_core_framework_tensor_shape_proto_rawDescData)
})
return file_tensorflow_core_framework_tensor_shape_proto_rawDescData
}
var file_tensorflow_core_framework_tensor_shape_proto_msgTypes = make([]protoimpl.MessageInfo, 2)
var file_tensorflow_core_framework_tensor_shape_proto_goTypes = []interface{}{
(*TensorShapeProto)(nil), // 0: tensorflow.TensorShapeProto
(*TensorShapeProto_Dim)(nil), // 1: tensorflow.TensorShapeProto.Dim
}
var file_tensorflow_core_framework_tensor_shape_proto_depIdxs = []int32{
1, // 0: tensorflow.TensorShapeProto.dim:type_name -> tensorflow.TensorShapeProto.Dim
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_framework_tensor_shape_proto_init() }
func file_tensorflow_core_framework_tensor_shape_proto_init() {
if File_tensorflow_core_framework_tensor_shape_proto != nil {
return
}
if !protoimpl.UnsafeEnabled {
file_tensorflow_core_framework_tensor_shape_proto_msgTypes[0].Exporter = func(v interface{}, i int) interface{} {
switch v := v.(*TensorShapeProto); i {
case 0:
return &v.state
case 1:
return &v.sizeCache
case 2:
return &v.unknownFields
default:
return nil
}
}
file_tensorflow_core_framework_tensor_shape_proto_msgTypes[1].Exporter = func(v interface{}, i int) interface{} {
switch v := v.(*TensorShapeProto_Dim); 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_framework_tensor_shape_proto_rawDesc,
NumEnums: 0,
NumMessages: 2,
NumExtensions: 0,
NumServices: 0,
},
GoTypes: file_tensorflow_core_framework_tensor_shape_proto_goTypes,
DependencyIndexes: file_tensorflow_core_framework_tensor_shape_proto_depIdxs,
MessageInfos: file_tensorflow_core_framework_tensor_shape_proto_msgTypes,
}.Build()
File_tensorflow_core_framework_tensor_shape_proto = out.File
file_tensorflow_core_framework_tensor_shape_proto_rawDesc = nil
file_tensorflow_core_framework_tensor_shape_proto_goTypes = nil
file_tensorflow_core_framework_tensor_shape_proto_depIdxs = nil
}