org.tensorflow.framework

Interface GraphDefOrBuilder

All Superinterfaces:

org.nd4j.shade.protobuf.MessageLiteOrBuilder, org.nd4j.shade.protobuf.MessageOrBuilder

All Known Implementing Classes:

GraphDef, GraphDef.Builder

public interface GraphDefOrBuilder
extends org.nd4j.shade.protobuf.MessageOrBuilder

Method Summary

Modifier and Type	Method and Description
FunctionDefLibrary	getLibrary() EXPERIMENTAL.
FunctionDefLibraryOrBuilder	getLibraryOrBuilder() EXPERIMENTAL.
NodeDef	getNode(int index) repeated .tensorflow.NodeDef node = 1;
int	getNodeCount() repeated .tensorflow.NodeDef node = 1;
List<NodeDef>	getNodeList() repeated .tensorflow.NodeDef node = 1;
NodeDefOrBuilder	getNodeOrBuilder(int index) repeated .tensorflow.NodeDef node = 1;
List<? extends NodeDefOrBuilder>	getNodeOrBuilderList() repeated .tensorflow.NodeDef node = 1;
int	getVersion() Deprecated.
VersionDef	getVersions() Compatibility versions of the graph.
VersionDefOrBuilder	getVersionsOrBuilder() Compatibility versions of the graph.
boolean	hasLibrary() EXPERIMENTAL.
boolean	hasVersions() Compatibility versions of the graph.

Methods inherited from interface org.nd4j.shade.protobuf.MessageOrBuilder

findInitializationErrors, getAllFields, getDefaultInstanceForType, getDescriptorForType, getField, getInitializationErrorString, getOneofFieldDescriptor, getRepeatedField, getRepeatedFieldCount, getUnknownFields, hasField, hasOneof

Methods inherited from interface org.nd4j.shade.protobuf.MessageLiteOrBuilder

isInitialized

Method Detail

getNodeList

List<NodeDef> getNodeList()

repeated .tensorflow.NodeDef node = 1;

getNode

NodeDef getNode(int index)

repeated .tensorflow.NodeDef node = 1;

getNodeCount

int getNodeCount()

repeated .tensorflow.NodeDef node = 1;

getNodeOrBuilderList

List<? extends NodeDefOrBuilder> getNodeOrBuilderList()

repeated .tensorflow.NodeDef node = 1;

getNodeOrBuilder

NodeDefOrBuilder getNodeOrBuilder(int index)

repeated .tensorflow.NodeDef node = 1;

hasVersions

boolean hasVersions()

 Compatibility versions of the graph.  See core/public/version.h for version
 history.  The GraphDef version is distinct from the TensorFlow version, and
 each release of TensorFlow will support a range of GraphDef versions.
 

.tensorflow.VersionDef versions = 4;

getVersions

VersionDef getVersions()

 Compatibility versions of the graph.  See core/public/version.h for version
 history.  The GraphDef version is distinct from the TensorFlow version, and
 each release of TensorFlow will support a range of GraphDef versions.
 

.tensorflow.VersionDef versions = 4;

getVersionsOrBuilder

VersionDefOrBuilder getVersionsOrBuilder()

 Compatibility versions of the graph.  See core/public/version.h for version
 history.  The GraphDef version is distinct from the TensorFlow version, and
 each release of TensorFlow will support a range of GraphDef versions.
 

.tensorflow.VersionDef versions = 4;

getVersion

@Deprecated
int getVersion()

Deprecated.

 Deprecated single version field; use versions above instead.  Since all
 GraphDef changes before "versions" was introduced were forward
 compatible, this field is entirely ignored.
 

int32 version = 3 [deprecated = true];

hasLibrary

boolean hasLibrary()

 EXPERIMENTAL. DO NOT USE OR DEPEND ON THIS YET.
 "library" provides user-defined functions.
 Naming:
   * library.function.name are in a flat namespace.
     NOTE: We may need to change it to be hierarchical to support
     different orgs. E.g.,
     { "/google/nn", { ... }},
     { "/google/vision", { ... }}
     { "/org_foo/module_bar", { ... }}
     map<string, FunctionDefLib> named_lib;
   * If node[i].op is the name of one function in "library",
     node[i] is deemed as a function call. Otherwise, node[i].op
     must be a primitive operation supported by the runtime.
 Function call semantics:
   * The callee may start execution as soon as some of its inputs
     are ready. The caller may want to use Tuple() mechanism to
     ensure all inputs are ready in the same time.
   * The consumer of return values may start executing as soon as
     the return values the consumer depends on are ready.  The
     consumer may want to use Tuple() mechanism to ensure the
     consumer does not start until all return values of the callee
     function are ready.
 

.tensorflow.FunctionDefLibrary library = 2;

getLibrary

FunctionDefLibrary getLibrary()

 EXPERIMENTAL. DO NOT USE OR DEPEND ON THIS YET.
 "library" provides user-defined functions.
 Naming:
   * library.function.name are in a flat namespace.
     NOTE: We may need to change it to be hierarchical to support
     different orgs. E.g.,
     { "/google/nn", { ... }},
     { "/google/vision", { ... }}
     { "/org_foo/module_bar", { ... }}
     map<string, FunctionDefLib> named_lib;
   * If node[i].op is the name of one function in "library",
     node[i] is deemed as a function call. Otherwise, node[i].op
     must be a primitive operation supported by the runtime.
 Function call semantics:
   * The callee may start execution as soon as some of its inputs
     are ready. The caller may want to use Tuple() mechanism to
     ensure all inputs are ready in the same time.
   * The consumer of return values may start executing as soon as
     the return values the consumer depends on are ready.  The
     consumer may want to use Tuple() mechanism to ensure the
     consumer does not start until all return values of the callee
     function are ready.
 

.tensorflow.FunctionDefLibrary library = 2;

getLibraryOrBuilder

FunctionDefLibraryOrBuilder getLibraryOrBuilder()

 EXPERIMENTAL. DO NOT USE OR DEPEND ON THIS YET.
 "library" provides user-defined functions.
 Naming:
   * library.function.name are in a flat namespace.
     NOTE: We may need to change it to be hierarchical to support
     different orgs. E.g.,
     { "/google/nn", { ... }},
     { "/google/vision", { ... }}
     { "/org_foo/module_bar", { ... }}
     map<string, FunctionDefLib> named_lib;
   * If node[i].op is the name of one function in "library",
     node[i] is deemed as a function call. Otherwise, node[i].op
     must be a primitive operation supported by the runtime.
 Function call semantics:
   * The callee may start execution as soon as some of its inputs
     are ready. The caller may want to use Tuple() mechanism to
     ensure all inputs are ready in the same time.
   * The consumer of return values may start executing as soon as
     the return values the consumer depends on are ready.  The
     consumer may want to use Tuple() mechanism to ensure the
     consumer does not start until all return values of the callee
     function are ready.
 

.tensorflow.FunctionDefLibrary library = 2;