public interface OpDefOrBuilder
extends com.github.os72.protobuf351.MessageOrBuilder
Modifier and Type | Method and Description |
---|---|
boolean |
getAllowsUninitializedInput()
By default, all inputs to an Op must be initialized Tensors.
|
OpDef.AttrDef |
getAttr(int index)
repeated .tensorflow.OpDef.AttrDef attr = 4; |
int |
getAttrCount()
repeated .tensorflow.OpDef.AttrDef attr = 4; |
List<OpDef.AttrDef> |
getAttrList()
repeated .tensorflow.OpDef.AttrDef attr = 4; |
OpDef.AttrDefOrBuilder |
getAttrOrBuilder(int index)
repeated .tensorflow.OpDef.AttrDef attr = 4; |
List<? extends OpDef.AttrDefOrBuilder> |
getAttrOrBuilderList()
repeated .tensorflow.OpDef.AttrDef attr = 4; |
OpDeprecation |
getDeprecation()
Optional deprecation based on GraphDef versions.
|
OpDeprecationOrBuilder |
getDeprecationOrBuilder()
Optional deprecation based on GraphDef versions.
|
String |
getDescription()
Additional, longer human-readable description of what the Op does.
|
com.github.os72.protobuf351.ByteString |
getDescriptionBytes()
Additional, longer human-readable description of what the Op does.
|
OpDef.ArgDef |
getInputArg(int index)
Description of the input(s).
|
int |
getInputArgCount()
Description of the input(s).
|
List<OpDef.ArgDef> |
getInputArgList()
Description of the input(s).
|
OpDef.ArgDefOrBuilder |
getInputArgOrBuilder(int index)
Description of the input(s).
|
List<? extends OpDef.ArgDefOrBuilder> |
getInputArgOrBuilderList()
Description of the input(s).
|
boolean |
getIsAggregate()
If is_aggregate is true, then this operation accepts N >= 2
inputs and produces 1 output all of the same type.
|
boolean |
getIsCommutative()
True if the operation is commutative ("op(a,b) == op(b,a)" for all inputs)
|
boolean |
getIsStateful()
Ops are marked as stateful if their behavior depends on some state beyond
their input tensors (e.g.
|
String |
getName()
Op names starting with an underscore are reserved for internal use.
|
com.github.os72.protobuf351.ByteString |
getNameBytes()
Op names starting with an underscore are reserved for internal use.
|
OpDef.ArgDef |
getOutputArg(int index)
Description of the output(s).
|
int |
getOutputArgCount()
Description of the output(s).
|
List<OpDef.ArgDef> |
getOutputArgList()
Description of the output(s).
|
OpDef.ArgDefOrBuilder |
getOutputArgOrBuilder(int index)
Description of the output(s).
|
List<? extends OpDef.ArgDefOrBuilder> |
getOutputArgOrBuilderList()
Description of the output(s).
|
String |
getSummary()
One-line human-readable description of what the Op does.
|
com.github.os72.protobuf351.ByteString |
getSummaryBytes()
One-line human-readable description of what the Op does.
|
boolean |
hasDeprecation()
Optional deprecation based on GraphDef versions.
|
findInitializationErrors, getAllFields, getDefaultInstanceForType, getDescriptorForType, getField, getInitializationErrorString, getOneofFieldDescriptor, getRepeatedField, getRepeatedFieldCount, getUnknownFields, hasField, hasOneof
String getName()
Op names starting with an underscore are reserved for internal use. Names should be CamelCase and match the regexp "[A-Z][a-zA-Z0-9_]*".
string name = 1;
com.github.os72.protobuf351.ByteString getNameBytes()
Op names starting with an underscore are reserved for internal use. Names should be CamelCase and match the regexp "[A-Z][a-zA-Z0-9_]*".
string name = 1;
List<OpDef.ArgDef> getInputArgList()
Description of the input(s).
repeated .tensorflow.OpDef.ArgDef input_arg = 2;
OpDef.ArgDef getInputArg(int index)
Description of the input(s).
repeated .tensorflow.OpDef.ArgDef input_arg = 2;
int getInputArgCount()
Description of the input(s).
repeated .tensorflow.OpDef.ArgDef input_arg = 2;
List<? extends OpDef.ArgDefOrBuilder> getInputArgOrBuilderList()
Description of the input(s).
repeated .tensorflow.OpDef.ArgDef input_arg = 2;
OpDef.ArgDefOrBuilder getInputArgOrBuilder(int index)
Description of the input(s).
repeated .tensorflow.OpDef.ArgDef input_arg = 2;
List<OpDef.ArgDef> getOutputArgList()
Description of the output(s).
repeated .tensorflow.OpDef.ArgDef output_arg = 3;
OpDef.ArgDef getOutputArg(int index)
Description of the output(s).
repeated .tensorflow.OpDef.ArgDef output_arg = 3;
int getOutputArgCount()
Description of the output(s).
repeated .tensorflow.OpDef.ArgDef output_arg = 3;
List<? extends OpDef.ArgDefOrBuilder> getOutputArgOrBuilderList()
Description of the output(s).
repeated .tensorflow.OpDef.ArgDef output_arg = 3;
OpDef.ArgDefOrBuilder getOutputArgOrBuilder(int index)
Description of the output(s).
repeated .tensorflow.OpDef.ArgDef output_arg = 3;
List<OpDef.AttrDef> getAttrList()
repeated .tensorflow.OpDef.AttrDef attr = 4;
OpDef.AttrDef getAttr(int index)
repeated .tensorflow.OpDef.AttrDef attr = 4;
int getAttrCount()
repeated .tensorflow.OpDef.AttrDef attr = 4;
List<? extends OpDef.AttrDefOrBuilder> getAttrOrBuilderList()
repeated .tensorflow.OpDef.AttrDef attr = 4;
OpDef.AttrDefOrBuilder getAttrOrBuilder(int index)
repeated .tensorflow.OpDef.AttrDef attr = 4;
boolean hasDeprecation()
Optional deprecation based on GraphDef versions.
.tensorflow.OpDeprecation deprecation = 8;
OpDeprecation getDeprecation()
Optional deprecation based on GraphDef versions.
.tensorflow.OpDeprecation deprecation = 8;
OpDeprecationOrBuilder getDeprecationOrBuilder()
Optional deprecation based on GraphDef versions.
.tensorflow.OpDeprecation deprecation = 8;
String getSummary()
One-line human-readable description of what the Op does.
string summary = 5;
com.github.os72.protobuf351.ByteString getSummaryBytes()
One-line human-readable description of what the Op does.
string summary = 5;
String getDescription()
Additional, longer human-readable description of what the Op does.
string description = 6;
com.github.os72.protobuf351.ByteString getDescriptionBytes()
Additional, longer human-readable description of what the Op does.
string description = 6;
boolean getIsCommutative()
True if the operation is commutative ("op(a,b) == op(b,a)" for all inputs)
bool is_commutative = 18;
boolean getIsAggregate()
If is_aggregate is true, then this operation accepts N >= 2 inputs and produces 1 output all of the same type. Should be associative and commutative, and produce output with the same shape as the input. The optimizer may replace an aggregate op taking input from multiple devices with a tree of aggregate ops that aggregate locally within each device (and possibly within groups of nearby devices) before communicating. TODO(josh11b): Implement that optimization.
bool is_aggregate = 16;
boolean getIsStateful()
Ops are marked as stateful if their behavior depends on some state beyond their input tensors (e.g. variable reading op) or if they have a side-effect (e.g. printing or asserting ops). Equivalently, stateless ops must always produce the same output for the same input and have no side-effects. By default Ops may be moved between devices. Stateful ops should either not be moved, or should only be moved if that state can also be moved (e.g. via some sort of save / restore). Stateful ops are guaranteed to never be optimized away by Common Subexpression Elimination (CSE).
bool is_stateful = 17;
boolean getAllowsUninitializedInput()
By default, all inputs to an Op must be initialized Tensors. Ops that may initialize tensors for the first time should set this field to true, to allow the Op to take an uninitialized Tensor as input.
bool allows_uninitialized_input = 19;
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