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// Generated by the protocol buffer compiler. DO NOT EDIT!
// source: tensorflow/core/protobuf/meta_graph.proto
package org.tensorflow.framework;
/**
*
* 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.
* 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"
* }
*
*
* Protobuf type {@code tensorflow.SignatureDef}
*/
public final class SignatureDef extends
org.nd4j.shade.protobuf.GeneratedMessageV3 implements
// @@protoc_insertion_point(message_implements:tensorflow.SignatureDef)
SignatureDefOrBuilder {
private static final long serialVersionUID = 0L;
// Use SignatureDef.newBuilder() to construct.
private SignatureDef(org.nd4j.shade.protobuf.GeneratedMessageV3.Builder builder) {
super(builder);
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throw new org.nd4j.shade.protobuf.InvalidProtocolBufferException(
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public static final org.nd4j.shade.protobuf.Descriptors.Descriptor
getDescriptor() {
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}
@SuppressWarnings({"rawtypes"})
protected org.nd4j.shade.protobuf.MapField internalGetMapField(
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public int getInputsCount() {
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/**
*
* Named input parameters.
*
*
* map<string, .tensorflow.TensorInfo> inputs = 1;
*/
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java.lang.String key) {
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/**
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*/
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public java.util.Map getInputs() {
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/**
*
*
* map<string, .tensorflow.TensorInfo> outputs = 2;
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/**
*
* 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.
*
* 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.
*
*
* string method_name = 3;
*/
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org.nd4j.shade.protobuf.ByteString b =
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methodName_ = b;
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org.nd4j.shade.protobuf.GeneratedMessageV3
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output,
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@java.lang.Override
public boolean equals(final java.lang.Object obj) {
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}
if (!(obj instanceof org.tensorflow.framework.SignatureDef)) {
return super.equals(obj);
}
org.tensorflow.framework.SignatureDef other = (org.tensorflow.framework.SignatureDef) obj;
boolean result = true;
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other.internalGetInputs());
result = result && internalGetOutputs().equals(
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public static org.tensorflow.framework.SignatureDef parseFrom(
java.nio.ByteBuffer data)
throws org.nd4j.shade.protobuf.InvalidProtocolBufferException {
return PARSER.parseFrom(data);
}
public static org.tensorflow.framework.SignatureDef parseFrom(
java.nio.ByteBuffer data,
org.nd4j.shade.protobuf.ExtensionRegistryLite extensionRegistry)
throws org.nd4j.shade.protobuf.InvalidProtocolBufferException {
return PARSER.parseFrom(data, extensionRegistry);
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public static org.tensorflow.framework.SignatureDef parseFrom(
org.nd4j.shade.protobuf.ByteString data)
throws org.nd4j.shade.protobuf.InvalidProtocolBufferException {
return PARSER.parseFrom(data);
}
public static org.tensorflow.framework.SignatureDef parseFrom(
org.nd4j.shade.protobuf.ByteString data,
org.nd4j.shade.protobuf.ExtensionRegistryLite extensionRegistry)
throws org.nd4j.shade.protobuf.InvalidProtocolBufferException {
return PARSER.parseFrom(data, extensionRegistry);
}
public static org.tensorflow.framework.SignatureDef parseFrom(byte[] data)
throws org.nd4j.shade.protobuf.InvalidProtocolBufferException {
return PARSER.parseFrom(data);
}
public static org.tensorflow.framework.SignatureDef parseFrom(
byte[] data,
org.nd4j.shade.protobuf.ExtensionRegistryLite extensionRegistry)
throws org.nd4j.shade.protobuf.InvalidProtocolBufferException {
return PARSER.parseFrom(data, extensionRegistry);
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public static org.tensorflow.framework.SignatureDef parseFrom(java.io.InputStream input)
throws java.io.IOException {
return org.nd4j.shade.protobuf.GeneratedMessageV3
.parseWithIOException(PARSER, input);
}
public static org.tensorflow.framework.SignatureDef parseFrom(
java.io.InputStream input,
org.nd4j.shade.protobuf.ExtensionRegistryLite extensionRegistry)
throws java.io.IOException {
return org.nd4j.shade.protobuf.GeneratedMessageV3
.parseWithIOException(PARSER, input, extensionRegistry);
}
public static org.tensorflow.framework.SignatureDef parseDelimitedFrom(java.io.InputStream input)
throws java.io.IOException {
return org.nd4j.shade.protobuf.GeneratedMessageV3
.parseDelimitedWithIOException(PARSER, input);
}
public static org.tensorflow.framework.SignatureDef parseDelimitedFrom(
java.io.InputStream input,
org.nd4j.shade.protobuf.ExtensionRegistryLite extensionRegistry)
throws java.io.IOException {
return org.nd4j.shade.protobuf.GeneratedMessageV3
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}
public static org.tensorflow.framework.SignatureDef parseFrom(
org.nd4j.shade.protobuf.CodedInputStream input)
throws java.io.IOException {
return org.nd4j.shade.protobuf.GeneratedMessageV3
.parseWithIOException(PARSER, input);
}
public static org.tensorflow.framework.SignatureDef parseFrom(
org.nd4j.shade.protobuf.CodedInputStream input,
org.nd4j.shade.protobuf.ExtensionRegistryLite extensionRegistry)
throws java.io.IOException {
return org.nd4j.shade.protobuf.GeneratedMessageV3
.parseWithIOException(PARSER, input, extensionRegistry);
}
public Builder newBuilderForType() { return newBuilder(); }
public static Builder newBuilder() {
return DEFAULT_INSTANCE.toBuilder();
}
public static Builder newBuilder(org.tensorflow.framework.SignatureDef prototype) {
return DEFAULT_INSTANCE.toBuilder().mergeFrom(prototype);
}
public Builder toBuilder() {
return this == DEFAULT_INSTANCE
? new Builder() : new Builder().mergeFrom(this);
}
@java.lang.Override
protected Builder newBuilderForType(
org.nd4j.shade.protobuf.GeneratedMessageV3.BuilderParent parent) {
Builder builder = new Builder(parent);
return builder;
}
/**
*
* 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.
* 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"
* }
*
*
* Protobuf type {@code tensorflow.SignatureDef}
*/
public static final class Builder extends
org.nd4j.shade.protobuf.GeneratedMessageV3.Builder implements
// @@protoc_insertion_point(builder_implements:tensorflow.SignatureDef)
org.tensorflow.framework.SignatureDefOrBuilder {
public static final org.nd4j.shade.protobuf.Descriptors.Descriptor
getDescriptor() {
return org.tensorflow.framework.MetaGraphProtos.internal_static_tensorflow_SignatureDef_descriptor;
}
@SuppressWarnings({"rawtypes"})
protected org.nd4j.shade.protobuf.MapField internalGetMapField(
int number) {
switch (number) {
case 1:
return internalGetInputs();
case 2:
return internalGetOutputs();
default:
throw new RuntimeException(
"Invalid map field number: " + number);
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@SuppressWarnings({"rawtypes"})
protected org.nd4j.shade.protobuf.MapField internalGetMutableMapField(
int number) {
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case 2:
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// Construct using org.tensorflow.framework.SignatureDef.newBuilder()
private Builder() {
maybeForceBuilderInitialization();
}
private Builder(
org.nd4j.shade.protobuf.GeneratedMessageV3.BuilderParent parent) {
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maybeForceBuilderInitialization();
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internalGetMutableOutputs().clear();
methodName_ = "";
return this;
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getDescriptorForType() {
return org.tensorflow.framework.MetaGraphProtos.internal_static_tensorflow_SignatureDef_descriptor;
}
public org.tensorflow.framework.SignatureDef getDefaultInstanceForType() {
return org.tensorflow.framework.SignatureDef.getDefaultInstance();
}
public org.tensorflow.framework.SignatureDef build() {
org.tensorflow.framework.SignatureDef result = buildPartial();
if (!result.isInitialized()) {
throw newUninitializedMessageException(result);
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return result;
}
public org.tensorflow.framework.SignatureDef buildPartial() {
org.tensorflow.framework.SignatureDef result = new org.tensorflow.framework.SignatureDef(this);
int from_bitField0_ = bitField0_;
int to_bitField0_ = 0;
result.inputs_ = internalGetInputs();
result.inputs_.makeImmutable();
result.outputs_ = internalGetOutputs();
result.outputs_.makeImmutable();
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result.bitField0_ = to_bitField0_;
onBuilt();
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return (Builder) super.clone();
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public Builder setField(
org.nd4j.shade.protobuf.Descriptors.FieldDescriptor field,
java.lang.Object value) {
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org.nd4j.shade.protobuf.Descriptors.FieldDescriptor field) {
return (Builder) super.clearField(field);
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public Builder clearOneof(
org.nd4j.shade.protobuf.Descriptors.OneofDescriptor oneof) {
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org.nd4j.shade.protobuf.Descriptors.FieldDescriptor field,
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public Builder addRepeatedField(
org.nd4j.shade.protobuf.Descriptors.FieldDescriptor field,
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public Builder mergeFrom(org.nd4j.shade.protobuf.Message other) {
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return mergeFrom((org.tensorflow.framework.SignatureDef)other);
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return this;
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public Builder mergeFrom(org.tensorflow.framework.SignatureDef other) {
if (other == org.tensorflow.framework.SignatureDef.getDefaultInstance()) return this;
internalGetMutableInputs().mergeFrom(
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internalGetMutableOutputs().mergeFrom(
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org.nd4j.shade.protobuf.ExtensionRegistryLite extensionRegistry)
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org.tensorflow.framework.SignatureDef parsedMessage = null;
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return org.nd4j.shade.protobuf.MapField.emptyMapField(
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/**
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*
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/**
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*/
@java.lang.Deprecated
public java.util.Map getInputs() {
return getInputsMap();
}
/**
*
* 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.
*
* 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.
*
* 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.
*
* 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.
*
* 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.
*
*
* string method_name = 3;
*/
public Builder setMethodNameBytes(
org.nd4j.shade.protobuf.ByteString value) {
if (value == null) {
throw new NullPointerException();
}
checkByteStringIsUtf8(value);
methodName_ = value;
onChanged();
return this;
}
public final Builder setUnknownFields(
final org.nd4j.shade.protobuf.UnknownFieldSet unknownFields) {
return super.setUnknownFieldsProto3(unknownFields);
}
public final Builder mergeUnknownFields(
final org.nd4j.shade.protobuf.UnknownFieldSet unknownFields) {
return super.mergeUnknownFields(unknownFields);
}
// @@protoc_insertion_point(builder_scope:tensorflow.SignatureDef)
}
// @@protoc_insertion_point(class_scope:tensorflow.SignatureDef)
private static final org.tensorflow.framework.SignatureDef DEFAULT_INSTANCE;
static {
DEFAULT_INSTANCE = new org.tensorflow.framework.SignatureDef();
}
public static org.tensorflow.framework.SignatureDef getDefaultInstance() {
return DEFAULT_INSTANCE;
}
private static final org.nd4j.shade.protobuf.Parser
PARSER = new org.nd4j.shade.protobuf.AbstractParser() {
public SignatureDef parsePartialFrom(
org.nd4j.shade.protobuf.CodedInputStream input,
org.nd4j.shade.protobuf.ExtensionRegistryLite extensionRegistry)
throws org.nd4j.shade.protobuf.InvalidProtocolBufferException {
return new SignatureDef(input, extensionRegistry);
}
};
public static org.nd4j.shade.protobuf.Parser parser() {
return PARSER;
}
@java.lang.Override
public org.nd4j.shade.protobuf.Parser getParserForType() {
return PARSER;
}
public org.tensorflow.framework.SignatureDef getDefaultInstanceForType() {
return DEFAULT_INSTANCE;
}
}
