Many resources are needed to download a project. Please understand that we have to compensate our server costs. Thank you in advance. Project price only 1 $
You can buy this project and download/modify it how often you want.
* L1 is the default level.
* Optimization performed at L1 :
* 1. Common subexpression elimination
* 2. Constant folding
*
*
* L1 = 0;
*/
L1(0),
/**
*
* No optimizations
*
*
* L0 = -1;
*/
L0(-1),
UNRECOGNIZED(-1),
;
/**
*
* L1 is the default level.
* Optimization performed at L1 :
* 1. Common subexpression elimination
* 2. Constant folding
*
*
* L1 = 0;
*/
public static final int L1_VALUE = 0;
/**
*
* No optimizations
*
*
* L0 = -1;
*/
public static final int L0_VALUE = -1;
public final int getNumber() {
if (this == UNRECOGNIZED) {
throw new java.lang.IllegalArgumentException(
"Can't get the number of an unknown enum value.");
}
return value;
}
/**
* @deprecated Use {@link #forNumber(int)} instead.
*/
@java.lang.Deprecated
public static Level valueOf(int value) {
return forNumber(value);
}
public static Level forNumber(int value) {
switch (value) {
case 0: return L1;
case -1: return L0;
default: return null;
}
}
public static org.nd4j.shade.protobuf.Internal.EnumLiteMap
internalGetValueMap() {
return internalValueMap;
}
private static final org.nd4j.shade.protobuf.Internal.EnumLiteMap<
Level> internalValueMap =
new org.nd4j.shade.protobuf.Internal.EnumLiteMap() {
public Level findValueByNumber(int number) {
return Level.forNumber(number);
}
};
public final org.nd4j.shade.protobuf.Descriptors.EnumValueDescriptor
getValueDescriptor() {
return getDescriptor().getValues().get(ordinal());
}
public final org.nd4j.shade.protobuf.Descriptors.EnumDescriptor
getDescriptorForType() {
return getDescriptor();
}
public static final org.nd4j.shade.protobuf.Descriptors.EnumDescriptor
getDescriptor() {
return org.tensorflow.framework.OptimizerOptions.getDescriptor().getEnumTypes().get(0);
}
private static final Level[] VALUES = values();
public static Level valueOf(
org.nd4j.shade.protobuf.Descriptors.EnumValueDescriptor desc) {
if (desc.getType() != getDescriptor()) {
throw new java.lang.IllegalArgumentException(
"EnumValueDescriptor is not for this type.");
}
if (desc.getIndex() == -1) {
return UNRECOGNIZED;
}
return VALUES[desc.getIndex()];
}
private final int value;
private Level(int value) {
this.value = value;
}
// @@protoc_insertion_point(enum_scope:tensorflow.OptimizerOptions.Level)
}
/**
*
* Control the use of the compiler/jit. Experimental.
*
* The following settings turn on compilation, with higher values being
* more aggressive. Higher values may reduce opportunities for parallelism
* and may use more memory. (At present, there is no distinction, but this
* is expected to change.)
*
* Default setting ("off" now, but later expected to be "on")
*
*
* DEFAULT = 0;
*/
public static final int DEFAULT_VALUE = 0;
/**
* OFF = -1;
*/
public static final int OFF_VALUE = -1;
/**
*
* The following settings turn on compilation, with higher values being
* more aggressive. Higher values may reduce opportunities for parallelism
* and may use more memory. (At present, there is no distinction, but this
* is expected to change.)
*
*
* ON_1 = 1;
*/
public static final int ON_1_VALUE = 1;
/**
* ON_2 = 2;
*/
public static final int ON_2_VALUE = 2;
public final int getNumber() {
if (this == UNRECOGNIZED) {
throw new java.lang.IllegalArgumentException(
"Can't get the number of an unknown enum value.");
}
return value;
}
/**
* @deprecated Use {@link #forNumber(int)} instead.
*/
@java.lang.Deprecated
public static GlobalJitLevel valueOf(int value) {
return forNumber(value);
}
public static GlobalJitLevel forNumber(int value) {
switch (value) {
case 0: return DEFAULT;
case -1: return OFF;
case 1: return ON_1;
case 2: return ON_2;
default: return null;
}
}
public static org.nd4j.shade.protobuf.Internal.EnumLiteMap
internalGetValueMap() {
return internalValueMap;
}
private static final org.nd4j.shade.protobuf.Internal.EnumLiteMap<
GlobalJitLevel> internalValueMap =
new org.nd4j.shade.protobuf.Internal.EnumLiteMap() {
public GlobalJitLevel findValueByNumber(int number) {
return GlobalJitLevel.forNumber(number);
}
};
public final org.nd4j.shade.protobuf.Descriptors.EnumValueDescriptor
getValueDescriptor() {
return getDescriptor().getValues().get(ordinal());
}
public final org.nd4j.shade.protobuf.Descriptors.EnumDescriptor
getDescriptorForType() {
return getDescriptor();
}
public static final org.nd4j.shade.protobuf.Descriptors.EnumDescriptor
getDescriptor() {
return org.tensorflow.framework.OptimizerOptions.getDescriptor().getEnumTypes().get(1);
}
private static final GlobalJitLevel[] VALUES = values();
public static GlobalJitLevel valueOf(
org.nd4j.shade.protobuf.Descriptors.EnumValueDescriptor desc) {
if (desc.getType() != getDescriptor()) {
throw new java.lang.IllegalArgumentException(
"EnumValueDescriptor is not for this type.");
}
if (desc.getIndex() == -1) {
return UNRECOGNIZED;
}
return VALUES[desc.getIndex()];
}
private final int value;
private GlobalJitLevel(int value) {
this.value = value;
}
// @@protoc_insertion_point(enum_scope:tensorflow.OptimizerOptions.GlobalJitLevel)
}
public static final int DO_COMMON_SUBEXPRESSION_ELIMINATION_FIELD_NUMBER = 1;
private boolean doCommonSubexpressionElimination_;
/**
*
* If true, optimize the graph using common subexpression elimination.
*
*
* bool do_common_subexpression_elimination = 1;
*/
public boolean getDoCommonSubexpressionElimination() {
return doCommonSubexpressionElimination_;
}
public static final int DO_CONSTANT_FOLDING_FIELD_NUMBER = 2;
private boolean doConstantFolding_;
/**
*
* If true, perform constant folding optimization on the graph.
*
*
* bool do_constant_folding = 2;
*/
public boolean getDoConstantFolding() {
return doConstantFolding_;
}
public static final int MAX_FOLDED_CONSTANT_IN_BYTES_FIELD_NUMBER = 6;
private long maxFoldedConstantInBytes_;
/**
*
* Constant folding optimization replaces tensors whose values can be
* predetermined, with constant nodes. To avoid inserting too large constants,
* the size of each constant created can be limited. If this value is zero, a
* default limit of 10 MiB will be applied. If constant folding optimization
* is disabled, this value is ignored.
*
*
* int64 max_folded_constant_in_bytes = 6;
*/
public long getMaxFoldedConstantInBytes() {
return maxFoldedConstantInBytes_;
}
public static final int DO_FUNCTION_INLINING_FIELD_NUMBER = 4;
private boolean doFunctionInlining_;
/**
*
* If true, perform function inlining on the graph.
*
*
* bool do_function_inlining = 4;
*/
public boolean getDoFunctionInlining() {
return doFunctionInlining_;
}
public static final int OPT_LEVEL_FIELD_NUMBER = 3;
private int optLevel_;
/**
*
* Overall optimization level. The actual optimizations applied will be the
* logical OR of the flags that this level implies and any flags already set.
*
*
* .tensorflow.OptimizerOptions.Level opt_level = 3;
*/
public int getOptLevelValue() {
return optLevel_;
}
/**
*
* Overall optimization level. The actual optimizations applied will be the
* logical OR of the flags that this level implies and any flags already set.
*
*
* .tensorflow.OptimizerOptions.Level opt_level = 3;
*/
public org.tensorflow.framework.OptimizerOptions.Level getOptLevel() {
org.tensorflow.framework.OptimizerOptions.Level result = org.tensorflow.framework.OptimizerOptions.Level.valueOf(optLevel_);
return result == null ? org.tensorflow.framework.OptimizerOptions.Level.UNRECOGNIZED : result;
}
public static final int GLOBAL_JIT_LEVEL_FIELD_NUMBER = 5;
private int globalJitLevel_;
/**
* .tensorflow.OptimizerOptions.GlobalJitLevel global_jit_level = 5;
*/
public int getGlobalJitLevelValue() {
return globalJitLevel_;
}
/**
* .tensorflow.OptimizerOptions.GlobalJitLevel global_jit_level = 5;
*/
public org.tensorflow.framework.OptimizerOptions.GlobalJitLevel getGlobalJitLevel() {
org.tensorflow.framework.OptimizerOptions.GlobalJitLevel result = org.tensorflow.framework.OptimizerOptions.GlobalJitLevel.valueOf(globalJitLevel_);
return result == null ? org.tensorflow.framework.OptimizerOptions.GlobalJitLevel.UNRECOGNIZED : result;
}
private byte memoizedIsInitialized = -1;
public final boolean isInitialized() {
byte isInitialized = memoizedIsInitialized;
if (isInitialized == 1) return true;
if (isInitialized == 0) return false;
memoizedIsInitialized = 1;
return true;
}
public void writeTo(org.nd4j.shade.protobuf.CodedOutputStream output)
throws java.io.IOException {
if (doCommonSubexpressionElimination_ != false) {
output.writeBool(1, doCommonSubexpressionElimination_);
}
if (doConstantFolding_ != false) {
output.writeBool(2, doConstantFolding_);
}
if (optLevel_ != org.tensorflow.framework.OptimizerOptions.Level.L1.getNumber()) {
output.writeEnum(3, optLevel_);
}
if (doFunctionInlining_ != false) {
output.writeBool(4, doFunctionInlining_);
}
if (globalJitLevel_ != org.tensorflow.framework.OptimizerOptions.GlobalJitLevel.DEFAULT.getNumber()) {
output.writeEnum(5, globalJitLevel_);
}
if (maxFoldedConstantInBytes_ != 0L) {
output.writeInt64(6, maxFoldedConstantInBytes_);
}
unknownFields.writeTo(output);
}
public int getSerializedSize() {
int size = memoizedSize;
if (size != -1) return size;
size = 0;
if (doCommonSubexpressionElimination_ != false) {
size += org.nd4j.shade.protobuf.CodedOutputStream
.computeBoolSize(1, doCommonSubexpressionElimination_);
}
if (doConstantFolding_ != false) {
size += org.nd4j.shade.protobuf.CodedOutputStream
.computeBoolSize(2, doConstantFolding_);
}
if (optLevel_ != org.tensorflow.framework.OptimizerOptions.Level.L1.getNumber()) {
size += org.nd4j.shade.protobuf.CodedOutputStream
.computeEnumSize(3, optLevel_);
}
if (doFunctionInlining_ != false) {
size += org.nd4j.shade.protobuf.CodedOutputStream
.computeBoolSize(4, doFunctionInlining_);
}
if (globalJitLevel_ != org.tensorflow.framework.OptimizerOptions.GlobalJitLevel.DEFAULT.getNumber()) {
size += org.nd4j.shade.protobuf.CodedOutputStream
.computeEnumSize(5, globalJitLevel_);
}
if (maxFoldedConstantInBytes_ != 0L) {
size += org.nd4j.shade.protobuf.CodedOutputStream
.computeInt64Size(6, maxFoldedConstantInBytes_);
}
size += unknownFields.getSerializedSize();
memoizedSize = size;
return size;
}
@java.lang.Override
public boolean equals(final java.lang.Object obj) {
if (obj == this) {
return true;
}
if (!(obj instanceof org.tensorflow.framework.OptimizerOptions)) {
return super.equals(obj);
}
org.tensorflow.framework.OptimizerOptions other = (org.tensorflow.framework.OptimizerOptions) obj;
boolean result = true;
result = result && (getDoCommonSubexpressionElimination()
== other.getDoCommonSubexpressionElimination());
result = result && (getDoConstantFolding()
== other.getDoConstantFolding());
result = result && (getMaxFoldedConstantInBytes()
== other.getMaxFoldedConstantInBytes());
result = result && (getDoFunctionInlining()
== other.getDoFunctionInlining());
result = result && optLevel_ == other.optLevel_;
result = result && globalJitLevel_ == other.globalJitLevel_;
result = result && unknownFields.equals(other.unknownFields);
return result;
}
@java.lang.Override
public int hashCode() {
if (memoizedHashCode != 0) {
return memoizedHashCode;
}
int hash = 41;
hash = (19 * hash) + getDescriptor().hashCode();
hash = (37 * hash) + DO_COMMON_SUBEXPRESSION_ELIMINATION_FIELD_NUMBER;
hash = (53 * hash) + org.nd4j.shade.protobuf.Internal.hashBoolean(
getDoCommonSubexpressionElimination());
hash = (37 * hash) + DO_CONSTANT_FOLDING_FIELD_NUMBER;
hash = (53 * hash) + org.nd4j.shade.protobuf.Internal.hashBoolean(
getDoConstantFolding());
hash = (37 * hash) + MAX_FOLDED_CONSTANT_IN_BYTES_FIELD_NUMBER;
hash = (53 * hash) + org.nd4j.shade.protobuf.Internal.hashLong(
getMaxFoldedConstantInBytes());
hash = (37 * hash) + DO_FUNCTION_INLINING_FIELD_NUMBER;
hash = (53 * hash) + org.nd4j.shade.protobuf.Internal.hashBoolean(
getDoFunctionInlining());
hash = (37 * hash) + OPT_LEVEL_FIELD_NUMBER;
hash = (53 * hash) + optLevel_;
hash = (37 * hash) + GLOBAL_JIT_LEVEL_FIELD_NUMBER;
hash = (53 * hash) + globalJitLevel_;
hash = (29 * hash) + unknownFields.hashCode();
memoizedHashCode = hash;
return hash;
}
public static org.tensorflow.framework.OptimizerOptions parseFrom(
java.nio.ByteBuffer data)
throws org.nd4j.shade.protobuf.InvalidProtocolBufferException {
return PARSER.parseFrom(data);
}
public static org.tensorflow.framework.OptimizerOptions parseFrom(
java.nio.ByteBuffer data,
org.nd4j.shade.protobuf.ExtensionRegistryLite extensionRegistry)
throws org.nd4j.shade.protobuf.InvalidProtocolBufferException {
return PARSER.parseFrom(data, extensionRegistry);
}
public static org.tensorflow.framework.OptimizerOptions parseFrom(
org.nd4j.shade.protobuf.ByteString data)
throws org.nd4j.shade.protobuf.InvalidProtocolBufferException {
return PARSER.parseFrom(data);
}
public static org.tensorflow.framework.OptimizerOptions 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.OptimizerOptions parseFrom(byte[] data)
throws org.nd4j.shade.protobuf.InvalidProtocolBufferException {
return PARSER.parseFrom(data);
}
public static org.tensorflow.framework.OptimizerOptions parseFrom(
byte[] data,
org.nd4j.shade.protobuf.ExtensionRegistryLite extensionRegistry)
throws org.nd4j.shade.protobuf.InvalidProtocolBufferException {
return PARSER.parseFrom(data, extensionRegistry);
}
public static org.tensorflow.framework.OptimizerOptions parseFrom(java.io.InputStream input)
throws java.io.IOException {
return org.nd4j.shade.protobuf.GeneratedMessageV3
.parseWithIOException(PARSER, input);
}
public static org.tensorflow.framework.OptimizerOptions 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.OptimizerOptions parseDelimitedFrom(java.io.InputStream input)
throws java.io.IOException {
return org.nd4j.shade.protobuf.GeneratedMessageV3
.parseDelimitedWithIOException(PARSER, input);
}
public static org.tensorflow.framework.OptimizerOptions parseDelimitedFrom(
java.io.InputStream input,
org.nd4j.shade.protobuf.ExtensionRegistryLite extensionRegistry)
throws java.io.IOException {
return org.nd4j.shade.protobuf.GeneratedMessageV3
.parseDelimitedWithIOException(PARSER, input, extensionRegistry);
}
public static org.tensorflow.framework.OptimizerOptions 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.OptimizerOptions 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.OptimizerOptions 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;
}
/**
*
* Options passed to the graph optimizer
*
*
* Protobuf type {@code tensorflow.OptimizerOptions}
*/
public static final class Builder extends
org.nd4j.shade.protobuf.GeneratedMessageV3.Builder implements
// @@protoc_insertion_point(builder_implements:tensorflow.OptimizerOptions)
org.tensorflow.framework.OptimizerOptionsOrBuilder {
public static final org.nd4j.shade.protobuf.Descriptors.Descriptor
getDescriptor() {
return org.tensorflow.framework.ConfigProtos.internal_static_tensorflow_OptimizerOptions_descriptor;
}
protected org.nd4j.shade.protobuf.GeneratedMessageV3.FieldAccessorTable
internalGetFieldAccessorTable() {
return org.tensorflow.framework.ConfigProtos.internal_static_tensorflow_OptimizerOptions_fieldAccessorTable
.ensureFieldAccessorsInitialized(
org.tensorflow.framework.OptimizerOptions.class, org.tensorflow.framework.OptimizerOptions.Builder.class);
}
// Construct using org.tensorflow.framework.OptimizerOptions.newBuilder()
private Builder() {
maybeForceBuilderInitialization();
}
private Builder(
org.nd4j.shade.protobuf.GeneratedMessageV3.BuilderParent parent) {
super(parent);
maybeForceBuilderInitialization();
}
private void maybeForceBuilderInitialization() {
if (org.nd4j.shade.protobuf.GeneratedMessageV3
.alwaysUseFieldBuilders) {
}
}
public Builder clear() {
super.clear();
doCommonSubexpressionElimination_ = false;
doConstantFolding_ = false;
maxFoldedConstantInBytes_ = 0L;
doFunctionInlining_ = false;
optLevel_ = 0;
globalJitLevel_ = 0;
return this;
}
public org.nd4j.shade.protobuf.Descriptors.Descriptor
getDescriptorForType() {
return org.tensorflow.framework.ConfigProtos.internal_static_tensorflow_OptimizerOptions_descriptor;
}
public org.tensorflow.framework.OptimizerOptions getDefaultInstanceForType() {
return org.tensorflow.framework.OptimizerOptions.getDefaultInstance();
}
public org.tensorflow.framework.OptimizerOptions build() {
org.tensorflow.framework.OptimizerOptions result = buildPartial();
if (!result.isInitialized()) {
throw newUninitializedMessageException(result);
}
return result;
}
public org.tensorflow.framework.OptimizerOptions buildPartial() {
org.tensorflow.framework.OptimizerOptions result = new org.tensorflow.framework.OptimizerOptions(this);
result.doCommonSubexpressionElimination_ = doCommonSubexpressionElimination_;
result.doConstantFolding_ = doConstantFolding_;
result.maxFoldedConstantInBytes_ = maxFoldedConstantInBytes_;
result.doFunctionInlining_ = doFunctionInlining_;
result.optLevel_ = optLevel_;
result.globalJitLevel_ = globalJitLevel_;
onBuilt();
return result;
}
public Builder clone() {
return (Builder) super.clone();
}
public Builder setField(
org.nd4j.shade.protobuf.Descriptors.FieldDescriptor field,
java.lang.Object value) {
return (Builder) super.setField(field, value);
}
public Builder clearField(
org.nd4j.shade.protobuf.Descriptors.FieldDescriptor field) {
return (Builder) super.clearField(field);
}
public Builder clearOneof(
org.nd4j.shade.protobuf.Descriptors.OneofDescriptor oneof) {
return (Builder) super.clearOneof(oneof);
}
public Builder setRepeatedField(
org.nd4j.shade.protobuf.Descriptors.FieldDescriptor field,
int index, java.lang.Object value) {
return (Builder) super.setRepeatedField(field, index, value);
}
public Builder addRepeatedField(
org.nd4j.shade.protobuf.Descriptors.FieldDescriptor field,
java.lang.Object value) {
return (Builder) super.addRepeatedField(field, value);
}
public Builder mergeFrom(org.nd4j.shade.protobuf.Message other) {
if (other instanceof org.tensorflow.framework.OptimizerOptions) {
return mergeFrom((org.tensorflow.framework.OptimizerOptions)other);
} else {
super.mergeFrom(other);
return this;
}
}
public Builder mergeFrom(org.tensorflow.framework.OptimizerOptions other) {
if (other == org.tensorflow.framework.OptimizerOptions.getDefaultInstance()) return this;
if (other.getDoCommonSubexpressionElimination() != false) {
setDoCommonSubexpressionElimination(other.getDoCommonSubexpressionElimination());
}
if (other.getDoConstantFolding() != false) {
setDoConstantFolding(other.getDoConstantFolding());
}
if (other.getMaxFoldedConstantInBytes() != 0L) {
setMaxFoldedConstantInBytes(other.getMaxFoldedConstantInBytes());
}
if (other.getDoFunctionInlining() != false) {
setDoFunctionInlining(other.getDoFunctionInlining());
}
if (other.optLevel_ != 0) {
setOptLevelValue(other.getOptLevelValue());
}
if (other.globalJitLevel_ != 0) {
setGlobalJitLevelValue(other.getGlobalJitLevelValue());
}
this.mergeUnknownFields(other.unknownFields);
onChanged();
return this;
}
public final boolean isInitialized() {
return true;
}
public Builder mergeFrom(
org.nd4j.shade.protobuf.CodedInputStream input,
org.nd4j.shade.protobuf.ExtensionRegistryLite extensionRegistry)
throws java.io.IOException {
org.tensorflow.framework.OptimizerOptions parsedMessage = null;
try {
parsedMessage = PARSER.parsePartialFrom(input, extensionRegistry);
} catch (org.nd4j.shade.protobuf.InvalidProtocolBufferException e) {
parsedMessage = (org.tensorflow.framework.OptimizerOptions) e.getUnfinishedMessage();
throw e.unwrapIOException();
} finally {
if (parsedMessage != null) {
mergeFrom(parsedMessage);
}
}
return this;
}
private boolean doCommonSubexpressionElimination_ ;
/**
*
* If true, optimize the graph using common subexpression elimination.
*
* Constant folding optimization replaces tensors whose values can be
* predetermined, with constant nodes. To avoid inserting too large constants,
* the size of each constant created can be limited. If this value is zero, a
* default limit of 10 MiB will be applied. If constant folding optimization
* is disabled, this value is ignored.
*
*
* int64 max_folded_constant_in_bytes = 6;
*/
public long getMaxFoldedConstantInBytes() {
return maxFoldedConstantInBytes_;
}
/**
*
* Constant folding optimization replaces tensors whose values can be
* predetermined, with constant nodes. To avoid inserting too large constants,
* the size of each constant created can be limited. If this value is zero, a
* default limit of 10 MiB will be applied. If constant folding optimization
* is disabled, this value is ignored.
*
* Constant folding optimization replaces tensors whose values can be
* predetermined, with constant nodes. To avoid inserting too large constants,
* the size of each constant created can be limited. If this value is zero, a
* default limit of 10 MiB will be applied. If constant folding optimization
* is disabled, this value is ignored.
*
* Overall optimization level. The actual optimizations applied will be the
* logical OR of the flags that this level implies and any flags already set.
*
*
* .tensorflow.OptimizerOptions.Level opt_level = 3;
*/
public int getOptLevelValue() {
return optLevel_;
}
/**
*
* Overall optimization level. The actual optimizations applied will be the
* logical OR of the flags that this level implies and any flags already set.
*
* Overall optimization level. The actual optimizations applied will be the
* logical OR of the flags that this level implies and any flags already set.
*
*
* .tensorflow.OptimizerOptions.Level opt_level = 3;
*/
public org.tensorflow.framework.OptimizerOptions.Level getOptLevel() {
org.tensorflow.framework.OptimizerOptions.Level result = org.tensorflow.framework.OptimizerOptions.Level.valueOf(optLevel_);
return result == null ? org.tensorflow.framework.OptimizerOptions.Level.UNRECOGNIZED : result;
}
/**
*
* Overall optimization level. The actual optimizations applied will be the
* logical OR of the flags that this level implies and any flags already set.
*
*
* .tensorflow.OptimizerOptions.Level opt_level = 3;
*/
public Builder setOptLevel(org.tensorflow.framework.OptimizerOptions.Level value) {
if (value == null) {
throw new NullPointerException();
}
optLevel_ = value.getNumber();
onChanged();
return this;
}
/**
*
* Overall optimization level. The actual optimizations applied will be the
* logical OR of the flags that this level implies and any flags already set.
*
*
* .tensorflow.OptimizerOptions.Level opt_level = 3;
*/
public Builder clearOptLevel() {
optLevel_ = 0;
onChanged();
return this;
}
private int globalJitLevel_ = 0;
/**
* .tensorflow.OptimizerOptions.GlobalJitLevel global_jit_level = 5;
*/
public int getGlobalJitLevelValue() {
return globalJitLevel_;
}
/**
* .tensorflow.OptimizerOptions.GlobalJitLevel global_jit_level = 5;
*/
public Builder setGlobalJitLevelValue(int value) {
globalJitLevel_ = value;
onChanged();
return this;
}
/**
* .tensorflow.OptimizerOptions.GlobalJitLevel global_jit_level = 5;
*/
public org.tensorflow.framework.OptimizerOptions.GlobalJitLevel getGlobalJitLevel() {
org.tensorflow.framework.OptimizerOptions.GlobalJitLevel result = org.tensorflow.framework.OptimizerOptions.GlobalJitLevel.valueOf(globalJitLevel_);
return result == null ? org.tensorflow.framework.OptimizerOptions.GlobalJitLevel.UNRECOGNIZED : result;
}
/**
* .tensorflow.OptimizerOptions.GlobalJitLevel global_jit_level = 5;
*/
public Builder setGlobalJitLevel(org.tensorflow.framework.OptimizerOptions.GlobalJitLevel value) {
if (value == null) {
throw new NullPointerException();
}
globalJitLevel_ = value.getNumber();
onChanged();
return this;
}
/**
* .tensorflow.OptimizerOptions.GlobalJitLevel global_jit_level = 5;
*/
public Builder clearGlobalJitLevel() {
globalJitLevel_ = 0;
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.OptimizerOptions)
}
// @@protoc_insertion_point(class_scope:tensorflow.OptimizerOptions)
private static final org.tensorflow.framework.OptimizerOptions DEFAULT_INSTANCE;
static {
DEFAULT_INSTANCE = new org.tensorflow.framework.OptimizerOptions();
}
public static org.tensorflow.framework.OptimizerOptions getDefaultInstance() {
return DEFAULT_INSTANCE;
}
private static final org.nd4j.shade.protobuf.Parser
PARSER = new org.nd4j.shade.protobuf.AbstractParser() {
public OptimizerOptions parsePartialFrom(
org.nd4j.shade.protobuf.CodedInputStream input,
org.nd4j.shade.protobuf.ExtensionRegistryLite extensionRegistry)
throws org.nd4j.shade.protobuf.InvalidProtocolBufferException {
return new OptimizerOptions(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.OptimizerOptions getDefaultInstanceForType() {
return DEFAULT_INSTANCE;
}
}
