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// Generated by the protocol buffer compiler.  DO NOT EDIT!
// source: tensorflow/core/protobuf/config.proto

package org.tensorflow.framework;

/**
 * 
 * Options passed to the graph optimizer
 * 
* * Protobuf type {@code tensorflow.OptimizerOptions} */ public final class OptimizerOptions extends org.nd4j.shade.protobuf.GeneratedMessageV3 implements // @@protoc_insertion_point(message_implements:tensorflow.OptimizerOptions) OptimizerOptionsOrBuilder { private static final long serialVersionUID = 0L; // Use OptimizerOptions.newBuilder() to construct. private OptimizerOptions(org.nd4j.shade.protobuf.GeneratedMessageV3.Builder builder) { super(builder); } private OptimizerOptions() { doCommonSubexpressionElimination_ = false; doConstantFolding_ = false; maxFoldedConstantInBytes_ = 0L; doFunctionInlining_ = false; optLevel_ = 0; globalJitLevel_ = 0; } @java.lang.Override public final org.nd4j.shade.protobuf.UnknownFieldSet getUnknownFields() { return this.unknownFields; } private OptimizerOptions( org.nd4j.shade.protobuf.CodedInputStream input, org.nd4j.shade.protobuf.ExtensionRegistryLite extensionRegistry) throws org.nd4j.shade.protobuf.InvalidProtocolBufferException { this(); if (extensionRegistry == null) { throw new java.lang.NullPointerException(); } int mutable_bitField0_ = 0; org.nd4j.shade.protobuf.UnknownFieldSet.Builder unknownFields = org.nd4j.shade.protobuf.UnknownFieldSet.newBuilder(); try { boolean done = false; while (!done) { int tag = input.readTag(); switch (tag) { case 0: done = true; break; default: { if (!parseUnknownFieldProto3( input, unknownFields, extensionRegistry, tag)) { done = true; } break; } case 8: { doCommonSubexpressionElimination_ = input.readBool(); break; } case 16: { doConstantFolding_ = input.readBool(); break; } case 24: { int rawValue = input.readEnum(); optLevel_ = rawValue; break; } case 32: { doFunctionInlining_ = input.readBool(); break; } case 40: { int rawValue = input.readEnum(); globalJitLevel_ = rawValue; break; } case 48: { maxFoldedConstantInBytes_ = input.readInt64(); break; } } } } catch (org.nd4j.shade.protobuf.InvalidProtocolBufferException e) { throw e.setUnfinishedMessage(this); } catch (java.io.IOException e) { throw new org.nd4j.shade.protobuf.InvalidProtocolBufferException( e).setUnfinishedMessage(this); } finally { this.unknownFields = unknownFields.build(); makeExtensionsImmutable(); } } 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); } /** *
   * Optimization level
   * 
* * Protobuf enum {@code tensorflow.OptimizerOptions.Level} */ public enum Level implements org.nd4j.shade.protobuf.ProtocolMessageEnum { /** *
     * 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.
   * 
* * Protobuf enum {@code tensorflow.OptimizerOptions.GlobalJitLevel} */ public enum GlobalJitLevel implements org.nd4j.shade.protobuf.ProtocolMessageEnum { /** *
     * Default setting ("off" now, but later expected to be "on")
     * 
* * DEFAULT = 0; */ DEFAULT(0), /** * OFF = -1; */ OFF(-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; */ ON_1(1), /** * ON_2 = 2; */ ON_2(2), UNRECOGNIZED(-1), ; /** *
     * 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.
     * 
* * bool do_common_subexpression_elimination = 1; */ public boolean getDoCommonSubexpressionElimination() { return doCommonSubexpressionElimination_; } /** *
     * If true, optimize the graph using common subexpression elimination.
     * 
* * bool do_common_subexpression_elimination = 1; */ public Builder setDoCommonSubexpressionElimination(boolean value) { doCommonSubexpressionElimination_ = value; onChanged(); return this; } /** *
     * If true, optimize the graph using common subexpression elimination.
     * 
* * bool do_common_subexpression_elimination = 1; */ public Builder clearDoCommonSubexpressionElimination() { doCommonSubexpressionElimination_ = false; onChanged(); return this; } private boolean doConstantFolding_ ; /** *
     * If true, perform constant folding optimization on the graph.
     * 
* * bool do_constant_folding = 2; */ public boolean getDoConstantFolding() { return doConstantFolding_; } /** *
     * If true, perform constant folding optimization on the graph.
     * 
* * bool do_constant_folding = 2; */ public Builder setDoConstantFolding(boolean value) { doConstantFolding_ = value; onChanged(); return this; } /** *
     * If true, perform constant folding optimization on the graph.
     * 
* * bool do_constant_folding = 2; */ public Builder clearDoConstantFolding() { doConstantFolding_ = false; onChanged(); return this; } 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_; } /** *
     * 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 Builder setMaxFoldedConstantInBytes(long value) { maxFoldedConstantInBytes_ = value; onChanged(); return this; } /** *
     * 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 Builder clearMaxFoldedConstantInBytes() { maxFoldedConstantInBytes_ = 0L; onChanged(); return this; } private boolean doFunctionInlining_ ; /** *
     * If true, perform function inlining on the graph.
     * 
* * bool do_function_inlining = 4; */ public boolean getDoFunctionInlining() { return doFunctionInlining_; } /** *
     * If true, perform function inlining on the graph.
     * 
* * bool do_function_inlining = 4; */ public Builder setDoFunctionInlining(boolean value) { doFunctionInlining_ = value; onChanged(); return this; } /** *
     * If true, perform function inlining on the graph.
     * 
* * bool do_function_inlining = 4; */ public Builder clearDoFunctionInlining() { doFunctionInlining_ = false; onChanged(); return this; } private int optLevel_ = 0; /** *
     * 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 Builder setOptLevelValue(int value) { optLevel_ = value; 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 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; } }




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