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// Generated by the protocol buffer compiler. DO NOT EDIT!
// source: tensorflow/contrib/tpu/profiler/op_profile.proto
package tensorflow.tpu.op_profile;
public final class OpProfile {
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tensorflow.tpu.op_profile.OpProfile.Node.InstructionCategory getCategory();
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tensorflow.tpu.op_profile.OpProfile.Node.InstructionCategoryOrBuilder getCategoryOrBuilder();
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tensorflow.tpu.op_profile.OpProfile.Node.XLAInstruction getXla();
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tensorflow.tpu.op_profile.OpProfile.Node.XLAInstructionOrBuilder getXlaOrBuilder();
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/**
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* repeated .tensorflow.tpu.op_profile.Node.XLAInstruction.LayoutAnalysis.Dimension dimensions = 1;
*/
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getDimensionsOrBuilderList() {
if (dimensionsBuilder_ != null) {
return dimensionsBuilder_.getMessageOrBuilderList();
} else {
return java.util.Collections.unmodifiableList(dimensions_);
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/**
*
* The physical data layout, from most-minor to most-major dimensions.
*
*
* repeated .tensorflow.tpu.op_profile.Node.XLAInstruction.LayoutAnalysis.Dimension dimensions = 1;
*/
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*
* The physical data layout, from most-minor to most-major dimensions.
*
*
* repeated .tensorflow.tpu.op_profile.Node.XLAInstruction.LayoutAnalysis.Dimension dimensions = 1;
*/
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/**
*
* The physical data layout, from most-minor to most-major dimensions.
*
*
* repeated .tensorflow.tpu.op_profile.Node.XLAInstruction.LayoutAnalysis.Dimension dimensions = 1;
*/
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}
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// @@protoc_insertion_point(builder_scope:tensorflow.tpu.op_profile.Node.XLAInstruction.LayoutAnalysis)
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public static tensorflow.tpu.op_profile.OpProfile.Node.XLAInstruction.LayoutAnalysis getDefaultInstance() {
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PARSER = new com.google.protobuf.AbstractParser() {
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public LayoutAnalysis parsePartialFrom(
com.google.protobuf.CodedInputStream input,
com.google.protobuf.ExtensionRegistryLite extensionRegistry)
throws com.google.protobuf.InvalidProtocolBufferException {
return new LayoutAnalysis(input, extensionRegistry);
}
};
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return PARSER;
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return PARSER;
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public tensorflow.tpu.op_profile.OpProfile.Node.XLAInstruction.LayoutAnalysis getDefaultInstanceForType() {
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}
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/**
*
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*
* string op = 1;
*/
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java.lang.Object ref = op_;
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com.google.protobuf.ByteString bs =
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java.lang.String s = bs.toStringUtf8();
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java.lang.Object ref = op_;
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com.google.protobuf.ByteString b =
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op_ = b;
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/**
*
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*
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com.google.protobuf.ByteString b =
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expression_ = b;
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/**
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*
* string provenance = 3;
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java.lang.Object ref = provenance_;
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java.lang.String s = bs.toStringUtf8();
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*
* string provenance = 3;
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java.lang.Object ref = provenance_;
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provenance_ = b;
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category_ = s;
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com.google.protobuf.ByteString b =
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category_ = b;
return b;
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private tensorflow.tpu.op_profile.OpProfile.Node.XLAInstruction.LayoutAnalysis layout_;
/**
*
* Describes the physical memory layout of the instruction's primary input.
* e.g. for a convolution, this analyzes the image and ignores the kernel.
*
*
* .tensorflow.tpu.op_profile.Node.XLAInstruction.LayoutAnalysis layout = 5;
*/
public boolean hasLayout() {
return layout_ != null;
}
/**
*
* Describes the physical memory layout of the instruction's primary input.
* e.g. for a convolution, this analyzes the image and ignores the kernel.
*
*
* .tensorflow.tpu.op_profile.Node.XLAInstruction.LayoutAnalysis layout = 5;
*/
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return layout_ == null ? tensorflow.tpu.op_profile.OpProfile.Node.XLAInstruction.LayoutAnalysis.getDefaultInstance() : layout_;
}
/**
*
* Describes the physical memory layout of the instruction's primary input.
* e.g. for a convolution, this analyzes the image and ignores the kernel.
*
*
* .tensorflow.tpu.op_profile.Node.XLAInstruction.LayoutAnalysis layout = 5;
*/
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com.google.protobuf.GeneratedMessageV3.writeString(output, 1, op_);
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if (!getProvenanceBytes().isEmpty()) {
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if (!getCategoryBytes().isEmpty()) {
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unknownFields.writeTo(output);
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size = 0;
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if (obj == this) {
return true;
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if (!(obj instanceof tensorflow.tpu.op_profile.OpProfile.Node.XLAInstruction)) {
return super.equals(obj);
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tensorflow.tpu.op_profile.OpProfile.Node.XLAInstruction other = (tensorflow.tpu.op_profile.OpProfile.Node.XLAInstruction) obj;
boolean result = true;
result = result && getOp()
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result = result && getExpression()
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result = result && getProvenance()
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result = result && getCategory()
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if (hasLayout()) {
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@java.lang.Override
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if (memoizedHashCode != 0) {
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int hash = 41;
hash = (19 * hash) + getDescriptor().hashCode();
hash = (37 * hash) + OP_FIELD_NUMBER;
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hash = (37 * hash) + EXPRESSION_FIELD_NUMBER;
hash = (53 * hash) + getExpression().hashCode();
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hash = (37 * hash) + CATEGORY_FIELD_NUMBER;
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public static tensorflow.tpu.op_profile.OpProfile.Node.XLAInstruction parseFrom(
java.nio.ByteBuffer data,
com.google.protobuf.ExtensionRegistryLite extensionRegistry)
throws com.google.protobuf.InvalidProtocolBufferException {
return PARSER.parseFrom(data, extensionRegistry);
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public static tensorflow.tpu.op_profile.OpProfile.Node.XLAInstruction parseFrom(
com.google.protobuf.ByteString data)
throws com.google.protobuf.InvalidProtocolBufferException {
return PARSER.parseFrom(data);
}
public static tensorflow.tpu.op_profile.OpProfile.Node.XLAInstruction parseFrom(
com.google.protobuf.ByteString data,
com.google.protobuf.ExtensionRegistryLite extensionRegistry)
throws com.google.protobuf.InvalidProtocolBufferException {
return PARSER.parseFrom(data, extensionRegistry);
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public static tensorflow.tpu.op_profile.OpProfile.Node.XLAInstruction parseFrom(byte[] data)
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public static tensorflow.tpu.op_profile.OpProfile.Node.XLAInstruction parseFrom(
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com.google.protobuf.ExtensionRegistryLite extensionRegistry)
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return PARSER.parseFrom(data, extensionRegistry);
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public static tensorflow.tpu.op_profile.OpProfile.Node.XLAInstruction parseFrom(java.io.InputStream input)
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public static tensorflow.tpu.op_profile.OpProfile.Node.XLAInstruction parseFrom(
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com.google.protobuf.ExtensionRegistryLite extensionRegistry)
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return com.google.protobuf.GeneratedMessageV3
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public static tensorflow.tpu.op_profile.OpProfile.Node.XLAInstruction parseDelimitedFrom(
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return com.google.protobuf.GeneratedMessageV3
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public static tensorflow.tpu.op_profile.OpProfile.Node.XLAInstruction parseFrom(
com.google.protobuf.CodedInputStream input)
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return com.google.protobuf.GeneratedMessageV3
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public static tensorflow.tpu.op_profile.OpProfile.Node.XLAInstruction parseFrom(
com.google.protobuf.CodedInputStream input,
com.google.protobuf.ExtensionRegistryLite extensionRegistry)
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return com.google.protobuf.GeneratedMessageV3
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@java.lang.Override
public Builder newBuilderForType() { return newBuilder(); }
public static Builder newBuilder() {
return DEFAULT_INSTANCE.toBuilder();
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public static Builder newBuilder(tensorflow.tpu.op_profile.OpProfile.Node.XLAInstruction prototype) {
return DEFAULT_INSTANCE.toBuilder().mergeFrom(prototype);
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@java.lang.Override
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return this == DEFAULT_INSTANCE
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@java.lang.Override
protected Builder newBuilderForType(
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/**
*
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*
*
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*/
public static final class Builder extends
com.google.protobuf.GeneratedMessageV3.Builder implements
// @@protoc_insertion_point(builder_implements:tensorflow.tpu.op_profile.Node.XLAInstruction)
tensorflow.tpu.op_profile.OpProfile.Node.XLAInstructionOrBuilder {
public static final com.google.protobuf.Descriptors.Descriptor
getDescriptor() {
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expression_ = "";
provenance_ = "";
category_ = "";
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if (!result.isInitialized()) {
throw newUninitializedMessageException(result);
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return result;
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result.op_ = op_;
result.expression_ = expression_;
result.provenance_ = provenance_;
result.category_ = category_;
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public Builder mergeFrom(tensorflow.tpu.op_profile.OpProfile.Node.XLAInstruction other) {
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private java.lang.Object op_ = "";
/**
*
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*
* string op = 1;
*/
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com.google.protobuf.ByteString bs =
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*
* Opcode like %multiply
*
*
* string op = 1;
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/**
*
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*
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*/
public Builder setOp(
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if (value == null) {
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}
op_ = value;
onChanged();
return this;
}
/**
*
* Opcode like %multiply
*
*
* string op = 1;
*/
public Builder clearOp() {
op_ = getDefaultInstance().getOp();
onChanged();
return this;
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/**
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public Builder setOpBytes(
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checkByteStringIsUtf8(value);
op_ = value;
onChanged();
return this;
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private java.lang.Object expression_ = "";
/**
*
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*
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com.google.protobuf.ByteString bs =
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/**
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*
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*/
public Builder setExpression(
java.lang.String value) {
if (value == null) {
throw new NullPointerException();
}
expression_ = value;
onChanged();
return this;
}
/**
*
* %multiply = [shape]multiply(operand1, operand2)
*
*
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public Builder clearExpression() {
expression_ = getDefaultInstance().getExpression();
onChanged();
return this;
}
/**
*
* %multiply = [shape]multiply(operand1, operand2)
*
*
* string expression = 2;
*/
public Builder setExpressionBytes(
com.google.protobuf.ByteString value) {
if (value == null) {
throw new NullPointerException();
}
checkByteStringIsUtf8(value);
expression_ = value;
onChanged();
return this;
}
private java.lang.Object provenance_ = "";
/**
*
* Typically the TensorFlow operation name.
*
*
* string provenance = 3;
*/
public java.lang.String getProvenance() {
java.lang.Object ref = provenance_;
if (!(ref instanceof java.lang.String)) {
com.google.protobuf.ByteString bs =
(com.google.protobuf.ByteString) ref;
java.lang.String s = bs.toStringUtf8();
provenance_ = s;
return s;
} else {
return (java.lang.String) ref;
}
}
/**
*
* Typically the TensorFlow operation name.
*
*
* string provenance = 3;
*/
public com.google.protobuf.ByteString
getProvenanceBytes() {
java.lang.Object ref = provenance_;
if (ref instanceof String) {
com.google.protobuf.ByteString b =
com.google.protobuf.ByteString.copyFromUtf8(
(java.lang.String) ref);
provenance_ = b;
return b;
} else {
return (com.google.protobuf.ByteString) ref;
}
}
/**
*
* Typically the TensorFlow operation name.
*
*
* string provenance = 3;
*/
public Builder setProvenance(
java.lang.String value) {
if (value == null) {
throw new NullPointerException();
}
provenance_ = value;
onChanged();
return this;
}
/**
*
* Typically the TensorFlow operation name.
*
*
* string provenance = 3;
*/
public Builder clearProvenance() {
provenance_ = getDefaultInstance().getProvenance();
onChanged();
return this;
}
/**
*
* Typically the TensorFlow operation name.
*
*
* string provenance = 3;
*/
public Builder setProvenanceBytes(
com.google.protobuf.ByteString value) {
if (value == null) {
throw new NullPointerException();
}
checkByteStringIsUtf8(value);
provenance_ = value;
onChanged();
return this;
}
private java.lang.Object category_ = "";
/**
* string category = 4;
*/
public java.lang.String getCategory() {
java.lang.Object ref = category_;
if (!(ref instanceof java.lang.String)) {
com.google.protobuf.ByteString bs =
(com.google.protobuf.ByteString) ref;
java.lang.String s = bs.toStringUtf8();
category_ = s;
return s;
} else {
return (java.lang.String) ref;
}
}
/**
* string category = 4;
*/
public com.google.protobuf.ByteString
getCategoryBytes() {
java.lang.Object ref = category_;
if (ref instanceof String) {
com.google.protobuf.ByteString b =
com.google.protobuf.ByteString.copyFromUtf8(
(java.lang.String) ref);
category_ = b;
return b;
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return (com.google.protobuf.ByteString) ref;
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/**
* string category = 4;
*/
public Builder setCategory(
java.lang.String value) {
if (value == null) {
throw new NullPointerException();
}
category_ = value;
onChanged();
return this;
}
/**
* string category = 4;
*/
public Builder clearCategory() {
category_ = getDefaultInstance().getCategory();
onChanged();
return this;
}
/**
* string category = 4;
*/
public Builder setCategoryBytes(
com.google.protobuf.ByteString value) {
if (value == null) {
throw new NullPointerException();
}
checkByteStringIsUtf8(value);
category_ = value;
onChanged();
return this;
}
private tensorflow.tpu.op_profile.OpProfile.Node.XLAInstruction.LayoutAnalysis layout_ = null;
private com.google.protobuf.SingleFieldBuilderV3<
tensorflow.tpu.op_profile.OpProfile.Node.XLAInstruction.LayoutAnalysis, tensorflow.tpu.op_profile.OpProfile.Node.XLAInstruction.LayoutAnalysis.Builder, tensorflow.tpu.op_profile.OpProfile.Node.XLAInstruction.LayoutAnalysisOrBuilder> layoutBuilder_;
/**
*
* Describes the physical memory layout of the instruction's primary input.
* e.g. for a convolution, this analyzes the image and ignores the kernel.
*
*
* .tensorflow.tpu.op_profile.Node.XLAInstruction.LayoutAnalysis layout = 5;
*/
public boolean hasLayout() {
return layoutBuilder_ != null || layout_ != null;
}
/**
*
* Describes the physical memory layout of the instruction's primary input.
* e.g. for a convolution, this analyzes the image and ignores the kernel.
*
*
* .tensorflow.tpu.op_profile.Node.XLAInstruction.LayoutAnalysis layout = 5;
*/
public tensorflow.tpu.op_profile.OpProfile.Node.XLAInstruction.LayoutAnalysis getLayout() {
if (layoutBuilder_ == null) {
return layout_ == null ? tensorflow.tpu.op_profile.OpProfile.Node.XLAInstruction.LayoutAnalysis.getDefaultInstance() : layout_;
} else {
return layoutBuilder_.getMessage();
}
}
/**
*
* Describes the physical memory layout of the instruction's primary input.
* e.g. for a convolution, this analyzes the image and ignores the kernel.
*
*
* .tensorflow.tpu.op_profile.Node.XLAInstruction.LayoutAnalysis layout = 5;
*/
public Builder setLayout(tensorflow.tpu.op_profile.OpProfile.Node.XLAInstruction.LayoutAnalysis value) {
if (layoutBuilder_ == null) {
if (value == null) {
throw new NullPointerException();
}
layout_ = value;
onChanged();
} else {
layoutBuilder_.setMessage(value);
}
return this;
}
/**
*
* Describes the physical memory layout of the instruction's primary input.
* e.g. for a convolution, this analyzes the image and ignores the kernel.
*
*
* .tensorflow.tpu.op_profile.Node.XLAInstruction.LayoutAnalysis layout = 5;
*/
public Builder setLayout(
tensorflow.tpu.op_profile.OpProfile.Node.XLAInstruction.LayoutAnalysis.Builder builderForValue) {
if (layoutBuilder_ == null) {
layout_ = builderForValue.build();
onChanged();
} else {
layoutBuilder_.setMessage(builderForValue.build());
}
return this;
}
/**
*
* Describes the physical memory layout of the instruction's primary input.
* e.g. for a convolution, this analyzes the image and ignores the kernel.
*
*
* .tensorflow.tpu.op_profile.Node.XLAInstruction.LayoutAnalysis layout = 5;
*/
public Builder mergeLayout(tensorflow.tpu.op_profile.OpProfile.Node.XLAInstruction.LayoutAnalysis value) {
if (layoutBuilder_ == null) {
if (layout_ != null) {
layout_ =
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} else {
layout_ = value;
}
onChanged();
} else {
layoutBuilder_.mergeFrom(value);
}
return this;
}
/**
*
* Describes the physical memory layout of the instruction's primary input.
* e.g. for a convolution, this analyzes the image and ignores the kernel.
*
*
* .tensorflow.tpu.op_profile.Node.XLAInstruction.LayoutAnalysis layout = 5;
*/
public Builder clearLayout() {
if (layoutBuilder_ == null) {
layout_ = null;
onChanged();
} else {
layout_ = null;
layoutBuilder_ = null;
}
return this;
}
/**
*
* Describes the physical memory layout of the instruction's primary input.
* e.g. for a convolution, this analyzes the image and ignores the kernel.
*
*
* .tensorflow.tpu.op_profile.Node.XLAInstruction.LayoutAnalysis layout = 5;
*/
public tensorflow.tpu.op_profile.OpProfile.Node.XLAInstruction.LayoutAnalysis.Builder getLayoutBuilder() {
onChanged();
return getLayoutFieldBuilder().getBuilder();
}
/**
*
* Describes the physical memory layout of the instruction's primary input.
* e.g. for a convolution, this analyzes the image and ignores the kernel.
*
*
* .tensorflow.tpu.op_profile.Node.XLAInstruction.LayoutAnalysis layout = 5;
*/
public tensorflow.tpu.op_profile.OpProfile.Node.XLAInstruction.LayoutAnalysisOrBuilder getLayoutOrBuilder() {
if (layoutBuilder_ != null) {
return layoutBuilder_.getMessageOrBuilder();
} else {
return layout_ == null ?
tensorflow.tpu.op_profile.OpProfile.Node.XLAInstruction.LayoutAnalysis.getDefaultInstance() : layout_;
}
}
/**
*
* Describes the physical memory layout of the instruction's primary input.
* e.g. for a convolution, this analyzes the image and ignores the kernel.
*
*
* .tensorflow.tpu.op_profile.Node.XLAInstruction.LayoutAnalysis layout = 5;
*/
private com.google.protobuf.SingleFieldBuilderV3<
tensorflow.tpu.op_profile.OpProfile.Node.XLAInstruction.LayoutAnalysis, tensorflow.tpu.op_profile.OpProfile.Node.XLAInstruction.LayoutAnalysis.Builder, tensorflow.tpu.op_profile.OpProfile.Node.XLAInstruction.LayoutAnalysisOrBuilder>
getLayoutFieldBuilder() {
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layoutBuilder_ = new com.google.protobuf.SingleFieldBuilderV3<
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getLayout(),
getParentForChildren(),
isClean());
layout_ = null;
}
return layoutBuilder_;
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final com.google.protobuf.UnknownFieldSet unknownFields) {
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@java.lang.Override
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final com.google.protobuf.UnknownFieldSet unknownFields) {
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// @@protoc_insertion_point(builder_scope:tensorflow.tpu.op_profile.Node.XLAInstruction)
}
// @@protoc_insertion_point(class_scope:tensorflow.tpu.op_profile.Node.XLAInstruction)
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static {
DEFAULT_INSTANCE = new tensorflow.tpu.op_profile.OpProfile.Node.XLAInstruction();
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public static tensorflow.tpu.op_profile.OpProfile.Node.XLAInstruction getDefaultInstance() {
return DEFAULT_INSTANCE;
}
private static final com.google.protobuf.Parser
PARSER = new com.google.protobuf.AbstractParser() {
@java.lang.Override
public XLAInstruction parsePartialFrom(
com.google.protobuf.CodedInputStream input,
com.google.protobuf.ExtensionRegistryLite extensionRegistry)
throws com.google.protobuf.InvalidProtocolBufferException {
return new XLAInstruction(input, extensionRegistry);
}
};
public static com.google.protobuf.Parser parser() {
return PARSER;
}
@java.lang.Override
public com.google.protobuf.Parser getParserForType() {
return PARSER;
}
@java.lang.Override
public tensorflow.tpu.op_profile.OpProfile.Node.XLAInstruction getDefaultInstanceForType() {
return DEFAULT_INSTANCE;
}
}
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private int contentsCase_ = 0;
private java.lang.Object contents_;
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CATEGORY(4),
XLA(5),
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this.value = value;
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return forNumber(value);
}
public static ContentsCase forNumber(int value) {
switch (value) {
case 4: return CATEGORY;
case 5: return XLA;
case 0: return CONTENTS_NOT_SET;
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}
public int getNumber() {
return this.value;
}
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public ContentsCase
getContentsCase() {
return ContentsCase.forNumber(
contentsCase_);
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/**
*
* Semantics depend on contents.
*
*
* string name = 1;
*/
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java.lang.Object ref = name_;
if (ref instanceof java.lang.String) {
return (java.lang.String) ref;
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com.google.protobuf.ByteString bs =
(com.google.protobuf.ByteString) ref;
java.lang.String s = bs.toStringUtf8();
name_ = s;
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getNameBytes() {
java.lang.Object ref = name_;
if (ref instanceof java.lang.String) {
com.google.protobuf.ByteString b =
com.google.protobuf.ByteString.copyFromUtf8(
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name_ = b;
return b;
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return (com.google.protobuf.ByteString) ref;
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public static final int METRICS_FIELD_NUMBER = 2;
private tensorflow.tpu.op_profile.OpProfile.Metrics metrics_;
/**
*
* May be omitted e.g. for fused instructions.
*
*
* .tensorflow.tpu.op_profile.Metrics metrics = 2;
*/
public boolean hasMetrics() {
return metrics_ != null;
}
/**
*
* May be omitted e.g. for fused instructions.
*
*
* .tensorflow.tpu.op_profile.Metrics metrics = 2;
*/
public tensorflow.tpu.op_profile.OpProfile.Metrics getMetrics() {
return metrics_ == null ? tensorflow.tpu.op_profile.OpProfile.Metrics.getDefaultInstance() : metrics_;
}
/**
*
* May be omitted e.g. for fused instructions.
*
*
* .tensorflow.tpu.op_profile.Metrics metrics = 2;
*/
public tensorflow.tpu.op_profile.OpProfile.MetricsOrBuilder getMetricsOrBuilder() {
return getMetrics();
}
public static final int CHILDREN_FIELD_NUMBER = 3;
private java.util.List children_;
/**
*
* Subjected to pruning.
*
*
* repeated .tensorflow.tpu.op_profile.Node children = 3;
*/
public java.util.List getChildrenList() {
return children_;
}
/**
*
* Subjected to pruning.
*
*
* repeated .tensorflow.tpu.op_profile.Node children = 3;
*/
public java.util.List
getChildrenOrBuilderList() {
return children_;
}
/**
*
* Subjected to pruning.
*
*
* repeated .tensorflow.tpu.op_profile.Node children = 3;
*/
public int getChildrenCount() {
return children_.size();
}
/**
*
* Subjected to pruning.
*
*
* repeated .tensorflow.tpu.op_profile.Node children = 3;
*/
public tensorflow.tpu.op_profile.OpProfile.Node getChildren(int index) {
return children_.get(index);
}
/**
*
* Subjected to pruning.
*
*
* repeated .tensorflow.tpu.op_profile.Node children = 3;
*/
public tensorflow.tpu.op_profile.OpProfile.NodeOrBuilder getChildrenOrBuilder(
int index) {
return children_.get(index);
}
public static final int CATEGORY_FIELD_NUMBER = 4;
/**
* .tensorflow.tpu.op_profile.Node.InstructionCategory category = 4;
*/
public boolean hasCategory() {
return contentsCase_ == 4;
}
/**
* .tensorflow.tpu.op_profile.Node.InstructionCategory category = 4;
*/
public tensorflow.tpu.op_profile.OpProfile.Node.InstructionCategory getCategory() {
if (contentsCase_ == 4) {
return (tensorflow.tpu.op_profile.OpProfile.Node.InstructionCategory) contents_;
}
return tensorflow.tpu.op_profile.OpProfile.Node.InstructionCategory.getDefaultInstance();
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/**
* .tensorflow.tpu.op_profile.Node.InstructionCategory category = 4;
*/
public tensorflow.tpu.op_profile.OpProfile.Node.InstructionCategoryOrBuilder getCategoryOrBuilder() {
if (contentsCase_ == 4) {
return (tensorflow.tpu.op_profile.OpProfile.Node.InstructionCategory) contents_;
}
return tensorflow.tpu.op_profile.OpProfile.Node.InstructionCategory.getDefaultInstance();
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public static final int XLA_FIELD_NUMBER = 5;
/**
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*/
public boolean hasXla() {
return contentsCase_ == 5;
}
/**
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if (contentsCase_ == 5) {
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/**
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*/
public tensorflow.tpu.op_profile.OpProfile.Node.XLAInstructionOrBuilder getXlaOrBuilder() {
if (contentsCase_ == 5) {
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tensorflow.tpu.op_profile.OpProfile.Node other = (tensorflow.tpu.op_profile.OpProfile.Node) obj;
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public static tensorflow.tpu.op_profile.OpProfile.Node parseFrom(
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return PARSER.parseFrom(data, extensionRegistry);
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public static tensorflow.tpu.op_profile.OpProfile.Node parseFrom(
com.google.protobuf.ByteString data)
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return PARSER.parseFrom(data);
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public static tensorflow.tpu.op_profile.OpProfile.Node parseFrom(
com.google.protobuf.ByteString data,
com.google.protobuf.ExtensionRegistryLite extensionRegistry)
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return PARSER.parseFrom(data, extensionRegistry);
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public static tensorflow.tpu.op_profile.OpProfile.Node parseFrom(byte[] data)
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return PARSER.parseFrom(data);
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public static tensorflow.tpu.op_profile.OpProfile.Node parseFrom(
byte[] data,
com.google.protobuf.ExtensionRegistryLite extensionRegistry)
throws com.google.protobuf.InvalidProtocolBufferException {
return PARSER.parseFrom(data, extensionRegistry);
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public static tensorflow.tpu.op_profile.OpProfile.Node parseFrom(java.io.InputStream input)
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public static tensorflow.tpu.op_profile.OpProfile.Node parseFrom(
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com.google.protobuf.ExtensionRegistryLite extensionRegistry)
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return com.google.protobuf.GeneratedMessageV3
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public static tensorflow.tpu.op_profile.OpProfile.Node parseDelimitedFrom(java.io.InputStream input)
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public static tensorflow.tpu.op_profile.OpProfile.Node parseDelimitedFrom(
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com.google.protobuf.ExtensionRegistryLite extensionRegistry)
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return com.google.protobuf.GeneratedMessageV3
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public static tensorflow.tpu.op_profile.OpProfile.Node parseFrom(
com.google.protobuf.CodedInputStream input)
throws java.io.IOException {
return com.google.protobuf.GeneratedMessageV3
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public static tensorflow.tpu.op_profile.OpProfile.Node parseFrom(
com.google.protobuf.CodedInputStream input,
com.google.protobuf.ExtensionRegistryLite extensionRegistry)
throws java.io.IOException {
return com.google.protobuf.GeneratedMessageV3
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public static Builder newBuilder() {
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public static Builder newBuilder(tensorflow.tpu.op_profile.OpProfile.Node prototype) {
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@java.lang.Override
protected Builder newBuilderForType(
com.google.protobuf.GeneratedMessageV3.BuilderParent parent) {
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/**
*
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*
*
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*/
public static final class Builder extends
com.google.protobuf.GeneratedMessageV3.Builder implements
// @@protoc_insertion_point(builder_implements:tensorflow.tpu.op_profile.Node)
tensorflow.tpu.op_profile.OpProfile.NodeOrBuilder {
public static final com.google.protobuf.Descriptors.Descriptor
getDescriptor() {
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return tensorflow.tpu.op_profile.OpProfile.Node.XLAInstruction.getDefaultInstance();
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if (xlaBuilder_ == null) {
if (value == null) {
throw new NullPointerException();
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contents_ = value;
onChanged();
} else {
xlaBuilder_.setMessage(value);
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contentsCase_ = 5;
return this;
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/**
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tensorflow.tpu.op_profile.OpProfile.Node.XLAInstruction.Builder builderForValue) {
if (xlaBuilder_ == null) {
contents_ = builderForValue.build();
onChanged();
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xlaBuilder_.setMessage(builderForValue.build());
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contentsCase_ = 5;
return this;
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/**
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contents_ = value;
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onChanged();
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if (contentsCase_ == 5) {
xlaBuilder_.mergeFrom(value);
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xlaBuilder_.setMessage(value);
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/**
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contentsCase_ = 0;
contents_ = null;
onChanged();
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if (contentsCase_ == 5) {
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xlaBuilder_.clear();
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return getXlaFieldBuilder().getBuilder();
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// @@protoc_insertion_point(interface_extends:tensorflow.tpu.op_profile.Metrics)
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/**
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double getTime();
/**
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double getFlops();
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double getRawFlops();
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double getRawBytesAccessed();
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// @@protoc_insertion_point(message_implements:tensorflow.tpu.op_profile.Metrics)
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/**
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tensorflow.tpu.op_profile.OpProfile.MetricsOrBuilder {
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setRawTime(other.getRawTime());
}
if (other.getRawFlops() != 0D) {
setRawFlops(other.getRawFlops());
}
if (other.getRawBytesAccessed() != 0D) {
setRawBytesAccessed(other.getRawBytesAccessed());
}
this.mergeUnknownFields(other.unknownFields);
onChanged();
return this;
}
@java.lang.Override
public final boolean isInitialized() {
return true;
}
@java.lang.Override
public Builder mergeFrom(
com.google.protobuf.CodedInputStream input,
com.google.protobuf.ExtensionRegistryLite extensionRegistry)
throws java.io.IOException {
tensorflow.tpu.op_profile.OpProfile.Metrics parsedMessage = null;
try {
parsedMessage = PARSER.parsePartialFrom(input, extensionRegistry);
} catch (com.google.protobuf.InvalidProtocolBufferException e) {
parsedMessage = (tensorflow.tpu.op_profile.OpProfile.Metrics) e.getUnfinishedMessage();
throw e.unwrapIOException();
} finally {
if (parsedMessage != null) {
mergeFrom(parsedMessage);
}
}
return this;
}
private double time_ ;
/**
*
* Core-time taken by this operation, as a fraction of all operations.
*
*
* double time = 1;
*/
public double getTime() {
return time_;
}
/**
*
* Core-time taken by this operation, as a fraction of all operations.
*
*
* double time = 1;
*/
public Builder setTime(double value) {
time_ = value;
onChanged();
return this;
}
/**
*
* Core-time taken by this operation, as a fraction of all operations.
*
*
* double time = 1;
*/
public Builder clearTime() {
time_ = 0D;
onChanged();
return this;
}
private double flops_ ;
/**
*
* Floating point computations performed by this operation, as a fraction of
* peak core FLOPS * program time. This representation has useful properties:
* - it is proportional to the number of floating point operations performed
* - utilization is flops/time
* - wasted potential flops is proportional to time - flops
* - it does not reveal the peak core FLOPS of the hardware
*
*
* double flops = 2;
*/
public double getFlops() {
return flops_;
}
/**
*
* Floating point computations performed by this operation, as a fraction of
* peak core FLOPS * program time. This representation has useful properties:
* - it is proportional to the number of floating point operations performed
* - utilization is flops/time
* - wasted potential flops is proportional to time - flops
* - it does not reveal the peak core FLOPS of the hardware
*
*
* double flops = 2;
*/
public Builder setFlops(double value) {
flops_ = value;
onChanged();
return this;
}
/**
*
* Floating point computations performed by this operation, as a fraction of
* peak core FLOPS * program time. This representation has useful properties:
* - it is proportional to the number of floating point operations performed
* - utilization is flops/time
* - wasted potential flops is proportional to time - flops
* - it does not reveal the peak core FLOPS of the hardware
*
*
* double flops = 2;
*/
public Builder clearFlops() {
flops_ = 0D;
onChanged();
return this;
}
private double memoryBandwidth_ ;
/**
*
* The memory bandwidth used to load operands, as a fraction of
* thereotical memory bandwidth on the specific hardware.
*
*
* double memory_bandwidth = 3;
*/
public double getMemoryBandwidth() {
return memoryBandwidth_;
}
/**
*
* The memory bandwidth used to load operands, as a fraction of
* thereotical memory bandwidth on the specific hardware.
*
*
* double memory_bandwidth = 3;
*/
public Builder setMemoryBandwidth(double value) {
memoryBandwidth_ = value;
onChanged();
return this;
}
/**
*
* The memory bandwidth used to load operands, as a fraction of
* thereotical memory bandwidth on the specific hardware.
*
*
* double memory_bandwidth = 3;
*/
public Builder clearMemoryBandwidth() {
memoryBandwidth_ = 0D;
onChanged();
return this;
}
private double rawTime_ ;
/**
*
* Elapsed core-time in picoseconds.
*
*
* double raw_time = 11;
*/
public double getRawTime() {
return rawTime_;
}
/**
*
* Elapsed core-time in picoseconds.
*
*
* double raw_time = 11;
*/
public Builder setRawTime(double value) {
rawTime_ = value;
onChanged();
return this;
}
/**
*
* Elapsed core-time in picoseconds.
*
*
* double raw_time = 11;
*/
public Builder clearRawTime() {
rawTime_ = 0D;
onChanged();
return this;
}
private double rawFlops_ ;
/**
*
* Total floating-point operations performed.
*
*
* double raw_flops = 12;
*/
public double getRawFlops() {
return rawFlops_;
}
/**
*
* Total floating-point operations performed.
*
*
* double raw_flops = 12;
*/
public Builder setRawFlops(double value) {
rawFlops_ = value;
onChanged();
return this;
}
/**
*
* Total floating-point operations performed.
*
*
* double raw_flops = 12;
*/
public Builder clearRawFlops() {
rawFlops_ = 0D;
onChanged();
return this;
}
private double rawBytesAccessed_ ;
/**
*
* Total bytes accessed (include read/write).
*
*
* double raw_bytes_accessed = 13;
*/
public double getRawBytesAccessed() {
return rawBytesAccessed_;
}
/**
*
* Total bytes accessed (include read/write).
*
*
* double raw_bytes_accessed = 13;
*/
public Builder setRawBytesAccessed(double value) {
rawBytesAccessed_ = value;
onChanged();
return this;
}
/**
*
* Total bytes accessed (include read/write).
*
*
* double raw_bytes_accessed = 13;
*/
public Builder clearRawBytesAccessed() {
rawBytesAccessed_ = 0D;
onChanged();
return this;
}
@java.lang.Override
public final Builder setUnknownFields(
final com.google.protobuf.UnknownFieldSet unknownFields) {
return super.setUnknownFieldsProto3(unknownFields);
}
@java.lang.Override
public final Builder mergeUnknownFields(
final com.google.protobuf.UnknownFieldSet unknownFields) {
return super.mergeUnknownFields(unknownFields);
}
// @@protoc_insertion_point(builder_scope:tensorflow.tpu.op_profile.Metrics)
}
// @@protoc_insertion_point(class_scope:tensorflow.tpu.op_profile.Metrics)
private static final tensorflow.tpu.op_profile.OpProfile.Metrics DEFAULT_INSTANCE;
static {
DEFAULT_INSTANCE = new tensorflow.tpu.op_profile.OpProfile.Metrics();
}
public static tensorflow.tpu.op_profile.OpProfile.Metrics getDefaultInstance() {
return DEFAULT_INSTANCE;
}
private static final com.google.protobuf.Parser
PARSER = new com.google.protobuf.AbstractParser() {
@java.lang.Override
public Metrics parsePartialFrom(
com.google.protobuf.CodedInputStream input,
com.google.protobuf.ExtensionRegistryLite extensionRegistry)
throws com.google.protobuf.InvalidProtocolBufferException {
return new Metrics(input, extensionRegistry);
}
};
public static com.google.protobuf.Parser parser() {
return PARSER;
}
@java.lang.Override
public com.google.protobuf.Parser getParserForType() {
return PARSER;
}
@java.lang.Override
public tensorflow.tpu.op_profile.OpProfile.Metrics getDefaultInstanceForType() {
return DEFAULT_INSTANCE;
}
}
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// @@protoc_insertion_point(outer_class_scope)
}
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