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

package org.tensorflow.proto.framework;

/**
 * Protobuf type {@code tensorflow.NodeDef}
 */
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    /**
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      /**
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       * Opaque string inserted into error messages created by the runtime.
       * This is intended to store the list of names of the nodes from the
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       * C, was result of a fusion of 2 nodes A and B, then 'original_node' would
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       * Opaque string inserted into error messages created by the runtime.
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       * <pre>
       * Opaque string inserted into error messages created by the runtime.
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       * C, was result of a fusion of 2 nodes A and B, then 'original_node' would
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       *
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       * <pre>
       * Opaque string inserted into error messages created by the runtime.
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       * original graph that this node was derived. For example if this node, say
       * C, was result of a fusion of 2 nodes A and B, then 'original_node' would
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       * Opaque string inserted into error messages created by the runtime.
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       * C, was result of a fusion of 2 nodes A and B, then 'original_node' would
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       *
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      public Builder setOriginalNodeNames(
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       * <pre>
       * Opaque string inserted into error messages created by the runtime.
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       * C, was result of a fusion of 2 nodes A and B, then 'original_node' would
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      /**
       * <pre>
       * Opaque string inserted into error messages created by the runtime.
       * This is intended to store the list of names of the nodes from the
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       * C, was result of a fusion of 2 nodes A and B, then 'original_node' would
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       *
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       * <pre>
       * Opaque string inserted into error messages created by the runtime.
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       * <code>repeated string original_node_names = 1;</code>
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      }
      /**
       * <pre>
       * Opaque string inserted into error messages created by the runtime.
       * This is intended to store the list of names of the nodes from the
       * original graph that this node was derived. For example if this node, say
       * C, was result of a fusion of 2 nodes A and B, then 'original_node' would
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      public Builder addOriginalNodeNamesBytes(
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      /**
       * <pre>
       * This is intended to store the list of names of the functions from the
       * original graph that this node was derived. For example if this node, say
       * C, was result of a fusion of node A in function FA and node B in function
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       * <pre>
       * This is intended to store the list of names of the functions from the
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       * <pre>
       * This is intended to store the list of names of the functions from the
       * original graph that this node was derived. For example if this node, say
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       * FB, then `original_funcs` would be {FA, FB}. If the node is in the top
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       * `original_node_names` can be used to map errors originating at the
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       * <pre>
       * This is intended to store the list of names of the functions from the
       * original graph that this node was derived. For example if this node, say
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       * `original_node_names` can be used to map errors originating at the
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      public Builder setOriginalFuncNames(
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       * <pre>
       * This is intended to store the list of names of the functions from the
       * original graph that this node was derived. For example if this node, say
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       * <pre>
       * This is intended to store the list of names of the functions from the
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       * FB, then `original_funcs` would be {FA, FB}. If the node is in the top
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       * `original_node_names` can be used to map errors originating at the
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       * <pre>
       * This is intended to store the list of names of the functions from the
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       * FB, then `original_funcs` would be {FA, FB}. If the node is in the top
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      @java.lang.Override
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      // @@protoc_insertion_point(builder_scope:tensorflow.NodeDef.ExperimentalDebugInfo)
    }

    // @@protoc_insertion_point(class_scope:tensorflow.NodeDef.ExperimentalDebugInfo)
    private static final org.tensorflow.proto.framework.NodeDef.ExperimentalDebugInfo DEFAULT_INSTANCE;
    static {
      DEFAULT_INSTANCE = new org.tensorflow.proto.framework.NodeDef.ExperimentalDebugInfo();
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      public ExperimentalDebugInfo parsePartialFrom(
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        return new ExperimentalDebugInfo(input, extensionRegistry);
      }
    };

    public static com.google.protobuf.Parser<ExperimentalDebugInfo> parser() {
      return PARSER;
    }

    @java.lang.Override
    public com.google.protobuf.Parser<ExperimentalDebugInfo> getParserForType() {
      return PARSER;
    }

    @java.lang.Override
    public org.tensorflow.proto.framework.NodeDef.ExperimentalDebugInfo getDefaultInstanceForType() {
      return DEFAULT_INSTANCE;
    }

  }

  public static final int NAME_FIELD_NUMBER = 1;
  private volatile java.lang.Object name_;
  /**
   * <pre>
   * The name given to this operator. Used for naming inputs,
   * logging, visualization, etc.  Unique within a single GraphDef.
   * Must match the regexp "[A-Za-z0-9.][A-Za-z0-9_&gt;./]*".
   * </pre>
   *
   * <code>string name = 1;</code>
   */
  public java.lang.String getName() {
    java.lang.Object ref = name_;
    if (ref instanceof java.lang.String) {
      return (java.lang.String) ref;
    } else {
      com.google.protobuf.ByteString bs = 
          (com.google.protobuf.ByteString) ref;
      java.lang.String s = bs.toStringUtf8();
      name_ = s;
      return s;
    }
  }
  /**
   * <pre>
   * The name given to this operator. Used for naming inputs,
   * logging, visualization, etc.  Unique within a single GraphDef.
   * Must match the regexp "[A-Za-z0-9.][A-Za-z0-9_&gt;./]*".
   * </pre>
   *
   * <code>string name = 1;</code>
   */
  public com.google.protobuf.ByteString
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    if (ref instanceof java.lang.String) {
      com.google.protobuf.ByteString b = 
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      name_ = b;
      return b;
    } else {
      return (com.google.protobuf.ByteString) ref;
    }
  }

  public static final int OP_FIELD_NUMBER = 2;
  private volatile java.lang.Object op_;
  /**
   * <pre>
   * The operation name.  There may be custom parameters in attrs.
   * Op names starting with an underscore are reserved for internal use.
   * </pre>
   *
   * <code>string op = 2;</code>
   */
  public java.lang.String getOp() {
    java.lang.Object ref = op_;
    if (ref instanceof java.lang.String) {
      return (java.lang.String) ref;
    } else {
      com.google.protobuf.ByteString bs = 
          (com.google.protobuf.ByteString) ref;
      java.lang.String s = bs.toStringUtf8();
      op_ = s;
      return s;
    }
  }
  /**
   * <pre>
   * The operation name.  There may be custom parameters in attrs.
   * Op names starting with an underscore are reserved for internal use.
   * </pre>
   *
   * <code>string op = 2;</code>
   */
  public com.google.protobuf.ByteString
      getOpBytes() {
    java.lang.Object ref = op_;
    if (ref instanceof java.lang.String) {
      com.google.protobuf.ByteString b = 
          com.google.protobuf.ByteString.copyFromUtf8(
              (java.lang.String) ref);
      op_ = b;
      return b;
    } else {
      return (com.google.protobuf.ByteString) ref;
    }
  }

  public static final int INPUT_FIELD_NUMBER = 3;
  private com.google.protobuf.LazyStringList input_;
  /**
   * <pre>
   * Each input is "node:src_output" with "node" being a string name and
   * "src_output" indicating which output tensor to use from "node". If
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   *
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   * * ""                                    (no specification)
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   * The expected syntax for this string is as follows:
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   * The values must have a type matching the corresponding OpDef
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  /**
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    /**
     * <pre>
     * The name given to this operator. Used for naming inputs,
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     *
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    /**
     * <pre>
     * The name given to this operator. Used for naming inputs,
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     *
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     * <pre>
     * The name given to this operator. Used for naming inputs,
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     * </pre>
     *
     * <code>string name = 1;</code>
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    /**
     * <pre>
     * The name given to this operator. Used for naming inputs,
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     * </pre>
     *
     * <code>string name = 1;</code>
     */
    public Builder clearName() {
      
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      onChanged();
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    }
    /**
     * <pre>
     * The name given to this operator. Used for naming inputs,
     * logging, visualization, etc.  Unique within a single GraphDef.
     * Must match the regexp "[A-Za-z0-9.][A-Za-z0-9_&gt;./]*".
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     *
     * <code>string name = 1;</code>
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    /**
     * <pre>
     * The operation name.  There may be custom parameters in attrs.
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     *
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     * The operation name.  There may be custom parameters in attrs.
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     *
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     * <pre>
     * The operation name.  There may be custom parameters in attrs.
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     *
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    /**
     * <pre>
     * The operation name.  There may be custom parameters in attrs.
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     * </pre>
     *
     * <code>string op = 2;</code>
     */
    public Builder clearOp() {
      
      op_ = getDefaultInstance().getOp();
      onChanged();
      return this;
    }
    /**
     * <pre>
     * The operation name.  There may be custom parameters in attrs.
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     *
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    /**
     * <pre>
     * Each input is "node:src_output" with "node" being a string name and
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     *
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     * Each input is "node:src_output" with "node" being a string name and
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     *
     * <code>repeated string input = 3;</code>
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     * <pre>
     * Each input is "node:src_output" with "node" being a string name and
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     * may optionally be followed by control inputs that have the format
     * "^node".
     * </pre>
     *
     * <code>repeated string input = 3;</code>
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    /**
     * <pre>
     * Each input is "node:src_output" with "node" being a string name and
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     * may optionally be followed by control inputs that have the format
     * "^node".
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     *
     * <code>repeated string input = 3;</code>
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     * <pre>
     * Each input is "node:src_output" with "node" being a string name and
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     * may optionally be followed by control inputs that have the format
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     * </pre>
     *
     * <code>repeated string input = 3;</code>
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     * <pre>
     * Each input is "node:src_output" with "node" being a string name and
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     * may optionally be followed by control inputs that have the format
     * "^node".
     * </pre>
     *
     * <code>repeated string input = 3;</code>
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    /**
     * <pre>
     * Each input is "node:src_output" with "node" being a string name and
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     * may optionally be followed by control inputs that have the format
     * "^node".
     * </pre>
     *
     * <code>repeated string input = 3;</code>
     */
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     * <pre>
     * Each input is "node:src_output" with "node" being a string name and
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     *
     * <code>repeated string input = 3;</code>
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    /**
     * <pre>
     * Each input is "node:src_output" with "node" being a string name and
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     *
     * <code>repeated string input = 3;</code>
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    /**
     * <pre>
     * A (possibly partial) specification for the device on which this
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     * The expected syntax for this string is as follows:
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     * PARTIAL_SPEC ::= ("/" CONSTRAINT) *
     * CONSTRAINT ::= ("job:" JOB_NAME)
     *              | ("replica:" [1-9][0-9]*)
     *              | ("task:" [1-9][0-9]*)
     *              | ("device:" [A-Za-z]* ":" ([1-9][0-9]* | "*") )
     * Valid values for this string include:
     * * "/job:worker/replica:0/task:1/device:GPU:3"  (full specification)
     * * "/job:worker/device:GPU:3"                   (partial specification)
     * * ""                                    (no specification)
     * If the constraints do not resolve to a single device (or if this
     * field is empty or not present), the runtime will attempt to
     * choose a device automatically.
     * </pre>
     *
     * <code>string device = 4;</code>
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    /**
     * <pre>
     * A (possibly partial) specification for the device on which this
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     * The expected syntax for this string is as follows:
     * DEVICE_SPEC ::= PARTIAL_SPEC
     * PARTIAL_SPEC ::= ("/" CONSTRAINT) *
     * CONSTRAINT ::= ("job:" JOB_NAME)
     *              | ("replica:" [1-9][0-9]*)
     *              | ("task:" [1-9][0-9]*)
     *              | ("device:" [A-Za-z]* ":" ([1-9][0-9]* | "*") )
     * Valid values for this string include:
     * * "/job:worker/replica:0/task:1/device:GPU:3"  (full specification)
     * * "/job:worker/device:GPU:3"                   (partial specification)
     * * ""                                    (no specification)
     * If the constraints do not resolve to a single device (or if this
     * field is empty or not present), the runtime will attempt to
     * choose a device automatically.
     * </pre>
     *
     * <code>string device = 4;</code>
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      }
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    /**
     * <pre>
     * A (possibly partial) specification for the device on which this
     * node should be placed.
     * The expected syntax for this string is as follows:
     * DEVICE_SPEC ::= PARTIAL_SPEC
     * PARTIAL_SPEC ::= ("/" CONSTRAINT) *
     * CONSTRAINT ::= ("job:" JOB_NAME)
     *              | ("replica:" [1-9][0-9]*)
     *              | ("task:" [1-9][0-9]*)
     *              | ("device:" [A-Za-z]* ":" ([1-9][0-9]* | "*") )
     * Valid values for this string include:
     * * "/job:worker/replica:0/task:1/device:GPU:3"  (full specification)
     * * "/job:worker/device:GPU:3"                   (partial specification)
     * * ""                                    (no specification)
     * If the constraints do not resolve to a single device (or if this
     * field is empty or not present), the runtime will attempt to
     * choose a device automatically.
     * </pre>
     *
     * <code>string device = 4;</code>
     */
    public Builder setDevice(
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      if (value == null) {
    throw new NullPointerException();
  }
  
      device_ = value;
      onChanged();
      return this;
    }
    /**
     * <pre>
     * A (possibly partial) specification for the device on which this
     * node should be placed.
     * The expected syntax for this string is as follows:
     * DEVICE_SPEC ::= PARTIAL_SPEC
     * PARTIAL_SPEC ::= ("/" CONSTRAINT) *
     * CONSTRAINT ::= ("job:" JOB_NAME)
     *              | ("replica:" [1-9][0-9]*)
     *              | ("task:" [1-9][0-9]*)
     *              | ("device:" [A-Za-z]* ":" ([1-9][0-9]* | "*") )
     * Valid values for this string include:
     * * "/job:worker/replica:0/task:1/device:GPU:3"  (full specification)
     * * "/job:worker/device:GPU:3"                   (partial specification)
     * * ""                                    (no specification)
     * If the constraints do not resolve to a single device (or if this
     * field is empty or not present), the runtime will attempt to
     * choose a device automatically.
     * </pre>
     *
     * <code>string device = 4;</code>
     */
    public Builder clearDevice() {
      
      device_ = getDefaultInstance().getDevice();
      onChanged();
      return this;
    }
    /**
     * <pre>
     * A (possibly partial) specification for the device on which this
     * node should be placed.
     * The expected syntax for this string is as follows:
     * DEVICE_SPEC ::= PARTIAL_SPEC
     * PARTIAL_SPEC ::= ("/" CONSTRAINT) *
     * CONSTRAINT ::= ("job:" JOB_NAME)
     *              | ("replica:" [1-9][0-9]*)
     *              | ("task:" [1-9][0-9]*)
     *              | ("device:" [A-Za-z]* ":" ([1-9][0-9]* | "*") )
     * Valid values for this string include:
     * * "/job:worker/replica:0/task:1/device:GPU:3"  (full specification)
     * * "/job:worker/device:GPU:3"                   (partial specification)
     * * ""                                    (no specification)
     * If the constraints do not resolve to a single device (or if this
     * field is empty or not present), the runtime will attempt to
     * choose a device automatically.
     * </pre>
     *
     * <code>string device = 4;</code>
     */
    public Builder setDeviceBytes(
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      if (value == null) {
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  checkByteStringIsUtf8(value);
      
      device_ = value;
      onChanged();
      return this;
    }

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    /**
     * <pre>
     * Operation-specific graph-construction-time configuration.
     * Note that this should include all attrs defined in the
     * corresponding OpDef, including those with a value matching
     * the default -- this allows the default to change and makes
     * NodeDefs easier to interpret on their own.  However, if
     * an attr with a default is not specified in this list, the
     * default will be used.
     * The "names" (keys) must match the regexp "[a-z][a-z0-9_]+" (and
     * one of the names from the corresponding OpDef's attr field).
     * The values must have a type matching the corresponding OpDef
     * attr's type field.
     * TODO(josh11b): Add some examples here showing best practices.
     * </pre>
     *
     * <code>map&lt;string, .tensorflow.AttrValue&gt; attr = 5;</code>
     */

    public boolean containsAttr(
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      if (key == null) { throw new java.lang.NullPointerException(); }
      return internalGetAttr().getMap().containsKey(key);
    }
    /**
     * Use {@link #getAttrMap()} instead.
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    @java.lang.Deprecated
    public java.util.Map<java.lang.String, org.tensorflow.proto.framework.AttrValue> getAttr() {
      return getAttrMap();
    }
    /**
     * <pre>
     * Operation-specific graph-construction-time configuration.
     * Note that this should include all attrs defined in the
     * corresponding OpDef, including those with a value matching
     * the default -- this allows the default to change and makes
     * NodeDefs easier to interpret on their own.  However, if
     * an attr with a default is not specified in this list, the
     * default will be used.
     * The "names" (keys) must match the regexp "[a-z][a-z0-9_]+" (and
     * one of the names from the corresponding OpDef's attr field).
     * The values must have a type matching the corresponding OpDef
     * attr's type field.
     * TODO(josh11b): Add some examples here showing best practices.
     * </pre>
     *
     * <code>map&lt;string, .tensorflow.AttrValue&gt; attr = 5;</code>
     */

    public java.util.Map<java.lang.String, org.tensorflow.proto.framework.AttrValue> getAttrMap() {
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    /**
     * <pre>
     * Operation-specific graph-construction-time configuration.
     * Note that this should include all attrs defined in the
     * corresponding OpDef, including those with a value matching
     * the default -- this allows the default to change and makes
     * NodeDefs easier to interpret on their own.  However, if
     * an attr with a default is not specified in this list, the
     * default will be used.
     * The "names" (keys) must match the regexp "[a-z][a-z0-9_]+" (and
     * one of the names from the corresponding OpDef's attr field).
     * The values must have a type matching the corresponding OpDef
     * attr's type field.
     * TODO(josh11b): Add some examples here showing best practices.
     * </pre>
     *
     * <code>map&lt;string, .tensorflow.AttrValue&gt; attr = 5;</code>
     */

    public org.tensorflow.proto.framework.AttrValue getAttrOrDefault(
        java.lang.String key,
        org.tensorflow.proto.framework.AttrValue defaultValue) {
      if (key == null) { throw new java.lang.NullPointerException(); }
      java.util.Map<java.lang.String, org.tensorflow.proto.framework.AttrValue> map =
          internalGetAttr().getMap();
      return map.containsKey(key) ? map.get(key) : defaultValue;
    }
    /**
     * <pre>
     * Operation-specific graph-construction-time configuration.
     * Note that this should include all attrs defined in the
     * corresponding OpDef, including those with a value matching
     * the default -- this allows the default to change and makes
     * NodeDefs easier to interpret on their own.  However, if
     * an attr with a default is not specified in this list, the
     * default will be used.
     * The "names" (keys) must match the regexp "[a-z][a-z0-9_]+" (and
     * one of the names from the corresponding OpDef's attr field).
     * The values must have a type matching the corresponding OpDef
     * attr's type field.
     * TODO(josh11b): Add some examples here showing best practices.
     * </pre>
     *
     * <code>map&lt;string, .tensorflow.AttrValue&gt; attr = 5;</code>
     */

    public org.tensorflow.proto.framework.AttrValue getAttrOrThrow(
        java.lang.String key) {
      if (key == null) { throw new java.lang.NullPointerException(); }
      java.util.Map<java.lang.String, org.tensorflow.proto.framework.AttrValue> map =
          internalGetAttr().getMap();
      if (!map.containsKey(key)) {
        throw new java.lang.IllegalArgumentException();
      }
      return map.get(key);
    }

    public Builder clearAttr() {
      internalGetMutableAttr().getMutableMap()
          .clear();
      return this;
    }
    /**
     * <pre>
     * Operation-specific graph-construction-time configuration.
     * Note that this should include all attrs defined in the
     * corresponding OpDef, including those with a value matching
     * the default -- this allows the default to change and makes
     * NodeDefs easier to interpret on their own.  However, if
     * an attr with a default is not specified in this list, the
     * default will be used.
     * The "names" (keys) must match the regexp "[a-z][a-z0-9_]+" (and
     * one of the names from the corresponding OpDef's attr field).
     * The values must have a type matching the corresponding OpDef
     * attr's type field.
     * TODO(josh11b): Add some examples here showing best practices.
     * </pre>
     *
     * <code>map&lt;string, .tensorflow.AttrValue&gt; attr = 5;</code>
     */

    public Builder removeAttr(
        java.lang.String key) {
      if (key == null) { throw new java.lang.NullPointerException(); }
      internalGetMutableAttr().getMutableMap()
          .remove(key);
      return this;
    }
    /**
     * Use alternate mutation accessors instead.
     */
    @java.lang.Deprecated
    public java.util.Map<java.lang.String, org.tensorflow.proto.framework.AttrValue>
    getMutableAttr() {
      return internalGetMutableAttr().getMutableMap();
    }
    /**
     * <pre>
     * Operation-specific graph-construction-time configuration.
     * Note that this should include all attrs defined in the
     * corresponding OpDef, including those with a value matching
     * the default -- this allows the default to change and makes
     * NodeDefs easier to interpret on their own.  However, if
     * an attr with a default is not specified in this list, the
     * default will be used.
     * The "names" (keys) must match the regexp "[a-z][a-z0-9_]+" (and
     * one of the names from the corresponding OpDef's attr field).
     * The values must have a type matching the corresponding OpDef
     * attr's type field.
     * TODO(josh11b): Add some examples here showing best practices.
     * </pre>
     *
     * <code>map&lt;string, .tensorflow.AttrValue&gt; attr = 5;</code>
     */
    public Builder putAttr(
        java.lang.String key,
        org.tensorflow.proto.framework.AttrValue value) {
      if (key == null) { throw new java.lang.NullPointerException(); }
      if (value == null) { throw new java.lang.NullPointerException(); }
      internalGetMutableAttr().getMutableMap()
          .put(key, value);
      return this;
    }
    /**
     * <pre>
     * Operation-specific graph-construction-time configuration.
     * Note that this should include all attrs defined in the
     * corresponding OpDef, including those with a value matching
     * the default -- this allows the default to change and makes
     * NodeDefs easier to interpret on their own.  However, if
     * an attr with a default is not specified in this list, the
     * default will be used.
     * The "names" (keys) must match the regexp "[a-z][a-z0-9_]+" (and
     * one of the names from the corresponding OpDef's attr field).
     * The values must have a type matching the corresponding OpDef
     * attr's type field.
     * TODO(josh11b): Add some examples here showing best practices.
     * </pre>
     *
     * <code>map&lt;string, .tensorflow.AttrValue&gt; attr = 5;</code>
     */

    public Builder putAllAttr(
        java.util.Map<java.lang.String, org.tensorflow.proto.framework.AttrValue> values) {
      internalGetMutableAttr().getMutableMap()
          .putAll(values);
      return this;
    }

    private org.tensorflow.proto.framework.NodeDef.ExperimentalDebugInfo experimentalDebugInfo_;
    private com.google.protobuf.SingleFieldBuilderV3<
        org.tensorflow.proto.framework.NodeDef.ExperimentalDebugInfo, org.tensorflow.proto.framework.NodeDef.ExperimentalDebugInfo.Builder, org.tensorflow.proto.framework.NodeDef.ExperimentalDebugInfoOrBuilder> experimentalDebugInfoBuilder_;
    /**
     * <pre>
     * This stores debug information associated with the node.
     * </pre>
     *
     * <code>.tensorflow.NodeDef.ExperimentalDebugInfo experimental_debug_info = 6;</code>
     */
    public boolean hasExperimentalDebugInfo() {
      return experimentalDebugInfoBuilder_ != null || experimentalDebugInfo_ != null;
    }
    /**
     * <pre>
     * This stores debug information associated with the node.
     * </pre>
     *
     * <code>.tensorflow.NodeDef.ExperimentalDebugInfo experimental_debug_info = 6;</code>
     */
    public org.tensorflow.proto.framework.NodeDef.ExperimentalDebugInfo getExperimentalDebugInfo() {
      if (experimentalDebugInfoBuilder_ == null) {
        return experimentalDebugInfo_ == null ? org.tensorflow.proto.framework.NodeDef.ExperimentalDebugInfo.getDefaultInstance() : experimentalDebugInfo_;
      } else {
        return experimentalDebugInfoBuilder_.getMessage();
      }
    }
    /**
     * <pre>
     * This stores debug information associated with the node.
     * </pre>
     *
     * <code>.tensorflow.NodeDef.ExperimentalDebugInfo experimental_debug_info = 6;</code>
     */
    public Builder setExperimentalDebugInfo(org.tensorflow.proto.framework.NodeDef.ExperimentalDebugInfo value) {
      if (experimentalDebugInfoBuilder_ == null) {
        if (value == null) {
          throw new NullPointerException();
        }
        experimentalDebugInfo_ = value;
        onChanged();
      } else {
        experimentalDebugInfoBuilder_.setMessage(value);
      }

      return this;
    }
    /**
     * <pre>
     * This stores debug information associated with the node.
     * </pre>
     *
     * <code>.tensorflow.NodeDef.ExperimentalDebugInfo experimental_debug_info = 6;</code>
     */
    public Builder setExperimentalDebugInfo(
        org.tensorflow.proto.framework.NodeDef.ExperimentalDebugInfo.Builder builderForValue) {
      if (experimentalDebugInfoBuilder_ == null) {
        experimentalDebugInfo_ = builderForValue.build();
        onChanged();
      } else {
        experimentalDebugInfoBuilder_.setMessage(builderForValue.build());
      }

      return this;
    }
    /**
     * <pre>
     * This stores debug information associated with the node.
     * </pre>
     *
     * <code>.tensorflow.NodeDef.ExperimentalDebugInfo experimental_debug_info = 6;</code>
     */
    public Builder mergeExperimentalDebugInfo(org.tensorflow.proto.framework.NodeDef.ExperimentalDebugInfo value) {
      if (experimentalDebugInfoBuilder_ == null) {
        if (experimentalDebugInfo_ != null) {
          experimentalDebugInfo_ =
            org.tensorflow.proto.framework.NodeDef.ExperimentalDebugInfo.newBuilder(experimentalDebugInfo_).mergeFrom(value).buildPartial();
        } else {
          experimentalDebugInfo_ = value;
        }
        onChanged();
      } else {
        experimentalDebugInfoBuilder_.mergeFrom(value);
      }

      return this;
    }
    /**
     * <pre>
     * This stores debug information associated with the node.
     * </pre>
     *
     * <code>.tensorflow.NodeDef.ExperimentalDebugInfo experimental_debug_info = 6;</code>
     */
    public Builder clearExperimentalDebugInfo() {
      if (experimentalDebugInfoBuilder_ == null) {
        experimentalDebugInfo_ = null;
        onChanged();
      } else {
        experimentalDebugInfo_ = null;
        experimentalDebugInfoBuilder_ = null;
      }

      return this;
    }
    /**
     * <pre>
     * This stores debug information associated with the node.
     * </pre>
     *
     * <code>.tensorflow.NodeDef.ExperimentalDebugInfo experimental_debug_info = 6;</code>
     */
    public org.tensorflow.proto.framework.NodeDef.ExperimentalDebugInfo.Builder getExperimentalDebugInfoBuilder() {
      
      onChanged();
      return getExperimentalDebugInfoFieldBuilder().getBuilder();
    }
    /**
     * <pre>
     * This stores debug information associated with the node.
     * </pre>
     *
     * <code>.tensorflow.NodeDef.ExperimentalDebugInfo experimental_debug_info = 6;</code>
     */
    public org.tensorflow.proto.framework.NodeDef.ExperimentalDebugInfoOrBuilder getExperimentalDebugInfoOrBuilder() {
      if (experimentalDebugInfoBuilder_ != null) {
        return experimentalDebugInfoBuilder_.getMessageOrBuilder();
      } else {
        return experimentalDebugInfo_ == null ?
            org.tensorflow.proto.framework.NodeDef.ExperimentalDebugInfo.getDefaultInstance() : experimentalDebugInfo_;
      }
    }
    /**
     * <pre>
     * This stores debug information associated with the node.
     * </pre>
     *
     * <code>.tensorflow.NodeDef.ExperimentalDebugInfo experimental_debug_info = 6;</code>
     */
    private com.google.protobuf.SingleFieldBuilderV3<
        org.tensorflow.proto.framework.NodeDef.ExperimentalDebugInfo, org.tensorflow.proto.framework.NodeDef.ExperimentalDebugInfo.Builder, org.tensorflow.proto.framework.NodeDef.ExperimentalDebugInfoOrBuilder> 
        getExperimentalDebugInfoFieldBuilder() {
      if (experimentalDebugInfoBuilder_ == null) {
        experimentalDebugInfoBuilder_ = new com.google.protobuf.SingleFieldBuilderV3<
            org.tensorflow.proto.framework.NodeDef.ExperimentalDebugInfo, org.tensorflow.proto.framework.NodeDef.ExperimentalDebugInfo.Builder, org.tensorflow.proto.framework.NodeDef.ExperimentalDebugInfoOrBuilder>(
                getExperimentalDebugInfo(),
                getParentForChildren(),
                isClean());
        experimentalDebugInfo_ = null;
      }
      return experimentalDebugInfoBuilder_;
    }

    private org.tensorflow.proto.framework.FullTypeDef experimentalType_;
    private com.google.protobuf.SingleFieldBuilderV3<
        org.tensorflow.proto.framework.FullTypeDef, org.tensorflow.proto.framework.FullTypeDef.Builder, org.tensorflow.proto.framework.FullTypeDefOrBuilder> experimentalTypeBuilder_;
    /**
     * <pre>
     * The complete type of this node. Experimental and subject to change.
     * Currently, the field only contains the return types of the node. That will
     * extend in the future to contain the entire signature of the node, as a
     * function type.
     * </pre>
     *
     * <code>.tensorflow.FullTypeDef experimental_type = 7;</code>
     */
    public boolean hasExperimentalType() {
      return experimentalTypeBuilder_ != null || experimentalType_ != null;
    }
    /**
     * <pre>
     * The complete type of this node. Experimental and subject to change.
     * Currently, the field only contains the return types of the node. That will
     * extend in the future to contain the entire signature of the node, as a
     * function type.
     * </pre>
     *
     * <code>.tensorflow.FullTypeDef experimental_type = 7;</code>
     */
    public org.tensorflow.proto.framework.FullTypeDef getExperimentalType() {
      if (experimentalTypeBuilder_ == null) {
        return experimentalType_ == null ? org.tensorflow.proto.framework.FullTypeDef.getDefaultInstance() : experimentalType_;
      } else {
        return experimentalTypeBuilder_.getMessage();
      }
    }
    /**
     * <pre>
     * The complete type of this node. Experimental and subject to change.
     * Currently, the field only contains the return types of the node. That will
     * extend in the future to contain the entire signature of the node, as a
     * function type.
     * </pre>
     *
     * <code>.tensorflow.FullTypeDef experimental_type = 7;</code>
     */
    public Builder setExperimentalType(org.tensorflow.proto.framework.FullTypeDef value) {
      if (experimentalTypeBuilder_ == null) {
        if (value == null) {
          throw new NullPointerException();
        }
        experimentalType_ = value;
        onChanged();
      } else {
        experimentalTypeBuilder_.setMessage(value);
      }

      return this;
    }
    /**
     * <pre>
     * The complete type of this node. Experimental and subject to change.
     * Currently, the field only contains the return types of the node. That will
     * extend in the future to contain the entire signature of the node, as a
     * function type.
     * </pre>
     *
     * <code>.tensorflow.FullTypeDef experimental_type = 7;</code>
     */
    public Builder setExperimentalType(
        org.tensorflow.proto.framework.FullTypeDef.Builder builderForValue) {
      if (experimentalTypeBuilder_ == null) {
        experimentalType_ = builderForValue.build();
        onChanged();
      } else {
        experimentalTypeBuilder_.setMessage(builderForValue.build());
      }

      return this;
    }
    /**
     * <pre>
     * The complete type of this node. Experimental and subject to change.
     * Currently, the field only contains the return types of the node. That will
     * extend in the future to contain the entire signature of the node, as a
     * function type.
     * </pre>
     *
     * <code>.tensorflow.FullTypeDef experimental_type = 7;</code>
     */
    public Builder mergeExperimentalType(org.tensorflow.proto.framework.FullTypeDef value) {
      if (experimentalTypeBuilder_ == null) {
        if (experimentalType_ != null) {
          experimentalType_ =
            org.tensorflow.proto.framework.FullTypeDef.newBuilder(experimentalType_).mergeFrom(value).buildPartial();
        } else {
          experimentalType_ = value;
        }
        onChanged();
      } else {
        experimentalTypeBuilder_.mergeFrom(value);
      }

      return this;
    }
    /**
     * <pre>
     * The complete type of this node. Experimental and subject to change.
     * Currently, the field only contains the return types of the node. That will
     * extend in the future to contain the entire signature of the node, as a
     * function type.
     * </pre>
     *
     * <code>.tensorflow.FullTypeDef experimental_type = 7;</code>
     */
    public Builder clearExperimentalType() {
      if (experimentalTypeBuilder_ == null) {
        experimentalType_ = null;
        onChanged();
      } else {
        experimentalType_ = null;
        experimentalTypeBuilder_ = null;
      }

      return this;
    }
    /**
     * <pre>
     * The complete type of this node. Experimental and subject to change.
     * Currently, the field only contains the return types of the node. That will
     * extend in the future to contain the entire signature of the node, as a
     * function type.
     * </pre>
     *
     * <code>.tensorflow.FullTypeDef experimental_type = 7;</code>
     */
    public org.tensorflow.proto.framework.FullTypeDef.Builder getExperimentalTypeBuilder() {
      
      onChanged();
      return getExperimentalTypeFieldBuilder().getBuilder();
    }
    /**
     * <pre>
     * The complete type of this node. Experimental and subject to change.
     * Currently, the field only contains the return types of the node. That will
     * extend in the future to contain the entire signature of the node, as a
     * function type.
     * </pre>
     *
     * <code>.tensorflow.FullTypeDef experimental_type = 7;</code>
     */
    public org.tensorflow.proto.framework.FullTypeDefOrBuilder getExperimentalTypeOrBuilder() {
      if (experimentalTypeBuilder_ != null) {
        return experimentalTypeBuilder_.getMessageOrBuilder();
      } else {
        return experimentalType_ == null ?
            org.tensorflow.proto.framework.FullTypeDef.getDefaultInstance() : experimentalType_;
      }
    }
    /**
     * <pre>
     * The complete type of this node. Experimental and subject to change.
     * Currently, the field only contains the return types of the node. That will
     * extend in the future to contain the entire signature of the node, as a
     * function type.
     * </pre>
     *
     * <code>.tensorflow.FullTypeDef experimental_type = 7;</code>
     */
    private com.google.protobuf.SingleFieldBuilderV3<
        org.tensorflow.proto.framework.FullTypeDef, org.tensorflow.proto.framework.FullTypeDef.Builder, org.tensorflow.proto.framework.FullTypeDefOrBuilder> 
        getExperimentalTypeFieldBuilder() {
      if (experimentalTypeBuilder_ == null) {
        experimentalTypeBuilder_ = new com.google.protobuf.SingleFieldBuilderV3<
            org.tensorflow.proto.framework.FullTypeDef, org.tensorflow.proto.framework.FullTypeDef.Builder, org.tensorflow.proto.framework.FullTypeDefOrBuilder>(
                getExperimentalType(),
                getParentForChildren(),
                isClean());
        experimentalType_ = null;
      }
      return experimentalTypeBuilder_;
    }
    @java.lang.Override
    public final Builder setUnknownFields(
        final com.google.protobuf.UnknownFieldSet unknownFields) {
      return super.setUnknownFields(unknownFields);
    }

    @java.lang.Override
    public final Builder mergeUnknownFields(
        final com.google.protobuf.UnknownFieldSet unknownFields) {
      return super.mergeUnknownFields(unknownFields);
    }


    // @@protoc_insertion_point(builder_scope:tensorflow.NodeDef)
  }

  // @@protoc_insertion_point(class_scope:tensorflow.NodeDef)
  private static final org.tensorflow.proto.framework.NodeDef DEFAULT_INSTANCE;
  static {
    DEFAULT_INSTANCE = new org.tensorflow.proto.framework.NodeDef();
  }

  public static org.tensorflow.proto.framework.NodeDef getDefaultInstance() {
    return DEFAULT_INSTANCE;
  }

  private static final com.google.protobuf.Parser<NodeDef>
      PARSER = new com.google.protobuf.AbstractParser<NodeDef>() {
    @java.lang.Override
    public NodeDef parsePartialFrom(
        com.google.protobuf.CodedInputStream input,
        com.google.protobuf.ExtensionRegistryLite extensionRegistry)
        throws com.google.protobuf.InvalidProtocolBufferException {
      return new NodeDef(input, extensionRegistry);
    }
  };

  public static com.google.protobuf.Parser<NodeDef> parser() {
    return PARSER;
  }

  @java.lang.Override
  public com.google.protobuf.Parser<NodeDef> getParserForType() {
    return PARSER;
  }

  @java.lang.Override
  public org.tensorflow.proto.framework.NodeDef getDefaultInstanceForType() {
    return DEFAULT_INSTANCE;
  }

}

