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com.intel.analytics.bigdl.ppml.fl.generated.NNServiceProto Maven / Gradle / Ivy

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// Generated by the protocol buffer compiler.  DO NOT EDIT!
// source: nn_service.proto

package com.intel.analytics.bigdl.ppml.fl.generated;

public final class NNServiceProto {
  private NNServiceProto() {}
  public static void registerAllExtensions(
      com.google.protobuf.ExtensionRegistryLite registry) {
  }

  public static void registerAllExtensions(
      com.google.protobuf.ExtensionRegistry registry) {
    registerAllExtensions(
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    /**
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    public static com.intel.analytics.bigdl.ppml.fl.generated.NNServiceProto.TrainRequest parseFrom(
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    public static com.intel.analytics.bigdl.ppml.fl.generated.NNServiceProto.TrainRequest 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 com.intel.analytics.bigdl.ppml.fl.generated.NNServiceProto.TrainRequest parseFrom(
        com.google.protobuf.ByteString data)
        throws com.google.protobuf.InvalidProtocolBufferException {
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    public static com.intel.analytics.bigdl.ppml.fl.generated.NNServiceProto.TrainRequest 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 com.intel.analytics.bigdl.ppml.fl.generated.NNServiceProto.TrainRequest parseFrom(byte[] data)
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      return PARSER.parseFrom(data);
    }
    public static com.intel.analytics.bigdl.ppml.fl.generated.NNServiceProto.TrainRequest parseFrom(
        byte[] data,
        com.google.protobuf.ExtensionRegistryLite extensionRegistry)
        throws com.google.protobuf.InvalidProtocolBufferException {
      return PARSER.parseFrom(data, extensionRegistry);
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    public static com.intel.analytics.bigdl.ppml.fl.generated.NNServiceProto.TrainRequest parseFrom(java.io.InputStream input)
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      return com.google.protobuf.GeneratedMessageV3
          .parseWithIOException(PARSER, input);
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    public static com.intel.analytics.bigdl.ppml.fl.generated.NNServiceProto.TrainRequest parseFrom(
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        com.google.protobuf.ExtensionRegistryLite extensionRegistry)
        throws java.io.IOException {
      return com.google.protobuf.GeneratedMessageV3
          .parseWithIOException(PARSER, input, extensionRegistry);
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    public static com.intel.analytics.bigdl.ppml.fl.generated.NNServiceProto.TrainRequest parseDelimitedFrom(java.io.InputStream input)
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    public static com.intel.analytics.bigdl.ppml.fl.generated.NNServiceProto.TrainRequest parseDelimitedFrom(
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        throws java.io.IOException {
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    public static com.intel.analytics.bigdl.ppml.fl.generated.NNServiceProto.TrainRequest parseFrom(
        com.google.protobuf.CodedInputStream input)
        throws java.io.IOException {
      return com.google.protobuf.GeneratedMessageV3
          .parseWithIOException(PARSER, input);
    }
    public static com.intel.analytics.bigdl.ppml.fl.generated.NNServiceProto.TrainRequest parseFrom(
        com.google.protobuf.CodedInputStream input,
        com.google.protobuf.ExtensionRegistryLite extensionRegistry)
        throws java.io.IOException {
      return com.google.protobuf.GeneratedMessageV3
          .parseWithIOException(PARSER, input, extensionRegistry);
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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(com.intel.analytics.bigdl.ppml.fl.generated.NNServiceProto.TrainRequest prototype) {
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    }
    @java.lang.Override
    public Builder toBuilder() {
      return this == DEFAULT_INSTANCE
          ? new Builder() : new Builder().mergeFrom(this);
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    @java.lang.Override
    protected Builder newBuilderForType(
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      Builder builder = new Builder(parent);
      return builder;
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    /**
     * Protobuf type {@code nn.TrainRequest}
     */
    public static final class Builder extends
        com.google.protobuf.GeneratedMessageV3.Builder implements
        // @@protoc_insertion_point(builder_implements:nn.TrainRequest)
        com.intel.analytics.bigdl.ppml.fl.generated.NNServiceProto.TrainRequestOrBuilder {
      public static final com.google.protobuf.Descriptors.Descriptor
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        return com.intel.analytics.bigdl.ppml.fl.generated.NNServiceProto.internal_static_nn_TrainRequest_descriptor;
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      // Construct using com.intel.analytics.bigdl.ppml.fl.generated.NNServiceProto.TrainRequest.newBuilder()
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        if (!result.isInitialized()) {
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        return result;
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      @java.lang.Override
      public com.intel.analytics.bigdl.ppml.fl.generated.NNServiceProto.TrainRequest buildPartial() {
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      @java.lang.Override
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          return this;
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      public Builder mergeFrom(com.intel.analytics.bigdl.ppml.fl.generated.NNServiceProto.TrainRequest other) {
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        if (other.getClientuuid() != 0) {
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        } catch (com.google.protobuf.InvalidProtocolBufferException e) {
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      /**
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       * @return This builder for chaining.
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        clientuuid_ = value;
        onChanged();
        return this;
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      /**
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      public Builder clearClientuuid() {
        
        clientuuid_ = 0;
        onChanged();
        return this;
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      private com.intel.analytics.bigdl.ppml.fl.generated.FlBaseProto.TensorMap data_;
      private com.google.protobuf.SingleFieldBuilderV3<
          com.intel.analytics.bigdl.ppml.fl.generated.FlBaseProto.TensorMap, com.intel.analytics.bigdl.ppml.fl.generated.FlBaseProto.TensorMap.Builder, com.intel.analytics.bigdl.ppml.fl.generated.FlBaseProto.TensorMapOrBuilder> dataBuilder_;
      /**
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      public boolean hasData() {
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      /**
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      public com.intel.analytics.bigdl.ppml.fl.generated.FlBaseProto.TensorMap getData() {
        if (dataBuilder_ == null) {
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        } else {
          return dataBuilder_.getMessage();
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      /**
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      public Builder setData(com.intel.analytics.bigdl.ppml.fl.generated.FlBaseProto.TensorMap value) {
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          if (value == null) {
            throw new NullPointerException();
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          data_ = value;
          onChanged();
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          dataBuilder_.setMessage(value);
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        return this;
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      /**
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      public Builder setData(
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        if (dataBuilder_ == null) {
          data_ = builderForValue.build();
          onChanged();
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        return this;
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      /**
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      public Builder mergeData(com.intel.analytics.bigdl.ppml.fl.generated.FlBaseProto.TensorMap value) {
        if (dataBuilder_ == null) {
          if (data_ != null) {
            data_ =
              com.intel.analytics.bigdl.ppml.fl.generated.FlBaseProto.TensorMap.newBuilder(data_).mergeFrom(value).buildPartial();
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            data_ = value;
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          onChanged();
        } else {
          dataBuilder_.mergeFrom(value);
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        return this;
      }
      /**
       * .TensorMap data = 2;
       */
      public Builder clearData() {
        if (dataBuilder_ == null) {
          data_ = null;
          onChanged();
        } else {
          data_ = null;
          dataBuilder_ = null;
        }

        return this;
      }
      /**
       * .TensorMap data = 2;
       */
      public com.intel.analytics.bigdl.ppml.fl.generated.FlBaseProto.TensorMap.Builder getDataBuilder() {
        
        onChanged();
        return getDataFieldBuilder().getBuilder();
      }
      /**
       * .TensorMap data = 2;
       */
      public com.intel.analytics.bigdl.ppml.fl.generated.FlBaseProto.TensorMapOrBuilder getDataOrBuilder() {
        if (dataBuilder_ != null) {
          return dataBuilder_.getMessageOrBuilder();
        } else {
          return data_ == null ?
              com.intel.analytics.bigdl.ppml.fl.generated.FlBaseProto.TensorMap.getDefaultInstance() : data_;
        }
      }
      /**
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      private com.google.protobuf.SingleFieldBuilderV3<
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          data_ = null;
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  private static final com.google.protobuf.Descriptors.Descriptor
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  private static final com.google.protobuf.Descriptors.Descriptor
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  private static final com.google.protobuf.Descriptors.Descriptor
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  private static final com.google.protobuf.Descriptors.Descriptor
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  private static final com.google.protobuf.Descriptors.Descriptor
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  private static final 
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  private static final com.google.protobuf.Descriptors.Descriptor
    internal_static_nn_SaveModelResponse_descriptor;
  private static final 
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  }
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      descriptor;
  static {
    java.lang.String[] descriptorData = {
      "\n\020nn_service.proto\022\002nn\032\rfl_base.proto\"O\n" +
      "\014TrainRequest\022\022\n\nclientuuid\030\001 \001(\005\022\030\n\004dat" +
      "a\030\002 \001(\0132\n.TensorMap\022\021\n\talgorithm\030\003 \001(\t\"I" +
      "\n\rTrainResponse\022\020\n\010response\030\001 \001(\t\022\030\n\004dat" +
      "a\030\002 \001(\0132\n.TensorMap\022\014\n\004code\030\003 \001(\005\"b\n\017Eva" +
      "luateRequest\022\022\n\nclientuuid\030\001 \001(\005\022\030\n\004data" +
      "\030\002 \001(\0132\n.TensorMap\022\021\n\talgorithm\030\003 \001(\t\022\016\n" +
      "\006return\030\004 \001(\010\"]\n\020EvaluateResponse\022\020\n\010res" +
      "ponse\030\001 \001(\t\022\030\n\004data\030\002 \001(\0132\n.TensorMap\022\014\n" +
      "\004code\030\003 \001(\005\022\017\n\007message\030\004 \001(\t\"Q\n\016PredictR" +
      "equest\022\022\n\nclientuuid\030\001 \001(\005\022\030\n\004data\030\002 \001(\013" +
      "2\n.TensorMap\022\021\n\talgorithm\030\003 \001(\t\"K\n\017Predi" +
      "ctResponse\022\020\n\010response\030\001 \001(\t\022\030\n\004data\030\002 \001" +
      "(\0132\n.TensorMap\022\014\n\004code\030\003 \001(\005\"r\n\021UploadMe" +
      "taRequest\022\023\n\013client_uuid\030\001 \001(\005\022\017\n\007loss_f" +
      "n\030\002 \001(\014\022#\n\toptimizer\030\003 \001(\0132\020.nn.ClassAnd" +
      "Args\022\022\n\naggregator\030\004 \001(\t\"\033\n\tByteChunk\022\016\n" +
      "\006buffer\030\001 \001(\014\")\n\014ClassAndArgs\022\013\n\003cls\030\001 \001" +
      "(\014\022\014\n\004args\030\002 \001(\014\"3\n\022UploadMetaResponse\022\017" +
      "\n\007message\030\001 \001(\t\022\014\n\004code\030\002 \001(\005\"J\n\020LoadMod" +
      "elRequest\022\021\n\tclient_id\030\001 \001(\005\022\017\n\007backend\030" +
      "\002 \001(\t\022\022\n\nmodel_path\030\003 \001(\t\"2\n\021LoadModelRe" +
      "sponse\022\017\n\007message\030\001 \001(\t\022\014\n\004code\030\002 \001(\005\"J\n" +
      "\020SaveModelRequest\022\021\n\tclient_id\030\001 \001(\005\022\017\n\007" +
      "backend\030\002 \001(\t\022\022\n\nmodel_path\030\003 \001(\t\"$\n\021Sav" +
      "eModelResponse\022\017\n\007message\030\001 \001(\t2\254\003\n\tNNSe" +
      "rvice\022.\n\005train\022\020.nn.TrainRequest\032\021.nn.Tr" +
      "ainResponse\"\000\0227\n\010evaluate\022\023.nn.EvaluateR" +
      "equest\032\024.nn.EvaluateResponse\"\000\0224\n\007predic" +
      "t\022\022.nn.PredictRequest\032\023.nn.PredictRespon" +
      "se\"\000\022>\n\013upload_meta\022\025.nn.UploadMetaReque" +
      "st\032\026.nn.UploadMetaResponse\"\000\0228\n\013upload_f" +
      "ile\022\r.nn.ByteChunk\032\026.nn.UploadMetaRespon" +
      "se\"\000(\001\022B\n\021save_server_model\022\024.nn.SaveMod" +
      "elRequest\032\025.nn.SaveModelResponse\"\000\022B\n\021lo" +
      "ad_server_model\022\024.nn.LoadModelRequest\032\025." +
      "nn.LoadModelResponse\"\000B=\n+com.intel.anal" +
      "ytics.bigdl.ppml.fl.generatedB\016NNService" +
      "Protob\006proto3"
    };
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      .internalBuildGeneratedFileFrom(descriptorData,
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    internal_static_nn_TrainRequest_descriptor =
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    internal_static_nn_TrainResponse_descriptor =
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    internal_static_nn_EvaluateRequest_descriptor =
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    internal_static_nn_PredictRequest_descriptor =
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    internal_static_nn_PredictResponse_descriptor =
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    internal_static_nn_UploadMetaRequest_descriptor =
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    internal_static_nn_UploadMetaRequest_fieldAccessorTable = new
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    internal_static_nn_ByteChunk_descriptor =
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    internal_static_nn_ClassAndArgs_descriptor =
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    com.intel.analytics.bigdl.ppml.fl.generated.FlBaseProto.getDescriptor();
  }

  // @@protoc_insertion_point(outer_class_scope)
}




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