Tensorflow processor輸入輸出為protobuf格式。當您使用SDK發送請求時，SDK對請求進行了封裝，您只需根據SDK提供的函數來構建請求即可。如果您希望自行構建服務請求，則可以參考如下pb定義來生成相關的代碼，詳情請參見TensorFlow服務請求構造。

syntax = "proto3";
option cc_enable_arenas = true;
option java_package = "com.aliyun.openservices.eas.predict.proto";
option java_outer_classname = "PredictProtos";
enum ArrayDataType {
  // Not a legal value for DataType. Used to indicate a DataType field
  // has not been set.
  DT_INVALID = 0;
  // Data types that all computation devices are expected to be
  // capable to support.
  DT_FLOAT = 1;
  DT_DOUBLE = 2;
  DT_INT32 = 3;
  DT_UINT8 = 4;
  DT_INT16 = 5;
  DT_INT8 = 6;
  DT_STRING = 7;
  DT_COMPLEX64 = 8;  // Single-precision complex.
  DT_INT64 = 9;
  DT_BOOL = 10;
  DT_QINT8 = 11;     // Quantized int8.
  DT_QUINT8 = 12;    // Quantized uint8.
  DT_QINT32 = 13;    // Quantized int32.
  DT_BFLOAT16 = 14;  // Float32 truncated to 16 bits.  Only for cast ops.
  DT_QINT16 = 15;    // Quantized int16.
  DT_QUINT16 = 16;   // Quantized uint16.
  DT_UINT16 = 17;
  DT_COMPLEX128 = 18;  // Double-precision complex.
  DT_HALF = 19;
  DT_RESOURCE = 20;
  DT_VARIANT = 21;  // Arbitrary C++ data types.
}
// Dimensions of an array.
message ArrayShape {
  repeated int64 dim = 1 [packed = true];
}
// Protocol buffer representing an array.
message ArrayProto {
  // Data Type.
  ArrayDataType dtype = 1;
  // Shape of the array.
  ArrayShape array_shape = 2;
  // DT_FLOAT.
  repeated float float_val = 3 [packed = true];
  // DT_DOUBLE.
  repeated double double_val = 4 [packed = true];
  // DT_INT32, DT_INT16, DT_INT8, DT_UINT8.
  repeated int32 int_val = 5 [packed = true];
  // DT_STRING.
  repeated bytes string_val = 6;
  // DT_INT64.
  repeated int64 int64_val = 7 [packed = true];
  // DT_BOOL.
  repeated bool bool_val = 8 [packed = true];
}
// PredictRequest specifies which TensorFlow model to run, as well as
// how inputs are mapped to tensors and how outputs are filtered before
// returning to user.
message PredictRequest {
  // A named signature to evaluate. If unspecified, the default signature
  // will be used.
  string signature_name = 1;
  // Input tensors.
  // Names of input tensor are alias names. The mapping from aliases to real
  // input tensor names is expected to be stored as named generic signature
  // under the key "inputs" in the model export.
  // Each alias listed in a generic signature named "inputs" should be provided
  // exactly once in order to run the prediction.
  map<string, ArrayProto> inputs = 2;
  // Output filter.
  // Names specified are alias names. The mapping from aliases to real output
  // tensor names is expected to be stored as named generic signature under
  // the key "outputs" in the model export.
  // Only tensors specified here will be run/fetched and returned, with the
  // exception that when none is specified, all tensors specified in the
  // named signature will be run/fetched and returned.
  repeated string output_filter = 3;
}
// Response for PredictRequest on successful run.
message PredictResponse {
  // Output tensors.
  map<string, ArrayProto> outputs = 1;
}