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{
  "type": "object",
  "properties": {
    "binData": {
      "type": "string",
      "format": "byte"
    },
    "data": {
      "type": "object",
      "properties": {
        "names": {
          "type": "array",
          "items": {
            "type": "string"
          }
        },
        "ndarry": {
          "type": "array",
          "items": {
            "description": "Can be anything: string, number, array, object, etc.",
            "type": "object"
          }
        },
        "tensor": {
          "type": "object",
          "properties": {
            "shape": {
              "type": "array",
              "items": {
                "type": "integer",
                "format": "int32"
              }
            },
            "values": {
              "type": "array",
              "items": {
                "type": "number",
                "format": "double"
              }
            }
          }
        },
        "tftensor": {
          "type": "object",
          "description": "Protocol buffer representing a tensor.",
          "properties": {
            "bool_val": {
              "type": "array",
              "items": {
                "type": "boolean",
                "format": "boolean"
              }
            },
            "dcomplex_val": {
              "type": "array",
              "description": "DT_COMPLEX128. dcomplex_val(2*i) and dcomplex_val(2*i+1) are real\nand imaginary parts of i-th double precision complex.",
              "items": {
                "type": "number",
                "format": "double"
              }
            },
            "double_val": {
              "type": "array",
              "description": "DT_DOUBLE.",
              "items": {
                "type": "number",
                "format": "double"
              }
            },
            "dtype": {
              "type": "string",
              "description": "- DT_INVALID: Not a legal value for DataType.  Used to indicate a DataType field\nhas not been set.\n - DT_FLOAT: Data types that all computation devices are expected to be\ncapable to support.\n - DT_FLOAT_REF: Do not use!  These are only for parameters.  Every enum above\nshould have a corresponding value below (verified by types_test).",
              "enum": [
                "DT_INVALID",
                "DT_FLOAT",
                "DT_DOUBLE",
                "DT_INT32",
                "DT_UINT8",
                "DT_INT16",
                "DT_INT8",
                "DT_STRING",
                "DT_COMPLEX64",
                "DT_INT64",
                "DT_BOOL",
                "DT_QINT8",
                "DT_QUINT8",
                "DT_QINT32",
                "DT_BFLOAT16",
                "DT_QINT16",
                "DT_QUINT16",
                "DT_UINT16",
                "DT_COMPLEX128",
                "DT_HALF",
                "DT_RESOURCE",
                "DT_VARIANT",
                "DT_UINT32",
                "DT_UINT64",
                "DT_FLOAT_REF",
                "DT_DOUBLE_REF",
                "DT_INT32_REF",
                "DT_UINT8_REF",
                "DT_INT16_REF",
                "DT_INT8_REF",
                "DT_STRING_REF",
                "DT_COMPLEX64_REF",
                "DT_INT64_REF",
                "DT_BOOL_REF",
                "DT_QINT8_REF",
                "DT_QUINT8_REF",
                "DT_QINT32_REF",
                "DT_BFLOAT16_REF",
                "DT_QINT16_REF",
                "DT_QUINT16_REF",
                "DT_UINT16_REF",
                "DT_COMPLEX128_REF",
                "DT_HALF_REF",
                "DT_RESOURCE_REF",
                "DT_VARIANT_REF",
                "DT_UINT32_REF",
                "DT_UINT64_REF"
              ]
            },
            "float_val": {
              "type": "array",
              "description": "DT_FLOAT.",
              "items": {
                "type": "number",
                "format": "float"
              }
            },
            "half_val": {
              "type": "array",
              "description": "DT_HALF, DT_BFLOAT16. Note that since protobuf has no int16 type, we'll\nhave some pointless zero padding for each value here.",
              "items": {
                "type": "integer",
                "format": "int32"
              }
            },
            "int64_val": {
              "type": "array",
              "items": {
                "type": "string",
                "format": "int64"
              }
            },
            "int_val": {
              "type": "array",
              "description": "DT_INT32, DT_INT16, DT_INT8, DT_UINT8.",
              "items": {
                "type": "integer",
                "format": "int32"
              }
            },
            "resource_handle_val": {
              "type": "array",
              "items": {
                "type": "object",
                "description": "Protocol buffer representing a handle to a tensorflow resource. Handles are\nnot valid across executions, but can be serialized back and forth from within\na single run.",
                "properties": {
                  "container": {
                    "type": "string",
                    "description": "Container in which this resource is placed."
                  },
                  "device": {
                    "type": "string",
                    "description": "Unique name for the device containing the resource."
                  },
                  "hash_code": {
                    "type": "string",
                    "format": "uint64",
                    "description": "Hash code for the type of the resource. Is only valid in the same device\nand in the same execution."
                  },
                  "maybe_type_name": {
                    "type": "string",
                    "description": "For debug-only, the name of the type pointed to by this handle, if\navailable."
                  },
                  "name": {
                    "type": "string",
                    "description": "Unique name of this resource."
                  }
                }
              }
            },
            "scomplex_val": {
              "type": "array",
              "description": "DT_COMPLEX64. scomplex_val(2*i) and scomplex_val(2*i+1) are real\nand imaginary parts of i-th single precision complex.",
              "items": {
                "type": "number",
                "format": "float"
              }
            },
            "string_val": {
              "type": "array",
              "items": {
                "type": "string",
                "format": "byte"
              }
            },
            "tensor_content": {
              "type": "string",
              "format": "byte",
              "description": "Serialized raw tensor content from either Tensor::AsProtoTensorContent or\nmemcpy in tensorflow::grpc::EncodeTensorToByteBuffer. This representation\ncan be used for all tensor types. The purpose of this representation is to\nreduce serialization overhead during RPC call by avoiding serialization of\nmany repeated small items."
            },
            "tensor_shape": {
              "type": "object",
              "description": "Shape of the tensor.  TODO(touts): sort out the 0-rank issues.",
              "properties": {
                "dim": {
                  "type": "array",
                  "description": "Dimensions of the tensor, such as {\"input\", 30}, {\"output\", 40}\nfor a 30 x 40 2D tensor.  If an entry has size -1, this\ncorresponds to a dimension of unknown size. The names are\noptional.\n\nThe order of entries in \"dim\" matters: It indicates the layout of the\nvalues in the tensor in-memory representation.\n\nThe first entry in \"dim\" is the outermost dimension used to layout the\nvalues, the last entry is the innermost dimension.  This matches the\nin-memory layout of RowMajor Eigen tensors.\n\nIf \"dim.size()\" > 0, \"unknown_rank\" must be false.",
                  "items": {
                    "type": "object",
                    "description": "One dimension of the tensor.",
                    "properties": {
                      "name": {
                        "type": "string",
                        "description": "Optional name of the tensor dimension."
                      },
                      "size": {
                        "type": "string",
                        "format": "int64",
                        "description": "Size of the tensor in that dimension.\nThis value must be >= -1, but values of -1 are reserved for \"unknown\"\nshapes (values of -1 mean \"unknown\" dimension).  Certain wrappers\nthat work with TensorShapeProto may fail at runtime when deserializing\na TensorShapeProto containing a dim value of -1."
                      }
                    }
                  }
                },
                "unknown_rank": {
                  "type": "boolean",
                  "format": "boolean",
                  "description": "If true, the number of dimensions in the shape is unknown.\n\nIf true, \"dim.size()\" must be 0."
                }
              }
            },
            "uint32_val": {
              "type": "array",
              "items": {
                "type": "integer",
                "format": "int64"
              }
            },
            "uint64_val": {
              "type": "array",
              "items": {
                "type": "string",
                "format": "uint64"
              }
            },
            "variant_val": {
              "type": "array",
              "items": {
                "type": "object",
                "description": "Protocol buffer representing the serialization format of DT_VARIANT tensors.",
                "properties": {
                  "metadata": {
                    "type": "string",
                    "format": "byte",
                    "description": "Portions of the object that are not Tensors."
                  },
                  "tensors": {
                    "type": "array",
                    "description": "Tensors contained within objects being serialized.",
                    "items": {
                      "type": "object",
                      "additionalProperties": true
                    }
                  },
                  "type_name": {
                    "type": "string",
                    "description": "Name of the type of objects being serialized."
                  }
                }
              }
            },
            "version_number": {
              "type": "integer",
              "format": "int32",
              "description": "Version number.\n\nIn version 0, if the \"repeated xxx\" representations contain only one\nelement, that element is repeated to fill the shape.  This makes it easy\nto represent a constant Tensor with a single value."
            }
          }
        }
      }
    },
    "meta": {
      "type": "object",
      "properties": {
        "metrics": {
          "type": "array",
          "items": {
            "type": "object",
            "properties": {
              "key": {
                "type": "string"
              },
              "type": {
                "type": "string",
                "enum": [
                  "COUNTER",
                  "GAUGE",
                  "TIMER"
                ]
              },
              "value": {
                "type": "number",
                "format": "float"
              }
            }
          }
        },
        "puid": {
          "type": "string"
        },
        "requestPath": {
          "type": "object"
        },
        "routing": {
          "type": "object"
        },
        "tags": {
          "type": "object"
        }
      }
    },
    "status": {
      "type": "object",
      "properties": {
        "code": {
          "type": "integer",
          "format": "int32"
        },
        "info": {
          "type": "string"
        },
        "reason": {
          "type": "string"
        },
        "status": {
          "type": "string",
          "enum": [
            "SUCCESS",
            "FAILURE"
          ]
        }
      }
    },
    "strData": {
      "type": "string"
    }
  }
}