action seldon_route2 {
  label: "Route2"
  provider: seldon
  method: GET
  path: "/route"
  encoding: json
  input: {
    type: "object"
    properties: {
      json: {
        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: "Dimensions of a tensor."
                    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"
          }
        }
      }
    }
    required: ["json"]
    additionalProperties: false
  }
  output: {
    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: "Dimensions of a tensor."
                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"
      }
    }
  }
}