643 matches
AI & ML/Seldon External
TransformInput
v1.0.0Output
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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"
}
}
}