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                      "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.",
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                        "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": {
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                            "type": "string",
                            "description": "Container in which this resource is placed."
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                            "description": "Unique name for the device containing the resource."
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                            "format": "uint64",
                            "description": "Hash code for the type of the resource. Is only valid in the same device\nand in the same execution."
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                            "description": "For debug-only, the name of the type pointed to by this handle, if\navailable."
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                            "description": "Unique name of this resource."
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                        "format": "float"
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                      "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."
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                      "description": "Shape of the tensor.  TODO(touts): sort out the 0-rank issues.",
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                          "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.",
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                                "description": "Optional name of the tensor dimension."
                              },
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                                "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."
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                        "type": "object",
                        "description": "Protocol buffer representing the serialization format of DT_VARIANT tensors.",
                        "properties": {
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                            "type": "string",
                            "format": "byte",
                            "description": "Portions of the object that are not Tensors."
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                          "tensors": {
                            "type": "array",
                            "description": "Tensors contained within objects being serialized.",
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                            "type": "string",
                            "description": "Name of the type of objects being serialized."
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                    "version_number": {
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                      "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."
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