package nnfusion.serialize

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Protocol buffer representing the value for an attr used to configure an Op. Comment indicates the corresponding attr type. Only the field matching the attr type may be filled.

Used in: NodeDef

• oneof value

  • bytes s = 2

    "string"

  • int64 i = 3

    "int"

  • float f = 4

    "float"

  • bool b = 5

    "bool"

  • PBType type = 6

    "type"

  • TensorShapeProto shape = 7

    "shape"

  • AttrValue.ListValue list = 1

    TensorProto tensor = 8; // "tensor"

    any "list(...)"

Used in: AttrValue

• repeated bytes s = 2

  "list(string)"

• repeated int64 i = 3

  "list(int)"

• repeated float f = 4

  "list(float)"

• repeated bool b = 5

  "list(bool)"

• repeated PBType type = 6

  "list(type)"

• repeated TensorShapeProto shape = 7

  "list(shape)"

Represents the graph of operations

• repeated NodeDef node = 1

• int32 version = 2

Used in: GraphDef

• string name = 1

  The name given to this operator. Used for naming inputs, logging, visualization, etc. Unique within a single GraphDef. Must match the regexp "[A-Za-z0-9.][A-Za-z0-9_>./]*".

• string op = 2

  The operation name. There may be custom parameters in attrs. Op names starting with an underscore are reserved for internal use.

• repeated string input = 3

  Each input is "node:src_output" with "node" being a string name and "src_output" indicating which output tensor to use from "node". If "src_output" is 0 the ":0" suffix can be omitted. Regular inputs may optionally be followed by control inputs that have the format "^node".

• map<string, AttrValue> attr = 5

  Operation-specific graph-construction-time configuration. Note that this should include all attrs defined in the corresponding OpDef, including those with a value matching the default -- this allows the default to change and makes NodeDefs easier to interpret on their own. However, if an attr with a default is not specified in this list, the default will be used. The "names" (keys) must match the regexp "[a-z][a-z0-9_]+" (and one of the names from the corresponding OpDef's attr field). The values must have a type matching the corresponding OpDef attr's type field. TODO(josh11b): Add some examples here showing best practices.

(== suppress_warning documentation-presence ==) LINT.IfChange

Used in: AttrValue, AttrValue.ListValue

• DT_INVALID = 0

  Not a legal value for Type. Used to indicate a Type field has not been set.

• DT_BOOL = 1

  Data types that all computation devices are expected to be capable to support.

• DT_CHAR = 2

• DT_FLOAT = 3

• DT_DOUBLE = 4

• DT_INT8 = 5

• DT_INT16 = 6

• DT_INT32 = 7

• DT_INT64 = 8

• DT_UINT8 = 9

• DT_UINT16 = 10

• DT_UINT32 = 11

• DT_UINT64 = 12

Dimensions of a tensor.

Used in: AttrValue, AttrValue.ListValue

• repeated TensorShapeProto.Dim dim = 2

  Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. If an entry has size -1, this corresponds to a dimension of unknown size. The names are optional. The order of entries in "dim" matters: It indicates the layout of the values in the tensor in-memory representation. The first entry in "dim" is the outermost dimension used to layout the values, the last entry is the innermost dimension. This matches the in-memory layout of RowMajor Eigen tensors. If "dim.size()" > 0, "unknown_rank" must be false.

• bool unknown_rank = 3

  If true, the number of dimensions in the shape is unknown. If true, "dim.size()" must be 0.

One dimension of the tensor.

Used in: TensorShapeProto

• int64 size = 1

  Size of the tensor in that dimension. This value must be >= -1, but values of -1 are reserved for "unknown" shapes (values of -1 mean "unknown" dimension). Certain wrappers that work with TensorShapeProto may fail at runtime when deserializing a TensorShapeProto containing a dim value of -1.

• string name = 2

  Optional name of the tensor dimension.