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syntax = "proto3";
package tensorflow;
option cc_enable_arenas = true;
option java_outer_classname = "FunctionProtos";
option java_multiple_files = true;
option java_package = "org.tensorflow.framework";
option go_package = "github.com/tensorflow/tensorflow/tensorflow/go/core/framework";
import "tensorflow/core/framework/attr_value.proto";
import "tensorflow/core/framework/node_def.proto";
import "tensorflow/core/framework/op_def.proto";
// A library is a set of named functions.
message FunctionDefLibrary {
repeated FunctionDef function = 1;
repeated GradientDef gradient = 2;
}
// A function can be instantiated when the runtime can bind every attr
// with a value. When a GraphDef has a call to a function, it must
// have binding for every attr defined in the signature.
//
// TODO(zhifengc):
// * device spec, etc.
message FunctionDef {
// The definition of the function's name, arguments, return values,
// attrs etc.
OpDef signature = 1;
// Attributes specific to this function definition.
map<string, AttrValue> attr = 5;
// NOTE: field id 2 deleted on Jan 11, 2017, GraphDef version 21.
reserved 2;
// In both of the following fields, there is the need to specify an
// output that is used as either the input to another node (in
// `node_def`) or as a return value of the function (in `ret`).
// Unlike the NodeDefs in GraphDef, we need to be able to specify a
// list in some cases (instead of just single outputs). Also, we
// need to be able to deal with lists of unknown length (so the
// output index may not be known at function definition time). So
// we use the following format instead:
// * "fun_in" where "fun_in" is the name of a function input arg in
// the `signature` field above. This represents that input, whether
// it is a single tensor or a list.
// * "fun_in:0" gives the first element of a function input arg (a
// non-list input is considered a list of length 1 for these
// purposes).
// * "node:out" where "node" is the name of a node in `node_def` and
// "out" is the name one of its op's output arguments (the name
// comes from the OpDef of the node's op). This represents that
// node's output, whether it is a single tensor or a list.
// Note: We enforce that an op's output arguments are never
// renamed in the backwards-compatibility test.
// * "node:out:0" gives the first element of a node output arg (a
// non-list output is considered a list of length 1 for these
// purposes).
//
// NOT CURRENTLY SUPPORTED (but may be in the future):
// * "node:out:-1" gives last element in a node output list
// * "node:out:1:" gives a list with all but the first element in a
// node output list
// * "node:out::-1" gives a list with all but the last element in a
// node output list
// The body of the function. Unlike the NodeDefs in a GraphDef, attrs
// may have values of type `placeholder` and the `input` field uses
// the "output" format above.
// By convention, "op" in node_def is resolved by consulting with a
// user-defined library first. If not resolved, "func" is assumed to
// be a builtin op.
repeated NodeDef node_def = 3;
// A mapping from the output arg names from `signature` to the
// outputs from `node_def` that should be returned by the function.
map<string, string> ret = 4;
}
// GradientDef defines the gradient function of a function defined in
// a function library.
//
// A gradient function g (specified by gradient_func) for a function f
// (specified by function_name) must follow the following:
//
// The function 'f' must be a numerical function which takes N inputs
// and produces M outputs. Its gradient function 'g', which is a
// function taking N + M inputs and produces N outputs.
//
// I.e. if we have
// (y1, y2, ..., y_M) = f(x1, x2, ..., x_N),
// then, g is
// (dL/dx1, dL/dx2, ..., dL/dx_N) = g(x1, x2, ..., x_N,
// dL/dy1, dL/dy2, ..., dL/dy_M),
// where L is a scalar-value function of (x1, x2, ..., xN) (e.g., the
// loss function). dL/dx_i is the partial derivative of L with respect
// to x_i.
message GradientDef {
string function_name = 1; // The function name.
string gradient_func = 2; // The gradient function's name.
}