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@d0k @tensorflower-gardener @drpngx
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syntax = "proto3";
package tensorflow.tf2xla;
import "tensorflow/core/framework/tensor_shape.proto";
import "tensorflow/core/framework/types.proto";
option cc_enable_arenas = true;
option java_outer_classname = "Tf2XlaProtos";
option java_multiple_files = true;
option java_package = "org.tensorflow.tf2xla";
// TensorId identifies a tensor in a TensorFlow graph, by specifying the output
// index of a particular node in the graph. If the output of the named node
// feeds into other node(s), this corresponds to one or more edges. Otherwise
// it doesn't correspond to any existing edges at all, e.g. for output nodes.
message TensorId {
string node_name = 1;
int64 output_index = 2;
}
// Feed represents a single feed tensor in the graph, which corresponds to an
// input argument for the generated computation.
message Feed {
TensorId id = 1;
TensorShapeProto shape = 2;
string name = 3; // Optional name for generated code.
// Optional data type. This is not normally required, as the graph itself
// contains this information. However, if the node being fed is an op that is
// not linked into the binary, then the type cannot be inferred from the node;
// in this case, the type should be set here.
DataType type = 4;
}
// Fetch represents a single fetch tensor in the graph, which corresponds to an
// output argument for the generated computation.
message Fetch {
TensorId id = 1;
string name = 2; // Optional name for generated code.
// Optional shape and data type. If specified, may be used for validation.
TensorShapeProto shape = 3;
DataType type = 4;
}
// Variable represents a resource variable with the given name, shape and type.
message Variable {
string node_name = 1;
string name =
2; // Optional name for generated code. If empty, node_name will be used.
TensorShapeProto shape = 3;
DataType type = 4;
// Flag for variables that are never assigned. Assigments to a read-only
// variable or unassigned variables that are not read-only are invalid.
bool readonly = 5;
}
// Options used during the conversion and compilation process.
message ConversionOptions {
// When true tf.fake_quant_* ops will be emitted as custom calls to a
// 'fake_quant_with_min_max_vars' function accepting the input, min, max,
// num_bits, and narrow_range values as runtime arguments.
bool custom_fake_quant_op_calls = 1;
}
// Config represents configuration information for tf2xla conversion.
message Config {
// Each feed is a positional input argument for the generated computation.
// The order of each entry matches the order of each input argument.
repeated Feed feed = 1;
// Each fetch is a positional output argument for the generated computation.
// The order of each entry matches the order of each output argument.
repeated Fetch fetch = 2;
// Each variable is a named input and output of the generated computation.
repeated Variable variable = 3;
// Optional conversion options.
ConversionOptions conversion_options = 4;
}
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