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syntax = "proto3";
package tensorflow;
option cc_enable_arenas = true;
option java_outer_classname = "TensorProtos";
option java_multiple_files = true;
option java_package = "org.tensorflow.framework";
import "tensorflow/core/framework/resource_handle.proto";
import "tensorflow/core/framework/tensor_shape.proto";
import "tensorflow/core/framework/types.proto";
// Protocol buffer representing a tensor.
message TensorProto {
DataType dtype = 1;
// Shape of the tensor. TODO(touts): sort out the 0-rank issues.
TensorShapeProto tensor_shape = 2;
// Only one of the representations below is set, one of "tensor_contents" and
// the "xxx_val" attributes. We are not using oneof because as oneofs cannot
// contain repeated fields it would require another extra set of messages.
// Version number.
//
// In version 0, if the "repeated xxx" representations contain only one
// element, that element is repeated to fill the shape. This makes it easy
// to represent a constant Tensor with a single value.
int32 version_number = 3;
// Serialized raw tensor content from either Tensor::AsProtoTensorContent or
// memcpy in tensorflow::grpc::EncodeTensorToByteBuffer. This representation
// can be used for all tensor types. The purpose of this representation is to
// reduce serialization overhead during RPC call by avoiding serialization of
// many repeated small items.
bytes tensor_content = 4;
// Type specific representations that make it easy to create tensor protos in
// all languages. Only the representation corresponding to "dtype" can
// be set. The values hold the flattened representation of the tensor in
// row major order.
// DT_HALF. Note that since protobuf has no int16 type, we'll have some
// pointless zero padding for each value here.
repeated int32 half_val = 13 [packed = true];
// DT_FLOAT.
repeated float float_val = 5 [packed = true];
// DT_DOUBLE.
repeated double double_val = 6 [packed = true];
// DT_INT32, DT_INT16, DT_INT8, DT_UINT8.
repeated int32 int_val = 7 [packed = true];
// DT_STRING
repeated bytes string_val = 8;
// DT_COMPLEX64. scomplex_val(2*i) and scomplex_val(2*i+1) are real
// and imaginary parts of i-th single precision complex.
repeated float scomplex_val = 9 [packed = true];
// DT_INT64
repeated int64 int64_val = 10 [packed = true];
// DT_BOOL
repeated bool bool_val = 11 [packed = true];
// DT_COMPLEX128. dcomplex_val(2*i) and dcomplex_val(2*i+1) are real
// and imaginary parts of i-th double precision complex.
repeated double dcomplex_val = 12 [packed = true];
// DT_RESOURCE
repeated ResourceHandleProto resource_handle_val = 14;
// DT_VARIANT
repeated VariantTensorDataProto variant_val = 15;
// DT_UINT32
repeated uint32 uint32_val = 16 [packed = true];
// DT_UINT64
repeated uint64 uint64_val = 17 [packed = true];
};
// Protocol buffer representing the serialization format of DT_VARIANT tensors.
message VariantTensorDataProto {
// Name of the type of objects being serialized.
string type_name = 1;
// Portions of the object that are not Tensors.
bytes metadata = 2;
// Tensors contained within objects being serialized.
repeated TensorProto tensors = 3;
}