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EncodeProto

public final class EncodeProto

The op serializes protobuf messages provided in the input tensors.

The types of the tensors in `values` must match the schema for the fields specified in `field_names`. All the tensors in `values` must have a common shape prefix, batch_shape.

The `sizes` tensor specifies repeat counts for each field. The repeat count (last dimension) of a each tensor in `values` must be greater than or equal to corresponding repeat count in `sizes`.

A `message_type` name must be provided to give context for the field names. The actual message descriptor can be looked up either in the linked-in descriptor pool or a filename provided by the caller using the `descriptor_source` attribute.

For the most part, the mapping between Proto field types and TensorFlow dtypes is straightforward. However, there are a few special cases:

- A proto field that contains a submessage or group can only be converted to `DT_STRING` (the serialized submessage). This is to reduce the complexity of the API. The resulting string can be used as input to another instance of the decode_proto op.

- TensorFlow lacks support for unsigned integers. The ops represent uint64 types as a `DT_INT64` with the same twos-complement bit pattern (the obvious way). Unsigned int32 values can be represented exactly by specifying type `DT_INT64`, or using twos-complement if the caller specifies `DT_INT32` in the `output_types` attribute.

The `descriptor_source` attribute selects the source of protocol descriptors to consult when looking up `message_type`. This may be:

- An empty string or "local://", in which case protocol descriptors are created for C++ (not Python) proto definitions linked to the binary.

- A file, in which case protocol descriptors are created from the file, which is expected to contain a `FileDescriptorSet` serialized as a string. NOTE: You can build a `descriptor_source` file using the `--descriptor_set_out` and `--include_imports` options to the protocol compiler `protoc`.

- A "bytes://", in which protocol descriptors are created from ``, which is expected to be a `FileDescriptorSet` serialized as a string.

Nested Classes

class EncodeProto.Options Optional attributes for EncodeProto  

Public Methods

Output<String>
asOutput()
Returns the symbolic handle of a tensor.
Output<String>
bytes()
Tensor of serialized protos with shape `batch_shape`.
static EncodeProto
create(Scope scope, Operand<Integer> sizes, Iterable<Operand<?>> values, List<String> fieldNames, String messageType, Options... options)
Factory method to create a class wrapping a new EncodeProto operation.
static EncodeProto.Options
descriptorSource(String descriptorSource)

Inherited Methods

Public Methods

public Output<String> asOutput ()

Returns the symbolic handle of a tensor.

Inputs to TensorFlow operations are outputs of another TensorFlow operation. This method is used to obtain a symbolic handle that represents the computation of the input.

public Output<String> bytes ()

Tensor of serialized protos with shape `batch_shape`.

public static EncodeProto create (Scope scope, Operand<Integer> sizes, Iterable<Operand<?>> values, List<String> fieldNames, String messageType, Options... options)

Factory method to create a class wrapping a new EncodeProto operation.

Parameters
scope current scope
sizes Tensor of int32 with shape `[batch_shape, len(field_names)]`.
values List of tensors containing values for the corresponding field.
fieldNames List of strings containing proto field names.
messageType Name of the proto message type to decode.
options carries optional attributes values
Returns
  • a new instance of EncodeProto

public static EncodeProto.Options descriptorSource (String descriptorSource)