|TensorFlow 1 version|
The op extracts fields from a serialized protocol buffers message into tensors.
Compat aliases for migration
See Migration guide for more details.
tf.io.decode_proto( bytes, message_type, field_names, output_types, descriptor_source='local://', message_format='binary', sanitize=False, name=None )
decode_proto op extracts fields from a serialized protocol buffers
message into tensors. The fields in
field_names are decoded and converted
to the corresponding
output_types if possible.
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
Each output tensor is a dense tensor. This means that it is padded to hold
the largest number of repeated elements seen in the input minibatch. (The
shape is also padded by one to prevent zero-sized dimensions). The actual
repeat counts for each example in the minibatch can be found in the
output. In many cases the output of
decode_proto is fed immediately into
tf.squeeze if missing values are not a concern. When using tf.squeeze, always
pass the squeeze dimension explicitly to avoid surprises.
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_INT64with 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
Both binary and text proto serializations are