def calculate(
self,
sources: Sequence[prensor.NodeTensor],
destinations: Sequence[expression.Expression],
options: calculate_options.Options,
side_info: Optional[prensor.Prensor] = None
) -> _ProtoRootNodeTensor:
if sources:
raise ValueError("_ProtoRootExpression has no sources")
size = tf.size(self._tensor_of_protos, out_type=tf.int64)
needed_fields = _get_needed_fields(destinations)
backing_str_tensor = None
if options.use_string_view:
assert self._message_format == "binary", (
"`options.use_string_view` is only compatible with 'binary' message "
"format. Please create the root expression with "
"message_format='binary'.")
backing_str_tensor = self._tensor_of_protos
fields = parse_message_level_ex.parse_message_level_ex(
self._tensor_of_protos,
self._descriptor,
needed_fields,
message_format=self._message_format,
backing_str_tensor=backing_str_tensor,
honor_proto3_optional_semantics=options.
experimental_honor_proto3_optional_semantics)
return _ProtoRootNodeTensor(size, fields)
def calculate_from_parsed_field(self,
parsed_field,
destinations
):
needed_fields = _get_needed_fields(destinations)
fields = parse_message_level_ex.parse_message_level_ex(
parsed_field.value, self._desc, needed_fields)
return _ProtoChildNodeTensor(parsed_field.index, self.is_repeated, fields)
def calculate_from_parsed_field(
self, parsed_field: struct2tensor_ops._ParsedField,
destinations: Sequence[expression.Expression]
) -> prensor.NodeTensor:
needed_fields = _get_needed_fields(destinations)
fields = parse_message_level_ex.parse_message_level_ex(
parsed_field.value, self._desc, needed_fields)
return _ProtoChildNodeTensor(parsed_field.index, self.is_repeated,
fields)
def calculate(self, sources,
destinations,
options):
if sources:
raise ValueError("_ProtoRootExpression has no sources")
size = tf.size(self._tensor_of_protos, out_type=tf.int64)
needed_fields = _get_needed_fields(destinations)
fields = parse_message_level_ex.parse_message_level_ex(
self._tensor_of_protos, self._descriptor, needed_fields)
return _ProtoRootNodeTensor(size, fields)
def _run_parse_message_level_ex(proto_list, fields, sess):
serialized = [x.SerializeToString() for x in proto_list]
parsed_field_dict = parse_message_level_ex.parse_message_level_ex(
tf.constant(serialized), proto_list[0].DESCRIPTOR, fields)
sess_input = {}
for key, value in parsed_field_dict.items():
local_dict = {}
local_dict[_INDEX] = value.index
local_dict[_VALUE] = value.value
sess_input[key] = local_dict
return sess.run(sess_input)
def calculate_from_parsed_field(
self, parsed_field: struct2tensor_ops._ParsedField,
destinations: Sequence[expression.Expression],
use_string_view: bool) -> prensor.NodeTensor:
needed_fields = _get_needed_fields(destinations)
backing_str_tensor = None
if use_string_view:
backing_str_tensor = self._backing_str_tensor
fields = parse_message_level_ex.parse_message_level_ex(
parsed_field.value,
self._desc,
needed_fields,
backing_str_tensor=backing_str_tensor)
return _ProtoChildNodeTensor(parsed_field.index, self.is_repeated,
fields)
def calculate(
self,
sources: Sequence[prensor.NodeTensor],
destinations: Sequence[expression.Expression],
options: calculate_options.Options,
side_info: Optional[prensor.Prensor] = None
) -> _ProtoRootNodeTensor:
if sources:
raise ValueError("_ProtoRootExpression has no sources")
size = tf.size(self._tensor_of_protos, out_type=tf.int64)
needed_fields = _get_needed_fields(destinations)
fields = parse_message_level_ex.parse_message_level_ex(
self._tensor_of_protos,
self._descriptor,
needed_fields,
message_format=self._message_format)
return _ProtoRootNodeTensor(size, fields)
def _run_parse_message_level_ex(proto_list, fields, message_format="binary"):
if message_format == "text":
serialized = [text_format.MessageToString(x) for x in proto_list]
elif message_format == "binary":
serialized = [x.SerializeToString() for x in proto_list]
else:
raise ValueError('Message format must be one of "text", "binary"')
parsed_field_dict = parse_message_level_ex.parse_message_level_ex(
tf.constant(serialized), proto_list[0].DESCRIPTOR, fields,
message_format)
sess_input = {}
for key, value in parsed_field_dict.items():
local_dict = {}
local_dict[_INDEX] = value.index
local_dict[_VALUE] = value.value
sess_input[key] = local_dict
return sess_input
def calculate_from_parsed_field(
self,
parsed_field: struct2tensor_ops._ParsedField, # pylint:disable=protected-access
destinations: Sequence[expression.Expression],
options: calculate_options.Options) -> prensor.NodeTensor:
needed_fields = _get_needed_fields(destinations)
backing_str_tensor = None
if options.use_string_view:
backing_str_tensor = self._backing_str_tensor
fields = parse_message_level_ex.parse_message_level_ex(
parsed_field.value,
self._desc,
needed_fields,
backing_str_tensor=backing_str_tensor,
honor_proto3_optional_semantics=options.
experimental_honor_proto3_optional_semantics)
return _ProtoChildNodeTensor(parsed_field.index, self.is_repeated,
fields)