def build_all_signature_defs(receiver_tensors,
export_outputs,
receiver_tensors_alternatives=None):
"""Build `SignatureDef`s for all export outputs."""
if not isinstance(receiver_tensors, dict):
receiver_tensors = {_SINGLE_RECEIVER_DEFAULT_NAME: receiver_tensors}
if export_outputs is None or not isinstance(export_outputs, dict):
raise ValueError('export_outputs must be a dict and not'
'{}'.format(type(export_outputs)))
signature_def_map = {}
excluded_signatures = {}
for output_key, export_output in export_outputs.items():
signature_name = '{}'.format(output_key or 'None')
try:
signature = export_output.as_signature_def(receiver_tensors)
signature_def_map[signature_name] = signature
except ValueError as e:
excluded_signatures[signature_name] = str(e)
if receiver_tensors_alternatives:
for receiver_name, receiver_tensors_alt in (
six.iteritems(receiver_tensors_alternatives)):
if not isinstance(receiver_tensors_alt, dict):
receiver_tensors_alt = {
_SINGLE_RECEIVER_DEFAULT_NAME: receiver_tensors_alt
}
for output_key, export_output in export_outputs.items():
signature_name = '{}:{}'.format(receiver_name or 'None',
output_key or 'None')
try:
signature = export_output.as_signature_def(
receiver_tensors_alt)
signature_def_map[signature_name] = signature
except ValueError as e:
excluded_signatures[signature_name] = str(e)
_log_signature_report(signature_def_map, excluded_signatures)
# The above calls to export_output.as_signature_def should return only
# valid signatures; if there is a validity problem, they raise ValueError,
# which we ignore above. Consequently the call to is_valid_signature here
# should not remove anything else; it's just an extra sanity check.
return {
k: v
for k, v in signature_def_map.items()
if signature_def_utils.is_valid_signature(v)
}
def build_all_signature_defs(receiver_tensors,
export_outputs,
receiver_tensors_alternatives=None):
"""Build `SignatureDef`s for all export outputs."""
if not isinstance(receiver_tensors, dict):
receiver_tensors = {_SINGLE_RECEIVER_DEFAULT_NAME: receiver_tensors}
if export_outputs is None or not isinstance(export_outputs, dict):
raise ValueError('export_outputs must be a dict and not'
'{}'.format(type(export_outputs)))
signature_def_map = {}
excluded_signatures = {}
for output_key, export_output in export_outputs.items():
signature_name = '{}'.format(output_key or 'None')
try:
signature = export_output.as_signature_def(receiver_tensors)
signature_def_map[signature_name] = signature
except ValueError as e:
excluded_signatures[signature_name] = str(e)
if receiver_tensors_alternatives:
for receiver_name, receiver_tensors_alt in (
six.iteritems(receiver_tensors_alternatives)):
if not isinstance(receiver_tensors_alt, dict):
receiver_tensors_alt = {_SINGLE_RECEIVER_DEFAULT_NAME:
receiver_tensors_alt}
for output_key, export_output in export_outputs.items():
signature_name = '{}:{}'.format(receiver_name or 'None',
output_key or 'None')
try:
signature = export_output.as_signature_def(receiver_tensors_alt)
signature_def_map[signature_name] = signature
except ValueError as e:
excluded_signatures[signature_name] = str(e)
_log_signature_report(signature_def_map, excluded_signatures)
# The above calls to export_output.as_signature_def should return only
# valid signatures; if there is a validity problem, they raise ValueError,
# which we ignore above. Consequently the call to is_valid_signature here
# should not remove anything else; it's just an extra sanity check.
return {k: v for k, v in signature_def_map.items()
if signature_def_utils.is_valid_signature(v)}
def build_all_signature_defs(receiver_tensors,
export_outputs,
receiver_tensors_alternatives=None,
serving_only=True):
"""Build `SignatureDef`s for all export outputs.
Args:
receiver_tensors: a `Tensor`, or a dict of string to `Tensor`, specifying
input nodes where this receiver expects to be fed by default. Typically,
this is a single placeholder expecting serialized `tf.Example` protos.
export_outputs: a dict of ExportOutput instances, each of which has
an as_signature_def instance method that will be called to retrieve
the signature_def for all export output tensors.
receiver_tensors_alternatives: a dict of string to additional
groups of receiver tensors, each of which may be a `Tensor` or a dict of
string to `Tensor`. These named receiver tensor alternatives generate
additional serving signatures, which may be used to feed inputs at
different points within the input receiver subgraph. A typical usage is
to allow feeding raw feature `Tensor`s *downstream* of the
tf.parse_example() op. Defaults to None.
serving_only: boolean; if true, resulting signature defs will only include
valid serving signatures. If false, all requested signatures will be
returned.
Returns:
signature_def representing all passed args.
Raises:
ValueError: if export_outputs is not a dict
"""
if not isinstance(receiver_tensors, dict):
receiver_tensors = {_SINGLE_RECEIVER_DEFAULT_NAME: receiver_tensors}
if export_outputs is None or not isinstance(export_outputs, dict):
raise ValueError('export_outputs must be a dict and not'
'{}'.format(type(export_outputs)))
signature_def_map = {}
excluded_signatures = {}
for output_key, export_output in export_outputs.items():
signature_name = '{}'.format(output_key or 'None')
try:
signature = export_output.as_signature_def(receiver_tensors)
signature_def_map[signature_name] = signature
except ValueError as e:
excluded_signatures[signature_name] = str(e)
if receiver_tensors_alternatives:
for receiver_name, receiver_tensors_alt in (
six.iteritems(receiver_tensors_alternatives)):
if not isinstance(receiver_tensors_alt, dict):
receiver_tensors_alt = {
_SINGLE_RECEIVER_DEFAULT_NAME: receiver_tensors_alt
}
for output_key, export_output in export_outputs.items():
signature_name = '{}:{}'.format(receiver_name or 'None', output_key or
'None')
try:
signature = export_output.as_signature_def(receiver_tensors_alt)
signature_def_map[signature_name] = signature
except ValueError as e:
excluded_signatures[signature_name] = str(e)
_log_signature_report(signature_def_map, excluded_signatures)
# The above calls to export_output.as_signature_def should return only
# valid signatures; if there is a validity problem, they raise a ValueError,
# in which case we exclude that signature from signature_def_map above.
# The is_valid_signature check ensures that the signatures produced are
# valid for serving, and acts as an additional sanity check for export
# signatures produced for serving. We skip this check for training and eval
# signatures, which are not intended for serving.
if serving_only:
signature_def_map = {
k: v
for k, v in signature_def_map.items()
if signature_def_utils.is_valid_signature(v)
}
return signature_def_map
def build_all_signature_defs(receiver_tensors,
export_outputs,
receiver_tensors_alternatives=None,
serving_only=True):
"""Build `SignatureDef`s for all export outputs.
Args:
receiver_tensors: a `Tensor`, or a dict of string to `Tensor`, specifying
input nodes where this receiver expects to be fed by default. Typically,
this is a single placeholder expecting serialized `tf.Example` protos.
export_outputs: a dict of ExportOutput instances, each of which has
an as_signature_def instance method that will be called to retrieve
the signature_def for all export output tensors.
receiver_tensors_alternatives: a dict of string to additional
groups of receiver tensors, each of which may be a `Tensor` or a dict of
string to `Tensor`. These named receiver tensor alternatives generate
additional serving signatures, which may be used to feed inputs at
different points within the input receiver subgraph. A typical usage is
to allow feeding raw feature `Tensor`s *downstream* of the
tf.parse_example() op. Defaults to None.
serving_only: boolean; if true, resulting signature defs will only include
valid serving signatures. If false, all requested signatures will be
returned.
Returns:
signature_def representing all passed args.
Raises:
ValueError: if export_outputs is not a dict
"""
if not isinstance(receiver_tensors, dict):
receiver_tensors = {_SINGLE_RECEIVER_DEFAULT_NAME: receiver_tensors}
if export_outputs is None or not isinstance(export_outputs, dict):
raise ValueError('export_outputs must be a dict and not'
'{}'.format(type(export_outputs)))
signature_def_map = {}
excluded_signatures = {}
for output_key, export_output in export_outputs.items():
signature_name = '{}'.format(output_key or 'None')
try:
signature = export_output.as_signature_def(receiver_tensors)
signature_def_map[signature_name] = signature
except ValueError as e:
excluded_signatures[signature_name] = str(e)
if receiver_tensors_alternatives:
for receiver_name, receiver_tensors_alt in (
six.iteritems(receiver_tensors_alternatives)):
if not isinstance(receiver_tensors_alt, dict):
receiver_tensors_alt = {_SINGLE_RECEIVER_DEFAULT_NAME:
receiver_tensors_alt}
for output_key, export_output in export_outputs.items():
signature_name = '{}:{}'.format(receiver_name or 'None',
output_key or 'None')
try:
signature = export_output.as_signature_def(receiver_tensors_alt)
signature_def_map[signature_name] = signature
except ValueError as e:
excluded_signatures[signature_name] = str(e)
_log_signature_report(signature_def_map, excluded_signatures)
# The above calls to export_output.as_signature_def should return only
# valid signatures; if there is a validity problem, they raise a ValueError,
# in which case we exclude that signature from signature_def_map above.
# The is_valid_signature check ensures that the signatures produced are
# valid for serving, and acts as an additional sanity check for export
# signatures produced for serving. We skip this check for training and eval
# signatures, which are not intended for serving.
if serving_only:
signature_def_map = {k: v for k, v in signature_def_map.items()
if signature_def_utils.is_valid_signature(v)}
return signature_def_map
