def generic_signature(name_tensor_map):
"""Creates a generic signature of name to Tensor name.
Args:
name_tensor_map: Map from logical name to Tensor.
Returns:
A Signature message.
"""
signature = manifest_pb2.Signature()
for name, tensor in six.iteritems(name_tensor_map):
signature.generic_signature.map[name].tensor_name = tensor.name
return signature
def regression_signature(input_tensor, output_tensor):
"""Creates a regression signature.
Args:
input_tensor: Tensor specifying the input to a graph.
output_tensor: Tensor specifying the output of a graph.
Returns:
A Signature message.
"""
signature = manifest_pb2.Signature()
signature.regression_signature.input.tensor_name = input_tensor.name
signature.regression_signature.output.tensor_name = output_tensor.name
return signature
def classification_signature(input_tensor,
classes_tensor=None,
scores_tensor=None):
"""Creates a classification signature.
Args:
input_tensor: Tensor specifying the input to a graph.
classes_tensor: Tensor specifying the output classes of a graph.
scores_tensor: Tensor specifying the scores of the output classes.
Returns:
A Signature message.
"""
signature = manifest_pb2.Signature()
signature.classification_signature.input.tensor_name = input_tensor.name
if classes_tensor is not None:
signature.classification_signature.classes.tensor_name = classes_tensor.name
if scores_tensor is not None:
signature.classification_signature.scores.tensor_name = scores_tensor.name
return signature