def summarize_graph(graph_def):
placeholders = dict()
outputs = list()
graph = tf_v1.Graph()
with graph.as_default(): # pylint: disable=not-context-manager
tf_v1.import_graph_def(graph_def, name='')
for node in graph.as_graph_def().node: # pylint: disable=no-member
if node.op == 'Placeholder':
node_dict = dict()
node_dict['type'] = tf_v1.DType(node.attr['dtype'].type).name
node_dict['shape'] = str(tf_v1.TensorShape(node.attr['shape'].shape)).replace(' ', '').replace('?', '-1')
placeholders[node.name] = node_dict
if len(children(node.name, graph)) == 0:
if node.op not in unlikely_output_types and node.name.split('/')[-1] not in unlikely_output_types:
outputs.append(node.name)
result = dict()
result['inputs'] = placeholders
result['outputs'] = outputs
return result
def attr_value_to_python_type(
attr_value, # type: tf.AttrValue
attr_name # type: String
):
# type (...) -> Any
"""
Inverse of python_type_to_attr_value().
Args:
attr_value: Protocol buffer version of a node's attribute value
Returns:
A Python object or built-in type corresponding to the field in
`attr_value` that is in use.
"""
# TODO(frreiss): Handle AttrValues that are lists
if attr_value.HasField("s"): # str
# TODO(frreiss): Should we return the binary value here?
return tf.compat.as_str(attr_value.s)
elif attr_value.HasField("i"): # int
return attr_value.i
elif attr_value.HasField("f"): # float
return attr_value.f
elif attr_value.HasField("b"): # bool
return attr_value.b
elif attr_value.HasField("type"): # DType
return tf.DType(attr_value.type)
elif attr_value.HasField("shape"): # TensorShape
# Undocumented behavior of public API: tf.TensorShape constructor accepts
# a TensorShapeProto.
return tf.TensorShape(attr_value.shape)
elif attr_value.HasField("tensor"): # TensorProto
return tf.make_ndarray(attr_value.tensor)
elif attr_value.HasField("list"): # list
return attr_value.list
elif attr_value.HasField("func"): # func
return attr_value.func
# TODO(frreiss): Convert the "placeholder" fields of the union here
else:
raise ValueError("Don't know how to convert AttrValue {} to "
"a Python object for attribute {}".format(
attr_value, attr_name))
