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from tensorboard.compat.proto.node_def_pb2 import NodeDef
from tensorboard.compat.proto.attr_value_pb2 import AttrValue
from tensorboard.compat.proto.tensor_shape_pb2 import TensorShapeProto
def attr_value_proto(dtype, shape, s):
"""Creates a dict of objects matching
https://github.com/tensorflow/tensorboard/blob/master/tensorboard/compat/proto/attr_value.proto
specifically designed for a NodeDef. The values have been
reverse engineered from standard TensorBoard logged data.
"""
attr = {}
if s is not None:
attr['attr'] = AttrValue(s=s.encode(encoding='utf_8'))
if shape is not None:
shapeproto = tensor_shape_proto(shape)
attr['_output_shapes'] = AttrValue(list=AttrValue.ListValue(shape=[shapeproto]))
return attr
def tensor_shape_proto(outputsize):
"""Creates an object matching
https://github.com/tensorflow/tensorboard/blob/master/tensorboard/compat/proto/tensor_shape.proto
"""
return TensorShapeProto(dim=[TensorShapeProto.Dim(size=d) for d in outputsize])
def node_proto(name,
op='UnSpecified',
input=None,
dtype=None,
shape=None, # type: tuple
outputsize=None,
attributes=''
):
"""Creates an object matching
https://github.com/tensorflow/tensorboard/blob/master/tensorboard/compat/proto/node_def.proto
"""
if input is None:
input = []
if not isinstance(input, list):
input = [input]
return NodeDef(
name=name.encode(encoding='utf_8'),
op=op,
input=input,
attr=attr_value_proto(dtype, outputsize, attributes)
)
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