1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
|
from typing import Optional
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: Optional[tuple] = None,
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),
)
|
