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