def scalar(name, tensor, summary_description=None, collections=None):
"""Outputs a `Summary` protocol buffer containing a single scalar value.
The generated Summary has a Tensor.proto containing the input Tensor.
Args:
name: A name for the generated node. Will also serve as the series name in
TensorBoard.
tensor: A tensor containing a single floating point or integer value.
summary_description: Optional summary_description_pb2.SummaryDescription
collections: Optional list of graph collections keys. The new summary op is
added to these collections. Defaults to `[GraphKeys.SUMMARIES]`.
Returns:
A scalar `Tensor` of type `string`. Which contains a `Summary` protobuf.
Raises:
ValueError: If tensor has the wrong shape or type.
"""
dtype = as_dtype(tensor.dtype)
if dtype.is_quantized or not (dtype.is_integer or dtype.is_floating):
raise ValueError("Can't create scalar summary for type %s." % dtype)
shape = tensor.get_shape()
if not shape.is_compatible_with(tensor_shape.scalar()):
raise ValueError("Can't create scalar summary for shape %s." % shape)
if summary_description is None:
summary_description = summary_pb2.SummaryDescription()
summary_description.type_hint = "scalar"
return tensor_summary(name, tensor, summary_description, collections)
def testTensorSummaryOpCreated(self):
c = tf.constant(0)
s = tf.summary.scalar('x', c)
self.assertEqual(s.op.type, 'TensorSummary')
self.assertEqual(s.op.inputs[0], c)
description = s.op.get_attr('description')
summary_description = summary_pb2.SummaryDescription()
json_format.Parse(description, summary_description)
self.assertEqual(summary_description.type_hint, 'scalar')
def get_summary_description(node_def):
"""Given a TensorSummary node_def, retrieve its SummaryDescription.
When a Summary op is instantiated, a SummaryDescription of associated
metadata is stored in its NodeDef. This method retrieves the description.
Args:
node_def: the node_def_pb2.NodeDef of a TensorSummary op
Returns:
a summary_pb2.SummaryDescription
Raises:
ValueError: if the node is not a summary op.
"""
if node_def.op != 'TensorSummary':
raise ValueError("Can't get_summary_description on %s" % node_def.op)
description_str = _compat.as_str_any(node_def.attr['description'].s)
summary_description = _summary_pb2.SummaryDescription()
_json_format.Parse(description_str, summary_description)
return summary_description
def tensor_summary( # pylint: disable=invalid-name
name,
tensor,
summary_description=None,
collections=None):
# pylint: disable=line-too-long
"""Outputs a `Summary` protocol buffer with a serialized tensor.proto.
The generated
[`Summary`](https://www.tensorflow.org/code/tensorflow/core/framework/summary.proto)
has one summary value containing the input tensor.
Args:
name: A name for the generated node. Will also serve as the series name in
TensorBoard.
tensor: A tensor of any type and shape to serialize.
summary_description: Optional summary_pb2.SummaryDescription()
collections: Optional list of graph collections keys. The new summary op is
added to these collections. Defaults to `[GraphKeys.SUMMARIES]`.
Returns:
A scalar `Tensor` of type `string`. The serialized `Summary` protocol
buffer.
"""
# pylint: enable=line-too-long
if summary_description is None:
summary_description = summary_pb2.SummaryDescription()
description = json_format.MessageToJson(summary_description)
with ops.name_scope(name, None, [tensor]) as scope:
val = gen_logging_ops._tensor_summary(
tensor=tensor,
description=description,
name=scope)
_Collect(val, collections, [ops.GraphKeys.SUMMARIES])
return val
