ServingInputReceiver
Defined in tensorflow/python/estimator/export/export.py.
A return type for a serving_input_receiver_fn.
The expected return values are: features: A Tensor, SparseTensor, or dict of string to Tensor or SparseTensor, specifying the features to be passed to the model. receiver_tensors: a Tensor, or a dict of string to Tensor, specifying input nodes where this receiver expects to be fed by default. Typically, this is a single placeholder expecting serialized tf.Example protos. receiver_tensors_alternatives: a dict of string to additional groups of receiver tensors, each of which may be a Tensor or a dict of string to Tensor. These named receiver tensor alternatives generate additional serving signatures, which may be used to feed inputs at different points within the input receiver subgraph. A typical usage is to allow feeding raw feature Tensors downstream of the tf.parse_example() op. Defaults to None.
featuresAlias for field number 0
receiver_tensorsAlias for field number 1
receiver_tensors_alternativesAlias for field number 2
__new__@staticmethod
__new__(
cls,
features,
receiver_tensors,
receiver_tensors_alternatives=None
)
Create new instance of ServingInputReceiver(features, receiver_tensors, receiver_tensors_alternatives)
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Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/api_docs/python/tf/estimator/export/ServingInputReceiver