InputFnOps
Defined in tensorflow/contrib/learn/python/learn/utils/input_fn_utils.py
.
A return type for an input_fn (deprecated).
THIS CLASS IS DEPRECATED. Please use tf.estimator.export.ServingInputReceiver instead.
This return type is currently only supported for serving input_fn. Training and eval input_fn should return a (features, labels)
tuple.
The expected return values are: features: A dict of string to Tensor
or SparseTensor
, specifying the features to be passed to the model. labels: A Tensor
, SparseTensor
, or a dict of string to Tensor
or SparseTensor
, specifying labels for training or eval. For serving, set labels
to None
. default_inputs: a dict of string to Tensor
or SparseTensor
, specifying the input placeholders (if any) that this input_fn expects to be fed. Typically, this is used by a serving input_fn, which expects to be fed serialized tf.Example
protos.
default_inputs
Alias for field number 2
features
Alias for field number 0
labels
Alias for field number 1
__new__
__new__( _cls, features, labels, default_inputs )
Create new instance of InputFnOps(features, labels, default_inputs)
© 2018 The TensorFlow Authors. All rights reserved.
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/contrib/learn/InputFnOps