tfr.data.build_tf_example_serving_input_receiver_fn

Builds a serving input fn for tensorflow.training.Example.

tfr.data.build_tf_example_serving_input_receiver_fn(
    context_feature_spec,
    example_feature_spec,
    size_feature_name=None,
    mask_feature_name=None,
    default_batch_size=None
)

Args
`context_feature_spec`	(dict) Map from feature keys to `FixedLenFeature`, `VarLenFeature` or `RaggedFeature` values.
`example_feature_spec`	(dict) Map from feature keys to `FixedLenFeature`, `VarLenFeature` or `RaggedFeature` values.
`size_feature_name`	(str) Name of feature for example list sizes. Populates the feature dictionary with a `tf.int32` Tensor of value 1, and of shape [batch_size] for this feature name. If None, which is default, this feature is not generated.
`mask_feature_name`	(str) Name of feature for example list masks. Populates the feature dictionary with a `tf.bool` Tensor of shape [batch_size, list_size] for this feature name. If None, which is default, this feature is not generated.
`default_batch_size`	(int) Number of instances expected per batch. Leave unset for variable batch size (recommended).

Returns
A `tf.estimator.export.ServingInputReceiver` object, which packages the placeholders and the resulting feature Tensors together.

tfr.data.build_tf_example_serving_input_receiver_fn

Args

Returns