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Build a supervised_input_receiver_fn for raw features and labels.
tf.estimator.experimental.build_raw_supervised_input_receiver_fn(
features, labels, default_batch_size=None
)
This function wraps tensor placeholders in a supervised_receiver_fn with the expectation that the features and labels appear precisely as the model_fn expects them. Features and labels can therefore be dicts of tensors, or raw tensors.
features
: a dict of string to Tensor
or Tensor
.labels
: a dict of string to Tensor
or Tensor
.default_batch_size
: the number of query examples expected per batch.
Leave unset for variable batch size (recommended).A supervised_input_receiver_fn.
ValueError
: if features and labels have overlapping keys.