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.
Args | |
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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). |
Returns | |
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A supervised_input_receiver_fn. |
Raises | |
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ValueError | if features and labels have overlapping keys. |
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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/versions/r2.4/api_docs/python/tf/estimator/experimental/build_raw_supervised_input_receiver_fn