tf.estimator.experimental.build_raw_supervised_input_receiver_fn
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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.
Args |
|---|
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 |
|---|
|
A supervised_input_receiver_fn.
|
Raises |
|---|
ValueError
|
if features and labels have overlapping keys.
|
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Last updated 2021-05-14 UTC.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2021-05-14 UTC."],[],[]]
View source on GitHub