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Added forward_features inside Estimator class of Adanet. #119

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Added forward_features inside Estimator class of Adanet. #119

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14 changes: 14 additions & 0 deletions adanet/core/estimator.py
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Original file line number Diff line number Diff line change
Expand Up @@ -450,6 +450,8 @@ def __init__(self,
enable_subnetwork_summaries=True,
global_step_combiner_fn=tf.math.reduce_mean,
max_iterations=None,
forward_feature_keys=None,
sparse_default_values=None,
**kwargs):
if subnetwork_generator is None:
raise ValueError("subnetwork_generator can't be None.")
Expand Down Expand Up @@ -596,6 +598,18 @@ def _latest_checkpoint_global_step(self):
return tf.train.load_variable(latest_checkpoint,
tf_compat.v1.GraphKeys.GLOBAL_STEP)

def forward_features(self,
estimator,
forward_feature_keys=None,
sparse_default_values=None):
if forward_feeature_keys is not None:
result = tf.contrib.estimator.forward_features(super(Estimator, self),
forward_feature_keys=forward_feature_keys,
sparse_default_values=sparse_default_values)
return result
else:
raise ValueError("No key/(s) provided to forward features.")

def train(self,
input_fn,
hooks=None,
Expand Down