Allow one tensor to be the input to the estimator.
PiperOrigin-RevId: 163747076
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@ -68,6 +68,9 @@ def model_builder(features, labels, mode, params, config):
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center_bias = params["center_bias"]
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if isinstance(features, ops.Tensor):
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features = {features.name: features}
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# Make a shallow copy of features to ensure downstream usage
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# is unaffected by modifications in the model function.
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training_features = copy.copy(features)
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@ -142,7 +142,7 @@ def extract_features(features, feature_columns):
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"""Extracts columns from a dictionary of features.
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Args:
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features: `Tensor` or `dict` of `Tensor` objects.
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features: `dict` of `Tensor` objects.
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feature_columns: A list of feature_columns.
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Returns:
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@ -161,9 +161,6 @@ def extract_features(features, feature_columns):
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if not features:
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raise ValueError("Features dictionary must be specified.")
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if isinstance(features, ops.Tensor):
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features = {features.name, features}
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# Make a shallow copy of features to ensure downstream usage
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# is unaffected by modifications in the model function.
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features = copy.copy(features)
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@ -277,7 +274,7 @@ class GradientBoostedDecisionTreeModel(object):
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examples based on the depth of the layer that's being built.
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learner_config: A learner config.
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print split, sorted_feature_names[split.feature_column]
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features: `Tensor` or `dict` of `Tensor` objects.
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features: `dict` of `Tensor` objects.
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feature_columns: A list of feature columns.
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Raises:
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