experiments/STT-tensorflow
1
0
Fork 0
Code Issues Pull Requests Projects Releases Wiki Activity

Allow one tensor to be the input to the estimator.

Browse Source 
PiperOrigin-RevId: 163747076
This commit is contained in:
A. Unique TensorFlower 2017-07-31 14:19:15 -07:00 committed by TensorFlower Gardener
parent 104f349e9e
commit 1333e77450
2 changed files with 5 additions and 5 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

3
tensorflow/contrib/boosted_trees/estimator_batch/model.py
View File

@ -68,6 +68,9 @@ def model_builder(features, labels, mode, params, config):
center_bias = params["center_bias"] center_bias = params["center_bias"]
if isinstance(features, ops.Tensor):
features = {features.name: features}
# Make a shallow copy of features to ensure downstream usage # Make a shallow copy of features to ensure downstream usage
# is unaffected by modifications in the model function. # is unaffected by modifications in the model function.
training_features = copy.copy(features) training_features = copy.copy(features)

7
tensorflow/contrib/boosted_trees/python/training/functions/gbdt_batch.py
View File

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