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Searched
refs:target_column
(Results
1 - 11
of
11
) sorted by null
/external/tensorflow/tensorflow/contrib/layers/python/layers/
target_column_test.py
21
from tensorflow.contrib.layers.python.layers import
target_column
as target_column_lib
33
target_column
= target_column_lib.regression_target()
38
5. / 3, sess.run(
target_column
.loss(prediction, labels, {})))
41
target_column
= target_column_lib.regression_target(
49
sess.run(
target_column
.loss(prediction, labels, features)),
53
sess.run(
target_column
.training_loss(prediction, labels, features)),
60
target_column
= target_column_lib.multi_class_target(n_classes=2)
68
sess.run(
target_column
.loss(logits, labels, {})),
72
target_column
= target_column_lib.multi_class_target(
82
sess.run(
target_column
.loss(logits, labels, features))
[
all
...]
__init__.py
33
from tensorflow.contrib.layers.python.layers.
target_column
import *
/external/tensorflow/tensorflow/python/estimator/inputs/
pandas_io.py
46
target_column
='target'):
63
target_column
: str, name to give the target column `y`.
83
if
target_column
in x:
86
'column with that name: %s' % (
target_column
, x.columns))
90
x[
target_column
] = y
120
target = features.pop(
target_column
)
/external/tensorflow/tensorflow/contrib/learn/python/learn/estimators/
dynamic_rnn_estimator.py
257
target_column
,
274
target_column
: An initialized `TargetColumn`, calculate predictions.
290
probabilities =
target_column
.logits_to_predictions(
296
predictions =
target_column
.logits_to_predictions(
303
activations, labels, sequence_length,
target_column
, features):
313
target_column
: An initialized `TargetColumn`, calculate predictions.
322
return
target_column
.loss(activations_masked, labels_masked, features)
326
activations, labels, sequence_length,
target_column
, features):
336
target_column
: An initialized `TargetColumn`, calculate predictions.
346
return
target_column
.loss(last_activations, labels, features
[
all
...]
state_saving_rnn_estimator.py
88
activations, labels, sequence_length,
target_column
, features):
98
target_column
: An initialized `TargetColumn`, calculate predictions.
107
return
target_column
.loss(activations_masked, labels_masked, features)
382
target_column
,
402
target_column
: An initialized `TargetColumn`, used to calculate prediction
492
num_label_columns=
target_column
.num_label_columns,
498
rnn_activations,
target_column
, problem_type, predict_probabilities)
501
target_column
, features)
614
target_column
= layers.regression_target()
619
target_column
= layers.multi_class_target(n_classes=num_classes
[
all
...]
rnn_common.py
243
def multi_value_predictions(activations,
target_column
, problem_type,
265
target_column
: An initialized `TargetColumn`, calculate predictions.
280
flat_probabilities =
target_column
.logits_to_predictions(
283
if
target_column
.num_label_columns == 1:
294
flat_predictions =
target_column
.logits_to_predictions(
state_saving_rnn_estimator_test.py
27
from tensorflow.contrib.layers.python.layers import
target_column
as target_column_lib
338
target_column
=target_column_lib.multi_class_target(n_classes=2),
dynamic_rnn_estimator_test.py
27
from tensorflow.contrib.layers.python.layers import
target_column
as target_column_lib
253
target_column
=target_column_lib.multi_class_target(n_classes=2),
/external/tensorflow/tensorflow/contrib/learn/python/learn/learn_io/
pandas_io.py
57
target_column
='target'):
66
target_column
=
target_column
)
/external/tensorflow/tensorflow/contrib/learn/python/learn/datasets/
text_datasets.py
65
train_path, target_dtype=np.int32, features_dtype=np.str,
target_column
=0)
67
test_path, target_dtype=np.int32, features_dtype=np.str,
target_column
=0)
base.py
40
target_column
=-1):
50
target[i] = np.asarray(row.pop(
target_column
), dtype=target_dtype)
59
target_column
=-1):
65
target.append(row.pop(
target_column
))
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