| /external/tensorflow/tensorflow/contrib/layers/python/layers/ |
| D | 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 …]
|
| D | __init__.py | 33 from tensorflow.contrib.layers.python.layers.target_column import *
|
| /external/tensorflow/tensorflow/contrib/learn/python/learn/estimators/ |
| D | dynamic_rnn_estimator.py | 262 target_column, argument
295 probabilities = target_column.logits_to_predictions(
301 predictions = target_column.logits_to_predictions(
308 activations, labels, sequence_length, target_column, features): argument
327 return target_column.loss(activations_masked, labels_masked, features)
331 activations, labels, sequence_length, target_column, features): argument
351 return target_column.loss(last_activations, labels, features)
387 target_column, argument
496 target_column.num_label_columns,
504 rnn_activations, target_column, problem_type, predict_probabilities)
[all …]
|
| D | state_saving_rnn_estimator.py | 93 activations, labels, sequence_length, target_column, features): argument
112 return target_column.loss(activations_masked, labels_masked, features)
387 target_column, argument
497 num_label_columns=target_column.num_label_columns,
503 rnn_activations, target_column, problem_type, predict_probabilities)
506 target_column, features)
625 target_column = layers.regression_target()
630 target_column = layers.multi_class_target(n_classes=num_classes)
643 target_column=target_column,
|
| D | rnn_common.py | 248 def multi_value_predictions(activations, target_column, problem_type, argument
285 flat_probabilities = target_column.logits_to_predictions(
288 if target_column.num_label_columns == 1:
299 flat_predictions = target_column.logits_to_predictions(
|
| D | 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),
|
| D | 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/ |
| D | pandas_io.py | 64 target_column='target'): argument
73 target_column=target_column)
|
| /external/tensorflow/tensorflow/contrib/learn/python/learn/datasets/ |
| D | base.py | 49 target_column=-1): argument
59 target[i] = np.asarray(row.pop(target_column), dtype=target_dtype)
69 target_column=-1): argument
75 target.append(row.pop(target_column))
|
| D | text_datasets.py | 73 train_path, target_dtype=np.int32, features_dtype=np.str, target_column=0)
75 test_path, target_dtype=np.int32, features_dtype=np.str, target_column=0)
|
| /external/tensorflow/tensorflow/tools/api/golden/v1/ |
| D | tensorflow.estimator.inputs.pbtxt | 9 …, \'num_epochs\', \'shuffle\', \'queue_capacity\', \'num_threads\', \'target_column\'], varargs=No…
|
| /external/tensorflow/tensorflow/contrib/layers/ |
| D | BUILD | 67 "python/layers/target_column.py",
|