| /external/tensorflow/tensorflow/contrib/learn/python/learn/estimators/ |
| D | head_test.py | 381 n_classes = 3
383 n_classes=n_classes, metric_class_ids=range(n_classes))
396 n_classes = 2
400 n_classes=n_classes, metric_class_ids=range(n_classes))
426 head = head_lib.multi_label_head(n_classes=len(self._labels[0]) + 1)
434 n_classes = 3
436 n_classes=n_classes, metric_class_ids=range(n_classes))
471 n_classes = 3
473 n_classes=n_classes, metric_class_ids=range(n_classes))
482 n_classes = 3
[all …]
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| D | dnn_test.py | 170 n_classes=3,
222 n_classes=3,
276 n_classes=2,
352 self, expected_len, n_classes, predictions): argument
355 self.assertIn(prediction, range(n_classes))
390 n_classes=2,
435 n_classes=2,
482 n_classes=2,
508 n_classes=3,
533 n_classes=3,
[all …]
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| D | debug_test.py | 95 classifier = debug.DebugClassifier(n_classes=N_CLASSES)
114 classifier = debug.DebugClassifier(n_classes=2)
131 classifier = debug.DebugClassifier(n_classes=2)
153 classifier = debug.DebugClassifier(n_classes=N_CLASSES)
176 classifier = debug.DebugClassifier(n_classes=2)
197 classifier = debug.DebugClassifier(n_classes=2)
208 estimator=debug.DebugClassifier(n_classes=3),
288 classifier = debug.DebugClassifier(n_classes=2)
318 classifier = debug.DebugClassifier(n_classes=2)
331 classifier = debug.DebugClassifier(n_classes=3)
[all …]
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| D | nonlinear_test.py | 44 n_classes=3,
100 n_classes=3,
112 n_classes=3,
124 n_classes=3,
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| D | head.py | 270 def multi_class_head(n_classes, argument
319 if (n_classes is None) or (n_classes < 2):
321 n_classes)
326 if n_classes == 2:
340 n_classes=n_classes,
388 def multi_label_head(n_classes, argument
432 if n_classes < 2:
438 n_classes=n_classes,
994 n_classes, argument
1036 logits_dimension=n_classes,
[all …]
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| D | debug.py | 165 n_classes=2, argument
197 n_classes=n_classes,
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| D | composable_model_test.py | 134 head = head_lib.multi_class_head(n_classes=2)
160 head = head_lib.multi_class_head(n_classes=2)
174 head = head_lib.multi_class_head(n_classes=3)
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| /external/tensorflow/tensorflow/contrib/learn/python/learn/learn_io/ |
| D | data_feeder.py | 48 def _get_in_out_shape(x_shape, y_shape, n_classes, batch_size=None): argument
52 if y_is_dict and n_classes is not None:
53 assert isinstance(n_classes, dict)
82 output_shape = out_el_shape(y_shape, n_classes)
85 out_el_shape(v, n_classes[k]
86 if n_classes is not None and
87 k in n_classes else None))
113 n_classes, argument
157 return StreamingDataFeeder(x, y, n_classes, batch_size)
159 x, y, n_classes, batch_size, shuffle=shuffle, epochs=epochs)
[all …]
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| D | data_feeder_test.py | 52 data_feeder.DataFeeder(input_data, None, n_classes=0, batch_size=1)
55 feeder = data_feeder.DataFeeder(input_data, None, n_classes=0, batch_size=1)
157 func(data_feeder.DataFeeder(data, None, n_classes=0, batch_size=1))
160 self._wrap_dict(data), None, n_classes=0, batch_size=1))
173 func(data_feeder.DataFeeder(x, y, n_classes=0, batch_size=3))
178 n_classes=self._wrap_dict(0, 'out'),
203 func(data_feeder.DataFeeder(data, labels, n_classes=0, batch_size=1))
208 n_classes=self._wrap_dict(0, 'out'),
222 func(data_feeder.DataFeeder(x, y, n_classes=0, batch_size=2))
227 n_classes=self._wrap_dict(0, 'out'),
[all …]
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| D | io_test.py | 46 n_classes=3)
62 n_classes=3)
117 n_classes=3)
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| /external/tensorflow/tensorflow/contrib/boosted_trees/estimator_batch/ |
| D | distillation_loss.py | 41 def _logits_to_label_for_tree(logits, n_classes): argument
42 if n_classes == 2:
48 def create_dnn_to_tree_squared_loss_fn(n_classes): argument
53 labels=_logits_to_label_for_tree(dnn_logits, n_classes),
54 logits=_logits_to_label_for_tree(tree_logits, n_classes),
60 def create_dnn_to_tree_cross_entropy_loss_fn(n_classes): argument
64 if n_classes == 2:
66 labels=_logits_to_label_for_tree(dnn_logits, n_classes),
71 labels=_logits_to_label_for_tree(dnn_logits, n_classes),
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| D | estimator.py | 46 n_classes=2, argument
104 if n_classes > 2:
112 num_classes=n_classes)
117 n_classes=n_classes,
123 learner_config.num_classes = n_classes
124 elif learner_config.num_classes != n_classes:
126 (learner_config.num_classes, n_classes))
526 n_classes, argument
534 labels=labels, logits=logits, weights=None, num_classes=n_classes)
539 n_classes=n_classes,
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| D | estimator_test.py | 330 n_classes=learner_config.num_classes,
356 n_classes=learner_config.num_classes,
383 n_classes=learner_config.num_classes,
530 n_classes = 3
532 learner_config.num_classes = n_classes
537 head_fn = estimator.core_multiclass_head(n_classes=n_classes)
557 n_classes = 3
559 learner_config.num_classes = n_classes
564 head_fn = estimator.core_multiclass_head(n_classes=n_classes)
584 n_classes = 3
[all …]
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| /external/tensorflow/tensorflow/contrib/learn/python/learn/datasets/ |
| D | synthetic.py | 37 n_classes=2, argument
72 linspace = np.linspace(0, 2 * np.pi, n_samples // n_classes)
79 for label in range(n_classes):
84 y = np.append(y, label * np.ones(n_samples // n_classes, dtype=np.int32))
87 extras = n_samples % n_classes
135 n_classes = 2 # I am not sure how to make it multiclass
148 linspace = np.linspace(0, 2 * n_loops * np.pi, n_samples // n_classes)
153 for label in range(n_classes):
157 y = np.append(y, label * np.ones(n_samples // n_classes, dtype=np.int32))
160 extras = n_samples % n_classes
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| D | synthetic_test.py | 56 n_classes = 2
58 n_samples=n_samples, noise=None, n_classes=n_classes)
62 self.assertSetEqual(set(circ.target), set(range(n_classes)))
74 n_samples=100, noise=noise, n_classes=2, seed=seed)
76 n_samples=100, noise=noise, n_classes=2, seed=seed)
81 n_samples=100, noise=noise, n_classes=2, seed=seed + 1)
88 n_samples=100, noise=noise / 2., n_classes=2, seed=seed)
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| /external/tensorflow/tensorflow/contrib/layers/python/layers/ |
| D | target_column_test.py | 60 target_column = target_column_lib.multi_class_target(n_classes=2)
73 n_classes=2, weight_column_name="label_weight")
86 target_column = target_column_lib.multi_class_target(n_classes=2)
99 target_column = target_column_lib.multi_class_target(n_classes=3)
110 n_classes=3, weight_column_name="label_weight")
122 target_column_lib.multi_class_target(n_classes=1)
129 target_column = target_column_lib.multi_class_target(n_classes=3)
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| D | target_column.py | 68 def multi_class_target(n_classes, label_name=None, weight_column_name=None): argument
87 if n_classes < 2:
89 if n_classes == 2:
95 n_classes=n_classes,
294 def __init__(self, loss_fn, n_classes, label_name, weight_column_name): argument
295 if n_classes < 2:
299 num_label_columns=1 if n_classes == 2 else n_classes,
385 n_classes=2,
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| /external/tensorflow/tensorflow/contrib/kernel_methods/python/ |
| D | kernel_estimators.py | 260 n_classes=2, argument
305 n_classes=n_classes, weight_column_name=weight_column_name),
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| D | kernel_estimators_test.py | 77 feature_columns=[feature], n_classes=1)
241 feature_columns=[feature_column], n_classes=3)
257 feature_columns=[], n_classes=3, kernel_mappers=kernel_mappers)
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| /external/tensorflow/tensorflow/contrib/learn/python/learn/ops/ |
| D | embeddings_ops.py | 73 def categorical_variable(tensor_in, n_classes, embedding_size, name): argument
91 [n_classes, embedding_size])
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| /external/tensorflow/tensorflow/lite/experimental/examples/lstm/ |
| D | unidirectional_sequence_rnn_test.py | 50 self.n_classes = 10
71 tf.random_normal([self.num_units, self.n_classes]))
72 out_bias = tf.Variable(tf.random_normal([self.n_classes]))
98 y = tf.placeholder("float", [None, self.n_classes])
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| D | unidirectional_sequence_lstm_test.py | 50 self.n_classes = 10
75 tf.random_normal([self.num_units, self.n_classes]))
76 out_bias = tf.Variable(tf.random_normal([self.n_classes]))
102 y = tf.placeholder("float", [None, self.n_classes])
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| D | bidirectional_sequence_lstm_test.py | 51 self.n_classes = 10
76 tf.random_normal([self.num_units * 2, self.n_classes]))
77 out_bias = tf.Variable(tf.random_normal([self.n_classes]))
111 y = tf.placeholder("float", [None, self.n_classes])
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| D | bidirectional_sequence_rnn_test.py | 52 self.n_classes = 10
78 tf.random_normal([self.num_units * 2, self.n_classes]))
79 out_bias = tf.Variable(tf.random_normal([self.n_classes]))
130 y = tf.placeholder("float", [None, self.n_classes])
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| /external/tensorflow/tensorflow/contrib/eager/python/examples/revnet/ |
| D | revnet_test.py | 62 maxval=config.n_classes,
77 self.assertEqual(y.shape, [self.config.batch_size, self.config.n_classes])
126 self.assertEqual(y.shape, [self.config.batch_size, self.config.n_classes])
155 maxval=self.config.n_classes,
182 [batch_size], minval=0, maxval=config.n_classes, dtype=tf.int32)
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