| /external/autotest/utils/ |
| D | labellib_unittest.py | 44 labels = ['webcam', 'pool:suites']
45 mapping = labellib.LabelsMapping(labels)
46 self.assertEqual(mapping.getlabels(), labels)
49 labels = ['webcam', 'pool:suites', 'pool:party']
50 mapping = labellib.LabelsMapping(labels)
54 labels = ['ohse:tsubame', 'webcam']
55 mapping = labellib.LabelsMapping(labels)
59 labels = ['webcam', 'exec', 'method']
60 mapping = labellib.LabelsMapping(labels)
64 labels = ['class:protecta', 'method:metafalica', 'exec:chronicle_key']
[all …]
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| /external/tensorflow/tensorflow/python/ops/ |
| D | metrics_impl.py | 84 def _remove_squeezable_dimensions(predictions, labels, weights): argument
108 if labels is not None:
109 labels, predictions = confusion_matrix.remove_squeezable_dimensions(
110 labels, predictions)
111 predictions.get_shape().assert_is_compatible_with(labels.get_shape())
114 return predictions, labels, None
120 return predictions, labels, weights
157 return predictions, labels, weights
160 def _maybe_expand_labels(labels, predictions): argument
176 with ops.name_scope(None, 'expand_labels', (labels, predictions)) as scope:
[all …]
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| D | confusion_matrix.py | 29 labels, predictions, expected_rank_diff=0, name=None): argument
55 [labels, predictions]):
57 labels = ops.convert_to_tensor(labels)
60 labels_shape = labels.get_shape()
70 labels = array_ops.squeeze(labels, [-1])
71 return labels, predictions
74 rank_diff = array_ops.rank(predictions) - array_ops.rank(labels)
83 labels = control_flow_ops.cond(
85 lambda: array_ops.squeeze(labels, [-1]),
86 lambda: labels)
[all …]
|
| D | ctc_ops.py | 71 def ctc_loss(labels, argument
183 labels,
194 def _ctc_loss_impl(labels, argument
209 if not isinstance(labels, sparse_tensor.SparseTensor):
235 labels.indices,
236 labels.values,
596 def _ilabel_to_state(labels, num_labels, ilabel_log_probs): argument
599 num_label_states = _get_dim(labels, 1)
602 one_hot = array_ops.one_hot(labels, depth=num_labels)
612 def _state_to_olabel(labels, num_labels, states): argument
[all …]
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| /external/tensorflow/tensorflow/python/ops/losses/ |
| D | losses_impl.py | 218 labels, predictions, weights=1.0, scope=None, argument
255 if labels is None:
260 (predictions, labels, weights)) as scope:
262 labels = math_ops.cast(labels, dtype=dtypes.float32)
263 predictions.get_shape().assert_is_compatible_with(labels.get_shape())
264 losses = math_ops.abs(math_ops.subtract(predictions, labels))
273 labels, predictions, axis=None, weights=1.0, scope=None, argument
310 if labels is None:
315 (predictions, labels, weights)) as scope:
317 labels = math_ops.cast(labels, dtype=dtypes.float32)
[all …]
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| /external/tensorflow/tensorflow/python/kernel_tests/sparse_ops/ |
| D | sparse_xent_op_test_base.py | 36 def _opFwdBwd(self, labels, logits): argument
42 labels=labels, logits=logits)
45 def _npXent(self, labels, logits): argument
47 labels = np.reshape(labels, [-1])
55 labels_mat[np.arange(batch_size), labels] = 1.0
61 np_loss, np_gradient = self._npXent(labels=np_labels, logits=np_logits)
62 tf_loss, tf_gradient = self._opFwdBwd(labels=np_labels, logits=np_logits)
69 labels=np.array([0, 0, 0]).astype(label_dtype),
76 labels = [4, 3, 0, -1]
79 loss, gradient = self._opFwdBwd(labels=labels, logits=logits)
[all …]
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| /external/grpc-grpc/tools/run_tests/sanity/ |
| D | check_test_filtering.py | 40 def test_filtering(self, changed_files=[], labels=_LIST_OF_LANGUAGE_LABELS): argument
61 if "sanity" in job.labels:
63 all_jobs = [job for job in all_jobs if "sanity" not in job.labels]
65 if "sanity" in job.labels:
68 job for job in filtered_jobs if "sanity" not in job.labels
73 for label in labels:
75 self.assertNotIn(label, job.labels)
78 for label in labels:
80 if (label in job.labels):
94 if label not in filter_pull_request_tests._CORE_TEST_SUITE.labels +
[all …]
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| /external/rust/crates/grpcio-sys/grpc/tools/run_tests/sanity/ |
| D | check_test_filtering.py | 40 def test_filtering(self, changed_files=[], labels=_LIST_OF_LANGUAGE_LABELS): argument
61 if "sanity" in job.labels:
63 all_jobs = [job for job in all_jobs if "sanity" not in job.labels]
65 if "sanity" in job.labels:
68 job for job in filtered_jobs if "sanity" not in job.labels
73 for label in labels:
75 self.assertNotIn(label, job.labels)
78 for label in labels:
80 if (label in job.labels):
93 if label not in filter_pull_request_tests._CORE_TEST_SUITE.labels +
[all …]
|
| /external/tensorflow/tensorflow/python/kernel_tests/nn_ops/ |
| D | xent_op_test_base.py | 37 def _opFwdBwd(self, labels, logits, axis=-1): argument
43 labels=labels, logits=logits, dim=axis)
46 def _npXent(self, labels, logits, dim=-1): argument
53 bp = (probs - labels)
54 l = -np.sum(labels * np.log(probs + 1.0e-20), axis=dim)
64 np_loss, np_gradient = self._npXent(labels=np_labels, logits=np_logits)
86 labels=np_labels, logits=np_logits, dim=dim)
93 labels=np.array([[-1.], [0.], [1.], [1.]]).astype(dtype),
107 labels = [[0., 0., 0., 1.], [0., .5, .5, 0.]]
128 np_loss, np_gradient = self._npXent(np.array(labels), np.array(logits))
[all …]
|
| D | ctc_loss_op_test.py | 63 def _ctc_loss_v2(labels, inputs, sequence_length, argument
73 labels=labels,
86 labels, argument
96 inputs=inputs_t, labels=labels, sequence_length=seq_lens)
227 labels = SimpleSparseTensorFrom([targets_0, targets_1])
244 self._testCTCLoss(inputs, seq_lens, labels, loss_truth, grad_truth)
255 labels = SimpleSparseTensorFrom([[0, 1], [1, 0]])
265 inputs=inputs_t, labels=labels, sequence_length=seq_lens)
268 labels=labels,
279 labels = SimpleSparseTensorFrom([[0, 1], [1, 0]])
[all …]
|
| D | losses_test.py | 109 labels = constant_op.constant([1, 9, 2, -5, -2, 6], shape=(2, 3))
110 losses.absolute_difference(labels, predictions)
118 labels = constant_op.constant([[1, 0, 0], [0, 1, 0], [0, 0, 1]])
121 losses.softmax_cross_entropy(labels, logits, weights=None)
128 labels = constant_op.constant([[1, 0, 0], [0, 1, 0], [0, 0, 1]])
129 loss = losses.softmax_cross_entropy(labels, logits)
137 labels = constant_op.constant([[0, 0, 1], [1, 0, 0], [0, 1, 0]])
140 loss = losses.softmax_cross_entropy(labels, logits)
148 labels = constant_op.constant([[0, 0, 1], [1, 0, 0], [0, 1, 0]])
151 loss = losses.softmax_cross_entropy(labels, logits, weights)
[all …]
|
| /external/tensorflow/tensorflow/python/kernel_tests/ |
| D | metrics_test.py | 50 def _binary_2d_label_to_2d_sparse_value(labels): argument
66 for row in labels:
78 shape = [len(labels), len(labels[0])]
84 def _binary_2d_label_to_1d_sparse_value(labels): argument
103 for row in labels:
115 if indices != [[i] for i in range(len(labels))]:
117 shape = [len(labels)]
123 def _binary_3d_label_to_sparse_value(labels): argument
137 for d0, labels_d0 in enumerate(labels):
147 shape = [len(labels), len(labels[0]), len(labels[0][0])]
[all …]
|
| D | xent_op_test_base.py | 41 def _opFwdBwd(self, labels, logits, axis=-1): argument
47 labels=labels, logits=logits, dim=axis)
50 def _npXent(self, labels, logits, dim=-1): argument
57 bp = (probs - labels)
58 l = -np.sum(labels * np.log(probs + 1.0e-20), axis=dim)
68 np_loss, np_gradient = self._npXent(labels=np_labels, logits=np_logits)
90 labels=np_labels, logits=np_logits, dim=dim)
97 labels=np.array([[-1.], [0.], [1.], [1.]]).astype(dtype),
111 labels = [[0., 0., 0., 1.], [0., .5, .5, 0.]]
132 np_loss, np_gradient = self._npXent(np.array(labels), np.array(logits))
[all …]
|
| /external/python/cpython3/Lib/encodings/ |
| D | idna.py | 162 labels = result.split(b'.')
163 for label in labels[:-1]:
166 if len(labels[-1]) >= 64:
171 labels = dots.split(input)
172 if labels and not labels[-1]:
174 del labels[-1]
177 for label in labels:
204 labels = input.split(b".")
206 if labels and len(labels[-1]) == 0:
208 del labels[-1]
[all …]
|
| /external/python/cpython2/Lib/encodings/ |
| D | idna.py | 157 labels = dots.split(input)
158 if labels and len(labels[-1])==0:
160 del labels[-1]
163 for label in labels:
178 labels = dots.split(input)
183 labels = input.split(".")
185 if labels and len(labels[-1]) == 0:
187 del labels[-1]
192 for label in labels:
206 labels = dots.split(input)
[all …]
|
| /external/javaparser/javaparser-core/src/main/java/com/github/javaparser/ast/stmt/ |
| D | SwitchEntry.java | 88 private NodeList<Expression> labels; field in SwitchEntry
99 …public SwitchEntry(final NodeList<Expression> labels, final Type type, final NodeList<Statement> s… in SwitchEntry() argument
100 this(null, labels, type, statements); in SwitchEntry()
107 …public SwitchEntry(TokenRange tokenRange, NodeList<Expression> labels, Type type, NodeList<Stateme… in SwitchEntry() argument
109 setLabels(labels); in SwitchEntry()
129 return labels; in getLabels()
144 public SwitchEntry setLabels(final NodeList<Expression> labels) { in setLabels() argument
145 assertNotNull(labels); in setLabels()
146 if (labels == this.labels) { in setLabels()
149 notifyPropertyChange(ObservableProperty.LABELS, this.labels, labels); in setLabels()
[all …]
|
| /external/tensorflow/tensorflow/python/distribute/ |
| D | metrics_v1_test.py | 151 labels = x["labels"]
153 return metrics.accuracy(labels, predictions)
166 labels = x["labels"]
169 labels, predictions, num_classes=5)
185 labels = x["labels"]
188 labels, predictions, num_classes=5)
222 labels = x["labels"]
224 return metrics.auc(labels, predictions, num_thresholds=8, curve="ROC",
236 labels = x["labels"]
238 return metrics.auc(labels, predictions, num_thresholds=8, curve="PR",
[all …]
|
| /external/openscreen/discovery/dnssd/impl/ |
| D | conversion_layer_unittest.cc | 72 ASSERT_EQ(query.name.labels().size(), size_t{7}); in TEST()
73 EXPECT_EQ(query.name.labels()[0], "instance.Id"); in TEST()
74 EXPECT_EQ(query.name.labels()[1], "_service-id"); in TEST()
75 EXPECT_EQ(query.name.labels()[2], "_udp"); in TEST()
76 EXPECT_EQ(query.name.labels()[3], "192"); in TEST()
77 EXPECT_EQ(query.name.labels()[4], "168"); in TEST()
78 EXPECT_EQ(query.name.labels()[5], "0"); in TEST()
79 EXPECT_EQ(query.name.labels()[6], "0"); in TEST()
87 ASSERT_EQ(query.name.labels().size(), size_t{6}); in TEST()
88 EXPECT_EQ(query.name.labels()[0], "_service-id"); in TEST()
[all …]
|
| /external/toolchain-utils/crosperf/ |
| D | machine_image_manager_unittest.py | 56 labels = []
65 labels.append(l)
66 return labels, duts
76 labels, duts = self.create_labels_and_duts_from_pattern(inp)
77 mim = MachineImageManager(labels, duts)
83 labels = [MockLabel("l1"), MockLabel("l2"), MockLabel("l3")]
85 mim = MachineImageManager(labels, [dut])
90 labels = [MockLabel("l1")]
92 mim = MachineImageManager(labels, duts)
97 labels = [
[all …]
|
| /external/autotest/server/hosts/ |
| D | host_info_unittest.py | 40 labels=['label1', 'label2', 'label1'],
44 labels=['label1', 'label2', 'label1'],
54 info1 = host_info.HostInfo(labels=['label'])
63 self.info.labels = ['cros-version', 'fwrw-version', 'fwro-version']
69 self.info.labels = ['not-at-start-cros-version:cros1']
75 self.info.labels = ['fwrw-version:fwrw1', 'fwro-version:fwro1']
81 self.info.labels = ['cros-version:cros1', 'cros-version:cros2']
87 self.info.labels = ['cheets-version:ab1', 'cros-version:cros1']
89 self.info.labels = ['cros-version:cros1', 'cheets-version:ab1']
95 self.info.labels = ['something_else', 'cros-version:hana',
[all …]
|
| D | afe_store.py | 54 return host_info.HostInfo(host.labels, host.attributes)
69 list(set(old_info.labels) - set(new_info.labels)))
71 list(set(new_info.labels) - set(old_info.labels)))
75 def _remove_labels_on_afe(self, labels): argument
80 if not labels:
83 logging.debug('removing labels: %s', labels)
86 labels=labels)
91 def _add_labels_on_afe(self, labels): argument
96 if not labels:
99 logging.info('adding labels: %s', labels)
[all …]
|
| /external/tensorflow/tensorflow/compiler/xla/service/gpu/tests/ |
| D | mnist.py | 51 def cast(images, labels): argument
54 labels = tf.cast(labels, tf.int64)
55 return (images, labels)
61 def train_mnist(images, labels): argument
62 images, labels = cast(images, labels)
67 logits=predicted_labels, labels=labels
73 for images, labels in train_ds:
76 train_mnist(images, labels)
78 images, labels = cast(test[0], test[1])
80 correct_prediction = tf.equal(tf.argmax(predicted_labels, 1), labels)
|
| /external/minijail/ |
| D | bpf.c | 299 int bpf_resolve_jumps(struct bpf_labels *labels, struct sock_filter *filter, in bpf_resolve_jumps() argument
319 if (instr->k >= labels->count) { in bpf_resolve_jumps()
323 if (labels->labels[instr->k].location == 0xffffffff) { in bpf_resolve_jumps()
325 labels->labels[instr->k].label); in bpf_resolve_jumps()
329 labels->labels[instr->k].location - (offset + 1); in bpf_resolve_jumps()
334 if (labels->labels[instr->k].location != 0xffffffff) { in bpf_resolve_jumps()
336 labels->labels[instr->k].label); in bpf_resolve_jumps()
339 labels->labels[instr->k].location = offset; in bpf_resolve_jumps()
350 int bpf_label_id(struct bpf_labels *labels, const char *label) in bpf_label_id() argument
352 struct __bpf_label *begin = labels->labels, *end; in bpf_label_id()
[all …]
|
| /external/tensorflow/tensorflow/python/eager/ |
| D | monitoring.py | 143 def get_cell(self, *labels): argument
145 if len(labels) != self._label_length:
149 self._metric, *labels)
188 def __init__(self, name, description, *labels): argument
196 super(Counter, self).__init__('Counter', _counter_methods, len(labels),
197 name, description, *labels)
199 def get_cell(self, *labels): argument
201 return CounterCell(super(Counter, self).get_cell(*labels))
240 def __init__(self, name, description, *labels): argument
248 super(IntGauge, self).__init__('IntGauge', _int_gauge_methods, len(labels),
[all …]
|
| /external/tensorflow/tensorflow/tools/api/golden/v1/ |
| D | tensorflow.metrics.pbtxt | 5 …argspec: "args=[\'labels\', \'predictions\', \'weights\', \'metrics_collections\', \'updates_colle…
9 …argspec: "args=[\'labels\', \'predictions\', \'weights\', \'num_thresholds\', \'metrics_collection…
13 …argspec: "args=[\'labels\', \'predictions\', \'k\', \'weights\', \'metrics_collections\', \'update…
17 …argspec: "args=[\'labels\', \'predictions\', \'weights\', \'metrics_collections\', \'updates_colle…
21 …argspec: "args=[\'labels\', \'predictions\', \'thresholds\', \'weights\', \'metrics_collections\',…
25 …argspec: "args=[\'labels\', \'predictions\', \'weights\', \'metrics_collections\', \'updates_colle…
29 …argspec: "args=[\'labels\', \'predictions\', \'thresholds\', \'weights\', \'metrics_collections\',…
37 …argspec: "args=[\'labels\', \'predictions\', \'weights\', \'metrics_collections\', \'updates_colle…
41 …argspec: "args=[\'labels\', \'predictions\', \'dim\', \'weights\', \'metrics_collections\', \'upda…
45 …argspec: "args=[\'labels\', \'predictions\', \'num_classes\', \'weights\', \'metrics_collections\'…
[all …]
|