| /external/tensorflow/tensorflow/examples/saved_model/integration_tests/ |
| use_model_in_sequential_keras.py | 36 labels = np.array([1, 0])
37 dataset = tf.data.Dataset.from_tensor_slices((features, labels))
|
| /external/tensorflow/tensorflow/contrib/boosted_trees/python/training/functions/ |
| gbdt_batch_test.py | 256 labels = array_ops.ones([4, 1], dtypes.float32)
261 _squared_loss(labels, weights, predictions)),
263 labels=labels)
349 labels = array_ops.constant([[-2], [-1], [1], [2]], dtypes.float32)
354 _squared_loss(labels, weights, predictions)),
356 labels=labels)
520 labels = array_ops.ones([4, 1], dtypes.float32)
525 _squared_loss(labels, weights, predictions))
[all...] |
| /external/autotest/server/cros/dynamic_suite/ |
| host_spec.py | 11 Currently, 'complex' means that the spec contains more labels.
18 return len(host_spec.labels)
207 def __init__(self, labels, num):
210 Given a set of labels specifying what kind of hosts we need,
214 @param labels: list of labels indicating what kind of hosts need
218 self._spec = HostSpec(labels)
219 self._meta_hosts = labels[:1]*num
220 self._dependencies = labels[1:]
266 Wraps a list of labels, for the purposes of specifying a set of host
279 def labels(self): member in class:HostSpec
[all...] |
| host_spec_unittest.py | 82 """Should be able to make a HostGroup from labels."""
83 labels = ['meta_host', 'dep1', 'dep2']
85 group = host_spec.MetaHostGroup(labels, num)
87 self.assertEquals(labels[:1] * num, args['meta_hosts'])
88 self.assertEquals(labels[1:], args['dependencies'])
173 labels = ['meta_host', 'dep1', 'dep2']
175 group = host_spec.MetaHostGroup(labels, num)
|
| /external/autotest/server/hosts/ |
| shadowing_store_unittest.py | 21 info = host_info.HostInfo(labels='blah', attributes='boo')
32 info = host_info.HostInfo(labels='blah', attributes='boo')
39 init_info = host_info.HostInfo(labels='init')
43 info = host_info.HostInfo(labels='blah', attributes='boo')
50 init_info = host_info.HostInfo(labels='init')
59 init_info = host_info.HostInfo(labels='init')
|
| base_label_unittest.py | 31 This is a variation of BaseLabel with multiple labels for _NAME
32 to ensure we handle a label that contains a list of labels for
43 This test class is to check that we properly construct the prefix labels
59 def __init__(self, labels=None, attributes=None):
60 self.labels = labels or []
81 """Let's make sure generate_labels() returns the labels expected."""
88 # We should get labels here.
97 """Check that we get the expected labels for get_all_labels()."""
101 # We want to check that we always get a list of labels regardless i
[all...] |
| factory_unittest.py | 54 def _gen_machine_dict(hostname='localhost', labels=[], attributes={}):
58 @param labels: list of host labels
63 afe_host = base_label_unittest.MockAFEHost(labels, attributes)
65 store.commit(host_info.HostInfo(labels, attributes))
113 machine = _gen_machine_dict(labels=['os:foo'])
123 machine = _gen_machine_dict(labels=['os:foo'],
|
| /external/desugar/test/java/com/google/devtools/build/android/desugar/ |
| ByteCodeTypePrinter.java | 147 public void visitLookupSwitchInsn(Label dflt, int[] keys, Label[] labels) {
148 printer.visitLookupSwitchInsn(dflt, keys, labels);
150 super.visitLookupSwitchInsn(dflt, keys, labels);
154 public void visitTableSwitchInsn(int min, int max, Label dflt, Label... labels) {
155 printer.visitTableSwitchInsn(min, max, dflt, labels);
157 super.visitTableSwitchInsn(min, max, dflt, labels);
|
| /external/tensorflow/tensorflow/contrib/eager/python/examples/revnet/ |
| main_estimator.py | 30 def model_fn(features, labels, mode, params):
35 labels: Labels of images
57 grads, loss = model.compute_gradients(saved_hidden, labels, training=True)
69 loss = model.compute_loss(labels=labels, logits=logits)
75 tf.metrics.accuracy(labels=labels, predictions=predictions)
|
| /external/tensorflow/tensorflow/contrib/tensor_forest/client/ |
| eval_metrics.py | 48 labels=targets, predictions=predictions, weights=weights)
97 labels=targets, predictions=predictions, weights=weights)
102 labels=targets,
110 labels=targets, predictions=predictions, weights=weights)
115 labels=targets,
123 labels=targets,
|
| random_forest_test.py | 38 labels = iris.target.astype(np.int32)
41 x=data, y=labels, batch_size=150, num_epochs=None, shuffle=False)
51 labels = boston.target.astype(np.int32)
54 x=data, y=labels, batch_size=506, num_epochs=None, shuffle=False)
121 labels = iris.target.astype(np.int32)
128 y=labels,
242 labels = iris.target.astype(np.int32)
245 x=data, y=labels, batch_size=150, num_epochs=None, shuffle=False)
307 labels = iris.target.astype(np.int32)
314 y=labels,
[all...] |
| /external/tensorflow/tensorflow/core/lib/monitoring/ |
| collection_registry.h | 61 // Collects the value with these labels.
62 void CollectValue(const std::array<string, NumLabels>& labels,
148 // metric_collector.CollectValue(cell.labels(), cell.value());
328 const std::array<string, NumLabels>& labels, const Value& value) {
333 point->labels.reserve(NumLabels);
335 point->labels.push_back({});
336 auto* const label = &point->labels.back();
338 label->value = labels[i];
|
| /external/v8/tools/ignition/ |
| bytecode_dispatches_report.py | 129 labels = sorted(dispatches_table.keys())
131 counters_matrix = numpy.empty([len(labels), len(labels)], dtype=int)
132 for from_index, from_name in enumerate(labels):
134 for to_index, to_name in enumerate(labels):
138 xlabels = labels
|
| /external/autotest/scheduler/ |
| rdb_cache_unittests.py | 19 """Get the cache line with the hosts that match given labels.
21 Confirm that all hosts have matching labels within a line,
22 then return the lines with the requested labels. There can
25 @param labels: A list of label names.
28 @return: A list of the cache lines with the requested labels.
34 labels = list(line)[0].labels.get_label_names()
35 if any(host.labels.get_label_names() != labels for host in line):
37 if required_labels == labels
[all...] |
| /external/tensorflow/tensorflow/contrib/eager/python/examples/densenet/ |
| densenet_test.py | 140 def compute_gradients(model, images, labels):
144 logits=logits, onehot_labels=labels)
167 labels = tf.random_uniform(
169 one_hot = tf.one_hot(labels, num_classes)
272 (images, labels) = random_batch(batch_size, data_format)
288 iterator = make_iterator((images, labels))
290 (images, labels) = iterator.next()
292 compute_gradients(model, images, labels))
300 (images, labels) = iterator.next()
302 compute_gradients(model, images, labels))
[all...] |
| /external/autotest/server/ |
| site_utils.py | 97 we only use attributes and labels but as time goes by and other
104 self.labels = []
132 """Retrieve a host's specific labels from the AFE.
134 Looks for the host labels that have the form <label_prefix>:<value>
142 @returns A list of labels that match the prefix or 'None'
145 labels = afe.get_labels(name__startswith=label_prefix,
147 if labels:
148 return [l.name.split(label_prefix, 1)[1] for l in labels]
164 labels = get_labels_from_afe(hostname, label_prefix, afe)
165 if labels and len(labels) == 1
[all...] |
| /external/tensorflow/tensorflow/contrib/timeseries/python/timeseries/ |
| head_test.py | 64 with self.assertRaisesRegexp(ValueError, "received a `labels`"):
65 model_fn(features={}, labels={"a": "b"}, mode=mode)
67 with self.assertRaisesRegexp(ValueError, "received a `labels`"):
68 model_fn(features={}, labels=array_ops.zeros([]), mode=mode)
73 model_fn(features={}, labels={}, mode="Not a mode")
120 features=features, labels=None, mode=estimator_lib.ModeKeys.EVAL)
206 labels=None,
216 labels=None,
230 labels=None,
244 labels=None
[all...] |
| /external/tensorflow/tensorflow/tools/compatibility/testdata/ |
| test_file_v0_11.py | 177 labels = [.8, .5, .2, .1]
181 logits, labels).eval(),
183 labels=labels, logits=logits).eval())
186 logits, labels).eval(),
188 labels=labels, logits=logits).eval())
|
| /external/toolchain-utils/fdo_scripts/ |
| vanilla_vs_fdo.py | 130 def _TestLabels(self, labels):
145 for label in labels:
146 # TODO(asharif): Fix crosperf so it accepts labels with symbols
224 labels = []
230 labels.append(minus_pgo)
235 labels.append(plus_pgo)
248 labels.append(updated_pgo_label)
251 self._TestLabels(labels)
|
| /external/tensorflow/tensorflow/python/compiler/tensorrt/test/ |
| quantization_mnist_test.py | 198 features, labels = iterator.get_next()
199 return features, labels
212 features, labels = iterator.get_next()
213 return features, labels
215 def _ModelFn(features, labels, mode):
227 labels=labels, logits=logits_out)
232 labels=labels, predictions=classes_out, name='acc_op')
|
| /development/tools/repo_pull/ |
| repo_review.py | 39 """Collect and check labels from args."""
42 labels = {}
45 labels[name] = int(value)
49 return labels
99 help='Labels to be added')
175 """Set review labels to selected change lists"""
186 labels = _get_labels_from_args(args)
209 labels, args.message, errors=errors)
|
| /external/autotest/server/cros/clique_lib/ |
| clique_dut_locker.py | 165 labels = []
166 labels.append(constants.BOARD_PREFIX + board_name)
167 labels.append('clique_dut')
170 afe, self.lock_manager, labels=labels) + '.cros'
|
| /external/autotest/site_utils/ |
| dut_status.py | 321 labels = labellib.LabelsMapping()
322 labels['board'] = arguments.board
323 labels['pool'] = arguments.pool
324 labels['model'] = arguments.model
326 afe, arguments.since, arguments.until, labels.getlabels())
|
| /external/jacoco/org.jacoco.core/src/org/jacoco/core/internal/analysis/filter/ |
| TryWithResourcesEcjFilter.java | 52 private final Map<String, LabelNode> labels = new HashMap<String, LabelNode>(); field in class:TryWithResourcesEcjFilter.Matcher
64 labels.clear();
239 final LabelNode expected = labels.get(name);
241 labels.put(name, actual);
257 final LabelNode expected = labels.get(name);
|
| /external/tensorflow/tensorflow/compiler/tests/ |
| jit_test.py | 68 """Returns all labels in run_metadata."""
69 labels = []
72 labels.append(node_stats.timeline_label)
73 return labels
76 def InLabels(labels, substr):
77 """Returns true iff one of the labels contains substr."""
78 return any(substr in x for x in labels)
458 labels = _Run(compiled=False)
459 self.assertFalse(InLabels(labels, "Log"))
460 self.assertTrue(InLabels(labels, "Reciprocal")
[all...] |
