| /external/tensorflow/tensorflow/lite/examples/python/ |
| label_image.py | 44 parser.add_argument("-l", "--label_file", default="/tmp/labels.txt", \
45 help="name of file containing labels")
81 labels = load_labels(args.label_file) variable
84 print('{0:08.6f}'.format(float(results[i]))+":", labels[i])
86 print('{0:08.6f}'.format(float(results[i]/255.0))+":", labels[i])
|
| /external/v8/src/torque/ |
| types.cc | 211 if (sig.labels.empty()) return;
213 os << " labels ";
214 for (size_t i = 0; i < sig.labels.size(); ++i) {
216 if (with_names) os << sig.labels[i].name;
218 if (sig.labels[i].types.size() > 0) os << "(" << sig.labels[i].types << ")";
254 if (labels.size() != other.labels.size()) {
258 for (auto l : labels) {
259 if (l.types != other.labels[i++].types)
[all...] |
| /bionic/tools/bionicbb/ |
| tasks.py | 94 labels = gmail_service.users().labels().list(userId='me').execute()
95 if not labels['labels']:
96 logging.error('Could not retrieve Gmail labels')
98 label_id = gmail.get_gerrit_label(labels['labels'])
|
| /external/autotest/server/cros/network/ |
| rf_switch_ap_box_test.py | 48 self.mock_host.labels = ['rf_switch_1', 'ap_box_1', 'rf_switch_aps']
63 self.mock_host.labels = ['rf_switch_1', 'rf_switch_aps']
68 'rf_switch labels' in context.exception)
73 self.mock_host.labels = ['ap_box_1', 'rf_switch_aps']
78 'rf_switch labels' in context.exception)
83 self.mock_host.labels = ['rf_switch_1', 'ap_box_1', 'rf_switch_aps']
|
| rf_switch_controller_test.py | 24 hostnames and labels. Create an instance of RfSwitchController and
35 self.rf_switch_host.labels = ['rf_switch', 'rf_switch_1']
36 self.ap_box_host.labels = ['rf_switch_1', 'ap_box_1', 'rf_switch_aps']
37 self.client_box_host.labels = [
86 """Test when RF Switch connected to Client Box with invalid labels."""
88 self.client_box_host.labels = ['rf_switch_1', 'client_1', 'rf_client']
|
| /external/jacoco/org.jacoco.core/src/org/jacoco/core/internal/instr/ |
| DuplicateFrameEliminator.java | 107 final Label dflt, final Label... labels) {
109 mv.visitTableSwitchInsn(min, max, dflt, labels);
114 final Label[] labels) {
116 mv.visitLookupSwitchInsn(dflt, keys, labels);
|
| /external/python/cpython2/Lib/lib2to3/pgen2/ |
| grammar.py | 62 labels -- a list of (x, y) pairs where x is either a token
71 keywords -- a dict mapping keyword strings to arc labels.
73 tokens -- a dict mapping token numbers to arc labels.
82 self.labels = [(0, "EMPTY")]
124 new.labels = self.labels[:]
140 print "labels"
141 pprint(self.labels)
|
| /external/python/cpython3/Lib/lib2to3/pgen2/ |
| grammar.py | 62 labels -- a list of (x, y) pairs where x is either a token
71 keywords -- a dict mapping keyword strings to arc labels.
73 tokens -- a dict mapping token numbers to arc labels.
82 self.labels = [(0, "EMPTY")]
123 new.labels = self.labels[:]
139 print("labels")
140 pprint(self.labels)
|
| /external/tensorflow/tensorflow/contrib/boosted_trees/estimator_batch/ |
| model.py | 39 labels,
48 labels: Labels used to train on.
137 update_op = gbdt_model.train(loss, predictions_dict, labels)
161 labels=labels,
170 labels=labels,
185 labels=labels,
[all...] |
| /external/tensorflow/tensorflow/core/kernels/ |
| xent_op.h | 33 // labels: batch_size, num_classes.
42 typename TTypes<T>::ConstMatrix labels,
58 typename TTypes<T>::ConstMatrix labels,
110 // sum(-labels *
113 loss.device(d) = (labels.broadcast(labels_bcast) *
118 // backprop: prob - labels, where
121 labels.broadcast(labels_bcast);
|
| /external/tensorflow/tensorflow/core/lib/monitoring/ |
| mobile_gauge.h | 56 template <typename... Labels>
57 GaugeCell<ValueType>* GetCell(const Labels&... labels) {
|
| /external/tensorflow/tensorflow/examples/speech_commands/ |
| recognize_commands.h | 40 // labels should be a list of the strings associated with each one-hot score.
50 explicit RecognizeCommands(const std::vector<string>& labels,
|
| /external/ltp/testcases/realtime/func/gtod_latency/ |
| gtod_latency.c | 82 char *labels[] = { "scatter plot x-axis", variable
163 labels[SCATTER_LABELX] = argv[++i];
172 labels[SCATTER_LABELY] = argv[++i];
181 labels[HIST_LABELX] = argv[++i];
190 labels[HIST_LABELY] = argv[++i];
337 labels[SCATTER_LABELX], labels[SCATTER_LABELY],
340 labels[HIST_LABELX], labels[HIST_LABELY], &hist,
|
| /external/smali/dexlib2/src/main/java/org/jf/dexlib2/builder/ |
| MethodLocation.java | 51 // the labels and debugItems lists only when they are needed
54 private List<Label> labels = null; field in class:MethodLocation
79 if (labels == null) {
81 labels = new ArrayList<Label>(1);
82 return labels;
86 return labels;
102 if (this.labels != null || other.labels != null) {
108 this.labels = null;
111 if (this.debugItems != null || other.labels != null)
[all...] |
| /external/tensorflow/tensorflow/contrib/distribute/python/examples/ |
| mnist_eager_multigpu.py | 65 def compute_loss(logits, labels):
68 logits=logits, labels=labels))
114 images, labels = inputs
117 loss = compute_loss(logits, labels)
121 training_accuracy.update_state(labels, logits)
124 images, labels = inputs
126 loss = compute_loss(logits, labels)
128 test_accuracy.update_state(labels, logits)
|
| mnist_tf1_tpu.py | 63 def compute_loss(logits, labels):
66 logits=logits, labels=labels))
107 images, labels = inputs
110 loss = compute_loss(logits, labels)
114 update_accuracy = training_accuracy.update_state(labels, logits)
120 images, labels = inputs
122 loss = compute_loss(logits, labels)
124 update_accuracy = test_accuracy.update_state(labels, logits)
|
| /external/tensorflow/tensorflow/contrib/eager/python/examples/revnet/ |
| revnet.py | 116 def compute_loss(self, logits, labels):
121 logits=logits, labels=labels)
125 labels = tf.one_hot(
126 labels, depth=self.config.n_classes, axis=1, dtype=self.config.dtype)
128 logits=logits, labels=labels)
132 def compute_gradients(self, saved_hidden, labels, training=True, l2_reg=True):
139 labels: One-hot labels for classificatio
[all...] |
| revnet_test.py | 32 def train_one_iter(model, inputs, labels, optimizer, global_step=None):
36 saved_hidden=saved_hidden, labels=labels)
106 saved_hidden=saved_hidden, labels=self.t)
117 loss_true = self.model.compute_loss(logits=logits, labels=self.t)
134 grads, _ = compute_gradients(saved_hidden=saved_hidden, labels=self.t)
160 grads, _ = model.compute_gradients(saved_hidden=saved_hidden, labels=t)
181 labels = tf.random_uniform(
184 return images, labels
284 (images, labels) = random_batch(batch_size, config
[all...] |
| /external/tensorflow/tensorflow/contrib/gan/python/estimator/python/ |
| head_impl.py | 150 def create_loss(self, features, mode, logits, labels):
159 labels: Must be `None`.
165 _validate_logits_and_labels(logits, labels)
166 del mode, labels, features # unused for this head.
173 self, features, mode, logits, labels=None,
183 labels: Must be `None`.
196 _validate_logits_and_labels(logits, labels)
211 features=None, mode=mode, logits=gan_model, labels=None)
250 def _validate_logits_and_labels(logits, labels):
251 if labels is not None
[all...] |
| /external/tensorflow/tensorflow/contrib/tensor_forest/python/ops/ |
| data_ops.py | 182 def ParseLabelTensorOrDict(labels):
183 """Return a tensor to use for input labels to tensor_forest.
192 labels: `Tensor` or `dict` of `Tensor` objects.
195 A 2-D tensor for labels/outputs.
197 if isinstance(labels, dict):
202 labels[k], default_value=-1) if isinstance(
203 labels, sparse_tensor.SparseTensor) else labels[k]
204 for k in sorted(labels.keys())
209 if isinstance(labels, sparse_tensor.SparseTensor)
[all...] |
| /external/tensorflow/tensorflow/go/ |
| example_inception_inference_test.go | 53 // A separate file contains a list of string labels corresponding to the
68 imagefile := flag.String("image", "", "Path of a JPEG-image to extract labels for")
117 // labels for each image in the "batch". The batch size was 1.
138 var labels []string
140 labels = append(labels, scanner.Text())
145 fmt.Printf("BEST MATCH: (%2.0f%% likely) %s\n", probabilities[bestIdx]*100.0, labels[bestIdx])
225 labels = filepath.Join(dir, "imagenet_comp_graph_label_strings.txt")
228 if filesExist(model, labels) == nil {
229 return model, labels, ni
[all...] |
| /external/jacoco/org.jacoco.core.test/src/org/jacoco/core/internal/flow/ |
| MethodProbesAdapterTest.java | 75 Label dflt, Label[] labels, IFrame frame) {
77 Integer.valueOf(max), dflt, labels);
83 Label[] labels, IFrame frame) {
84 rec("visitLookupSwitchInsnWithProbes", dflt, keys, labels);
226 final Label[] labels = new Label[] { label, label }; local
228 adapter.visitLookupSwitchInsn(label, keys, labels);
231 expectedVisitor.visitLookupSwitchInsnWithProbes(label, keys, labels,
245 final Label[] labels = new Label[] { label2, label }; local
247 adapter.visitLookupSwitchInsn(label, keys, labels);
250 expectedVisitor.visitLookupSwitchInsnWithProbes(label, keys, labels,
261 final Label[] labels = new Label[] { label, label }; local
274 final Label[] labels = new Label[] { label, label }; local
292 final Label[] labels = new Label[] { label2, label }; local
307 final Label[] labels = new Label[] { label, label }; local
[all...] |
| /external/minijail/ |
| syscall_filter.c | 159 unsigned int get_label_id(struct bpf_labels *labels, const char *label_str)
161 int label_id = bpf_label_id(labels, label_str);
167 unsigned int group_end_lbl(struct bpf_labels *labels, int nr, int idx)
171 return get_label_id(labels, lbl_str);
174 unsigned int success_lbl(struct bpf_labels *labels, int nr)
178 return get_label_id(labels, lbl_str);
187 char *atom, struct bpf_labels *labels, int nr, int grp_idx)
251 unsigned int id = group_end_lbl(labels, nr, grp_idx);
306 struct bpf_labels *labels,
396 if (compile_atom(state, head, comp, labels, nr
710 struct bpf_labels labels; local
[all...] |
| /external/tensorflow/tensorflow/contrib/eager/python/examples/resnet50/ |
| resnet50_test.py | 46 labels = tf.random_uniform(
48 one_hot = tf.one_hot(labels, num_classes)
53 def compute_gradients(model, images, labels, num_replicas=1):
57 logits=logits, onehot_labels=labels)
127 images, labels = random_batch(2, data_format)
129 compute_gradients(model, images, labels))
147 images, labels = random_batch(2, data_format)
154 compute_gradients(model, images, labels))
162 compute_gradients(model, images, labels))
264 (images, labels) = random_batch(batch_size, data_format
[all...] |
| /external/tensorflow/tensorflow/core/util/ctc/ |
| ctc_loss_calculator.h | 45 // training labels do not have a class value of N-1, as training will skip
63 Status CalculateLoss(const VectorIn& seq_len, const LabelSequences& labels,
95 const LabelSequences& labels, size_t* max_u_prime,
101 // Delay for target labels in time steps.
109 const VectorIn& seq_len, const LabelSequences& labels,
161 batch_size, num_classes, seq_len, labels, &max_u_prime, &l_primes);
167 auto ComputeLossAndGradients = [this, num_classes, &labels, &l_primes,
174 // Return zero gradient for empty sequences or sequences with labels
178 labels[b].size() > seq_len(b) - this->output_delay_)) {
183 << b << ": " << str_util::Join(labels[b], " ")
[all...] |
