Lines Matching refs:features
53 features, labels = features_and_labels
54 train_set = (features[:int(len(features) / 2)],
55 labels[:int(len(features) / 2)])
56 test_set = (features[int(len(features) / 2):],
57 labels[int(len(features) / 2):])
61 def _input_fn_builder(features, labels):
64 feature_dict = {'features': constant_op.constant(features)}
77 self.features = np.random.rand(NUM_EXAMPLES, 5)
89 [self.features, self.labels])
107 [self.features, self.binary_labels])
124 [self.features, self.binary_float_labels])
143 [self.features, self.labels])
166 [self.features, self.binary_labels])
187 [self.features, self.binary_float_labels])
274 features = {
286 return features, constant_op.constant([[1], [0], [0]], dtype=dtypes.int32)
303 features = {
316 return features, labels
370 features = {
373 return features, labels
389 features = {
392 return features, labels
407 features = {
411 return features, labels
416 features = {
420 features, labels
439 features = {
443 return features, labels
448 features = {
452 return features, labels
466 features = {
472 return features, labels
530 features = {
542 return features, constant_op.constant([[1], [0], [0]], dtype=dtypes.int32)
596 self.features = np.random.rand(NUM_EXAMPLES, 5)
603 [self.features, self.targets])
667 features = {
679 return features, constant_op.constant([1., 0., 0.2], dtype=dtypes.float32)
696 features = {
699 return features, labels
715 features = {
719 return features, labels
724 features = {
728 return features, labels
745 features = {
749 return features, labels
754 features = {
758 return features, labels
773 features = {
779 return features, labels
825 features = {
837 return features, constant_op.constant([1., 0., 0.2], dtype=dtypes.float32)
