/external/tensorflow/tensorflow/python/keras/_impl/keras/utils/ |
np_utils_test.py | 40 for label, one_hot, expected_shape in zip(labels, 44 self.assertEqual(one_hot.shape, expected_shape) 46 self.assertTrue(np.all(one_hot.sum(axis=-1) == 1)) 49 np.argmax(one_hot, -1).reshape(label.shape) == label))
|
/external/tensorflow/tensorflow/compiler/tf2xla/kernels/ |
one_hot_op.cc | 65 xla::ComputationDataHandle one_hot; variable 69 ctx->Input(3), &one_hot)); 70 ctx->SetOutput(0, one_hot);
|
/external/tensorflow/tensorflow/contrib/learn/python/learn/datasets/ |
mnist.py | 77 def extract_labels(f, one_hot=False, num_classes=10): 82 one_hot: Does one hot encoding for the result. 100 if one_hot: 111 one_hot=False, 116 one_hot arg is used only if fake_data is true. `dtype` can be either 129 self.one_hot = one_hot 170 if self.one_hot: 215 one_hot=False, 225 [], [], fake_data=True, one_hot=one_hot, dtype=dtype, seed=seed [all...] |
/external/tensorflow/tensorflow/contrib/gan/python/features/python/ |
conditioning_utils_impl.py | 76 def _one_hot_to_embedding(one_hot, embedding_size): 78 num_tokens = one_hot.shape[1] 79 label_id = math_ops.argmax(one_hot, axis=1)
|
/external/tensorflow/tensorflow/contrib/keras/api/keras/preprocessing/text/ |
__init__.py | 21 from tensorflow.python.keras._impl.keras.preprocessing.text import one_hot
|
/external/tensorflow/tensorflow/python/keras/preprocessing/text/ |
__init__.py | 21 from tensorflow.python.keras._impl.keras.preprocessing.text import one_hot
|
/external/tensorflow/tensorflow/python/keras/_impl/keras/preprocessing/ |
text_test.py | 31 encoded = keras.preprocessing.text.one_hot(text, 5) 38 encoded = keras.preprocessing.text.one_hot(text, 5)
|
/external/tensorflow/tensorflow/compiler/tf2xla/ |
xla_helpers.h | 109 xla::ComputationDataHandle* one_hot);
|
xla_helpers.cc | 232 xla::ComputationDataHandle* one_hot) { 270 *one_hot = builder->Select(
|
/external/tensorflow/tensorflow/contrib/eager/python/examples/mnist/ |
mnist_test.py | 38 labels = tf.one_hot(digits, 10)
|
/external/tensorflow/tensorflow/contrib/eager/python/examples/rnn_colorbot/ |
rnn_colorbot_test.py | 37 chars = tf.one_hot(
|
/external/tensorflow/tensorflow/contrib/eager/python/examples/resnet50/ |
resnet50_graph_test.py | 46 one_hot = np.zeros((batch_size, num_classes)).astype(np.float32) 47 one_hot[np.arange(batch_size), labels] = 1. 48 return images, one_hot
|
resnet50_test.py | 49 one_hot = tf.one_hot(labels, num_classes) 51 return images, one_hot
|
/external/tensorflow/tensorflow/contrib/distributions/python/ops/ |
onehot_categorical.py | 183 samples = array_ops.one_hot(samples, self.event_size, dtype=self.dtype) 215 ret = array_ops.one_hot(ret, self.event_size, dtype=self.dtype)
|
/external/tensorflow/tensorflow/contrib/gan/python/ |
train_test.py | 87 return (discriminator_model(inputs, _), array_ops.one_hot( 96 return (discriminator_model(inputs, _), array_ops.one_hot( 182 one_hot_labels=array_ops.one_hot([0, 1, 2], 10), 183 discriminator_real_classification_logits=array_ops.one_hot([0, 1, 3], 10), 184 discriminator_gen_classification_logits=array_ops.one_hot([0, 1, 4], 10)) 190 one_hot_labels=array_ops.one_hot([0, 1, 2], 10), 191 discriminator_real_classification_logits=array_ops.one_hot([0, 1, 3], 10), 192 discriminator_gen_classification_logits=array_ops.one_hot([0, 1, 4], 10)) 201 one_hot_labels=array_ops.one_hot([0, 1, 2], 10)) 210 one_hot_labels=array_ops.one_hot([0, 1, 2], 10) [all...] |
/external/tensorflow/tensorflow/contrib/boosted_trees/python/utils/ |
losses.py | 74 target_one_hot = array_ops.one_hot(indices=labels, depth=num_classes)
|
/external/tensorflow/tensorflow/contrib/data/python/ops/ |
resampling.py | 183 array_ops.one_hot(c, num_classes, dtype=dtypes.int64), 0))
|
/external/tensorflow/tensorflow/contrib/kernel_methods/python/ |
losses.py | 129 one_cold_labels = array_ops.one_hot(
|
/external/tensorflow/tensorflow/contrib/seq2seq/python/ops/ |
beam_search_decoder.py | 231 self._finished = array_ops.one_hot( 303 log_probs = array_ops.one_hot( # shape(batch_sz, beam_sz) 554 lengths_to_add = array_ops.one_hot( 723 finished_row = array_ops.one_hot(
|
/external/tensorflow/tensorflow/examples/learn/ |
random_forest_mnist.py | 58 mnist = input_data.read_data_sets(FLAGS.data_dir, one_hot=False)
|
text_classification_character_rnn.py | 45 byte_vectors = tf.one_hot(features[CHARS_FEATURE], 256, 1., 0.)
|
/external/tensorflow/tensorflow/contrib/layers/python/layers/ |
feature_column_test.py | 311 one_hot = fc.one_hot_column(sparse_column) 318 one_hot_output = one_hot._to_dnn_input_layer( 328 one_hot = fc.one_hot_column(weighted_ids) 329 self.assertEqual(one_hot.sparse_id_column.name, "ids_weighted_by_weights") 330 self.assertEqual(one_hot.length, 3) 385 one_hot = fc.one_hot_column(weighted_ids) 391 features, [one_hot]) 399 one_hot = fc.one_hot_column(ids) 402 features, [one_hot]) [all...] |
/external/tensorflow/tensorflow/contrib/distributions/python/ops/bijectors/ |
softmax_centered.py | 175 begin = array_ops.one_hot(indices=ndims-1,
|
/external/tensorflow/tensorflow/contrib/seq2seq/python/kernel_tests/ |
basic_decoder_test.py | 384 return array_ops.one_hot(samples, cell_depth, dtype=dtypes.float32) 515 start_inputs = array_ops.one_hot( 523 lambda x: array_ops.one_hot(x, vocabulary_size, dtype=dtypes.float32)) 596 start_inputs = array_ops.one_hot(
|
/external/tensorflow/tensorflow/contrib/tensor_forest/client/ |
eval_metrics.py | 61 return array_ops.one_hot(math_ops.to_int32(targets), depth)
|