/external/tensorflow/tensorflow/contrib/data/python/ops/ |
get_single_element.py | 25 def get_single_element(dataset): 26 """Returns the single element in `dataset` as a nested structure of tensors. 28 This function enables you to use a @{tf.data.Dataset} in a stateless 31 as a `Dataset`, and you want to use the transformation at serving time. 41 dataset = (tf.data.Dataset.from_tensor_slices(input_batch) 45 image_batch, label_batch = tf.contrib.data.get_single_element(dataset) 49 dataset: A @{tf.data.Dataset} object containing a single element. 53 element of `dataset` [all...] |
readers.py | 84 dataset to combine in a single batch. 88 and (optional) `reader_args` and returns a `Dataset` of Examples. 92 dataset. If None, cycles through the dataset forever. 101 dataset = reader(filenames, *reader_args) 103 dataset = reader(filenames) 104 if dataset.output_types == (dtypes.string, dtypes.string): 105 dataset = dataset.map(lambda _, v: v) 107 dataset = dataset.repeat(num_epochs [all...] |
batching.py | 15 """Batching dataset transformations.""" 36 Like `Dataset.padded_batch()`, this transformation combines multiple 37 consecutive elements of the dataset, which might have different 47 # contents of a dataset. 63 number of consecutive elements of this dataset to combine in a 67 resulting `tf.SparseTensor`. Each element of this dataset must 72 A `Dataset` transformation function, which can be passed to 73 @{tf.data.Dataset.apply}. 76 def _apply_fn(dataset): 77 return DenseToSparseBatchDataset(dataset, batch_size, row_shape [all...] |
enumerate_ops.py | 15 """Enumerate dataset transformations.""" 27 """A transformation that enumerate the elements of a dataset. 34 # contents of a dataset. 39 # structure of elements in the resulting dataset. 49 A `Dataset` transformation function, which can be passed to 50 @{tf.data.Dataset.apply}. 53 def _apply_fn(dataset): 55 return dataset_ops.Dataset.zip((dataset_ops.Dataset.range(start, max_value), 56 dataset)) [all...] |
/external/tensorflow/tensorflow/contrib/tensor_forest/kernels/v4/ |
decision_node_evaluator_test.cc | 37 std::unique_ptr<tensorflow::tensorforest::TensorDataSet> dataset( 41 ASSERT_EQ(eval->Decide(dataset, 2), 0); 42 ASSERT_EQ(eval->Decide(dataset, 3), 0); 43 ASSERT_EQ(eval->Decide(dataset, 4), 1); 54 std::unique_ptr<tensorflow::tensorforest::TensorDataSet> dataset( 58 ASSERT_EQ(eval->Decide(dataset, 2), 0); 59 ASSERT_EQ(eval->Decide(dataset, 3), 1); 60 ASSERT_EQ(eval->Decide(dataset, 4), 1); 72 std::unique_ptr<tensorflow::tensorforest::TensorDataSet> dataset( 76 ASSERT_EQ(eval->Decide(dataset, 2), 1) [all...] |
decision_node_evaluator.h | 32 virtual int32 Decide(const std::unique_ptr<TensorDataSet>& dataset, 52 int32 Decide(const std::unique_ptr<TensorDataSet>& dataset, 70 int32 Decide(const std::unique_ptr<TensorDataSet>& dataset, 85 int32 Decide(const std::unique_ptr<TensorDataSet>& dataset,
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grow_stats_test.cc | 56 std::unique_ptr<tensorflow::tensorforest::TensorDataSet> dataset( 60 stats->AddSplit(MakeSplit("0", 10.0), dataset, target, 0); 61 stats->AddSplit(MakeSplit("1", 4.0), dataset, target, 0); 64 stats->AddExample(dataset, target, i); 180 std::unique_ptr<tensorflow::tensorforest::TensorDataSet> dataset( 191 stat->AddExample(dataset, target.get(), 0); 198 stat->AddExample(dataset, target.get(), 0); 225 std::unique_ptr<tensorflow::tensorforest::TensorDataSet> dataset( 231 stats.AddSplit(MakeSplit("0", 0.0), dataset, &target, 0); 232 stats.AddSplit(MakeSplit("1", 0.0), dataset, &target, 0) [all...] |
/system/extras/tests/sdcard/ |
plot_sdcard.py | 47 class DataSet(object): 48 """Dataset holds the summary and data (time,value pairs).""" 117 def UpdateWith(self, dataset): 118 self.duration = max(self.duration, dataset.duration) 119 self.name = dataset.name 134 data = [] # array of dataset 135 dataset = None 149 if line.startswith('# StopWatch'): # Start of a new dataset 150 if dataset: 151 if dataset.summary [all...] |
/external/tensorflow/tensorflow/examples/learn/ |
iris.py | 14 """Example of DNNClassifier for Iris plant dataset. 70 dataset = tf.data.TextLineDataset([file_name]) 72 dataset = dataset.skip(1) 73 dataset = dataset.map(_parse_csv) 76 # For this small dataset, which can fit into memory, to achieve true 78 # elements in the dataset. 79 dataset = dataset.shuffle(num_data [all...] |
/external/tensorflow/tensorflow/contrib/slim/python/slim/data/ |
dataset_data_provider.py | 15 """A DataProvider that provides data from a Dataset. 31 slim.datasets.pascal_voc.Dataset(), 54 dataset, 69 dataset: An instance of the Dataset class. 79 record_key: The item name to use for the dataset record keys in the 84 ValueError: If `record_key` matches one of the items in the dataset. 87 dataset.data_sources, 88 reader_class=dataset.reader, 98 items = dataset.decoder.list_items( [all...] |
/external/tensorflow/tensorflow/contrib/training/python/training/ |
tensor_queue_dataset_test.py | 37 dataset = dataset_ops.Dataset.from_tensor_slices([0, 1, 2]) 38 dataset = dataset.apply( 40 self.assertEqual((dtypes.variant, dtypes.int32), dataset.output_types) 42 [x.as_list() for x in dataset.output_shapes]) 43 iterator = dataset.make_one_shot_iterator() 52 dataset = dataset_ops.Dataset.from_tensor_slices([0, 1, 2]) 53 dataset = dataset.apply [all...] |
/external/tensorflow/tensorflow/examples/how_tos/reading_data/ |
fully_connected_reader.py | 100 over the dataset once. On the other hand there is no special initialization 111 dataset = tf.data.TFRecordDataset(filename) 112 dataset = dataset.repeat(num_epochs) 115 dataset = dataset.map(decode) 116 dataset = dataset.map(augment) 117 dataset = dataset.map(normalize [all...] |
/libcore/benchmarks/src/benchmarks/ |
XmlSerializeBenchmark.java | 36 double[] dataset; field in class:XmlSerializeBenchmark 42 double contChance = dataset[0]; 43 double levelUpChance = dataset[1]; 44 double levelDownChance = dataset[2]; 45 double attributeChance = dataset[3]; 46 double writeChance1 = dataset[4]; 47 double writeChance2 = dataset[5]; 89 dataset = new double[splitted.length]; 91 dataset[i] = Double.parseDouble(splitted[i]);
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/external/tensorflow/tensorflow/python/grappler/ |
datasets_test.py | 50 dataset = dataset_ops.Dataset.from_tensors(test_case['tensor']) 51 iterator = dataset.make_one_shot_iterator() 75 dataset = dataset_ops.Dataset.from_tensor_slices(test_case['tensor']) 76 iterator = dataset.make_one_shot_iterator() 108 dataset = dataset_ops.Dataset.from_generator( 112 iterator = dataset.make_one_shot_iterator() 124 dataset = dataset_ops.Dataset.range(42 [all...] |
/external/tensorflow/tensorflow/python/data/kernel_tests/ |
dataset_constructor_op_test.py | 42 """Test a dataset that represents a single tuple of tensors.""" 45 iterator = (dataset_ops.Dataset.from_tensors(components) 67 """Test a dataset that represents a single tuple of tensors.""" 78 dataset_ops.Dataset.from_tensors(components) 96 """Test an dataset that represents a single tuple of tensors.""" 108 dataset_ops.Dataset.from_tensors(components) 130 """Test a dataset that represents the slices from a tuple of tensors.""" 137 iterator = (dataset_ops.Dataset.from_tensor_slices(components) 155 """Test a dataset that represents the slices from a tuple of tensors.""" 166 dataset_ops.Dataset.from_tensor_slices(components [all...] |
shard_dataset_op_test.py | 28 dataset = dataset_ops.Dataset.range(10).shard(5, 2) 29 iterator = dataset.make_one_shot_iterator() 38 dataset_a = dataset_ops.Dataset.range(10) 39 dataset_b = dataset_ops.Dataset.range(10, 0, -1) 40 dataset = dataset_ops.Dataset.zip((dataset_a, dataset_b)).shard(5, 2) 41 iterator = dataset.make_one_shot_iterator() 50 dataset = dataset_ops.Dataset.range(10).shard(5, 0 [all...] |
list_files_dataset_op_test.py | 46 dataset = dataset_ops.Dataset.list_files(path.join(self.tmp_dir, '*')) 48 itr = dataset.make_one_shot_iterator() 56 dataset = dataset_ops.Dataset.list_files(path.join(self.tmp_dir, '*')) 58 itr = dataset.make_one_shot_iterator() 72 dataset = dataset_ops.Dataset.list_files(filename_placeholder) 75 itr = dataset.make_initializable_iterator() 88 dataset = dataset_ops.Dataset.list_files(filename_placeholder [all...] |
/external/tensorflow/tensorflow/core/kernels/data/ |
dataset_utils.h | 20 #include "tensorflow/core/kernels/data/dataset.h" 24 namespace dataset { namespace in namespace:tensorflow 31 } // namespace dataset
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cache_dataset_ops.cc | 17 #include "tensorflow/core/kernels/data/dataset.h" 109 input_impl_(params.dataset->input_->MakeIterator(params.prefix)), 110 writer_(params.dataset->env_, params.dataset->filename_), 111 lockfile_(strings::StrCat(params.dataset->filename_, ".lockfile")), 139 if (out_tensors->size() != dataset()->num_tensors_) { 142 dataset()->num_tensors_, " got: ", out_tensors->size()); 146 DCHECK_LT(tensor_index, dataset()->num_tensors_); 147 string key = dataset()->FormatName(cur_index_, tensor_index++); 166 if (dataset()->env_->FileExists(lockfile_).ok()) [all...] |
/developers/build/prebuilts/gradle/NavigationDrawer/kotlinApp/Application/src/main/java/com/example/android/navigationdrawer/ |
PlanetAdapter.kt | 29 private val dataset: Array<String>, 52 textView.text = dataset[position] 57 override fun getItemCount() = dataset.size
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/developers/samples/android/ui/views/NavigationDrawer/kotlinApp/Application/src/main/java/com/example/android/navigationdrawer/ |
PlanetAdapter.kt | 29 private val dataset: Array<String>, 52 textView.text = dataset[position] 57 override fun getItemCount() = dataset.size
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/developers/samples/android/input/autofill/AutofillFramework/afservice/src/main/java/com/example/android/autofill/service/data/adapter/ |
ResponseAdapter.java | 21 import android.service.autofill.Dataset; 57 Dataset dataset = mDatasetAdapter.buildDatasetForFocusedNode(field, fieldType, remoteViews); local 58 if (dataset != null) { 59 responseBuilder.addDataset(dataset); 76 Dataset dataset; local 84 dataset = mDatasetAdapter.buildDataset(fieldTypesByAutofillHint, 89 dataset = mDatasetAdapter.buildDataset(fieldTypesByAutofillHint, 92 if (dataset != null) [all...] |
/external/tensorflow/tensorflow/core/framework/ |
dataset_stateful_op_whitelist.h | 22 namespace dataset { namespace in namespace:tensorflow 23 // Registry for stateful ops that need to be used in dataset functions. 50 } // namespace dataset 72 ::tensorflow::dataset::WhitelistedStatefulOpRegistry::Global()->Add( \
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/external/tensorflow/tensorflow/contrib/eager/python/examples/mnist/ |
mnist_test.py | 39 return tf.data.Dataset.from_tensors((images, labels)) 47 dataset = random_dataset() 50 mnist.train_one_epoch(model, optimizer, dataset) 55 dataset = random_dataset() 60 mnist.test(model, dataset)
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/external/tensorflow/tensorflow/contrib/eager/python/examples/rnn_colorbot/ |
rnn_colorbot_test.py | 44 return tf.data.Dataset.from_tensors((labels, chars, sequence_length)) 55 dataset = random_dataset() 57 rnn_colorbot.train_one_epoch(model, optimizer, dataset) 64 dataset = random_dataset() 66 rnn_colorbot.test(model, dataset)
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