| /external/tensorflow/tensorflow/lite/toco/graph_transformations/ |
| resolve_gather_attributes.cc | 21 #include "tensorflow/lite/toco/model.h"
27 ::tensorflow::Status ResolveGatherAttributes::Run(Model* model,
31 auto* gather_op = model->operators[op_index].get();
41 if (!IsConstantParameterArray(*model, op->inputs[2]))
44 const auto& indices_array = model->GetArray(op->inputs[2]);
52 DeleteArrayIfUsedOnce(op->inputs[2], model);
|
| quantize.cc | 25 #include "tensorflow/lite/toco/model.h"
83 const MinMax& GetOrComputeMinMax(Model* model, const string& array_name) {
84 auto& array = model->GetArray(array_name);
184 GraphTransformation* transformation, Model* model, const Operator& op,
188 auto& array = model->GetArray(input);
218 model->GetArray(op.inputs[activations_input_index]);
219 const auto& input_weights = model->GetArray(op.inputs[weights_input_index]);
239 const MinMax& minmax = GetOrComputeMinMax(model, input)
[all...] |
| fuse_binary_into_following_affine.cc | 22 #include "tensorflow/lite/toco/model.h"
31 void FuseAddOrSubParamsIntoFollowingAffine(Model* model, Operator* following_op,
45 const auto& weights = model->GetArray(following_op->inputs[1]);
46 auto& bias = model->GetArray(following_op->inputs[2]);
49 model->GetArray(add_or_sub_op->inputs[index_of_constant_input]);
113 void FuseMulOrDivParamsIntoFollowingAffine(Model* model, Operator* following_op,
125 auto& weights = model->GetArray(weights_name);
126 DropMinMax(model, weights_name)
[all...] |
| resolve_batch_to_space_nd_attributes.cc | 21 #include "tensorflow/lite/toco/model.h"
27 ::tensorflow::Status ResolveBatchToSpaceNDAttributes::Run(Model* model,
31 const auto op_it = model->operators.begin() + op_index;
44 if (!IsConstantParameterArray(*model, op->inputs[1]) ||
45 !IsConstantParameterArray(*model, op->inputs[2]))
49 const auto& crops_array = model->GetArray(op->inputs[2]);
65 const auto& block_shape_array = model->GetArray(op->inputs[1]);
|
| resolve_fake_quant_args_from_vars.cc | 22 #include "tensorflow/lite/toco/model.h"
28 ::tensorflow::Status ResolveFakeQuantArgsFromVars::Run(Model* model,
32 const auto fakequant_it = model->operators.begin() + op_index;
48 if (!IsConstantParameterArray(*model, fakequant_op->inputs[i])) {
54 const auto& min_array = model->GetArray(fakequant_op->inputs[1]);
55 const auto& max_array = model->GetArray(fakequant_op->inputs[2]);
77 DeleteArrayIfUsedOnce(fakequant_op->inputs[i], model);
|
| resolve_space_to_batch_nd_attributes.cc | 21 #include "tensorflow/lite/toco/model.h"
27 ::tensorflow::Status ResolveSpaceToBatchNDAttributes::Run(Model* model,
31 const auto op_it = model->operators.begin() + op_index;
47 if (!IsConstantParameterArray(*model, op->inputs[block_shape_index]) ||
48 !IsConstantParameterArray(*model, op->inputs[paddings_index]))
52 const auto& paddings_array = model->GetArray(op->inputs[paddings_index]);
69 model->GetArray(op->inputs[block_shape_index]);
|
| /external/tensorflow/tensorflow/lite/nnapi/ |
| NeuralNetworksShim.h | 139 * The model should be constructed with calls to
143 * <p>{@link ANeuralNetworksModel_finish} should be called once the model
146 * <p>{@link ANeuralNetworksModel_free} should be called once the model
149 * @param model The {@link ANeuralNetworksModel} to be created.
154 inline int ANeuralNetworksModel_create(ANeuralNetworksModel** model) {
156 EXECUTE_FUNCTION_RETURN(model);
160 * Destroy a model.
162 * The model need not have been finished by a call to
167 * @param model The model to be destroyed. Passing NULL is acceptable an
[all...] |
| /external/tensorflow/tensorflow/python/keras/engine/ |
| training_arrays.py | 45 def model_iteration(model,
69 model: Keras Model instance.
114 - In PREDICT mode: Outputs of the Model called on inputs.
138 input_iterator = _get_iterator(inputs, model._distribution_strategy)
144 if model._distribution_strategy:
146 strategy=model._distribution_strategy,
151 f = _make_execution_function(model, mode)
168 ins = _prepare_feed_values(model, inputs, targets, sample_weights, mode)
189 val_iterator = _get_iterator(val_inputs, model._distribution_strategy
[all...] |
| /external/tensorflow/tensorflow/contrib/eager/python/examples/resnet50/ |
| resnet50_test.py | 15 """Tests and benchmarks for the ResNet50 model, executed eagerly."""
53 def compute_gradients(model, images, labels, num_replicas=1):
55 logits = model(images, training=True)
66 grads = grad_tape.gradient(loss, model.variables)
70 def apply_gradients(model, optimizer, gradients):
71 optimizer.apply_gradients(zip(gradients, model.variables))
78 model = resnet50.ResNet50(data_format)
80 model.call = tfe.function(model.call)
83 output = model(images, training=False
[all...] |
| /external/tensorflow/tensorflow/python/keras/ |
| metrics_correctness_test.py | 15 """Tests metrics correctness using Keras model."""
46 model = testing_utils.get_multi_io_model(branch_a, branch_b)
47 model.compile(
55 return model
138 model = self._get_multi_io_model()
139 history = model.fit([self.x, self.x], [self.y, self.y],
151 model = self._get_multi_io_model()
152 eval_result = model.evaluate([self.x, self.x], [self.y, self.y],
164 mse1 = model.evaluate([x, x], [y, y], sample_weight=[w, w], batch_size=5)[3]
165 mse2 = model.evaluate([x, x], [y, y], sample_weight=[w, w]
[all...] |
| /external/glide/library/src/main/java/com/bumptech/glide/load/resource/gif/ |
| GifFrameModelLoader.java | 6 import com.bumptech.glide.load.model.ModelLoader;
11 public DataFetcher<GifDecoder> getResourceFetcher(GifDecoder model, int width, int height) {
12 return new GifFrameDataFetcher(model);
|
| /external/junit/src/main/java/org/junit/internal/runners/statements/ |
| RunAfters.java | 6 import org.junit.runners.model.FrameworkMethod;
7 import org.junit.runners.model.MultipleFailureException;
8 import org.junit.runners.model.Statement;
|
| /external/tensorflow/tensorflow/examples/saved_model/integration_tests/ |
| use_text_rnn_model.py | 15 """Load and use RNN model stored as a SavedModel."""
37 model = tf.saved_model.load(FLAGS.model_dir)
38 model.train(tf.constant(sentences))
39 decoded = model.decode_greedy(
|
| /external/tensorflow/tensorflow/lite/examples/minimal/ |
| minimal.cc | 18 #include "tensorflow/lite/model.h"
21 // This is an example that is minimal to read a model
29 // Usage: minimal <tflite model>
41 fprintf(stderr, "minimal <tflite model>\n");
46 // Load model
47 std::unique_ptr<tflite::FlatBufferModel> model = local
49 TFLITE_MINIMAL_CHECK(model != nullptr);
53 InterpreterBuilder builder(*model, resolver);
|
| /external/tensorflow/tensorflow/lite/tools/ |
| gen_op_registration.cc | 19 #include "tensorflow/lite/model.h"
31 void ReadOpsFromModel(const ::tflite::Model* model,
34 if (!model) return;
35 auto opcodes = model->operator_codes();
|
| /external/testng/src/main/java/org/testng/mustache/ |
| Mustache.java | 12 return run(template, new Model(m));
15 String run(String template, Model model) throws IOException {
43 Value value = model.resolveValue(conditionalVariable);
54 model.push(conditionalVariable, o);
55 String r = new Mustache().run(subTemplate, model);
56 model.popSubModel();
57 chunks.add(new StringChunk(model, r));
63 model.push(conditionalVariable, v);
64 String r = new Mustache().run(subTemplate, model);
[all...] |
| /external/u-boot/board/gateworks/gw_ventana/ |
| eeprom.c | 47 if (info->model[0] != 'G' || info->model[1] != 'W') {
48 puts("EEPROM: Invalid Model in EEPROM\n");
62 baseboard = info->model[3];
63 if (strncasecmp((const char *)info->model, "GW5400-A", 8) == 0)
84 if (info->model[4] == '1') {
87 } else if (info->model[4] == '2') {
90 } else if (info->model[4] == '3') {
96 if (info->model[4] == '0')
100 if (info->model[4] == '0' && info->model[5] == '3'
[all...] |
| /external/dagger2/compiler/src/main/java/dagger/internal/codegen/ |
| InjectFieldValidator.java | 21 import javax.lang.model.element.AnnotationMirror;
22 import javax.lang.model.element.Modifier;
23 import javax.lang.model.element.VariableElement;
31 import static javax.lang.model.element.Modifier.FINAL;
32 import static javax.lang.model.element.Modifier.PRIVATE;
33 import static javax.lang.model.element.Modifier.STATIC;
|
| /external/deqp-deps/SPIRV-Tools/source/val/ |
| validate_barriers.cpp | 45 [](SpvExecutionModel model, std::string* message) {
46 if (model != SpvExecutionModelTessellationControl &&
47 model != SpvExecutionModelGLCompute &&
48 model != SpvExecutionModelKernel &&
49 model != SpvExecutionModelTaskNV &&
50 model != SpvExecutionModelMeshNV) {
|
| /external/glide/library/src/main/java/com/bumptech/glide/load/model/file_descriptor/ |
| FileDescriptorUriLoader.java | 1 package com.bumptech.glide.load.model.file_descriptor;
11 import com.bumptech.glide.load.model.GenericLoaderFactory;
12 import com.bumptech.glide.load.model.GlideUrl;
13 import com.bumptech.glide.load.model.ModelLoader;
14 import com.bumptech.glide.load.model.ModelLoaderFactory;
15 import com.bumptech.glide.load.model.UriLoader;
23 * The default factory for {@link com.bumptech.glide.load.model.file_descriptor.FileDescriptorUriLoader}s.
|
| /external/glide/library/src/main/java/com/bumptech/glide/load/model/stream/ |
| StreamUriLoader.java | 1 package com.bumptech.glide.load.model.stream;
10 import com.bumptech.glide.load.model.GenericLoaderFactory;
11 import com.bumptech.glide.load.model.GlideUrl;
12 import com.bumptech.glide.load.model.ModelLoader;
13 import com.bumptech.glide.load.model.ModelLoaderFactory;
14 import com.bumptech.glide.load.model.UriLoader;
26 * THe default factory for {@link com.bumptech.glide.load.model.stream.StreamUriLoader}s.
|
| /external/robolectric-shadows/processor/src/main/java/org/robolectric/annotation/processing/validator/ |
| FoundOnImplementsValidator.java | 4 import javax.lang.model.element.AnnotationMirror;
5 import javax.lang.model.element.Element;
6 import javax.lang.model.element.ExecutableElement;
7 import javax.lang.model.element.TypeElement;
8 import javax.lang.model.element.VariableElement;
9 import javax.lang.model.type.TypeMirror;
|
| /external/swiftshader/third_party/SPIRV-Tools/source/val/ |
| validate_barriers.cpp | 45 [](SpvExecutionModel model, std::string* message) {
46 if (model != SpvExecutionModelTessellationControl &&
47 model != SpvExecutionModelGLCompute &&
48 model != SpvExecutionModelKernel &&
49 model != SpvExecutionModelTaskNV &&
50 model != SpvExecutionModelMeshNV) {
|
| /external/tensorflow/tensorflow/contrib/distribute/python/examples/ |
| keras_model_with_estimator.py | 15 """An example of training tf.keras Model using MirroredStrategy."""
45 # Define a Keras Model.
46 model = tf.keras.Sequential()
47 model.add(tf.keras.layers.Dense(16, activation='relu', input_shape=(10,)))
48 model.add(tf.keras.layers.Dense(1, activation='sigmoid'))
50 # Compile the model.
52 model.compile(loss='binary_crossentropy', optimizer=optimizer)
53 model.summary()
56 # Define a DistributionStrategy and convert the Keras Model to an
63 keras_model=model, config=config, model_dir=model_dir
[all...] |
| /external/tensorflow/tensorflow/contrib/eager/python/examples/revnet/ |
| main.py | 44 model = revnet.RevNet(config=config)
52 optimizer=optimizer, model=model, optimizer_step=global_step)
55 model.call = tfe.defun(model.call)
56 model.compute_gradients = tfe.defun(model.compute_gradients)
57 model.get_moving_stats = tfe.defun(model.get_moving_stats)
58 model.restore_moving_stats = tfe.defun(model.restore_moving_stats
[all...] |
