| /external/tensorflow/tensorflow/lite/ |
| model_flex_test.cc | 15 #include "tensorflow/lite/model.h"
23 // Ensures that a model with TensorFlow ops can be imported as long as the
26 auto model = FlatBufferModel::BuildFromFile( local
28 ASSERT_TRUE(model);
31 ASSERT_EQ(InterpreterBuilder(*model,
|
| /external/tensorflow/tensorflow/lite/toco/graph_transformations/ |
| remove_tensorflow_identity.cc | 22 #include "tensorflow/lite/toco/model.h"
28 ::tensorflow::Status RemoveTensorFlowIdentity::Run(Model* model,
32 const auto passthru_it = model->operators.begin() + op_index;
38 *modified = RemoveTrivialPassthroughOp(this, model, op_index);
|
| resolve_tensorflow_switch.cc | 21 #include "tensorflow/lite/toco/model.h"
27 ::tensorflow::Status ResolveTensorFlowSwitch::Run(Model* model,
31 const auto switch_it = model->operators.begin() + op_index;
42 if (!IsConstantParameterArray(*model, predicate_name)) {
50 const auto& predicate_array = model->GetArray(predicate_name);
76 for (const auto& other_op : model->operators) {
92 for (const auto& other_op : model->operators) {
110 if (!GetOpWithInput(*model, switch_op->outputs[i])) {
111 model->EraseArray(switch_op->outputs[i])
[all...] |
| convert_squeeze_to_reshape.cc | 22 #include "tensorflow/lite/toco/model.h"
33 ::tensorflow::Status ConvertSqueezeToReshape::Run(Model* model,
37 auto squeeze_it = model->operators.begin() + op_index;
45 const auto& input_array = model->GetArray(squeeze_op->inputs[0]);
54 if (!model->HasArray(squeeze_op->outputs[0]) ||
55 !model->GetArray(squeeze_op->outputs[0]).has_shape()) {
61 const auto& output_shape = model->GetArray(squeeze_op->outputs[0]).shape();
71 CreateInt32Array(model, squeeze_op->outputs[0] + "_shape",
80 const auto reshape_it = model->operators.emplace(squeeze_it, reshape_op)
[all...] |
| identify_l2_pool.cc | 21 #include "tensorflow/lite/toco/model.h"
30 Model* model, const Operator* op) {
31 auto it = model->operators.begin();
32 for (; it != model->operators.end(); ++it) {
41 ::tensorflow::Status IdentifyL2Pool::Run(Model* model, std::size_t op_index,
44 const auto sqrt_it = model->operators.begin() + op_index;
56 Operator* prev_to_sqrt_op = GetOpWithOutput(*model, sqrt_op->inputs[0]);
75 square_op = GetOpWithOutput(*model, avpool_op->inputs[0])
[all...] |
| identify_prelu.cc | 21 #include "tensorflow/lite/toco/model.h"
46 ::tensorflow::Status IdentifyPRelu::Run(Model* model, std::size_t op_index,
49 const auto add_op_it = model->operators.begin() + op_index;
57 const auto* relu_input_op = GetOpWithOutput(*model, add_op->inputs[0]);
67 const auto* mul_op = GetOpWithOutput(*model, add_op->inputs[1]);
76 const auto* relu_neg_input_op = GetOpWithOutput(*model, mul_op->inputs[1]);
92 GetOpWithOutput(*model, relu_neg_input_op->inputs[0]);
111 AvailableArrayName(*model, neg_alpha_tensor_name + "_neg");
112 model->GetOrCreateArray(alpha_tensor_name)
[all...] |
| remove_trivial_passthrough.h | 19 #include "tensorflow/lite/toco/model.h"
43 // designated as a global input/output array of the graph, e.g. the model's
45 // specified by the model.
53 Model* model, std::size_t op_index,
|
| propagate_array_data_types.cc | 21 #include "tensorflow/lite/toco/model.h"
27 void SetDataTypeForAllOutputs(Model* model, Operator* op,
30 model->GetArray(output).data_type = data_type;
35 ::tensorflow::Status PropagateArrayDataTypes::Run(Model* model,
39 auto it = model->operators.begin() + op_index;
44 if (!model->IsOptionalArray(input) &&
45 model->GetArray(input).data_type == ArrayDataType::kNone) {
53 old_output_data_types[output] = model->GetArray(output).data_type
[all...] |
| reorder_elementwise_unary.cc | 22 #include "tensorflow/lite/toco/model.h"
67 ::tensorflow::Status ReorderElementwiseUnary::Run(Model* model,
71 const auto element_op_it = model->operators.begin() + op_index;
78 auto it = FindOpWithOutput(*model, intermediate_name);
79 if (it == model->operators.end()) {
90 if (CountOpsWithInput(*model, intermediate_name) != 1) {
96 if (!IsDiscardableArray(*model, intermediate_name)) {
114 if (!IsDiscardableArray(*model, output_name)) {
118 AvailableArrayName(*model, element_op->outputs[0] + "_reorder")
[all...] |
| resolve_constant_pack.cc | 18 #include "tensorflow/lite/toco/model.h"
27 void Pack(Model* model, PackOperator const& op) {
28 auto& output_array = model->GetArray(op.outputs[0]);
41 const auto& input_array = model->GetArray(op.inputs[i]);
52 ::tensorflow::Status ResolveConstantPack::Run(Model* model,
56 auto it = model->operators.begin() + op_index;
65 auto& output_array = model->GetArray(op->outputs[0]);
77 if (!IsConstantParameterArray(*model, input))
[all...] |
| create_im2col_arrays.cc | 22 #include "tensorflow/lite/toco/model.h"
28 bool ProcessConvOperator(Model* model, ConvOperator* op) {
33 const auto& weights_array = model->GetArray(op->inputs[1]);
53 AvailableArrayName(*model, op->inputs[0] + "_im2col");
54 model->GetOrCreateArray(im2col_array_name);
60 bool ProcessTransposeConvOperator(Model* model, TransposeConvOperator* op) {
69 *model, op->inputs[TransposeConvOperator::DATA_INPUT] + "_im2col");
70 model->GetOrCreateArray(im2col_array_name)
[all...] |
| identify_relu1.cc | 21 #include "tensorflow/lite/toco/model.h"
30 Model* model, const Operator* op) {
31 auto it = model->operators.begin();
32 for (; it != model->operators.end(); ++it) {
40 bool CheckArrayIsScalarFloat(Model* model, const std::string& name, float val) {
41 const auto& op_array = model->GetArray(name);
51 int GetSingleScalarInputIndexOfBinaryOp(Model* model, const Operator* op
[all...] |
| /cts/tests/openglperf2/jni/graphics/ |
| SceneGraphNode.cpp | 26 void SceneGraphNode::draw(Program& program, Matrix& model, Matrix& view, Matrix& projection) {
27 before(program, model, view, projection);
29 mChildren[i]->draw(program, model, view, projection);
31 after(program, model, view, projection);
|
| /developers/build/prebuilts/gradle/AutofillFramework/afservice/src/main/java/com/example/android/autofill/service/model/ |
| DalCheck.java | 17 package com.example.android.autofill.service.model;
|
| /developers/samples/android/input/autofill/AutofillFramework/afservice/src/main/java/com/example/android/autofill/service/model/ |
| DalCheck.java | 17 package com.example.android.autofill.service.model;
|
| /external/antlr/gunit/src/main/java/org/antlr/gunit/swingui/model/ |
| ITestCaseInput.java | 28 package org.antlr.gunit.swingui.model;
|
| ITestCaseOutput.java | 33 package org.antlr.gunit.swingui.model;
|
| /external/tensorflow/tensorflow/lite/toco/ |
| dump_graphviz.h | 20 #include "tensorflow/lite/toco/model.h"
24 void DumpGraphviz(const Model& model, string* output_file_contents,
|
| /external/tensorflow/tensorflow/python/keras/ |
| model_subclassing_test.py | 15 """Tests for Model subclassing."""
47 class SimpleTestModel(keras.Model):
71 class SimpleConvTestModel(keras.Model):
87 class MultiIOTestModel(keras.Model):
114 class NestedTestModel1(keras.Model):
115 """A model subclass nested inside a model subclass.
136 # A simple functional-API model (a.k.a. graph network)
141 return keras.Model(inputs, outputs)
144 class NestedTestModel2(keras.Model)
1036 model = TestModel1() variable in class:GraphSpecificModelSubclassingTests.test_updates_and_losses_for_nested_models_in_subclassed_model.TestModel1
1057 model = TestModel2() variable in class:GraphSpecificModelSubclassingTests.test_updates_and_losses_for_nested_models_in_subclassed_model.TestModel2
1081 model = TestModel3() variable in class:GraphSpecificModelSubclassingTests.test_updates_and_losses_for_nested_models_in_subclassed_model.TestModel3
[all...] |
| /frameworks/av/media/libaaudio/tests/ |
| test_clock_model.cpp | 17 // Unit tests for Isochronous Clock Model
41 model.setSampleRate(SAMPLE_RATE);
42 model.setFramesPerBurst(HW_FRAMES_PER_BURST);
56 model.start(startTimeNanos);
64 model.processTimestamp(startPositionFrames, markerTime);
65 ASSERT_EQ(startPositionFrames, model.convertTimeToPosition(markerTime));
81 model.processTimestamp(alignedPosition, currentTimeNanos);
83 ASSERT_EQ(alignedPosition, model.convertTimeToPosition(currentTimeNanos));
87 IsochronousClockModel model; member in class:ClockModelTestFixture
92 ASSERT_EQ(SAMPLE_RATE, model.getSampleRate())
[all...] |
| /external/ImageMagick/www/source/ |
| examples.pl | 8 # Read model & smile image.
16 $model=Image::Magick->new();
17 $x=$model->ReadImage('model.gif');
19 $model->Label('Magick');
20 $model->Set(background=>'white');
34 $example=$model->Clone();
40 $example=$model->Clone();
46 $example=$model->Clone();
52 $example=$model->Clone()
[all...] |
| /external/ImageMagick/Magick++/demo/ |
| demo.cpp | 38 // Read model & smile image.
42 Image model( srcdir + "model.miff" );
43 model.label( "Magick++" );
44 model.borderColor( "black" );
45 model.backgroundColor( "black" );
62 Image example = model;
81 example = model;
93 example = model;
99 example = model;
[all...] |
| /external/tensorflow/tensorflow/lite/toco/graph_transformations/tests/ |
| resolve_constant_concatenation_test.cc | 21 #include "tensorflow/lite/toco/model.h"
106 // Prepare a hypothetical TOCO model with one Concatenation operator in it
109 void PrepareModel(Model* model, int axis) {
124 Array& in_array = model->GetOrCreateArray(concat_input_name);
145 Array& out_array = model->GetOrCreateArray(concatenation_op->outputs[0]);
157 model->operators.push_back(std::unique_ptr<Operator>(concatenation_op));
162 Model model; local
164 PrepareModel(&model, axis)
184 Model model; local
206 Model model; local
[all...] |
| /external/tensorflow/tensorflow/python/keras/saving/ |
| saving_utils.py | 16 """Utils related to keras model saving."""
26 def extract_model_metrics(model):
27 """Convert metrics from a Keras model `compile` API to dictionary.
32 model: A `tf.keras.Model` object.
36 the model does not contain any metrics.
38 if not getattr(model, '_compile_metrics', None):
41 # TODO(psv/kathywu): use this implementation in model to estimator flow.
42 # We are not using model.metrics here because we want to exclude the metrics
44 return {m.name: m for m in model._compile_metric_functions
[all...] |
| /external/python/google-api-python-client/tests/ |
| test_json_model.py | 17 """JSON Model tests
19 Unit tests for the JSON model.
31 import googleapiclient.model
35 from googleapiclient.model import JsonModel
40 class Model(unittest.TestCase):
42 model = JsonModel(data_wrapper=False)
49 headers, unused_params, query, body = model.request(
58 model = JsonModel(data_wrapper=False)
65 headers, unused_params, query, body = model.request(
74 model = JsonModel(data_wrapper=True
[all...] |
