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  /external/tensorflow/tensorflow/python/keras/engine/
training_test.py 63 return keras.models.Model(input_a, [output_a, output_b])
65 def _do_test_compile_with_model_and_single_loss(self, model, loss):
66 model.compile(optimizer='adam', loss=loss)
67 self.assertEqual(model.loss, loss)
71 loss_list = [loss] * len(model.outputs)
73 self.assertEqual(len(model.loss_functions), len(loss_list))
75 self.assertIsInstance(model.loss_functions[i], losses.LossFunctionWrapper)
77 self.assertEqual(model.loss_functions[i].fn, loss_list[i])
78 self.assertAllEqual(model.loss_weights_list, [1.] * len(loss_list))
85 model = testing_utils.get_small_sequential_mlp
821 model = keras.Model(inputs, outputs) variable in class:TrainingTest.test_static_batch_in_input_layer.Counter
828 model = keras.Sequential( variable in class:TrainingTest.test_static_batch_in_input_layer.Counter
2678 model = testing_utils.get_model_from_layers(layers, input_shape=(1,)) variable in class:TestTrainingWithMetrics.test_invalid_metric_tensor.TestLayer
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  /cts/tests/openglperf2/jni/graphics/
MeshNode.h 27 virtual void before(Program& program, Matrix& model, Matrix& view, Matrix& projection) = 0;
28 virtual void after(Program& program, Matrix& model, Matrix& view, Matrix& projection) = 0;
PerspectiveMeshNode.h 28 virtual void before(Program& program, Matrix& model, Matrix& view, Matrix& projection);
29 virtual void after(Program& program, Matrix& model, Matrix& view, Matrix& projection);
Program.cpp 21 void Program::before(Matrix& model, Matrix& view, Matrix& projection) {
25 void Program::after(Matrix& model, Matrix& view, Matrix& projection) {
Program.h 25 virtual void before(Matrix& model, Matrix& view, Matrix& projection);
26 virtual void after(Matrix& model, Matrix& view, Matrix& projection);
TexturedMeshNode.h 28 virtual void before(Program& program, Matrix& model, Matrix& view, Matrix& projection);
29 virtual void after(Program& program, Matrix& model, Matrix& view, Matrix& projection);
TransformationNode.h 26 virtual void before(Program& program, Matrix& model, Matrix& view,
28 virtual void after(Program& program, Matrix& model, Matrix& view,
  /external/glide/library/src/main/java/com/bumptech/glide/load/model/
ModelLoader.java 1 package com.bumptech.glide.load.model;
6 * A factory interface for translating an arbitrarily complex data model into a concrete data type that can be used
7 * by an {@link DataFetcher} to obtain the data for a resource represented by the model.
11 * 1. To translate a specific model into a data type that can be decoded into a resource.
13 * 2. To allow a model to be combined with the dimensions of the view to fetch a resource of a specific size.
23 * @param <T> The type of the model.
30 * Obtains an {@link DataFetcher} that can fetch the data required to decode the resource represented by this model.
34 * Note - If no valid data fetcher can be returned (for example if a model has a null URL), then it is
39 * @param model The model representing the resource
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  /external/glide/library/src/main/java/com/bumptech/glide/request/
RequestListener.java 8 * @param <T> The type of the model being loaded.
15 * for the given model in the given target. It is recommended to create a single instance per activity/fragment
19 * It is safe to reload this or a different model or change what is displayed in the target at this point.
23 * public void onException(Exception e, T model, Target target, boolean isFirstResource) {
25 * Glide.load(model).into(target);
32 * Note - if you want to reload this or any other model after an exception, you will need to include all
37 * @param model The model we were trying to load when the exception occurred.
43 boolean onException(Exception e, T model, Target<R> target, boolean isFirstResource);
50 * @param model The specific model that was used to load the image
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  /external/junit/src/main/java/org/junit/internal/runners/model/
MultipleFailureException.java 1 package org.junit.internal.runners.model;
6 public class MultipleFailureException extends org.junit.runners.model.MultipleFailureException {
  /external/junit/src/main/java/org/junit/rules/
MethodRule.java 4 import org.junit.runners.model.FrameworkMethod;
5 import org.junit.runners.model.Statement;
  /external/junit-params/src/main/java/junitparams/internal/
MethodBlockSupplier.java 19 import org.junit.runners.model.FrameworkMethod;
20 import org.junit.runners.model.Statement;
  /external/python/cpython3/Lib/xml/parsers/
expat.py 7 sys.modules['xml.parsers.expat.model'] = model
  /external/tensorflow/tensorflow/lite/toco/graph_transformations/
remove_trivial_quantized_min_max.cc 23 #include "tensorflow/lite/toco/model.h"
33 bool IsTrivialMinMax(GraphTransformation* transformation, const Model& model,
36 const auto& clamp_value_array = model.GetArray(clamp_value_array_name);
37 if (!IsConstantParameterArray(model, clamp_value_array_name)) {
63 const auto& input_array = model.GetArray(input_array_name);
72 ::tensorflow::Status RemoveTrivialQuantizedMinMax::Run(Model* model,
76 const auto it = model->operators.begin() + op_index;
83 if (IsTrivialMinMax(this, *model, op->type, op->inputs[0], op->inputs[1]))
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reorder_reshape_transpose.cc 22 #include "tensorflow/lite/toco/model.h"
30 bool OperatorReady(const Model& model, const Operator* op) {
31 if (!model.HasArray(op->inputs[0]) || !model.HasArray(op->inputs[1]) ||
32 !model.HasArray(op->outputs[0])) {
36 if (!model.GetArray(op->inputs[0]).has_shape() ||
37 !model.GetArray(op->outputs[0]).has_shape()) {
42 if (!model.GetArray(op->inputs[1]).buffer) {
104 ::tensorflow::Status ReorderReshapeTranspose::Run(Model* model
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resolve_constant_shape_or_rank.cc 16 #include "tensorflow/lite/toco/model.h"
22 ::tensorflow::Status ResolveConstantShapeOrRank::Run(Model* model,
26 const auto it = model->operators.begin() + op_index;
33 auto& output_array = model->GetArray(op->outputs[0]);
39 const auto& input_array = model->GetArray(op->inputs[0]);
65 if (IsDiscardableArray(*model, op->inputs[0]) &&
66 CountOpsWithInput(*model, op->inputs[0]) == 1) {
67 model->EraseArray(op->inputs[0]);
70 model->operators.erase(it)
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  /external/tensorflow/tensorflow/lite/toco/graph_transformations/tests/
resolve_constant_unary_test.cc 21 #include "tensorflow/lite/toco/model.h"
33 Model model; local
34 Array& input0 = model.GetOrCreateArray("input0");
35 Array& input1 = model.GetOrCreateArray("input1");
36 Array& output = model.GetOrCreateArray("output");
52 model.operators.push_back(std::move(sum_op));
54 ASSERT_TRUE(ResolveConstantUnaryOperator().Run(&model, 0, &modified).ok());
55 EXPECT_EQ(model.GetArray("output").GetBuffer<ArrayDataType::kFloat>().data,
57 EXPECT_EQ(model.GetArray("output").shape().dims(), output_shape)
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  /external/testng/src/main/java/org/testng/mustache/
StringChunk.java 7 public StringChunk(Model model, String string) {
8 super(model);
VariableChunk.java 7 public VariableChunk(Model model, String variable) {
8 super(model);
21 return "[VariableChunk " + m_variable + " model:" + m_model + "]";
  /external/u-boot/arch/arm/dts/
armada-372x.dtsi 51 model = "Marvell Armada 3720 SoC";
armada-8040.dtsi 54 model = "Marvell Armada 8040";
at91sam9xe.dtsi 49 model = "Atmel AT91SAM9XE family SoC";
imx6ul-isiot-emmc.dts 49 model = "Engicam Is.IoT MX6UL eMMC Starterkit";
sun5i-a13-empire-electronix-m712.dts 49 model = "Empire Electronix M712 tablet";
sun8i-h3-nanopi-m1-plus.dts 46 model = "FriendlyArm NanoPi M1 Plus";

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