/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 [all...] |
/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;
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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);
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Program.cpp | 21 void Program::before(Matrix& model, Matrix& view, Matrix& projection) { 25 void Program::after(Matrix& model, Matrix& view, Matrix& projection) {
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Program.h | 25 virtual void before(Matrix& model, Matrix& view, Matrix& projection); 26 virtual void after(Matrix& model, Matrix& view, Matrix& projection);
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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);
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TransformationNode.h | 26 virtual void before(Program& program, Matrix& model, Matrix& view, 28 virtual void after(Program& program, Matrix& model, Matrix& view,
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/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 [all...] |
/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 [all...] |
/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 {
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/external/junit/src/main/java/org/junit/rules/ |
MethodRule.java | 4 import org.junit.runners.model.FrameworkMethod; 5 import org.junit.runners.model.Statement;
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/external/junit-params/src/main/java/junitparams/internal/ |
MethodBlockSupplier.java | 19 import org.junit.runners.model.FrameworkMethod; 20 import org.junit.runners.model.Statement;
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/external/python/cpython3/Lib/xml/parsers/ |
expat.py | 7 sys.modules['xml.parsers.expat.model'] = model
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/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])) [all...] |
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 [all...] |
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) [all...] |
/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) [all...] |
/external/testng/src/main/java/org/testng/mustache/ |
StringChunk.java | 7 public StringChunk(Model model, String string) { 8 super(model);
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VariableChunk.java | 7 public VariableChunk(Model model, String variable) { 8 super(model); 21 return "[VariableChunk " + m_variable + " model:" + m_model + "]";
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/external/u-boot/arch/arm/dts/ |
armada-372x.dtsi | 51 model = "Marvell Armada 3720 SoC";
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armada-8040.dtsi | 54 model = "Marvell Armada 8040";
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at91sam9xe.dtsi | 49 model = "Atmel AT91SAM9XE family SoC";
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imx6ul-isiot-emmc.dts | 49 model = "Engicam Is.IoT MX6UL eMMC Starterkit";
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sun5i-a13-empire-electronix-m712.dts | 49 model = "Empire Electronix M712 tablet";
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sun8i-h3-nanopi-m1-plus.dts | 46 model = "FriendlyArm NanoPi M1 Plus";
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