| /external/junit/src/main/java/org/junit/internal/runners/model/ |
| ReflectiveCallable.java | 1 package org.junit.internal.runners.model;
|
| /external/junit/src/main/java/org/junit/internal/runners/rules/ |
| ValidationError.java | 3 import org.junit.runners.model.FrameworkMember;
|
| /external/junit/src/main/java/org/junit/internal/runners/statements/ |
| Fail.java | 3 import org.junit.runners.model.Statement;
|
| /external/junit/src/main/java/org/junit/rules/ |
| Verifier.java | 4 import org.junit.runners.model.Statement;
|
| /external/junit/src/main/java/org/junit/runners/parameterized/ |
| BlockJUnit4ClassRunnerWithParametersFactory.java | 4 import org.junit.runners.model.InitializationError;
|
| /external/junit-params/src/main/java/junitparams/internal/ |
| DescribableFrameworkMethod.java | 7 import org.junit.runners.model.FrameworkMethod;
|
| /external/libyuv/files/util/ |
| cpuid.c | 28 uint32 family, model, cpu_info[4]; local
46 // CPU Family and Model
48 // 7:4 - Model
51 // 19:16 - Extended Model
55 model = ((cpu_info[0] >> 4) & 0x0f) | ((cpu_info[0] >> 12) & 0xf0);
56 printf("Cpu Family %d (0x%x), Model %d (0x%x)\n", family, family,
57 model, model);
|
| /external/mp4parser/isoparser/src/main/java/com/googlecode/mp4parser/h264/model/ |
| AspectRatio.java | 21 package com.googlecode.mp4parser.h264.model;
|
| ScalingMatrix.java | 21 package com.googlecode.mp4parser.h264.model;
|
| /external/pdfium/fxjs/xfa/ |
| cjx_logpseudomodel.h | 19 explicit CJX_LogPseudoModel(CScript_LogPseudoModel* model);
|
| cjx_signaturepseudomodel.h | 17 explicit CJX_SignaturePseudoModel(CScript_SignaturePseudoModel* model);
|
| /external/protobuf/src/google/protobuf/stubs/ |
| atomicops_internals_x86_gcc.cc | 92 // get feature flags in ecx/edx, and family/model in eax
95 int family = (eax >> 8) & 0xf; // family and model fields
96 int model = (eax >> 4) & 0xf; local
97 if (family == 0xf) { // use extended family and model fields
99 model += ((eax >> 16) & 0xf) << 4;
106 // so we test only for Rev E, which is family 15, model 32..63 inclusive.
109 32 <= model && model <= 63) {
|
| /external/robolectric-shadows/processor/src/main/java/org/robolectric/annotation/processing/validator/ |
| ResetterValidator.java | 6 import javax.lang.model.element.ExecutableElement;
7 import javax.lang.model.element.Modifier;
8 import javax.lang.model.element.TypeElement;
9 import javax.lang.model.element.VariableElement;
|
| /external/tensorflow/tensorflow/lite/toco/ |
| allocate_transient_arrays.h | 18 #include "tensorflow/lite/toco/model.h"
39 void AllocateTransientArrays(Model* model,
|
| /external/tensorflow/tensorflow/lite/toco/graph_transformations/ |
| lstm_utils.h | 22 #include "tensorflow/lite/toco/model.h"
65 void CreateOptionalArray(Model* model, string* input_array_buffer,
69 Buffer<ArrayDataType::kFloat>* CreateFloatArrayBuffer(Model* model,
94 void CopySubArrayToArray(Model* model, string* array_name,
106 bool GetMatchingRnnArray(Model* model, const string& back_edge_source_array,
|
| propagate_default_min_max.cc | 22 #include "tensorflow/lite/toco/model.h"
42 ::tensorflow::Status PropagateDefaultMinMax::Run(Model* model,
46 const auto it = model->operators.begin() + op_index;
52 auto& input_array = model->GetArray(input);
60 auto& output_array = model->GetArray(output);
|
| resolve_constant_transpose.cc | 18 #include "tensorflow/lite/toco/model.h"
29 void Transpose(Model* model, const Array& input_array,
104 ::tensorflow::Status ResolveConstantTranspose::Run(Model* model,
108 auto it = model->operators.begin() + op_index;
117 auto& output_array = model->GetArray(op->outputs[0]);
128 if (!IsConstantParameterArray(*model, op->inputs[0]) ||
129 !IsConstantParameterArray(*model, op->inputs[1])) {
132 const Array& input_array = model->GetArray(op->inputs[0])
[all...] |
| resolve_pad_attributes.cc | 21 #include "tensorflow/lite/toco/model.h"
27 ::tensorflow::Status ResolvePadAttributes::Run(Model* model,
31 const auto pad_it = model->operators.begin() + op_index;
39 if (!IsConstantParameterArray(*model, op->inputs[1]))
42 const auto& array = model->GetArray(op->inputs[1]);
|
| resolve_padv2_attributes.cc | 21 #include "tensorflow/lite/toco/model.h"
27 ::tensorflow::Status ResolvePadV2Attributes::Run(Model* model,
31 const auto pad_it = model->operators.begin() + op_index;
39 if (!IsConstantParameterArray(*model, op->inputs[1]))
42 const auto& array = model->GetArray(op->inputs[1]);
|
| resolve_transpose_attributes.cc | 21 #include "tensorflow/lite/toco/model.h"
27 ::tensorflow::Status ResolveTransposeAttributes::Run(Model* model,
31 const auto op_it = model->operators.begin() + op_index;
39 if (!IsConstantParameterArray(*model, op->inputs[1]))
43 const auto& perm_array = model->GetArray(op->inputs[1]);
|
| /external/tensorflow/tensorflow/lite/tools/optimize/calibration/ |
| calibration_reader.cc | 35 TfLiteStatus CalibrationReader::AddCalibrationToModel(ModelT* model) const {
36 if (!model || model->subgraphs.empty()) {
39 const auto& subgraph = model->subgraphs[0];
|
| calibration_reader.h | 21 #include "tensorflow/lite/model.h"
43 // Annotates the tensors in the given model with statistics captured during
45 virtual TfLiteStatus AddCalibrationToModel(ModelT* model) const;
|
| /external/tensorflow/tensorflow/python/keras/engine/ |
| training_arrays_test.py | 15 """Tests for model.fit calls with a Dataset object passed as validation_data."""
42 # Create a model that learns y=Mx.
44 model = testing_utils.get_model_from_layers(layers, input_shape=(1,))
45 model.compile(loss="mse", optimizer="adam", metrics=["mean_absolute_error"])
50 history = model.fit(x=train_dataset, validation_data=eval_dataset, epochs=2)
51 evaluation = model.evaluate(x=eval_dataset)
55 # of evaluating the model on the same eval dataset.
|
| /external/tensorflow/tensorflow/python/keras/saving/ |
| saved_model.py | 16 """Utility functions to save/load keras Model to/from SavedModel."""
48 def export_saved_model(model,
54 """Exports a `tf.keras.Model` as a Tensorflow SavedModel.
61 To load the model, use the function
66 1. a checkpoint containing the model weights.
69 the model has not been compiled, then only the graph computing predictions
71 3. the model's json config. If the model is subclassed, this will only be
72 included if the model's `get_config()` method is overwritten.
79 # Create a tf.keras model
[all...] |
| /external/turbine/java/com/google/turbine/model/ |
| TurbineConstantTypeKind.java | 17 package com.google.turbine.model;
|
