| /packages/apps/Dialer/java/com/android/dialer/p13n/inference/protocol/ |
| P13nRankerFactory.java | 15 package com.android.dialer.p13n.inference.protocol;
|
| P13nRanker.java | 15 package com.android.dialer.p13n.inference.protocol;
55 * Refreshes ranking cache (pulls fresh contextual features, pre-caches inference results, etc.).
|
| /external/apache-commons-math/src/main/java/org/apache/commons/math/stat/inference/ |
| OneWayAnova.java | 17 package org.apache.commons.math.stat.inference;
28 * the {@link org.apache.commons.math.stat.inference.TTest}.
|
| UnknownDistributionChiSquareTest.java | 17 package org.apache.commons.math.stat.inference;
|
| ChiSquareTest.java | 17 package org.apache.commons.math.stat.inference;
|
| TTest.java | 17 package org.apache.commons.math.stat.inference;
[all...] |
| OneWayAnovaImpl.java | 17 package org.apache.commons.math.stat.inference;
|
| TestUtils.java | 17 package org.apache.commons.math.stat.inference;
24 * A collection of static methods to create inference test instances or to
25 * perform inference tests.
156 * @see org.apache.commons.math.stat.inference.TTest#homoscedasticT(double[], double[])
164 * @see org.apache.commons.math.stat.inference.TTest#homoscedasticT(org.apache.commons.math.stat.descriptive.StatisticalSummary, org.apache.commons.math.stat.descriptive.StatisticalSummary)
173 * @see org.apache.commons.math.stat.inference.TTest#homoscedasticTTest(double[], double[], double)
182 * @see org.apache.commons.math.stat.inference.TTest#homoscedasticTTest(double[], double[])
190 * @see org.apache.commons.math.stat.inference.TTest#homoscedasticTTest(org.apache.commons.math.stat.descriptive.StatisticalSummary, org.apache.commons.math.stat.descriptive.StatisticalSummary)
199 * @see org.apache.commons.math.stat.inference.TTest#pairedT(double[], double[])
207 * @see org.apache.commons.math.stat.inference.TTest#pairedTTest(double[], double[], double
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| ChiSquareTestImpl.java | 17 package org.apache.commons.math.stat.inference;
34 /** Distribution used to compute inference statistics. */
46 * inference statistics.
47 * @param x distribution used to compute inference statistics.
415 * Modify the distribution used to compute inference statistics.
|
| TTestImpl.java | 17 package org.apache.commons.math.stat.inference;
38 /** Distribution used to compute inference statistics.
53 * inference statistics.
54 * @param t distribution used to compute inference statistics.
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| /packages/apps/Dialer/java/com/android/dialer/p13n/inference/ |
| P13nRanking.java | 17 package com.android.dialer.p13n.inference;
26 import com.android.dialer.p13n.inference.protocol.P13nRanker;
27 import com.android.dialer.p13n.inference.protocol.P13nRankerFactory;
|
| /external/desugar/test/java/com/google/devtools/build/android/desugar/ |
| ByteCodeTypePrinter.java | 88 BytecodeTypeInference inference = new BytecodeTypeInference(access, internalName, name, desc); local
89 mv = new MethodIrTypeDumper(mv, inference, printWriter);
90 inference.setDelegateMethodVisitor(mv);
91 // Let the type inference runs first.
92 return inference;
109 private final BytecodeTypeInference inference; field in class:ByteCodeTypePrinter.MethodIrTypeDumper
114 MethodVisitor visitor, BytecodeTypeInference inference, PrintWriter printWriter) {
116 this.inference = inference;
121 printer.print(" |__STACK: " + inference.getOperandStackAsString() + "\n")
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| /external/desugar/java/com/google/devtools/build/android/desugar/ |
| TryWithResourcesRewriter.java | 203 BytecodeTypeInference inference = null; local
210 inference = new BytecodeTypeInference(access, internalName, name, desc);
211 inference.setDelegateMethodVisitor(visitor);
212 visitor = inference;
216 new TryWithResourceVisitor(internalName, name + desc, visitor, classLoader, inference);
288 + "but the type inference is null.",
|
| /external/tensorflow/tensorflow/examples/tutorials/mnist/ |
| mnist.py | 18 Implements the inference/loss/training pattern for model building.
20 1. inference() - Builds the model as far as required for running the network
22 2. loss() - Adds to the inference model the layers required to generate loss.
45 def inference(images, hidden1_units, hidden2_units): function
46 """Build the MNIST model up to where it may be used for inference.
|
| fully_connected_feed.py | 128 # Build a Graph that computes predictions from the inference model.
129 logits = mnist.inference(images_placeholder,
|
| /external/icu/icu4c/source/samples/ufortune/resources/ |
| fortune_resources.mak | 37 # File name extensions for inference rule matching.
44 # Inference rule, for compiling a .txt file into a .res file.
|
| /external/tensorflow/tensorflow/contrib/factorization/examples/ |
| mnist.py | 121 def inference(inp, num_clusters, hidden1_units, hidden2_units): function
122 """Build the MNIST model up to where it may be used for inference.
195 # Build a Graph that computes predictions from the inference model.
196 logits, clustering_loss, kmeans_init, kmeans_training_op = inference(
|
| /external/tensorflow/tensorflow/contrib/model_pruning/examples/cifar10/ |
| cifar10_eval.py | 112 # inference model.
113 logits = cifar10.inference(images)
|
| cifar10_train.py | 64 # inference model.
65 logits = cifar10.inference(images)
|
| cifar10_pruning.py | 23 # Compute inference on the model inputs to make a prediction.
24 predictions = inference(inputs)
170 def inference(images): function
278 logits: Logits from inference().
|
| /external/tensorflow/tensorflow/examples/how_tos/reading_data/ |
| fully_connected_preloaded.py | 66 # Build a Graph that computes predictions from the inference model.
67 logits = mnist.inference(images, FLAGS.hidden1, FLAGS.hidden2)
|
| fully_connected_preloaded_var.py | 72 # Build a Graph that computes predictions from the inference model.
73 logits = mnist.inference(images, FLAGS.hidden1, FLAGS.hidden2)
|
| fully_connected_reader.py | 136 # Build a Graph that computes predictions from the inference model.
137 logits = mnist.inference(image_batch, FLAGS.hidden1, FLAGS.hidden2)
|
| /external/protobuf/js/ |
| debug.js | 85 var message = thing; // Copy because we don't want type inference on thing.
|
| /external/tensorflow/tensorflow/compiler/xla/tools/parser/ |
| hlo_parser_test.cc | 552 // batch norm inference
563 ROOT %batch-norm-inference = f32[2,2,2,2]{3,2,1,0} batch-norm-inference(f32[2,2,2,2]{3,2,1,0} %input, f32[2]{0} %offset, f32[2]{0} %scale, f32[2]{0} %mean, f32[2]{0} %variance), epsilon=0.001, feature_index=0
[all...] |
