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/aosp_15_r20/external/tensorflow/tensorflow/lite/testing/nnapi_tflite_zip_tests/
H A Dnot_supported.txt157 mean/mean_axis=0,const_axis=True,input_dtype=tf.float32,input_shape=[3,3,2,4],keepdims=True
158 mean/mean_axis=0,const_axis=True,input_dtype=tf.float32,input_shape=[3,3,2,4],keepdims=False
159 mean/mean_axis=0,const_axis=False,input_dtype=tf.float32,input_shape=[3,3,2,4],keepdims=True
160 mean/mean_axis=0,const_axis=False,input_dtype=tf.float32,input_shape=[3,3,2,4],keepdims=False
161 mean/mean_axis=0,const_axis=True,input_dtype=tf.int32,input_shape=[3,3,2,4],keepdims=True
162 mean/mean_axis=0,const_axis=True,input_dtype=tf.int32,input_shape=[3,3,2,4],keepdims=False
163 mean/mean_axis=0,const_axis=False,input_dtype=tf.int32,input_shape=[3,3,2,4],keepdims=True
164 mean/mean_axis=0,const_axis=False,input_dtype=tf.int32,input_shape=[3,3,2,4],keepdims=False
165 mean/mean_axis=0,const_axis=True,input_dtype=tf.int64,input_shape=[3,3,2,4],keepdims=True
166 mean/mean_axis=0,const_axis=True,input_dtype=tf.int64,input_shape=[3,3,2,4],keepdims=False
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/aosp_15_r20/external/tensorflow/tensorflow/python/framework/testdata/
H A Dmetrics_export_meta_graph.pb764 name: "mean/total/Initializer/zeros"
770 s: "loc:@mean/total"
802 name: "mean/total"
809 s: "loc:@mean/total"
849 name: "mean/total/Assign"
851 input: "mean/total"
852 input: "mean/total/Initializer/zeros"
864 s: "loc:@mean/total"
891 name: "mean/total/read"
893 input: "mean/total"
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/aosp_15_r20/external/guava/android/guava/src/com/google/common/math/
H A DStats.java38 * A bundle of statistical summary values -- sum, count, mean/average, min and max, and several
52 * calculate <i>only</i> the mean.
67 private final double mean; field in Stats
79 * <li>If {@code count} is 0, {@code mean} may have any finite value (its only usage will be to
86 Stats(long count, double mean, double sumOfSquaresOfDeltas, double min, double max) { in Stats() argument
88 this.mean = mean; in Stats()
159 * Returns the <a href="http://en.wikipedia.org/wiki/Arithmetic_mean">arithmetic mean</a> of the
163 * the arithmetic mean of the population.
174 * <p>If you only want to calculate the mean, use {@link #meanOf} instead of creating a {@link
179 public double mean() { in mean() method in Stats
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H A DStatsAccumulator.java43 private double mean = 0.0; // any finite value will do, we only use it to multiply by zero for sum field in StatsAccumulator
52 mean = value; in add()
60 if (isFinite(value) && isFinite(mean)) { in add()
62 double delta = value - mean; in add()
63 mean += delta / count; in add()
64 sumOfSquaresOfDeltas += delta * (value - mean); in add()
66 mean = calculateNewMeanNonFinite(mean, value); in add()
140 merge(values.count(), values.mean(), values.sumOfSquaresOfDeltas(), values.min(), values.max()); in addAll()
153 merge(values.count(), values.mean(), values.sumOfSquaresOfDeltas(), values.min(), values.max()); in addAll()
164 mean = otherMean; in merge()
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/aosp_15_r20/external/apache-commons-math/src/main/java/org/apache/commons/math/distribution/
H A DExponentialDistributionImpl.java43 /** The mean of this distribution. */
44 private double mean; field in ExponentialDistributionImpl
50 * Create a exponential distribution with the given mean.
51 * @param mean mean of this distribution.
53 public ExponentialDistributionImpl(double mean) { in ExponentialDistributionImpl() argument
54 this(mean, DEFAULT_INVERSE_ABSOLUTE_ACCURACY); in ExponentialDistributionImpl()
58 * Create a exponential distribution with the given mean.
59 * @param mean mean of this distribution.
64 public ExponentialDistributionImpl(double mean, double inverseCumAccuracy) { in ExponentialDistributionImpl() argument
66 setMeanInternal(mean); in ExponentialDistributionImpl()
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H A DPoissonDistributionImpl.java55 * Holds the Poisson mean for the distribution.
57 private double mean; field in PoissonDistributionImpl
73 * Create a new Poisson distribution with the given the mean. The mean value
76 * @param p the Poisson mean
84 * Create a new Poisson distribution with the given mean, convergence criterion
87 * @param p the Poisson mean
99 * Create a new Poisson distribution with the given mean and convergence criterion.
101 * @param p the Poisson mean
111 * Create a new Poisson distribution with the given mean and maximum number of iterations.
113 * @param p the Poisson mean
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/aosp_15_r20/external/aws-sdk-java-v2/test/sdk-benchmarks/src/main/resources/software/amazon/awssdk/benchmark/
H A Dbaseline.json13 "mean": 11083.712145086858, number
33 "mean": 3133.078992847664, number
53 "mean": 9400.788325804802, number
73 "mean": 10081.234880927226, number
93 "mean": 2318.064309904416, number
113 "mean": 2668.2980888540214, number
133 "mean": 6452.047990499835, number
153 "mean": 7299.549654768969, number
173 "mean": 2253.2698214846414, number
193 "mean": 2349.62389971199, number
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/aosp_15_r20/frameworks/base/core/java/com/android/internal/ml/clustering/
H A DKMeans.java63 public List<Mean> predict(final int k, final float[][] inputData) { in predict()
67 final ArrayList<Mean> means = new ArrayList<>(); in predict()
69 Mean m = new Mean(dimension); in predict()
97 public static double score(@NonNull List<Mean> means) { in score()
101 Mean mean = means.get(i); in score() local
103 Mean compareTo = means.get(j); in score()
104 if (mean == compareTo) { in score()
107 double distance = Math.sqrt(sqDistance(mean.mCentroid, compareTo.mCentroid)); in score()
140 private boolean step(final ArrayList<Mean> means, final float[][] inputData) { in step()
143 // which point belongs to each mean again. in step()
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/aosp_15_r20/external/tensorflow/tensorflow/lite/delegates/gpu/common/tasks/
H A Dmean_stddev_normalization_test_util.cc30 // Parameterized test: mean, difference, tolerance.
31 // Input is constructed as [mean-2*diff, mean-diff, mean+diff, mean+2*diff]
32 absl::Status MeanStddevNormSeparateBatchesTest(float mean, float diff, in MeanStddevNormSeparateBatchesTest() argument
37 src_tensor.data = {mean - 2 * diff, mean - diff, mean + diff, in MeanStddevNormSeparateBatchesTest()
38 mean + 2 * diff, mean - 2 * diff, mean - diff, in MeanStddevNormSeparateBatchesTest()
39 mean + diff, mean + 2 * diff}; in MeanStddevNormSeparateBatchesTest()
89 0.0f, 0.0f, 0.0f, 0.0f, // zero mean, zero variance in MeanStddevNormalizationAllBatchesTest()
90 -0.02f, -0.01f, 0.01f, 0.02f, // zero mean, small variance in MeanStddevNormalizationAllBatchesTest()
91 -200.0f, -100.0f, 100.0f, 200.0f, // zero mean, large variance in MeanStddevNormalizationAllBatchesTest()
92 0.01f, 0.01f, 0.01f, 0.01f, // small mean, zero variance in MeanStddevNormalizationAllBatchesTest()
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/aosp_15_r20/external/apache-commons-math/src/main/java/org/apache/commons/math3/distribution/
H A DExponentialDistribution.java59 /** The mean of this distribution. */
60 private final double mean; field in ExponentialDistribution
62 /** The logarithm of the mean, stored to reduce computing time. * */
92 * Create an exponential distribution with the given mean.
100 * @param mean mean of this distribution.
102 public ExponentialDistribution(double mean) { in ExponentialDistribution() argument
103 this(mean, DEFAULT_INVERSE_ABSOLUTE_ACCURACY); in ExponentialDistribution()
107 * Create an exponential distribution with the given mean.
115 * @param mean Mean of this distribution.
118 * @throws NotStrictlyPositiveException if {@code mean <= 0}.
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H A DNormalDistribution.java51 /** Mean of this distribution. */
52 private final double mean; field in NormalDistribution
64 * Create a normal distribution with mean equal to zero and standard deviation equal to one.
77 * Create a normal distribution using the given mean and standard deviation.
85 * @param mean Mean for this distribution.
89 public NormalDistribution(double mean, double sd) throws NotStrictlyPositiveException { in NormalDistribution() argument
90 this(mean, sd, DEFAULT_INVERSE_ABSOLUTE_ACCURACY); in NormalDistribution()
94 * Create a normal distribution using the given mean, standard deviation and inverse cumulative
103 * @param mean Mean for this distribution.
109 public NormalDistribution(double mean, double sd, double inverseCumAccuracy) in NormalDistribution() argument
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/aosp_15_r20/external/guava/guava/src/com/google/common/math/
H A DStats.java42 * A bundle of statistical summary values -- sum, count, mean/average, min and max, and several
56 * calculate <i>only</i> the mean.
71 private final double mean; field in Stats
83 * <li>If {@code count} is 0, {@code mean} may have any finite value (its only usage will be to
90 Stats(long count, double mean, double sumOfSquaresOfDeltas, double min, double max) { in Stats() argument
92 this.mean = mean; in Stats()
235 * Returns the <a href="http://en.wikipedia.org/wiki/Arithmetic_mean">arithmetic mean</a> of the
239 * the arithmetic mean of the population.
250 * <p>If you only want to calculate the mean, use {@link #meanOf} instead of creating a {@link
255 public double mean() { in mean() method
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/aosp_15_r20/external/tflite-support/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/ops/
H A DNormalizeOp.java26 * Normalizes a {@link TensorBuffer} with given mean and stddev: output = (input - mean) / stddev.
30 // mean.length should always be equal to stddev.length and always >= 1.
31 private final float[] mean; field in NormalizeOp
41 * output = (input - mean) / stddev
44 * <p>In the following two cases, reset {@code mean} to 0 and {@code stddev} to 1 to bypass the
46 * 1. Both {@code mean} and {code stddev} are 0. <br>
47 * 2. {@code mean} is 0 and {stddev} is Infinity.
49 * <p>Note: If {@code mean} is set to 0 and {@code stddev} is set to 1, no computation will
53 * present, except when the input is a {@link DataType#UINT8} tensor, {@code mean} is set to 0 and
56 * @param mean the mean value to be subtracted first.
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/aosp_15_r20/external/clang/test/SemaCXX/
H A Dtypo-correction.cpp4 int a(-rsing[2]); // expected-error {{undeclared identifier 'rsing'; did you mean 'using'?}}
46 … 'basetype' does not name a non-static data member or base class; did you mean the base class 'Bas… in Derived()
52 …return st->Base_Type; // expected-error{{no member named 'Base_Type' in 'Derived'; did you mean 'b… in get_type()
58 somename Foo; // expected-error {{unknown type name 'somename'; did you mean 'some_name'?}}
60 using namespace somename; // expected-error {{no namespace named 'somename'; did you mean 'SomeName…
72 …error{{field designator 'fielda' does not refer to any field in type 'st'; did you mean 'FieldA'?}}
81 …ng str; // expected-error{{use of undeclared identifier 'another_std'; did you mean 'AnotherStd'?}}
82 another_str *cstr = new AnotherStr; // expected-error{{unknown type name 'AnotherStr'; did you mean…
88 …cted-error{{'TyreNames' does not refer to the name of a parameter pack; did you mean 'TypeNames'?}}
96 …ted-error{{no type named 'stream_out' in namespace 'unknown_type_test'; did you mean 'StreamOut'?}}
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/aosp_15_r20/external/guava/android/guava-tests/benchmark/com/google/common/math/
H A DStatsBenchmark.java27 * Benchmarks for various algorithms for computing the mean and/or variance.
36 double mean(double[] values) { in mean() method
46 double mean(double[] values) { in mean() method
60 double mean(double[] values) { in mean() method
61 double mean = values[0]; in mean() local
63 mean = mean + (values[i] - mean) / (i + 1); in mean()
65 return mean; in mean()
69 abstract double mean(double[] values); in mean() method in StatsBenchmark.MeanAlgorithm
73 private final double mean; field in StatsBenchmark.MeanAndVariance
76 MeanAndVariance(double mean, double variance) { in MeanAndVariance() argument
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/aosp_15_r20/external/guava/guava-tests/benchmark/com/google/common/math/
H A DStatsBenchmark.java27 * Benchmarks for various algorithms for computing the mean and/or variance.
36 double mean(double[] values) { in mean() method
46 double mean(double[] values) { in mean() method
60 double mean(double[] values) { in mean() method
61 double mean = values[0]; in mean() local
63 mean = mean + (values[i] - mean) / (i + 1); in mean()
65 return mean; in mean()
69 abstract double mean(double[] values); in mean() method in StatsBenchmark.MeanAlgorithm
73 private final double mean; field in StatsBenchmark.MeanAndVariance
76 MeanAndVariance(double mean, double variance) { in MeanAndVariance() argument
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/aosp_15_r20/external/pytorch/benchmarks/dynamo/microbenchmarks/
H A Dmatmul_relu.py66 torch mm mean: 0.0592 ms
67 torch mm + relu mean: 0.0759 ms
68 inductor mm mean: 0.0653 ms
70 torch mm mean: 0.0231 ms
71 torch mm + relu mean: 0.0316 ms
72 inductor mm mean: 0.0252 ms
74 torch mm mean: 0.0190 ms
75 torch mm + relu mean: 0.0277 ms
76 inductor mm mean: 0.0274 ms
78 torch mm mean: 0.0188 ms
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/aosp_15_r20/external/pytorch/torch/nn/modules/
H A Dloss.py41 def __init__(self, size_average=None, reduce=None, reduction: str = "mean") -> None:
55 reduction: str = "mean",
63 r"""Creates a criterion that measures the mean absolute error (MAE) between each element in
73 (default ``'mean'``), then:
78 \operatorname{mean}(L), & \text{if reduction} = \text{`mean';}\\
102 ``'none'`` | ``'mean'`` | ``'sum'``. ``'none'``: no reduction will be applied,
103 ``'mean'``: the sum of the output will be divided by the number of
106 specifying either of those two args will override :attr:`reduction`. Default: ``'mean'``
124 def __init__(self, size_average=None, reduce=None, reduction: str = "mean") -> None:
163 (default ``'mean'``), then
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/aosp_15_r20/external/apache-commons-math/src/main/java/org/apache/commons/math3/stat/descriptive/moment/
H A DVariance.java32 * variance = sum((x_i - mean)^2) / (n - 1) </p>
34 * where mean is the {@link Mean} and <code>n</code> is the number
56 * The "population variance" ( sum((x_i - mean)^2) / n ) can also
266 Mean mean = new Mean(); in evaluate() local
267 double m = mean.evaluate(values, begin, length); in evaluate()
282 * where weightedMean is the weighted mean</p>
326 Mean mean = new Mean(); in evaluate() local
327 double m = mean.evaluate(values, weights, begin, length); in evaluate()
341 * where weightedMean is the weighted mean</p>
379 * the input array, using the precomputed mean value. Returns
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/aosp_15_r20/external/apache-commons-math/src/main/java/org/apache/commons/math/stat/descriptive/moment/
H A DVariance.java30 * variance = sum((x_i - mean)^2) / (n - 1) </p>
32 * where mean is the {@link Mean} and <code>n</code> is the number
54 * The "population variance" ( sum((x_i - mean)^2) / n ) can also
252 Mean mean = new Mean(); in evaluate() local
253 double m = mean.evaluate(values, begin, length); in evaluate()
268 * where weightedMean is the weighted mean</p>
312 Mean mean = new Mean(); in evaluate() local
313 double m = mean.evaluate(values, weights, begin, length); in evaluate()
327 * where weightedMean is the weighted mean</p>
364 * the input array, using the precomputed mean value. Returns
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/aosp_15_r20/external/clang/test/FixIt/
H A Dfixit.cpp54 …expected-error{{use of undeclared identifier 'getNumComponenets'; did you mean 'getNumComponents'?… in dump()
75 int x1 &= 0; // expected-error {{invalid '&=' at end of declaration; did you mean '='?}}
76 int x2 *= 0; // expected-error {{invalid '*=' at end of declaration; did you mean '='?}}
77 int x3 += 0; // expected-error {{invalid '+=' at end of declaration; did you mean '='?}}
78 int x4 -= 0; // expected-error {{invalid '-=' at end of declaration; did you mean '='?}}
79 int x5 != 0; // expected-error {{invalid '!=' at end of declaration; did you mean '='?}}
80 int x6 /= 0; // expected-error {{invalid '/=' at end of declaration; did you mean '='?}}
81 int x7 %= 0; // expected-error {{invalid '%=' at end of declaration; did you mean '='?}}
82 int x8 <= 0; // expected-error {{invalid '<=' at end of declaration; did you mean '='?}}
83 int x9 <<= 0; // expected-error {{invalid '<<=' at end of declaration; did you mean '='?}}
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H A Dtypo.cpp24 other_std::strng str1; // expected-error{{use of undeclared identifier 'other_std'; did you mean 'o…
25 // expected-error{{no type named 'strng' in namespace 'otherstd'; did you mean 'string'?}}
26 tring str2; // expected-error{{unknown type name 'tring'; did you mean 'string'?}}
28 … // expected-error{{no member named 'other_std' in the global namespace; did you mean 'otherstd'?}}
32 return radious * pi; // expected-error{{did you mean 'radius'?}} in area()
35 using namespace othestd; // expected-error{{no namespace named 'othestd'; did you mean 'otherstd'?}}
37 …rg; // expected-error{{no namespace named 'blarg' in the global namespace; did you mean 'blargh'?}}
39 namespace wibble = blarg; // expected-error{{no namespace named 'blarg'; did you mean 'blargh'?}}
40 …rg; // expected-error{{no namespace named 'blarg' in the global namespace; did you mean 'blargh'?}}
43 …basc_string<char> b1; // expected-error{{no template named 'basc_string'; did you mean 'basic_stri… in test_string()
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/aosp_15_r20/external/apache-commons-math/src/main/java/org/apache/commons/math/stat/inference/
H A DTTestImpl.java100 * at which one can reject the null hypothesis that the mean of the paired
101 * differences is 0 in favor of the two-sided alternative that the mean paired
137 * mean of the paired differences between <code>sample1</code> and
139 * mean paired difference is not equal to 0, with significance level
177 * This statistic can be used to perform a one sample t-test for the mean.
191 return t(StatUtils.mean(observed), mu, StatUtils.variance(observed), in t()
197 * t statistic </a> to use in comparing the mean of the dataset described by
200 * This statistic can be used to perform a one sample t-test for the mean.
232 * <strong><code> m1</code></strong> is the mean of first sample;
233 * <strong><code> m2</code></strong> is the mean of second sample</li>
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/aosp_15_r20/packages/apps/Dialer/java/com/android/dialer/about/res/raw/
Dthird_party_licenses26 "License" shall mean the terms and conditions for use, reproduction,
29 "Licensor" shall mean the copyright owner or entity authorized by
32 "Legal Entity" shall mean the union of the acting entity and all
40 "You" (or "Your") shall mean an individual or Legal Entity
43 "Source" form shall mean the preferred form for making modifications,
47 "Object" form shall mean any form resulting from mechanical
52 "Work" shall mean the work of authorship, whether in Source or
57 "Derivative Works" shall mean any work, whether in Source or Object
65 "Contribution" shall mean any work of authorship, including
79 "Contributor" shall mean Licensor and any individual or Legal Entity
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/aosp_15_r20/external/apache-commons-math/src/main/java/org/apache/commons/math3/stat/
H A DStatUtils.java29 import org.apache.commons.math3.stat.descriptive.moment.Mean;
65 /** mean */
66 private static final UnivariateStatistic MEAN = new Mean(); field in StatUtils
74 /** geometric mean */
213 * Returns the arithmetic mean of the entries in the input array, or <code>Double.NaN</code> if
218 * <p>See {@link org.apache.commons.math3.stat.descriptive.moment.Mean} for details on the
222 * @return the mean of the values or Double.NaN if the array is empty
225 public static double mean(final double[] values) throws MathIllegalArgumentException { in mean() method in StatUtils
226 return MEAN.evaluate(values); in mean()
230 * Returns the arithmetic mean of the entries in the specified portion of the input array, or
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