| /external/tensorflow/tensorflow/lite/testing/nnapi_tflite_zip_tests/ |
| D | not_supported.txt | 157 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
[all …]
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| /external/igt-gpu-tools/tests/ |
| D | kms_sysfs_edid_timing.c | 49 struct igt_mean mean = {}; variable
63 igt_mean_init(&mean);
73 igt_mean_add(&mean, igt_nsec_elapsed(&ts));
81 mean.max, mean.max / 1e3, mean.max / 1e6,
82 mean.mean, mean.mean / 1e3, mean.mean / 1e6);
84 if (mean.max > (THRESHOLD_PER_CONNECTOR * 1e6)) {
87 mean.max / 1e6, mean.mean / 1e6);
89 igt_assert_f(mean.mean < (THRESHOLD_TOTAL * 1e6),
92 mean.max / 1e6, mean.mean / 1e6);
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| /external/guava/guava-tests/benchmark/com/google/common/math/ |
| D | StatsBenchmark.java | 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
77 this.mean = mean; in MeanAndVariance()
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| /external/guava/android/guava-tests/benchmark/com/google/common/math/ |
| D | StatsBenchmark.java | 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
77 this.mean = mean; in MeanAndVariance()
[all …]
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| /external/guava/android/guava/src/com/google/common/math/ |
| D | Stats.java | 67 private final double mean; field in Stats
86 Stats(long count, double mean, double sumOfSquaresOfDeltas, double min, double max) { in Stats() argument
88 this.mean = mean; in Stats()
179 public double mean() { in mean() method in Stats
181 return mean; in mean()
197 return mean * count; in sum()
353 && doubleToLongBits(mean) == doubleToLongBits(other.mean) in equals()
367 return Objects.hashCode(count, mean, sumOfSquaresOfDeltas, min, max); in hashCode()
375 .add("mean", mean) in toString()
416 double mean = values.next().doubleValue(); in meanOf() local
[all …]
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| D | StatsAccumulator.java | 43 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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| /external/guava/guava/src/com/google/common/math/ |
| D | Stats.java | 71 private final double mean; field in Stats
90 Stats(long count, double mean, double sumOfSquaresOfDeltas, double min, double max) { in Stats() argument
92 this.mean = mean; in Stats()
255 public double mean() { in mean() method
257 return mean; in mean()
273 return mean * count; in sum()
429 && doubleToLongBits(mean) == doubleToLongBits(other.mean) in equals()
443 return Objects.hashCode(count, mean, sumOfSquaresOfDeltas, min, max); in hashCode()
451 .add("mean", mean) in toString()
492 double mean = values.next().doubleValue(); in meanOf() local
[all …]
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| D | StatsAccumulator.java | 46 private double mean = 0.0; // any finite value will do, we only use it to multiply by zero for sum field in StatsAccumulator
55 mean = value; in add()
63 if (isFinite(value) && isFinite(mean)) { in add()
65 double delta = value - mean; in add()
66 mean += delta / count; in add()
67 sumOfSquaresOfDeltas += delta * (value - mean); in add()
69 mean = calculateNewMeanNonFinite(mean, value); in add()
174 merge(values.count(), values.mean(), values.sumOfSquaresOfDeltas(), values.min(), values.max()); in addAll()
187 merge(values.count(), values.mean(), values.sumOfSquaresOfDeltas(), values.min(), values.max()); in addAll()
198 mean = otherMean; in merge()
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| /external/apache-commons-math/src/main/java/org/apache/commons/math/distribution/ |
| D | ExponentialDistributionImpl.java | 44 private double mean; field in ExponentialDistributionImpl
53 public ExponentialDistributionImpl(double mean) { in ExponentialDistributionImpl() argument
54 this(mean, DEFAULT_INVERSE_ABSOLUTE_ACCURACY); in ExponentialDistributionImpl()
64 public ExponentialDistributionImpl(double mean, double inverseCumAccuracy) { in ExponentialDistributionImpl() argument
66 setMeanInternal(mean); in ExponentialDistributionImpl()
77 public void setMean(double mean) { in setMean() argument
78 setMeanInternal(mean); in setMean()
90 this.mean = newMean; in setMeanInternal()
98 return mean; in getMean()
125 return FastMath.exp(-x / mean) / mean; in density()
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| D | NormalDistributionImpl.java | 50 private double mean = 0; field in NormalDistributionImpl
63 public NormalDistributionImpl(double mean, double sd){ in NormalDistributionImpl() argument
64 this(mean, sd, DEFAULT_INVERSE_ABSOLUTE_ACCURACY); in NormalDistributionImpl()
76 public NormalDistributionImpl(double mean, double sd, double inverseCumAccuracy) { in NormalDistributionImpl() argument
78 setMeanInternal(mean); in NormalDistributionImpl()
96 return mean; in getMean()
105 public void setMean(double mean) { in setMean() argument
106 setMeanInternal(mean); in setMean()
114 this.mean = newMean; in setMeanInternal()
171 double x0 = x - mean; in density()
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| /external/apache-commons-math/src/main/java/org/apache/commons/math3/distribution/ |
| D | ExponentialDistribution.java | 60 private final double mean; field in ExponentialDistribution
102 public ExponentialDistribution(double mean) { in ExponentialDistribution() argument
103 this(mean, DEFAULT_INVERSE_ABSOLUTE_ACCURACY); in ExponentialDistribution()
121 public ExponentialDistribution(double mean, double inverseCumAccuracy) { in ExponentialDistribution() argument
122 this(new Well19937c(), mean, inverseCumAccuracy); in ExponentialDistribution()
133 public ExponentialDistribution(RandomGenerator rng, double mean) in ExponentialDistribution() argument
135 this(rng, mean, DEFAULT_INVERSE_ABSOLUTE_ACCURACY); in ExponentialDistribution()
148 public ExponentialDistribution(RandomGenerator rng, double mean, double inverseCumAccuracy) in ExponentialDistribution() argument
152 if (mean <= 0) { in ExponentialDistribution()
153 throw new NotStrictlyPositiveException(LocalizedFormats.MEAN, mean); in ExponentialDistribution()
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| D | NormalDistribution.java | 52 private final double mean; field in NormalDistribution
89 public NormalDistribution(double mean, double sd) throws NotStrictlyPositiveException { in NormalDistribution() argument
90 this(mean, sd, DEFAULT_INVERSE_ABSOLUTE_ACCURACY); in NormalDistribution()
109 public NormalDistribution(double mean, double sd, double inverseCumAccuracy) in NormalDistribution() argument
111 this(new Well19937c(), mean, sd, inverseCumAccuracy); in NormalDistribution()
123 public NormalDistribution(RandomGenerator rng, double mean, double sd) in NormalDistribution() argument
125 this(rng, mean, sd, DEFAULT_INVERSE_ABSOLUTE_ACCURACY); in NormalDistribution()
139 RandomGenerator rng, double mean, double sd, double inverseCumAccuracy) in NormalDistribution() argument
147 this.mean = mean; in NormalDistribution()
159 return mean; in getMean()
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| /external/tflite-support/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/ops/ |
| D | NormalizeOp.java | 31 private final float[] mean; field in NormalizeOp
60 public NormalizeOp(float mean, float stddev) { in NormalizeOp() argument
69 if (mean == 0.0f && (stddev == 0.0f || Float.isInfinite(stddev))) { in NormalizeOp()
75 if (mean == 0.0f && stddev == 1.0f) { in NormalizeOp()
80 this.mean = new float[] {mean}; in NormalizeOp()
106 public NormalizeOp(@NonNull float[] mean, @NonNull float[] stddev) { in NormalizeOp() argument
107 SupportPreconditions.checkNotNull(mean, "Mean cannot be null"); in NormalizeOp()
110 mean.length == stddev.length, in NormalizeOp()
112 SupportPreconditions.checkArgument(mean.length > 0, "Means and stddevs are empty."); in NormalizeOp()
113 this.mean = mean.clone(); in NormalizeOp()
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| /external/tensorflow/tensorflow/python/framework/testdata/ |
| D | metrics_export_meta_graph.pb | 764 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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| /external/rust/android-crates-io/crates/criterion/src/ |
| D | estimate.rs | 65 mean: to_estimate(points.mean, &distributions.mean), in build_estimates()
93 mean: to_estimate(points.mean, &distributions.mean), in build_change_estimates()
99 pub mean: f64, field
107 pub mean: Estimate, field
115 self.slope.as_ref().unwrap_or(&self.mean) in typical()
119 Statistic::Mean => Some(&self.mean), in get()
130 pub mean: Distribution<f64>, field
138 self.slope.as_ref().unwrap_or(&self.mean) in typical()
142 Statistic::Mean => Some(&self.mean), in get()
153 pub mean: f64, field
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| /external/apache-commons-math/src/main/java/org/apache/commons/math3/random/ |
| D | UncorrelatedRandomVectorGenerator.java | 37 private final double[] mean; field in UncorrelatedRandomVectorGenerator
53 double[] mean, double[] standardDeviation, NormalizedRandomGenerator generator) { in UncorrelatedRandomVectorGenerator() argument
54 if (mean.length != standardDeviation.length) { in UncorrelatedRandomVectorGenerator()
55 throw new DimensionMismatchException(mean.length, standardDeviation.length); in UncorrelatedRandomVectorGenerator()
57 this.mean = mean.clone(); in UncorrelatedRandomVectorGenerator()
71 mean = new double[dimension]; in UncorrelatedRandomVectorGenerator()
84 double[] random = new double[mean.length]; in nextVector()
86 random[i] = mean[i] + standardDeviation[i] * generator.nextNormalizedDouble(); in nextVector()
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| D | CorrelatedRandomVectorGenerator.java | 55 private final double[] mean; field in CorrelatedRandomVectorGenerator
79 double[] mean, in CorrelatedRandomVectorGenerator() argument
84 if (mean.length != order) { in CorrelatedRandomVectorGenerator()
85 throw new DimensionMismatchException(mean.length, order); in CorrelatedRandomVectorGenerator()
87 this.mean = mean.clone(); in CorrelatedRandomVectorGenerator()
110 mean = new double[order]; in CorrelatedRandomVectorGenerator()
112 mean[i] = 0; in CorrelatedRandomVectorGenerator()
168 double[] correlated = new double[mean.length]; in nextVector()
170 correlated[i] = mean[i]; in nextVector()
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| /external/apache-commons-math/src/main/java/org/apache/commons/math/random/ |
| D | UncorrelatedRandomVectorGenerator.java | 40 private final double[] mean; field in UncorrelatedRandomVectorGenerator
53 public UncorrelatedRandomVectorGenerator(double[] mean, in UncorrelatedRandomVectorGenerator() argument
56 if (mean.length != standardDeviation.length) { in UncorrelatedRandomVectorGenerator()
57 throw new DimensionMismatchException(mean.length, standardDeviation.length); in UncorrelatedRandomVectorGenerator()
59 this.mean = mean.clone(); in UncorrelatedRandomVectorGenerator()
73 mean = new double[dimension]; in UncorrelatedRandomVectorGenerator()
84 double[] random = new double[mean.length]; in nextVector()
86 random[i] = mean[i] + standardDeviation[i] * generator.nextNormalizedDouble(); in nextVector()
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| /external/pigweed/pw_allocator/benchmarks/ |
| D | measurements.cc | 32 float mean = nanoseconds_.value(); in Update() local
33 mean += (data.nanoseconds - mean) / count_; in Update()
34 nanoseconds_.Set(mean); in Update()
36 mean = fragmentation_.value(); in Update()
37 mean += (data.fragmentation - mean) / count_; in Update()
38 fragmentation_.Set(mean); in Update()
40 mean = largest_.value(); in Update()
41 mean += (data.largest - mean) / count_; in Update()
42 largest_.Set(mean); in Update()
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| /external/libopus/dnn/torch/dnntools/dnntools/relegance/ |
| D | meta_critic.py | 63 …mean = torch.mean(real_scores.detach()).cpu().item() - torch.mean(generated_scores.detach()).cpu()…
69 …self.disc_stats[key]['mean'] = self.gamma * self.disc_stats[key]['mean'] + (1 - self.gamma) * mean
73 'mean': mean
77 mean = self.disc_stats[key]['mean']
79 mean, std = 0, 1
81 relevance = torch.relu((real_scores - generated_scores - mean) / std + mean - self.beta)
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| /external/cronet/tot/third_party/abseil-cpp/absl/random/ |
| D | poisson_distribution_test.cc | 112 const double mean = std::min(kMax, m); in TYPED_TEST() local
113 const param_type param(mean); in TYPED_TEST()
116 absl::poisson_distribution<TypeParam> before(mean); in TYPED_TEST()
117 EXPECT_EQ(before.mean(), param.mean()); in TYPED_TEST()
136 LOG(INFO) << "Range {" << param.mean() << "}: " << sample_min << ", " in TYPED_TEST()
145 EXPECT_NE(before.mean(), after.mean()); in TYPED_TEST()
151 EXPECT_EQ(before.mean(), after.mean()) // in TYPED_TEST()
164 explicit PoissonModel(double mean) : mean_(mean) {} in PoissonModel() argument
166 double mean() const { return mean_; } in mean() function in __anone7f9c6ed0111::PoissonModel
215 const size_t max_i = 50 * stddev() + mean(); in InitCDF()
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| /external/rust/android-crates-io/crates/grpcio-sys/grpc/third_party/abseil-cpp/absl/random/ |
| D | poisson_distribution_test.cc | 113 const double mean = std::min(kMax, m); in TYPED_TEST() local
114 const param_type param(mean); in TYPED_TEST()
117 absl::poisson_distribution<TypeParam> before(mean); in TYPED_TEST()
118 EXPECT_EQ(before.mean(), param.mean()); in TYPED_TEST()
137 ABSL_INTERNAL_LOG(INFO, absl::StrCat("Range {", param.mean(), "}: ", in TYPED_TEST()
146 EXPECT_NE(before.mean(), after.mean()); in TYPED_TEST()
152 EXPECT_EQ(before.mean(), after.mean()) // in TYPED_TEST()
165 explicit PoissonModel(double mean) : mean_(mean) {} in PoissonModel() argument
167 double mean() const { return mean_; } in mean() function in __anon56c7c3990111::PoissonModel
217 const size_t max_i = 50 * stddev() + mean(); in InitCDF()
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| /external/openscreen/third_party/abseil/src/absl/random/ |
| D | poisson_distribution_test.cc | 113 const double mean = std::min(kMax, m); in TYPED_TEST() local
114 const param_type param(mean); in TYPED_TEST()
117 absl::poisson_distribution<TypeParam> before(mean); in TYPED_TEST()
118 EXPECT_EQ(before.mean(), param.mean()); in TYPED_TEST()
137 ABSL_INTERNAL_LOG(INFO, absl::StrCat("Range {", param.mean(), "}: ", in TYPED_TEST()
146 EXPECT_NE(before.mean(), after.mean()); in TYPED_TEST()
152 EXPECT_EQ(before.mean(), after.mean()) // in TYPED_TEST()
165 explicit PoissonModel(double mean) : mean_(mean) {} in PoissonModel() argument
167 double mean() const { return mean_; } in mean() function in __anonb325cf150111::PoissonModel
217 const size_t max_i = 50 * stddev() + mean(); in InitCDF()
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| /external/abseil-cpp/absl/random/ |
| D | poisson_distribution_test.cc | 113 const double mean = std::min(kMax, m); in TYPED_TEST() local
114 const param_type param(mean); in TYPED_TEST()
117 absl::poisson_distribution<TypeParam> before(mean); in TYPED_TEST()
118 EXPECT_EQ(before.mean(), param.mean()); in TYPED_TEST()
137 LOG(INFO) << "Range {" << param.mean() << "}: " << sample_min << ", " in TYPED_TEST()
146 EXPECT_NE(before.mean(), after.mean()); in TYPED_TEST()
152 EXPECT_EQ(before.mean(), after.mean()) // in TYPED_TEST()
165 explicit PoissonModel(double mean) : mean_(mean) {} in PoissonModel() argument
167 double mean() const { return mean_; } in mean() function in __anon57d543d40111::PoissonModel
216 const size_t max_i = 50 * stddev() + mean(); in InitCDF()
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| /external/angle/third_party/abseil-cpp/absl/random/ |
| D | poisson_distribution_test.cc | 112 const double mean = std::min(kMax, m); in TYPED_TEST() local
113 const param_type param(mean); in TYPED_TEST()
116 absl::poisson_distribution<TypeParam> before(mean); in TYPED_TEST()
117 EXPECT_EQ(before.mean(), param.mean()); in TYPED_TEST()
136 LOG(INFO) << "Range {" << param.mean() << "}: " << sample_min << ", " in TYPED_TEST()
145 EXPECT_NE(before.mean(), after.mean()); in TYPED_TEST()
151 EXPECT_EQ(before.mean(), after.mean()) // in TYPED_TEST()
164 explicit PoissonModel(double mean) : mean_(mean) {} in PoissonModel() argument
166 double mean() const { return mean_; } in mean() function in __anona66b36e30111::PoissonModel
215 const size_t max_i = 50 * stddev() + mean(); in InitCDF()
[all …]
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