| /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 …]
|
| /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);
|
| /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 …]
|
| /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()
[all …]
|
| /external/guava/android/guava/src/com/google/common/math/ |
| D | Stats.java | 66 private final double mean; field in Stats
85 Stats(long count, double mean, double sumOfSquaresOfDeltas, double min, double max) { in Stats() argument
87 this.mean = mean; in Stats()
178 public double mean() { in mean() method in Stats
180 return mean; in mean()
196 return mean * count; in sum()
352 && doubleToLongBits(mean) == doubleToLongBits(other.mean) in equals()
366 return Objects.hashCode(count, mean, sumOfSquaresOfDeltas, min, max); in hashCode()
374 .add("mean", mean) in toString()
415 double mean = values.next().doubleValue(); in meanOf() local
[all …]
|
| D | StatsAccumulator.java | 42 private double mean = 0.0; // any finite value will do, we only use it to multiply by zero for sum field in StatsAccumulator
51 mean = value; in add()
59 if (isFinite(value) && isFinite(mean)) { in add()
61 double delta = value - mean; in add()
62 mean += delta / count; in add()
63 sumOfSquaresOfDeltas += delta * (value - mean); in add()
65 mean = calculateNewMeanNonFinite(mean, value); in add()
139 merge(values.count(), values.mean(), values.sumOfSquaresOfDeltas(), values.min(), values.max()); in addAll()
152 merge(values.count(), values.mean(), values.sumOfSquaresOfDeltas(), values.min(), values.max()); in addAll()
163 mean = otherMean; in merge()
[all …]
|
| /external/guava/guava/src/com/google/common/math/ |
| D | Stats.java | 70 private final double mean; field in Stats
89 Stats(long count, double mean, double sumOfSquaresOfDeltas, double min, double max) { in Stats() argument
91 this.mean = mean; in Stats()
254 public double mean() { in mean() method
256 return mean; in mean()
272 return mean * count; in sum()
428 && doubleToLongBits(mean) == doubleToLongBits(other.mean) in equals()
442 return Objects.hashCode(count, mean, sumOfSquaresOfDeltas, min, max); in hashCode()
450 .add("mean", mean) in toString()
491 double mean = values.next().doubleValue(); in meanOf() local
[all …]
|
| D | StatsAccumulator.java | 45 private double mean = 0.0; // any finite value will do, we only use it to multiply by zero for sum field in StatsAccumulator
54 mean = value; in add()
62 if (isFinite(value) && isFinite(mean)) { in add()
64 double delta = value - mean; in add()
65 mean += delta / count; in add()
66 sumOfSquaresOfDeltas += delta * (value - mean); in add()
68 mean = calculateNewMeanNonFinite(mean, value); in add()
173 merge(values.count(), values.mean(), values.sumOfSquaresOfDeltas(), values.min(), values.max()); in addAll()
186 merge(values.count(), values.mean(), values.sumOfSquaresOfDeltas(), values.min(), values.max()); in addAll()
197 mean = otherMean; in merge()
[all …]
|
| /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()
[all …]
|
| 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()
[all …]
|
| /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()
[all …]
|
| /external/ImageMagick/filters/ |
| D | analyze.c | 87 mean, member
220 brightness.mean=brightness.sum[1]/area; in analyzeImage()
221 (void) FormatLocaleString(text,MagickPathExtent,"%g",brightness.mean); in analyzeImage()
230 brightness.kurtosis=(brightness.sum[4]/area-4.0*brightness.mean* in analyzeImage()
231 brightness.sum[3]/area+6.0*brightness.mean*brightness.mean* in analyzeImage()
232 brightness.sum[2]/area-3.0*brightness.mean*brightness.mean* in analyzeImage()
233 brightness.mean*brightness.mean)/(brightness.standard_deviation* in analyzeImage()
239 brightness.skewness=(brightness.sum[3]/area-3.0*brightness.mean* in analyzeImage()
240 brightness.sum[2]/area+2.0*brightness.mean*brightness.mean* in analyzeImage()
241 brightness.mean)/(brightness.standard_deviation* in analyzeImage()
[all …]
|
| /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"
[all …]
|
| /external/rust/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
[all …]
|
| /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()
|
| /external/tensorflow/tensorflow/python/keras/layers/preprocessing/ |
| D | normalization.py | 91 def __init__(self, axis=-1, mean=None, variance=None, **kwargs): argument
107 if isinstance(mean, variables.Variable):
113 if mean is not None and variance is not None:
114 mean = convert_to_ndarray(mean)
116 elif mean is not None or variance is not None:
119 'must be set. Got mean: {} and variance: {}'.format(mean, variance))
120 self.mean_val = mean
150 self.mean = self.add_weight(
174 self.mean.assign(mean_val)
196 total_mean = self.mean * existing_weight + batch_mean * batch_weight
[all …]
|
| /external/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 ABSL_INTERNAL_LOG(INFO, absl::StrCat("Range {", param.mean(), "}: ", 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 __anon3b9c9a850111::PoissonModel
216 const size_t max_i = 50 * stddev() + mean(); in InitCDF()
[all …]
|
| /external/angle/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 __anon6b4cbfd40111::PoissonModel
217 const size_t max_i = 50 * stddev() + mean(); in InitCDF()
[all …]
|
| /external/rust/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 __anonbd44bce60111::PoissonModel
217 const size_t max_i = 50 * stddev() + mean(); in InitCDF()
[all …]
|
| D | gaussian_distribution_test.cc | 84 const TypeParam mean = (mod & 0x1) ? -x : x; in TYPED_TEST() local
86 const param_type param(mean, stddev); in TYPED_TEST()
88 absl::gaussian_distribution<TypeParam> before(mean, stddev); in TYPED_TEST()
89 EXPECT_EQ(before.mean(), param.mean()); in TYPED_TEST()
110 INFO, absl::StrFormat("Range{%f, %f}: %f, %f", mean, stddev, in TYPED_TEST()
117 if (!std::isfinite(mean) || !std::isfinite(stddev)) { in TYPED_TEST()
125 EXPECT_NE(before.mean(), after.mean()); in TYPED_TEST()
142 if (mean <= std::numeric_limits<double>::max() && in TYPED_TEST()
143 mean >= std::numeric_limits<double>::lowest()) { in TYPED_TEST()
144 EXPECT_EQ(static_cast<double>(before.mean()), in TYPED_TEST()
[all …]
|
| /external/libtextclassifier/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 __anon8683c0550111::PoissonModel
217 const size_t max_i = 50 * stddev() + mean(); in InitCDF()
[all …]
|
| D | gaussian_distribution_test.cc | 84 const TypeParam mean = (mod & 0x1) ? -x : x; in TYPED_TEST() local
86 const param_type param(mean, stddev); in TYPED_TEST()
88 absl::gaussian_distribution<TypeParam> before(mean, stddev); in TYPED_TEST()
89 EXPECT_EQ(before.mean(), param.mean()); in TYPED_TEST()
110 INFO, absl::StrFormat("Range{%f, %f}: %f, %f", mean, stddev, in TYPED_TEST()
117 if (!std::isfinite(mean) || !std::isfinite(stddev)) { in TYPED_TEST()
125 EXPECT_NE(before.mean(), after.mean()); in TYPED_TEST()
142 if (mean <= std::numeric_limits<double>::max() && in TYPED_TEST()
143 mean >= std::numeric_limits<double>::lowest()) { in TYPED_TEST()
144 EXPECT_EQ(static_cast<double>(before.mean()), in TYPED_TEST()
[all …]
|
| /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 __anon1c6796a60111::PoissonModel
217 const size_t max_i = 50 * stddev() + mean(); in InitCDF()
[all …]
|
| D | gaussian_distribution_test.cc | 84 const TypeParam mean = (mod & 0x1) ? -x : x; in TYPED_TEST() local
86 const param_type param(mean, stddev); in TYPED_TEST()
88 absl::gaussian_distribution<TypeParam> before(mean, stddev); in TYPED_TEST()
89 EXPECT_EQ(before.mean(), param.mean()); in TYPED_TEST()
110 INFO, absl::StrFormat("Range{%f, %f}: %f, %f", mean, stddev, in TYPED_TEST()
117 if (!std::isfinite(mean) || !std::isfinite(stddev)) { in TYPED_TEST()
125 EXPECT_NE(before.mean(), after.mean()); in TYPED_TEST()
142 if (mean <= std::numeric_limits<double>::max() && in TYPED_TEST()
143 mean >= std::numeric_limits<double>::lowest()) { in TYPED_TEST()
144 EXPECT_EQ(static_cast<double>(before.mean()), in TYPED_TEST()
[all …]
|
| /external/webrtc/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 ABSL_INTERNAL_LOG(INFO, absl::StrCat("Range {", param.mean(), "}: ", 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 __anon7df3b2f40111::PoissonModel
216 const size_t max_i = 50 * stddev() + mean(); in InitCDF()
[all …]
|