| /third_party/typescript/tests/baselines/reference/ |
| D | variance.symbols | 1 === tests/cases/conformance/types/conditional/variance.ts ===
7 >Foo : Symbol(Foo, Decl(variance.ts, 0, 0))
8 >T : Symbol(T, Decl(variance.ts, 4, 14))
11 >prop : Symbol(Foo.prop, Decl(variance.ts, 4, 18))
12 >T : Symbol(T, Decl(variance.ts, 4, 14))
16 >foo : Symbol(foo, Decl(variance.ts, 8, 5))
17 >prop : Symbol(prop, Decl(variance.ts, 8, 13))
20 >x : Symbol(x, Decl(variance.ts, 9, 5))
21 >Foo : Symbol(Foo, Decl(variance.ts, 0, 0))
22 >foo : Symbol(foo, Decl(variance.ts, 8, 5))
[all …]
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| /third_party/boost/boost/accumulators/statistics/ |
| D | variance.hpp | 96 : variance(numeric::fdiv(args[sample | Sample()], numeric::one<std::size_t>::value)) in variance_impl()
109 this->variance = in operator ()()
110 numeric::fdiv(this->variance * (cnt - 1), cnt) in operator ()()
117 return this->variance; in result()
124 ar & variance; in serialize() local
128 result_type variance; member
147 struct variance struct
163 extractor<tag::variance> const variance = {}; variable
166 BOOST_ACCUMULATORS_IGNORE_GLOBAL(variance)
170 using extract::variance;
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| D | error_of_mean.hpp | 40 extractor<Variance> const variance = {}; in result() local
41 return sqrt(numeric::fdiv(variance(args), count(args) - 1)); in result()
63 : depends_on<variance, count>
67 typedef accumulators::impl::error_of_mean_impl<mpl::_1, variance> impl;
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| /third_party/boost/libs/accumulators/test/ |
| D | variance.cpp | 34 accumulator_set<int, stats<tag::variance(lazy)> > acc1; in test_stat()
45 BOOST_CHECK_CLOSE(2., variance(acc1), 1e-5); in test_stat()
48 accumulator_set<int, stats<tag::variance> > acc2; in test_stat()
58 BOOST_CHECK_CLOSE(2., variance(acc2), 1e-5); in test_stat()
69 accumulator_set<int, stats<tag::variance(lazy)> > acc1; in test_persistency()
70 accumulator_set<int, stats<tag::variance> > acc2; in test_persistency()
81 BOOST_CHECK_CLOSE(2., variance(acc2), epsilon); in test_persistency()
82 BOOST_CHECK_CLOSE(2., variance(acc1), epsilon); in test_persistency()
87 accumulator_set<int, stats<tag::variance(lazy)> > acc1; in test_persistency()
88 accumulator_set<int, stats<tag::variance> > acc2; in test_persistency()
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| /third_party/mindspore/tests/ut/cpp/python_input/gtest_input/pre_activate/ |
| D | bn_split.py | 53 def before(x, scale, b, mean, variance): argument
54 bn_output = bn(x, scale, b, mean, variance)
59 def after(x, scale, b, mean, variance): argument
63 fused_bn2_output = fused_bn2(fused_bn2_input0, fused_bn2_input1, mean, variance)
83 def before(x, scale, b, mean, variance): argument
84 bn_output = bn(x, scale, b, mean, variance)
89 def after(x, scale, b, mean, variance): argument
94 scale, b, mean, variance)
106 def before(x, scale, b, mean, variance): argument
107 bn_output = sync_bn(x, scale, b, mean, variance)
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| /third_party/mindspore/tests/st/ops/gpu/ |
| D | test_batchnorm_fold_op.py | 31 def __init__(self, mean, variance): argument
34 self.variance = variance
39 a, b, c, d = self.op(x, self.mean, self.variance, current_step)
62 variance = np.random.uniform(1, 10, size=[c]).astype('float32')
65 ms_var_t = Tensor(variance)
71 expect1, expect2, expect3, expect4, expect5, expect6 = np_result(x, mean, variance, 0.9, 1e-12)
87 variance = np.random.uniform(1, 10, size=[c]).astype('float32')
90 ms_var_t = Tensor(variance)
95 expect1, expect2, expect3, _, expect5, expect6 = np_result(x, mean, variance, 0.9, 1e-12)
110 variance = np.random.uniform(1, 10, size=[c]).astype('float32')
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| /third_party/mindspore/mindspore/lite/src/runtime/kernel/arm/int8/ |
| D | batchnorm_int8.cc | 53 auto variance = in_tensors_.at(kNumInput2); in InitConstTensor() local
58 auto var_ptr = reinterpret_cast<int8_t *>(variance->MutableData()); in InitConstTensor()
66 CHECK_LESS_RETURN(MAX_MALLOC_SIZE, static_cast<size_t>(variance->ElementsNum()) * sizeof(float)); in InitConstTensor()
67 …beta_addr_ = reinterpret_cast<float *>(malloc(static_cast<size_t>(variance->ElementsNum()) * sizeo… in InitConstTensor()
76 CHECK_LESS_RETURN(variance->quant_params().size(), 1); in InitConstTensor()
80 auto zp_var = variance->quant_params().front().zeroPoint; in InitConstTensor()
84 auto s_var = variance->quant_params().front().scale; in InitConstTensor()
105 auto variance = in_tensors_.at(kNumInput4); in InitFusedConstTensor() local
114 auto var_ptr = reinterpret_cast<int8_t *>(variance->MutableData()); in InitFusedConstTensor()
123 CHECK_LESS_RETURN(MAX_MALLOC_SIZE, static_cast<size_t>(variance->ElementsNum()) * sizeof(float)); in InitFusedConstTensor()
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| /third_party/mindspore/mindspore/lite/micro/coder/opcoders/nnacl/int8/ |
| D | batchnorm_int8_coder.cc | 72 Tensor *variance = input_tensors_.at(2); in InitConstTensor() local
76 auto var_ptr = reinterpret_cast<int8_t *>(variance->MutableData()); in InitConstTensor()
85 …allocator_->Malloc(kNumberTypeFloat, variance->ElementsNum() * sizeof(float), kOfflinePackWeight)); in InitConstTensor()
90 int32_t zp_var = variance->quant_params().at(0).zeroPoint; in InitConstTensor()
94 auto s_var = static_cast<float>(variance->quant_params().at(0).scale); in InitConstTensor()
114 Tensor *variance = input_tensors_.at(4); in InitFusedConstTensor() local
120 auto var_ptr = reinterpret_cast<int8_t *>(variance->MutableData()); in InitFusedConstTensor()
131 …allocator_->Malloc(kNumberTypeFloat, variance->ElementsNum() * sizeof(float), kOfflinePackWeight)); in InitFusedConstTensor()
138 int32_t zp_var = variance->quant_params().at(0).zeroPoint; in InitFusedConstTensor()
144 auto s_var = static_cast<float>(variance->quant_params().at(0).scale); in InitFusedConstTensor()
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| /third_party/boost/libs/histogram/test/ |
| D | histogram_test.cpp | 246 BOOST_TEST_EQ(algorithm::sum(h).variance(), 7.25); in run_tests()
249 BOOST_TEST_EQ(h[-1].variance(), 1); in run_tests()
251 BOOST_TEST_EQ(h[0].variance(), 1.25); in run_tests()
253 BOOST_TEST_EQ(h[1].variance(), 1); in run_tests()
255 BOOST_TEST_EQ(h[2].variance(), 4); in run_tests()
271 BOOST_TEST_EQ(h[0].variance(), 1); in run_tests()
274 BOOST_TEST_EQ(h[1].variance(), 1); in run_tests()
340 BOOST_TEST_EQ(algorithm::sum(h).variance(), 150); in run_tests()
358 BOOST_TEST_EQ(h.at(-1, 0).variance(), 0); in run_tests()
359 BOOST_TEST_EQ(h.at(-1, 1).variance(), 49); in run_tests()
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| D | accumulators_test.cpp | 47 BOOST_TEST_EQ(w.variance(), 1); in main()
53 BOOST_TEST_EQ(w.variance(), 5); in main()
59 BOOST_TEST_EQ(w.variance(), 7); in main()
93 BOOST_TEST_EQ(a.variance(), 30); in main()
107 BOOST_TEST_EQ(b.variance(), 30); in main()
114 BOOST_TEST_IS_CLOSE(c.variance(), 25.714, 1e-3); in main()
143 BOOST_TEST_IS_CLOSE(a.variance(), 0.8, 1e-3); in main()
154 BOOST_TEST_IS_CLOSE(b.variance(), 0.615, 1e-3); in main()
209 BOOST_TEST_EQ(w.variance(), 2e200); in main()
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| D | accumulators_weighted_sum_test.cpp | 32 BOOST_TEST_EQ(w.variance(), 1); in main()
38 BOOST_TEST_EQ(w.variance(), 5); in main()
44 BOOST_TEST_EQ(w.variance(), 7); in main()
76 BOOST_TEST_EQ(w.variance(), 2e200); in main()
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| /third_party/mindspore/mindspore/_extends/graph_kernel/expanders/ |
| D | layernorm.py | 76 variance = graph_builder.emit('Mul', [variance_red, mean_cof_v])
78 … variance = graph_builder.emit('Reshape', [variance], attrs={'shape': ori_reduced_shape_x})
83 normalize_add = graph_builder.emit('Add', [variance, epsilon_v])
94 variance = graph_builder.emit('Cast', [variance], attrs={'dst_type': 'float16'})
95 return res, mean, variance
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| /third_party/abseil-cpp/absl/random/internal/ |
| D | distribution_test_util_test.cc | 162 m.variance = 1; in TEST()
167 m.variance = 1; in TEST()
172 m.variance = 100; in TEST()
180 m.variance = 1; in TEST()
185 m.variance = 1; in TEST()
190 m.variance = 100; in TEST()
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| D | chi_square.cc | 125 const double variance = 2.0 / (9 * dof); in ChiSquareValue() local
127 if (variance != 0) { in ChiSquareValue()
128 return std::pow(z * std::sqrt(variance) + mean, 3.0) * dof; in ChiSquareValue()
172 const double variance = 2.0 / (9 * dof); in ChiSquarePValue() local
174 if (variance != 0) { in ChiSquarePValue()
175 const double z = (chi_square_scaled - mean) / std::sqrt(variance); in ChiSquarePValue()
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| /third_party/skia/third_party/externals/abseil-cpp/absl/random/internal/ |
| D | distribution_test_util_test.cc | 162 m.variance = 1; in TEST()
167 m.variance = 1; in TEST()
172 m.variance = 100; in TEST()
180 m.variance = 1; in TEST()
185 m.variance = 1; in TEST()
190 m.variance = 100; in TEST()
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| D | chi_square.cc | 125 const double variance = 2.0 / (9 * dof); in ChiSquareValue() local
127 if (variance != 0) { in ChiSquareValue()
128 return std::pow(z * std::sqrt(variance) + mean, 3.0) * dof; in ChiSquareValue()
172 const double variance = 2.0 / (9 * dof); in ChiSquarePValue() local
174 if (variance != 0) { in ChiSquarePValue()
175 const double z = (chi_square_scaled - mean) / std::sqrt(variance); in ChiSquarePValue()
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| /third_party/boost/libs/math/example/ |
| D | inverse_chi_squared_find_df_example.cpp | 48 double variance = 1.; // true variance in main() local
53 << ", variance = " << variance << ", ratio = " << diff/variance in main()
57 inverse_chi_square_df_estimator<> a_df(alpha, beta, variance, diff); in main()
72 double df = inverse_chi_squared::find_degrees_of_freedom(diff, alpha, beta, variance, 100); in main()
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| /third_party/mindspore/mindspore/ops/_op_impl/_custom_op/ |
| D | batchnorm_fold.py | 60 def _batchnorm_fold_compute(x_input, x_sum, x_square_sum, mean, variance, momentum, epsilon): argument
87 var_mul_rev = te.lang.cce.vmuls(variance, factor_reverse)
92 running_std = te.lang.cce.vsqrt(te.lang.cce.vadds(variance, epsilon))
100 def batchnorm_fold(x, x_sum, x_square_sum, mean, variance, argument
112 shape_variance = variance.get("shape")
115 dtype_variance = variance.get("dtype")
146 variance = tvm.placeholder(shape_mean, name="variance", dtype=dtype_variance.lower())
148 res = _batchnorm_fold_compute(x_input, x_sum, x_square_sum, mean, variance, momentum, epsilon)
152 "tensor_list": [x_input, x_sum, x_square_sum, mean, variance] + res}
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| /third_party/gstreamer/gstplugins_bad/gst/dvbsubenc/libimagequant/ |
| D | mediancut.c | 30 f_pixel variance; member
206 float variance; member
212 return ((const channelvariance *) ch1)->variance > in comparevariance()
213 ((const channelvariance *) ch2)->variance ? -1 : (((const channelvariance in comparevariance()
214 *) ch1)->variance < in comparevariance()
215 ((const channelvariance *) ch2)->variance ? 1 : 0); in comparevariance()
227 {index_of_channel (r), b->variance.r}, in prepare_sort()
228 {index_of_channel (g), b->variance.g}, in prepare_sort()
229 {index_of_channel (b), b->variance.b}, in prepare_sort()
230 {index_of_channel (a), b->variance.a}, in prepare_sort()
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| /third_party/boost/libs/math/doc/distributions/ |
| D | beta.qbk | 28 // Parameter estimators of alpha or beta from mean and variance.
31 RealType variance); // Expected value of variance.
35 RealType variance); // Expected value of variance.
139 from presumed-known mean and variance.
153 RealType variance); // Expected value of variance.
156 beta distribution with mean /mean/ and variance /variance/.
160 RealType variance); // Expected value of variance.
163 beta distribution with mean /mean/ and variance /variance/.
239 [[variance][`a * b / (a+b)^2 * (a + b + 1)`]]
245 [[alpha (from mean and variance)][`mean * (( (mean * (1 - mean)) / variance)- 1)`]]
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| D | chi_squared.qbk | 70 RealType variance,
74 variance in a Chi-Squared test for equal standard deviations.
77 [[difference_from_variance][The difference from the assumed nominal variance
82 [[variance][The nominal variance being tested against.]]
91 whether they are testing for a variance greater than a nominal value (positive
92 /difference_from_variance/) or testing for a variance less than a nominal value
94 a requirement that `variance + difference_from_variance > 0`, since no sample
95 can have a negative variance!
139 [[variance][2v]]
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| /third_party/boost/libs/math/test/ |
| D | test_students_t.cpp | 572 BOOST_MATH_CHECK_THROW(variance(students_t_distribution<RealType>(nan)), std::domain_error); in test_spots()
574 BOOST_MATH_CHECK_THROW(variance(students_t_distribution<RealType>(-1)), std::domain_error); in test_spots()
575 BOOST_MATH_CHECK_THROW(variance(students_t_distribution<RealType>(0)), std::domain_error); in test_spots()
576 BOOST_MATH_CHECK_THROW(variance(students_t_distribution<RealType>(1)), std::domain_error); in test_spots()
577 …BOOST_MATH_CHECK_THROW(variance(students_t_distribution<RealType>(static_cast<RealType>(1.99999L))… in test_spots()
578 …BOOST_MATH_CHECK_THROW(variance(students_t_distribution<RealType>(static_cast<RealType>(1.99999L))… in test_spots()
579 …BOOST_MATH_CHECK_THROW(variance(students_t_distribution<RealType>(2)), std::domain_error); // df =… in test_spots()
580 BOOST_CHECK_EQUAL(variance(students_t_distribution<RealType>(2.5)), 5); // OK. in test_spots()
581 BOOST_CHECK_EQUAL(variance(students_t_distribution<RealType>(3)), 3); // OK. in test_spots()
582 BOOST_CHECK_EQUAL(variance(students_t_distribution<RealType>(inf)), 1); // OK. in test_spots()
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| D | test_weibull.cpp | 273 variance(dist) in test_spots()
278 , sqrt(variance(dist)), tolerance); in test_spots()
302 …1 + 3/dist.shape()) * pow(dist.scale(), RealType(3)) - 3 * mean(dist) * variance(dist) - pow(mean(… in test_spots()
312 - 3 * variance(dist) * variance(dist) in test_spots()
313 - 4 * skewness(dist) * variance(dist) * standard_deviation(dist) * mean(dist) in test_spots()
314 - 6 * variance(dist) * mean(dist) * mean(dist) in test_spots()
315 - pow(mean(dist), RealType(4))) / (variance(dist) * variance(dist)), in test_spots()
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| /third_party/boost/boost/math/distributions/ |
| D | beta.hpp | 135 …inline bool check_variance(const char* function, const RealType& variance, RealType* result, const… in check_variance() argument
137 if(!(boost::math::isfinite)(variance) || (variance <= 0)) in check_variance()
141 "variance argument is %1%, but must be > 0 !", variance, pol); in check_variance()
187 RealType variance) // Expected value of variance. in find_alpha() argument
194 && beta_detail::check_variance(function, variance, &result, Policy()) in find_alpha()
200 return mean * (( (mean * (1 - mean)) / variance)- 1); in find_alpha()
205 RealType variance) // Expected value of variance. in find_beta() argument
213 beta_detail::check_variance(function, variance, &result, Policy()) in find_beta()
219 return (1 - mean) * (((mean * (1 - mean)) /variance)-1); in find_beta()
296 inline RealType variance(const beta_distribution<RealType, Policy>& dist) in variance() function
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| /third_party/boost/boost/histogram/accumulators/ |
| D | weighted_sum.hpp | 33 : weighted_sum(s.value(), s.variance()) {} in weighted_sum()
36 weighted_sum(const_reference value, const_reference variance) noexcept in weighted_sum() argument
37 : sum_of_weights_(value), sum_of_weights_squared_(variance) {} in weighted_sum()
79 const_reference variance() const noexcept { return sum_of_weights_squared_; } in variance() function in boost::histogram::accumulators::weighted_sum
|