| /third_party/mindspore/mindspore/nn/probability/distribution/ |
| D | normal.py | 135 mean=None, argument
177 def _get_dist_args(self, mean=None, sd=None): argument
188 def _mean(self, mean=None, sd=None): argument
195 def _mode(self, mean=None, sd=None): argument
202 def _sd(self, mean=None, sd=None): argument
209 def _entropy(self, mean=None, sd=None): argument
219 def _cross_entropy(self, dist, mean_b, sd_b, mean=None, sd=None): argument
233 def _log_prob(self, value, mean=None, sd=None): argument
254 def _cdf(self, value, mean=None, sd=None): argument
273 def _kl_loss(self, dist, mean_b, sd_b, mean=None, sd=None): argument
[all …]
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| /third_party/abseil-cpp/absl/random/ |
| D | poisson_distribution.h | 63 double mean() const { return mean_; } in mean() function
90 explicit poisson_distribution(double mean) : param_(mean) {} in poisson_distribution()
112 double mean() const { return param_.mean(); } in mean() function
133 poisson_distribution<IntType>::param_type::param_type(double mean) in param_type()
248 double mean = random_internal::read_floating_point<double>(is); variable
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| D | gaussian_distribution.h | 96 : mean_(mean), stddev_(stddev) {} in mean_() argument
100 result_type mean() const { return mean_; } in mean() function
126 : param_(mean, stddev) {} in param_() argument
152 result_type mean() const { return param_.mean(); } in mean() function
199 auto mean = random_internal::read_floating_point<result_type>(is); variable
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| /third_party/skia/third_party/externals/abseil-cpp/absl/random/ |
| D | poisson_distribution.h | 63 double mean() const { return mean_; } in mean() function
90 explicit poisson_distribution(double mean) : param_(mean) {} in poisson_distribution()
112 double mean() const { return param_.mean(); } in mean() function
133 poisson_distribution<IntType>::param_type::param_type(double mean) in param_type()
248 double mean = random_internal::read_floating_point<double>(is); variable
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| D | gaussian_distribution.h | 96 : mean_(mean), stddev_(stddev) {} in mean_() argument
100 result_type mean() const { return mean_; } in mean() function
126 : param_(mean, stddev) {} in param_() argument
152 result_type mean() const { return param_.mean(); } in mean() function
199 auto mean = random_internal::read_floating_point<result_type>(is); variable
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| /third_party/boost/boost/math/distributions/ |
| D | poisson.hpp | 62 …inline bool check_mean(const char* function, const RealType& mean, RealType* result, const Policy&… in check_mean()
75 …inline bool check_mean_NZ(const char* function, const RealType& mean, RealType* result, const Poli… in check_mean_NZ()
88 …inline bool check_dist(const char* function, const RealType& mean, RealType* result, const Policy&… in check_dist()
107 …inline bool check_dist_and_k(const char* function, RealType mean, RealType k, RealType* result, co… in check_dist_and_k()
131 …inline bool check_dist_and_prob(const char* function, RealType mean, RealType p, RealType* result… in check_dist_and_prob()
159 RealType mean() const in mean() function in boost::math::poisson_distribution
188 inline RealType mean(const poisson_distribution<RealType, Policy>& dist) in mean() function
255 RealType mean = dist.mean(); in pdf() local
301 RealType mean = dist.mean(); in cdf() local
352 RealType mean = dist.mean(); in cdf() local
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| D | inverse_gaussian.hpp | 88 RealType mean()const in mean() function in boost::math::inverse_gaussian_distribution
139 RealType mean = dist.mean(); in pdf() local
176 RealType mean = dist.mean(); in cdf() local
325 RealType mean = dist.mean(); in quantile() local
371 RealType mean = c.dist.mean(); in cdf() local
421 RealType mean = c.dist.mean(); in quantile() local
451 inline RealType mean(const inverse_gaussian_distribution<RealType, Policy>& dist) in mean() function
473 RealType mean = dist.mean(); in standard_deviation() local
483 RealType mean = dist.mean(); in mode() local
494 RealType mean = dist.mean(); in skewness() local
[all …]
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| D | normal.hpp | 44 RealType mean()const in mean() function in boost::math::normal_distribution
117 RealType mean = dist.mean(); in pdf() local
160 RealType mean = dist.mean(); in cdf() local
200 RealType mean = dist.mean(); in quantile() local
224 RealType mean = c.dist.mean(); in cdf() local
261 RealType mean = c.dist.mean(); in quantile() local
278 inline RealType mean(const normal_distribution<RealType, Policy>& dist) in mean() function
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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
59 def after(x, scale, b, mean, variance): argument
83 def before(x, scale, b, mean, variance): argument
89 def after(x, scale, b, mean, variance): argument
106 def before(x, scale, b, mean, variance): argument
112 def after(x, scale, b, mean, variance): argument
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| /third_party/mindspore/mindspore/nn/wrap/ |
| D | grad_reducer.py | 83 def _tensors_allreduce(degree, mean, allgather, allreduce, allreduce_filter, grad): argument
107 def _tensors_allreduce_post(degree, mean, allreduce_filter, grad): argument
130 def _tensors_allreduce_ps(degree, mean, allgather, allreduce, allreduce_filter, grad, ps_parameter): argument
158 def _tensors_allreduce_with_sparse(degree, mean, allgather, allreduce, allreduce_filter, grad): argument
184 def _tensors_allreduce_with_sparse_ps(degree, mean, allgather, allreduce, allreduce_filter, grad, p… argument
366 …def __init__(self, parameters, mean=True, degree=None, fusion_type=1, group=GlobalComm.WORLD_COMM_… argument
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| /third_party/mindspore/tests/ut/python/dataset/ |
| D | test_normalizeOp.py | 32 def normalize_np(image, mean, std): argument
44 def util_test_normalize(mean, std, op_type): argument
72 def util_test_normalize_grayscale(num_output_channels, mean, std): argument
346 def util_test(item, mean, std): argument
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| /third_party/boost/boost/histogram/accumulators/ |
| D | mean.hpp | 27 class mean { class
36 mean(const mean<T>& o) noexcept in mean() function in boost::histogram::accumulators::mean
40 mean(const_reference n, const_reference mean, const_reference variance) noexcept in mean() argument
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| /third_party/abseil-cpp/absl/base/internal/ |
| D | exponential_biased.cc | 41 int64_t ExponentialBiased::GetSkipCount(int64_t mean) { in GetSkipCount()
72 int64_t ExponentialBiased::GetStride(int64_t mean) { in GetStride()
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| /third_party/skia/third_party/externals/abseil-cpp/absl/base/internal/ |
| D | exponential_biased.cc | 41 int64_t ExponentialBiased::GetSkipCount(int64_t mean) { in GetSkipCount()
72 int64_t ExponentialBiased::GetStride(int64_t mean) { in GetStride()
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| /third_party/mindspore/mindspore/ccsrc/backend/kernel_compiler/gpu/cuda_impl/ |
| D | layer_norm_impl.cu | 26 inline __device__ void MeanAndVarAccumulation(T *mean, T *var, T *num, const T &val) { in MeanAndVarAccumulation()
50 inline __device__ void ThreadReduce(const int &col_dim, const T *block_addr, T *mean, T *var, T *nu… in ThreadReduce()
64 inline __device__ void WarpReduce(T *mean, T *var, T *num) { in WarpReduce()
74 inline __device__ void BlockReduce(const int &col_dim, T *mean, T *var, T *num, T *mean_addr, T *va… in BlockReduce()
127 T mean = 0; in LayerNormKernel() local
144 const T *gamma, const T *beta, T *y, T *mean, T *var, cudaStream_t stream) { in LayerNorm()
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| /third_party/mindspore/mindspore/ops/composite/ |
| D | random_ops.py | 30 def normal(shape, mean, stddev, seed=None): argument
86 def laplace(shape, mean, lambda_param, seed=None): argument
279 def poisson(shape, mean, seed=None): argument
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| /third_party/mindspore/mindspore/ccsrc/minddata/dataset/kernels/ir/vision/ |
| D | normalize_ir.cc | 26 NormalizeOperation::NormalizeOperation(const std::vector<float> &mean, const std::vector<float> &st… in NormalizeOperation()
51 std::vector<float> mean = op_params["mean"]; in from_json() local
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| D | normalize_pad_ir.cc | 31 NormalizePadOperation::NormalizePadOperation(const std::vector<float> &mean, const std::vector<floa… in NormalizePadOperation()
70 std::vector<float> mean = op_params["mean"]; in from_json() local
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| /third_party/mindspore/tests/ut/cpp/dataset/ |
| D | normalizepad_op_test.cc | 38 float mean[3] = {121.0, 115.0, 100.0}; in TEST_F() local
53 float mean[3] = {121.0, 115.0, 100.0}; in TEST_F() local
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| /third_party/boost/boost/accumulators/statistics/ |
| D | mean.hpp | 81 ar & mean; in serialize() local
85 result_type mean; member
100 struct mean struct
105 typedef accumulators::impl::mean_impl<mpl::_1, sum> impl;
155 extractor<tag::mean> const mean = {}; variable
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| /third_party/mindspore/tests/st/ops/gpu/ |
| D | test_batchnorm_fold_op.py | 31 def __init__(self, mean, variance): argument
43 def np_result(x, mean, var, momentum, epsilon): argument
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| /third_party/boost/boost/compute/random/ |
| D | normal_distribution.hpp | 44 normal_distribution(RealType mean = 0.f, RealType stddev = 1.f) in normal_distribution()
56 result_type mean() const in mean() function in boost::compute::normal_distribution
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| /third_party/boost/libs/compute/include/boost/compute/random/ |
| D | normal_distribution.hpp | 44 normal_distribution(RealType mean = 0.f, RealType stddev = 1.f) in normal_distribution()
56 result_type mean() const in mean() function in boost::compute::normal_distribution
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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
100 def batchnorm_fold(x, x_sum, x_square_sum, mean, variance, argument
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| /third_party/boost/libs/math/test/ |
| D | test_normal.cpp | 46 RealType NaivePDF(RealType mean, RealType sd, RealType x) in NaivePDF()
56 void check_normal(RealType mean, RealType sd, RealType x, RealType p, RealType q, RealType tol) in check_normal()
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