| /aosp_15_r20/external/pytorch/torch/distributions/ |
| H A D | distribution.py | 53 arg_constraints = self.arg_constraints
55 arg_constraints = {}
61 for param, constraint in arg_constraints.items():
116 def arg_constraints(self) -> Dict[str, constraints.Constraint]: member in Distribution
333 param_names = [k for k, _ in self.arg_constraints.items() if k in self.__dict__]
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| H A D | relaxed_categorical.py | 37 arg_constraints = {"probs": constraints.simplex, "logits": constraints.real_vector} variable in ExpRelaxedCategorical
118 arg_constraints = {"probs": constraints.simplex, "logits": constraints.real_vector} variable in RelaxedOneHotCategorical
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| H A D | relaxed_bernoulli.py | 41 arg_constraints = {"probs": constraints.unit_interval, "logits": constraints.real} variable in LogitRelaxedBernoulli
130 arg_constraints = {"probs": constraints.unit_interval, "logits": constraints.real} variable in RelaxedBernoulli
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| H A D | continuous_bernoulli.py | 48 arg_constraints = {"probs": constraints.unit_interval, "logits": constraints.real} variable in ContinuousBernoulli
66 if not self.arg_constraints["probs"].check(self.probs).all():
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| H A D | wishart.py | 67 arg_constraints = { variable in Wishart
120 self.arg_constraints["df"] = constraints.greater_than(event_shape[-1] - 1)
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| H A D | chi2.py | 24 arg_constraints = {"df": constraints.positive} variable in Chi2
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| H A D | logistic_normal.py | 34 arg_constraints = {"loc": constraints.real, "scale": constraints.positive} variable in LogisticNormal
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| H A D | log_normal.py | 30 arg_constraints = {"loc": constraints.real, "scale": constraints.positive} variable in LogNormal
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| H A D | inverse_gamma.py | 33 arg_constraints = { variable in InverseGamma
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| H A D | half_normal.py | 32 arg_constraints = {"scale": constraints.positive} variable in HalfNormal
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| H A D | pareto.py | 27 arg_constraints = {"alpha": constraints.positive, "scale": constraints.positive} variable in Pareto
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| H A D | poisson.py | 32 arg_constraints = {"rate": constraints.nonnegative} variable in Poisson
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| H A D | half_cauchy.py | 32 arg_constraints = {"scale": constraints.positive} variable in HalfCauchy
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| H A D | exponential.py | 28 arg_constraints = {"rate": constraints.positive} variable in Exponential
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| H A D | gumbel.py | 31 arg_constraints = {"loc": constraints.real, "scale": constraints.positive} variable in Gumbel
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| H A D | weibull.py | 29 arg_constraints = { variable in Weibull
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| H A D | kumaraswamy.py | 40 arg_constraints = { variable in Kumaraswamy
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| H A D | cauchy.py | 33 arg_constraints = {"loc": constraints.real, "scale": constraints.positive} variable in Cauchy
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| H A D | beta.py | 32 arg_constraints = { variable in Beta
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| H A D | independent.py | 43 arg_constraints: Dict[str, constraints.Constraint] = {} variable in Independent
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| H A D | laplace.py | 29 arg_constraints = {"loc": constraints.real, "scale": constraints.positive} variable in Laplace
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| H A D | uniform.py | 32 arg_constraints = { variable in Uniform
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| H A D | geometric.py | 44 arg_constraints = {"probs": constraints.unit_interval, "logits": constraints.real} variable in Geometric
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| H A D | gamma.py | 35 arg_constraints = { variable in Gamma
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| H A D | lkj_cholesky.py | 60 arg_constraints = {"concentration": constraints.positive} variable in LKJCholesky
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