/usr/local/lib64/python3.6/site-packages/torch/distributions/__pycache__
NameSizeModeActions
bernoulli.cpython-36.pyc44450644editdlrm
beta.cpython-36.pyc36820644editdlrm
binomial.cpython-36.pyc47610644editdlrm
categorical.cpython-36.pyc58130644editdlrm
cauchy.cpython-36.pyc33100644editdlrm
chi2.cpython-36.pyc14190644editdlrm
constraints.cpython-36.pyc222170644editdlrm
constraint_registry.cpython-36.pyc98950644editdlrm
continuous_bernoulli.cpython-36.pyc80770644editdlrm
dirichlet.cpython-36.pyc40850644editdlrm
distribution.cpython-36.pyc118220644editdlrm
exponential.cpython-36.pyc33630644editdlrm
exp_family.cpython-36.pyc28760644editdlrm
fishersnedecor.cpython-36.pyc32120644editdlrm
gamma.cpython-36.pyc34550644editdlrm
geometric.cpython-36.pyc41830644editdlrm
gumbel.cpython-36.pyc28640644editdlrm
half_cauchy.cpython-36.pyc29300644editdlrm
half_normal.cpython-36.pyc28210644editdlrm
independent.cpython-36.pyc45060644editdlrm
kl.cpython-36.pyc258440644editdlrm
kumaraswamy.cpython-36.pyc30400644editdlrm
laplace.cpython-36.pyc34420644editdlrm
lkj_cholesky.cpython-36.pyc45750644editdlrm
logistic_normal.cpython-36.pyc23200644editdlrm
log_normal.cpython-36.pyc24380644editdlrm
lowrank_multivariate_normal.cpython-36.pyc80740644editdlrm
mixture_same_family.cpython-36.pyc70730644editdlrm
multinomial.cpython-36.pyc50200644editdlrm
multivariate_normal.cpython-36.pyc85340644editdlrm
negative_binomial.cpython-36.pyc41490644editdlrm
normal.cpython-36.pyc41380644editdlrm
one_hot_categorical.cpython-36.pyc51730644editdlrm
pareto.cpython-36.pyc25160644editdlrm
poisson.cpython-36.pyc26820644editdlrm
relaxed_bernoulli.cpython-36.pyc55950644editdlrm
relaxed_categorical.cpython-36.pyc55630644editdlrm
studentT.cpython-36.pyc34830644editdlrm
transformed_distribution.cpython-36.pyc73350644editdlrm
transforms.cpython-36.pyc429810644editdlrm
uniform.cpython-36.pyc35800644editdlrm
utils.cpython-36.pyc68020644editdlrm
von_mises.cpython-36.pyc50790644editdlrm
weibull.cpython-36.pyc27370644editdlrm
__init__.cpython-36.pyc59810644editdlrm
Edit: /usr/local/lib64/python3.6/site-packages/torch/distributions/__pycache__/pareto.cpython-36.pyc (2516B)
3 Eg ใ@sTddlmZddlmZddlmZddlmZmZddl m Z Gdd„deƒZ dS) ้)ฺ constraints)ฺ Exponential)ฺTransformedDistribution)ฺAffineTransformฺ ExpTransform)ฺ broadcast_allcsteZdZdZejejdœZd‡fdd„ Zd‡fdd„ Ze dd „ƒZ e d d „ƒZ ej d d ddd„ƒZ dd„Z‡ZS)ฺParetoa‰ Samples from a Pareto Type 1 distribution. Example:: >>> m = Pareto(torch.tensor([1.0]), torch.tensor([1.0])) >>> m.sample() # sample from a Pareto distribution with scale=1 and alpha=1 tensor([ 1.5623]) Args: scale (float or Tensor): Scale parameter of the distribution alpha (float or Tensor): Shape parameter of the distribution )ฺalphaฺscaleNcsNt||ƒ\|_|_t|j|d}tƒtd|jdg}tt|ƒj|||ddS)N)ฺ validate_argsr)ฺlocr ) rr r rrrฺsuperrฺ__init__)ฺselfr r r Z base_distZ transforms)ฺ __class__ฉ๚F/usr/local/lib64/python3.6/site-packages/torch/distributions/pareto.pyrszPareto.__init__cs<|jt|ƒ}|jj|ƒ|_|jj|ƒ|_tt|ƒj||dS)N)ฺ _instance)Z_get_checked_instancerr ฺexpandr r )rZ batch_shaperฺnew)rrrrs z Pareto.expandcCs |jjdd}||j|dS)N้)ฺmin)r ฺclampr )rฺarrrฺmean$sz Pareto.meancCs4|jjdd}|jjdƒ||djdƒ|dS)N้)rr)r rr ฺpow)rrrrrฺvariance*szPareto.varianceFr)Z is_discreteZ event_dimcCs tj|jƒS)N)rฺ greater_thanr )rrrrฺsupport0szPareto.supportcCs|j|jjƒd|jjƒS)Nr)r r ฺlogZ reciprocal)rrrrฺentropy4szPareto.entropy)N)N)ฺ__name__ฺ __module__ฺ __qualname__ฺ__doc__rZpositiveZarg_constraintsrrฺpropertyrrZdependent_propertyrr!ฺ __classcell__rr)rrrs   rN) Ztorch.distributionsrZtorch.distributions.exponentialrZ,torch.distributions.transformed_distributionrZtorch.distributions.transformsrrZtorch.distributions.utilsrrrrrrฺs