/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__/kumaraswamy.cpython-36.pyc (3040B)
3 Ego @shddlZddlmZddlmZddlmZddlmZm Z ddl m Z m Z ddZ Gd d d eZdS) N) constraints)Uniform)TransformedDistribution)AffineTransformPowerTransform) broadcast_alleuler_constantcCs<d||}tj|tj|tj||}|tj|S)zE Computes nth moment of Kumaraswamy using using torch.lgamma )torchlgammaexp)abnZarg1Z log_valuerK/usr/local/lib64/python3.6/site-packages/torch/distributions/kumaraswamy.py_moments s "rcsheZdZdZejejdZejZdZ dfdd Z dfdd Z e d d Z e d d Zd dZZS) Kumaraswamya Samples from a Kumaraswamy distribution. Example:: >>> m = Kumaraswamy(torch.tensor([1.0]), torch.tensor([1.0])) >>> m.sample() # sample from a Kumaraswamy distribution with concentration alpha=1 and beta=1 tensor([ 0.1729]) Args: concentration1 (float or Tensor): 1st concentration parameter of the distribution (often referred to as alpha) concentration0 (float or Tensor): 2nd concentration parameter of the distribution (often referred to as beta) )concentration1concentration0TNcst||\|_|_tj|jj}ttj|jdtj|jd|d}t|jj dt dddt|jj dg}t t |j |||ddS)Nrr ) validate_args)exponentg?)locZscaleg)rrrr finfoZdtyperZ full_liker reciprocalrsuperr__init__)selfrrrrZ base_distZ transforms) __class__rrr&s  zKumaraswamy.__init__cs<|jt|}|jj||_|jj||_tt|j||dS)N) _instance)Z_get_checked_instancerrexpandrr)rZ batch_shapernew)rrrr 1s zKumaraswamy.expandcCst|j|jdS)Nr )rrr)rrrrmean7szKumaraswamy.meancCst|j|jdtj|jdS)N)rrrr powr")rrrrvariance;szKumaraswamy.variancecCsTd|jj}d|jj}tj|jdt}|||tj|jtj|jS)Nr )rrrr Zdigammarlog)rt1t0ZH0rrrentropy?szKumaraswamy.entropy)N)N)__name__ __module__ __qualname____doc__rZpositiveZarg_constraintsZ unit_intervalZsupportZ has_rsamplerr propertyr"r%r) __classcell__rr)rrrs   r)r Ztorch.distributionsrZtorch.distributions.uniformrZ,torch.distributions.transformed_distributionrZtorch.distributions.transformsrrZtorch.distributions.utilsrrrrrrrrs