/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__/exponential.cpython-36.pyc (3363B)
3 Eg @sLddlmZddlZddlmZddlmZddlmZGdddeZ dS))NumberN) constraints)ExponentialFamily) broadcast_allcseZdZdZdejiZejZdZdZ e ddZ e ddZ e d d Z dfd d Zdfdd ZejfddZddZddZddZddZe ddZddZZS) Exponentiala4 Creates a Exponential distribution parameterized by :attr:`rate`. Example:: >>> m = Exponential(torch.tensor([1.0])) >>> m.sample() # Exponential distributed with rate=1 tensor([ 0.1046]) Args: rate (float or Tensor): rate = 1 / scale of the distribution rateTrcCs |jjS)N)r reciprocal)selfr K/usr/local/lib64/python3.6/site-packages/torch/distributions/exponential.pymeanszExponential.meancCs |jjS)N)rr)r r r r stddevszExponential.stddevcCs |jjdS)N)rpow)r r r r variance#szExponential.varianceNcs@t|\|_t|trtjn|jj}tt|j ||ddS)N) validate_args) rr isinstancertorchSizesizesuperr__init__)r rr batch_shape) __class__r r r's zExponential.__init__csD|jt|}tj|}|jj||_tt|j|dd|j|_|S)NF)r) Z_get_checked_instancerrrrexpandrr_validate_args)r rZ _instancenew)rr r r,s   zExponential.expandcCsT|j|}tjjr>tj||jj|jjd}| j |jS|jj |j |jS)N)dtypedevice) Z_extended_shaper_CZ_get_tracing_stateZrandrrrlog1prZ exponential_)r Z sample_shapeshapeur r r rsample4s   zExponential.rsamplecCs$|jr|j||jj|j|S)N)r_validate_samplerlog)r valuer r r log_prob<s zExponential.log_probcCs&|jr|j|dtj|j |S)N)rr%rexpr)r r'r r r cdfAs zExponential.cdfcCstjd| |jS)Nr))rr&r)r r'r r r icdfFszExponential.icdfcCsdtj|jS)Ng?)rr&r)r r r r entropyIszExponential.entropycCs |j fS)N)r)r r r r _natural_paramsLszExponential._natural_paramscCstj|  S)N)rr&)r xr r r _log_normalizerPszExponential._log_normalizer)N)N)__name__ __module__ __qualname____doc__rZpositiveZarg_constraintsZsupportZ has_rsampleZ_mean_carrier_measurepropertyr r rrrrrr$r(r+r,r-r.r0 __classcell__r r )rr r s"      r) ZnumbersrrZtorch.distributionsrZtorch.distributions.exp_familyrZtorch.distributions.utilsrrr r r r s