/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__/dirichlet.cpython-36.pyc (4085B)
3 Eg@sdddlZddlmZddlmZddlmZddlmZddZ Gdd d eZ Gd d d eZ dS) N)Function)once_differentiable) constraints)ExponentialFamilycCs8|jddj|}tj|||}||||jddS)NTr)sumZ expand_astorchZ_dirichlet_grad)x concentration grad_outputtotalZgradrI/usr/local/lib64/python3.6/site-packages/torch/distributions/dirichlet.py_Dirichlet_backward src@s(eZdZeddZeeddZdS) _DirichletcCstj|}|j|||S)N)r Z_sample_dirichletZsave_for_backward)ctxr r rrrforwards  z_Dirichlet.forwardcCs|j\}}t|||S)N)Z saved_tensorsr)rr r r rrrbackwards z_Dirichlet.backwardN)__name__ __module__ __qualname__ staticmethodrrrrrrrrs rcseZdZdZdejejdiZejZ dZ dfdd Z dfdd Z ffd d Z d d ZeddZeddZddZeddZddZZS) Dirichleta Creates a Dirichlet distribution parameterized by concentration :attr:`concentration`. Example:: >>> m = Dirichlet(torch.tensor([0.5, 0.5])) >>> m.sample() # Dirichlet distributed with concentrarion concentration tensor([ 0.1046, 0.8954]) Args: concentration (Tensor): concentration parameter of the distribution (often referred to as alpha) r rTNcsR|jdkrtd||_|jdd|jdd}}tt|j|||ddS)Nrz;`concentration` parameter must be at least one-dimensional.) validate_argsrr)Zdim ValueErrorr shapesuperr__init__)selfr r batch_shape event_shape) __class__rrr/s  zDirichlet.__init__csN|jt|}tj|}|jj||j|_tt|j||jdd|j |_ |S)NF)r) Z_get_checked_instancerr Sizer expandr!rr_validate_args)rr Z _instancenew)r"rrr$6s   zDirichlet.expandcCs |j|}|jj|}tj|S)N)Z_extended_shaper r$rapply)rZ sample_shaperr rrrrsample>s  zDirichlet.rsamplecCsN|jr|j|tj||jdjdtj|jjdtj|jjdS)Ng?rrrr)r%Z_validate_sampler logr rlgamma)rvaluerrrlog_probCs *zDirichlet.log_probcCs|j|jjddS)NrTr)r r)rrrrmeanJszDirichlet.meancCs0|jjdd}|j||j|jd|dS)NrTr)r rpow)rZcon0rrrvarianceNszDirichlet.variancecCsb|jjd}|jjd}tj|jjdtj|||tj||jdtj|jjdS)Nrg?rrrr)r sizerr r*Zdigamma)rkZa0rrrentropySs  ,zDirichlet.entropycCs|jfS)N)r )rrrr_natural_paramsZszDirichlet._natural_paramscCs|jjdtj|jdS)Nrrr)r*rr )rr rrr_log_normalizer^szDirichlet._log_normalizer)N)N)rrr__doc__rZ independentZpositiveZarg_constraintsZsimplexZsupportZ has_rsamplerr$r(r,propertyr-r0r3r4r5 __classcell__rr)r"rrs     r) r Ztorch.autogradrZtorch.autograd.functionrZtorch.distributionsrZtorch.distributions.exp_familyrrrrrrrrs