/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__/gamma.cpython-36.pyc (3455B)
3 Eg1 @sTddlmZddlZddlmZddlmZddlmZddZ Gdd d eZ dS) )NumberN) constraints)ExponentialFamily) broadcast_allcCs tj|S)N)torch_standard_gamma) concentrationr E/usr/local/lib64/python3.6/site-packages/torch/distributions/gamma.pyr srcseZdZdZejejdZejZdZdZ e ddZ e ddZ dfd d Z dfd d ZejfddZddZddZe ddZddZZS)Gammaa  Creates a Gamma distribution parameterized by shape :attr:`concentration` and :attr:`rate`. Example:: >>> m = Gamma(torch.tensor([1.0]), torch.tensor([1.0])) >>> m.sample() # Gamma distributed with concentration=1 and rate=1 tensor([ 0.1046]) Args: concentration (float or Tensor): shape parameter of the distribution (often referred to as alpha) rate (float or Tensor): rate = 1 / scale of the distribution (often referred to as beta) )rrateTrcCs |j|jS)N)rr )selfr r r mean"sz Gamma.meancCs|j|jjdS)N)rr pow)r r r r variance&szGamma.varianceNcsRt||\|_|_t|tr0t|tr0tj}n |jj}tt |j ||ddS)N) validate_args) rrr isinstancerrSizesizesuperr __init__)r rr r batch_shape) __class__r r r*s   zGamma.__init__csR|jt|}tj|}|jj||_|jj||_tt|j|dd|j |_ |S)NF)r) Z_get_checked_instancer rrrexpandr rr_validate_args)r rZ _instancenew)rr r r2s  z Gamma.expandcCsD|j|}t|jj||jj|}|jjtj|j j d|S)N)min) Z_extended_shaperrrr detachZclamp_rZfinfodtypeZtiny)r Z sample_shapeshapevaluer r r rsample;s z Gamma.rsamplecCsdtj||jj|jjd}|jr(|j||jtj|j|jdtj||j|tj |jS)N)rdevice) rZ as_tensorr rr#rZ_validate_samplerloglgamma)r r!r r r log_probAs zGamma.log_probcCs4|jtj|jtj|jd|jtj|jS)Ng?)rrr%r r&Zdigamma)r r r r entropyIsz Gamma.entropycCs|jd|j fS)Nr$)rr )r r r r _natural_paramsMszGamma._natural_paramscCs&tj|d|dtj|j S)Nr$)rr&r%Z reciprocal)r xyr r r _log_normalizerQszGamma._log_normalizer)N)N)__name__ __module__ __qualname____doc__rZpositiveZarg_constraintsZsupportZ has_rsampleZ_mean_carrier_measurepropertyrrrrrrr"r'r(r)r, __classcell__r r )rr r s    r ) ZnumbersrrZtorch.distributionsrZtorch.distributions.exp_familyrZtorch.distributions.utilsrrr r r r r s