Αi!.SSKJr SSKrSSKJr SSKrSSKrSSKJr SSK J r J r SSK J r SSKJrJr \(aSSKJr SS KJr SS KJr SS KJrJr "S S 5rg)) annotationsN) TYPE_CHECKING)_C_ops)check_variable_and_dtype convert_dtype)Variable)in_dynamic_or_pir_mode in_pir_mode)Sequence) TypeGuard)Tensor)NestedNumericSequence TensorLikecl^\rSrSrSrSSU4Sjjjr\SSj5r\SSj5r\SSj5r \SSj5r /4SSjjr /4SS jjr SS jr SS jrSS jrSS jrSSjrSSjrSSjrS SjrS!SjrS"S#SjjrS"S$SjjrS SjrSrU=r$)% Distribution(a The abstract base class for probability distributions. Functions are implemented in specific distributions. Args: batch_shape(Sequence[int], optional): independent, not identically distributed draws, aka a "collection" or "bunch" of distributions. event_shape(Sequence[int], optional): the shape of a single draw from the distribution; it may be dependent across dimensions. For scalar distributions, the event shape is []. For n-dimension multivariate distribution, the event shape is [n]. c>[U[5(aUO [U5Ul[U[5(aUO [U5Ul[TU]5 gN) isinstancetuple _batch_shape _event_shapesuper__init__)self batch_shape event_shape __class__s `/var/www/html/banglarbhumi/venv/lib/python3.13/site-packages/paddle/distribution/distribution.pyrDistribution.__init__6sX +u-- {# +u-- {#  cUR$)zMReturns batch shape of distribution Returns: Sequence[int]: batch shape )rrs rrDistribution.batch_shapeF   r!cUR$)zMReturns event shape of distribution Returns: Sequence[int]: event shape )rr#s rrDistribution.event_shapeOr%r!c[e)zMean of distributionNotImplementedErrorr#s rmeanDistribution.meanX "!r!c[e)zVariance of distributionr)r#s rvarianceDistribution.variance]r-r!c[e)zSampling from the distribution.r)rshapes rsampleDistribution.sampleb!!r!c[e)zreparameterized sampler)r2s rrsampleDistribution.rsamplefr6r!c[e)z The entropy of the distribution.r)r#s rentropyDistribution.entropyjr6r!c[e)z7The KL-divergence between self distributions and other.r))rothers r kl_divergenceDistribution.kl_divergencenr6r!c@URU5R5$)zoProbability density/mass function evaluated at value. 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Args: param (Tensor): low and high in Uniform class, loc and scale in Normal class. value (Tensor): The input tensor. Returns: value (Tensor): Change value's dtype if value's dtype is different from param. rEr^r_rB)r^r_ztdtype of input 'value' needs to be the same as parameters of distribution class. dtype of 'value' will be converted.r`) rR is_complexrmrar r rrrkrlrcast)rparamrEs r_check_values_dtype_in_probs)Distribution._check_values_dtype_in_probss   U # #<< , , ! # #}}(7Y $:J{{ekk)mEKK.HM/ K{{5++66L    "   ;;%++ % MMG ;;uKK8 8 r!cU(a.[R"U5[R"U*5- $[R"U5$)z Converts probabilities into logits. For the binary, probs denotes the probability of occurrence of the event indexed by `1`. For the multi-dimensional, values of last axis denote the probabilities of occurrence of each of the events. )rRloglog1p)rrK is_binarys r_probs_to_logitsDistribution._probs_to_logitss=ZZ uf!5 5 E" r!cU(a)[RRRU5$[RRR USS9$)z Converts logits into probabilities. For the binary, each value denotes log odds, whereas for the multi-dimensional case, the values along the last dimension denote the log probabilities of the events. )axis)rRnn functionalsigmoidsoftmax)rlogitsrs r_logits_to_probsDistribution._logits_to_probs(sJ II ( ( 0 %%--f2-> r!c UHgn[U[[[[R [ [RR45(aMR[S[U535e [SU55(d[R"5nUH@n[U[ [RR45(dM4URn O UVs/sHHn[U[ [RR45(aUO[R"X#S9PMJ nn[R "U5$[R "U5$s snf)aP Returns a list where each arg is broadcasted. Scalar args are upcast to tensors having the same data type as the first Tensor passed to `args`. If all the args are scalars, then they are upcasted to Tensors with paddle default data type. Args: value (float, list, numpy.ndarray, Tensor) Returns: Broadcasted Tensor of args. r]c3v# UH/n[U[[RR45v M1 g7fr)rrrRrSrT).0rYs r .Distribution._broadcast_all..Ls, EIcJsXvzz'7'78 9 9Ts79r`)rrbrcrrdrerrRrSrTrfrgallget_default_dtypera to_tensorbroadcast_tensors)rrVrYranew_argss r_broadcast_allDistribution._broadcast_all6s;CeRZZ6::;K;KL pquvyqzp{|  EI   ,,.EcHfjj.>.>#?@@IIE   C"#&**2B2B'CDD))#;< ++H5 5''--s$AE!)rr)r)r Sequence[int]rrreturnNone)rr)rr )r3rrr )r>rrr )rEr rr )rNzSequence[int] | Tensorrr )rV"TensorLike | NestedNumericSequencerzTypeGuard[Tensor])rVrrztuple[Tensor, ...])rr rEr rr )F)rKfloat | Tensorrboolrr )rrrrrr )__name__ __module__ __qualname____firstlineno____doc__rpropertyrrr+r/r4r8r;r?rFrBrKrOrZr{rrrr__static_attributes__ __classcell__)rs@rrr(sZ MO(  $  15    '.7'. '.'.r!r) __future__rrktypingrnumpyrdrRrpaddle.base.data_feederrrpaddle.base.frameworkrpaddle.frameworkr r collections.abcr typing_extensionsr r paddle._typingrrrrr!rrsA#  K* (+@u.u.r!