\;j#dddlZddlZddlZddlmZddlmZmZddlm Z ddl m Z GddZ y)N)_C_ops)check_variable_and_dtype convert_dtype)Variable)in_dynamic_modeceZdZdZdfd ZedZedZedZedZ ddZ ddZ d Z d Z d Zd Zd ZdZdZdZdZddZddZxZS) Distributiona> 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]. ct|tr|n t||_t|tr|n t||_t|y)N) isinstancetuple _batch_shape _event_shapesuper__init__)self batch_shape event_shape __class__s iG:\00. PROJECTS\API\Inventory\templateJSON\kerjaOCR\Lib\site-packages\paddle/distribution/distribution.pyrzDistribution.__init__/sR+u- {# +u- {#  c|jS)zeReturns batch shape of distribution Returns: Sequence[int]: batch shape )r rs rrzDistribution.batch_shape=   rc|jS)zeReturns event shape of distribution Returns: Sequence[int]: event shape )rrs rrzDistribution.event_shapeFrrct)zMean of distributionNotImplementedErrorrs rmeanzDistribution.meanO "!rct)zVariance of distributionrrs rvariancezDistribution.varianceTrrct)zSampling from the distribution.rrshapes rsamplezDistribution.sampleY!!rct)zreparameterized samplerr#s rrsamplezDistribution.rsample]r&rct)z The entropy of the distribution.rrs rentropyzDistribution.entropyar&rct)z7The KL-divergence between self distributions and other.r)rothers r kl_divergencezDistribution.kl_divergenceer&rc@|j|jS)zProbability density/mass function evaluated at value. Args: value (Tensor): value which will be evaluated )log_probexprvalues rprobzDistribution.probis }}U#''))rct)z&Log probability density/mass function.rr1s rr/zDistribution.log_probqr&rct)zProbability density/mass function. Note: This method will be deprecated in the future, please use `prob` instead. rr1s rprobszDistribution.probsus "!rcpt|t|jzt|jzS)zcompute shape of the sample Args: sample_shape (Tensor): sample shape Returns: Tensor: generated sample data shape )r r r)r sample_shapes r _extend_shapezDistribution._extend_shapes7 , D%%& 'D%%& ' rcdd}d}|D]}t|trd}d}|r |r td|S)z Argument validation for distribution args Args: value (float, list, numpy.ndarray, Tensor) Raises ValueError: if one argument is Tensor, all arguments should be Tensor FTz9if one argument is Tensor, all arguments should be Tensor)r r ValueError)rargs is_variable is_numberargs r_validate_argszDistribution._validate_argssK  C#x("   9K rc g}g}d}|D]}t|ttttj t fs#tdjt|t j|}|j}t|dk7r4t|dk7rtjd|jd}||z}|j!||j}|D]b}t j"||\} } t$j&j)|} t%j*| | |j!| dt|S)z Argument convert args to Tensor Args: value (float, list, numpy.ndarray, Tensor) Returns: Tensor of args. gz\Type of input args must be float, list, tuple, numpy.ndarray or Tensor, but received type {}float32float64zadata type of argument only support float32 and float64, your argument will be convert to float32.dtype)r floatlistr npndarrayr TypeErrorformattypearrayrEstrwarningswarnastypeappendbroadcast_arrayspaddletensor create_tensorassign) rr< numpy_args variable_argstmpr?arg_np arg_dtyperEarg_broadcasted_ arg_variables r _to_tensorzDistribution._to_tensors,  CcE4 H#MNryyS  XXc]F I9~*y>Y.MM{ y1,C   f %), C!#!4!4S#!> OQ!==66U6CL MM/< 8   .  ]##rctrg|j|jk7rLt|jdvr5tjdt j ||jS|St|dddgd|j|jk7r6tjdtj ||jS|S)a Log_prob and probs methods have input ``value``, if value's dtype is different from param, convert value's dtype to be consistent with param's dtype. 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. )rBrCztdtype of input 'value' needs to be the same as parameters of distribution class. dtype of 'value' will be converted.r2rBrCr/rD) rrErrOrPrcastrrT)rparamr2s r_check_values_dtype_in_probsz)Distribution._check_values_dtype_in_probss  {{ekk)mEKK.HM/ K{{5%++66L 7Y 2J  ;;%++ % MMG ;;uEKK8 8 rc|r,tj|tj| z Stj|S)a 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. )rTloglog1p)rr6 is_binarys r_probs_to_logitszDistribution._probs_to_logitss=ZZ uf!5 5 E" rc|r)tjjj|Stjjj |dS)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)rTnn functionalsigmoidsoftmax)rlogitsrhs r_logits_to_probszDistribution._logits_to_probssJ II ( ( 0 %%--f2-> r)rs)rs)F)__name__ __module__ __qualname____doc__rpropertyrrrr!r%r(r*r-r3r/r6r9r@r`rdrirr __classcell__)rs@rr r !s  !!!!""""""""*""  .*$XB    rr ) rOnumpyrHrTrpaddle.base.data_feederrrpaddle.base.frameworkrpaddle.frameworkrr rsrrr~s(, K*,h h r