U 9%e$0@sdddlZddlmZmZmZmZddlZddlmZddl m Z ddl m Z dgZ GdddZdS)N)AnyDictOptionalTuple) constraints) lazy_property)_size Distributioncs"eZdZdZdZdZdZeeddddZ e e dfe j e j e edfd d Z d=e j d d d Zee j dddZee j dddZeeeejfdddZee edddZee jdddZee jdddZee jdddZee jdddZe fe j e jdd d!Ze fe j e jdd"d#Ze e jd$d%d&Z!e je jdd'd(Z"e je jdd)d*Z#e je jdd+d,Z$d>ee jd-d.d/Z%e jdd0d1Z&e jdd2d3Z'e fe(e)e d4fdd5d6Z*e jddd7d8Z+d?d9d:Z,edd;d<Z-Z.S)@r zP Distribution is the abstract base class for probability distributions. FTN)valuereturncCs|dkr t|t_dS)a Sets whether validation is enabled or disabled. The default behavior mimics Python's ``assert`` statement: validation is on by default, but is disabled if Python is run in optimized mode (via ``python -O``). Validation may be expensive, so you may want to disable it once a model is working. Args: value (bool): Whether to enable validation. )TFN) ValueErrorr _validate_args)r r_/var/www/html/Darija-Ai-API/env/lib/python3.8/site-packages/torch/distributions/distribution.pyset_default_validate_argss z&Distribution.set_default_validate_args) batch_shape event_shape validate_argsc s||_||_|dk r||_|jrz |j}Wn2tk r\i}t|jdddYnX|D]\}}t |rzqf||j krt t t||trqft ||}||}|sftd|dt|jdt|jdt|dt|d | qftdS) Nz$ does not define `arg_constraints`. zAPlease set `arg_constraints = {}` or initialize the distribution z2with `validate_args=False` to turn off validation.zExpected parameter z ( of shape z) of distribution z to satisfy the constraint , but found invalid values: ) _batch_shape _event_shaper arg_constraintsNotImplementedErrorwarningswarn __class__itemsrZ is_dependent__dict__ isinstancegetattrtypercheckallr __name__tupleshapereprsuper__init__) selfrrrrparam constraintr validrrrr)&s>        :zDistribution.__init__)rcCstdS)a/ Returns a new distribution instance (or populates an existing instance provided by a derived class) with batch dimensions expanded to `batch_shape`. This method calls :class:`~torch.Tensor.expand` on the distribution's parameters. As such, this does not allocate new memory for the expanded distribution instance. Additionally, this does not repeat any args checking or parameter broadcasting in `__init__.py`, when an instance is first created. Args: batch_shape (torch.Size): the desired expanded size. _instance: new instance provided by subclasses that need to override `.expand`. Returns: New distribution instance with batch dimensions expanded to `batch_size`. Nr)r*r _instancerrrexpandMszDistribution.expand)r cCs|jS)zF Returns the shape over which parameters are batched. )rr*rrrrbszDistribution.batch_shapecCs|jS)zJ Returns the shape of a single sample (without batching). )rr2rrrriszDistribution.event_shapecCstdS)a  Returns a dictionary from argument names to :class:`~torch.distributions.constraints.Constraint` objects that should be satisfied by each argument of this distribution. Args that are not tensors need not appear in this dict. Nr/r2rrrrpszDistribution.arg_constraintscCstdS)z Returns a :class:`~torch.distributions.constraints.Constraint` object representing this distribution's support. Nr/r2rrrsupportzszDistribution.supportcCstdS)z7 Returns the mean of the distribution. Nr/r2rrrmeanszDistribution.meancCst|jddS)z7 Returns the mode of the distribution. z does not implement modeN)rrr2rrrmodeszDistribution.modecCstdS)z; Returns the variance of the distribution. Nr/r2rrrvarianceszDistribution.variancecCs |jS)zE Returns the standard deviation of the distribution. )r6sqrtr2rrrstddevszDistribution.stddev) sample_shaper c Cs*t||W5QRSQRXdS)z Generates a sample_shape shaped sample or sample_shape shaped batch of samples if the distribution parameters are batched. N)torchZno_gradrsampler*r9rrrsamples zDistribution.samplecCstdS)z Generates a sample_shape shaped reparameterized sample or sample_shape shaped batch of reparameterized samples if the distribution parameters are batched. Nr/r<rrrr;szDistribution.rsample)nr cCstdt|t|fS)zq Generates n samples or n batches of samples if the distribution parameters are batched. z6sample_n will be deprecated. Use .sample((n,)) instead)rr UserWarningr=r:Size)r*r>rrrsample_ns zDistribution.sample_ncCstdS)z Returns the log of the probability density/mass function evaluated at `value`. Args: value (Tensor): Nr/r*r rrrlog_probszDistribution.log_probcCstdS)z Returns the cumulative density/mass function evaluated at `value`. Args: value (Tensor): Nr/rBrrrcdfszDistribution.cdfcCstdS)z Returns the inverse cumulative density/mass function evaluated at `value`. Args: value (Tensor): Nr/rBrrricdfszDistribution.icdf)r1r cCstdS)ar Returns tensor containing all values supported by a discrete distribution. 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