L iddlmZmZddlZddlmZddlmZddlmZddl m Z m Z m Z m Z ddlmZddlmZmZd gZGd d eZy) )OptionalUnionN)Tensor) constraints) Distribution) broadcast_all lazy_propertylogits_to_probsprobs_to_logits) binary_cross_entropy_with_logits)_NumberNumber Geometricc ZeZdZdZej ej dZejZ dde e e e fde e e e fde eddffd Zdfd Zede fd Zede fd Zede fd Zede fd Zede fdZej2fdZdZdZxZS)ra Creates a Geometric distribution parameterized by :attr:`probs`, where :attr:`probs` is the probability of success of Bernoulli trials. .. math:: P(X=k) = (1-p)^{k} p, k = 0, 1, ... .. note:: :func:`torch.distributions.geometric.Geometric` :math:`(k+1)`-th trial is the first success hence draws samples in :math:`\{0, 1, \ldots\}`, whereas :func:`torch.Tensor.geometric_` `k`-th trial is the first success hence draws samples in :math:`\{1, 2, \ldots\}`. Example:: >>> # xdoctest: +IGNORE_WANT("non-deterministic") >>> m = Geometric(torch.tensor([0.3])) >>> m.sample() # underlying Bernoulli has 30% chance 1; 70% chance 0 tensor([ 2.]) Args: probs (Number, Tensor): the probability of sampling `1`. Must be in range (0, 1] logits (Number, Tensor): the log-odds of sampling `1`. )probslogitsNrr validate_argsreturnc 2|du|duk(r td|t|\|_n|Jt|\|_||n|}t |t rt j}n|J|j}t |)|||jr{|x|j}|dkD}|jsV|j|}tdt|jdt!|j"dt%|d|yyy)Nz;Either `probs` or `logits` must be specified, but not both.rrzExpected parameter probs (z of shape z) of distribution z* to be positive but found invalid values: ) ValueErrorrrr isinstancer torchSizesizesuper__init___validate_argsalldatatype__name__tupleshaperepr) selfrrrprobs_or_logits batch_shapevaluevalid invalid_value __class__s c/mnt/ssd/data/python-lab/Trading/venv/lib/python3.12/site-packages/torch/distributions/geometric.pyrzGeometric.__init__2s: TMv~ .M   )%0MTZ% %%*62NT[#(#4%& ow /**,K". ..)..0K MB   5#4JJEAIE99; % E6 2  U ,,-Zekk8J7KL''+Dzl3AANQ $5 cb|jt|}tj|}d|jvr |j j ||_d|jvr |jj ||_tt|'|d|j|_ |S)NrrFr) _get_checked_instancerrr__dict__rexpandrrrr)r&r( _instancenewr,s r-r2zGeometric.expandUs((I>jj- dmm # ))+6CI t}} $++K8CJ i&{%&H!00 r.c&d|jz dz SNg?rr&s r-meanzGeometric.mean`sTZZ#%%r.c@tj|jSN)r zeros_likerr8s r-modezGeometric.modeds ++r.c@d|jz dz |jz Sr6r7r8s r-variancezGeometric.variancehsdjj 3&$**44r.c0t|jdSNT) is_binary)r rr8s r-rzGeometric.logitslstzzT::r.c0t|jdSrA)r rr8s r-rzGeometric.probspst{{d;;r.c|j|}tj|jjj }tj 5tjjrStj||jj|jj}|j|}n+|jj|j|d}|j|j jz j!cdddS#1swYyxYw)N)dtypedevice)min)_extended_shaperfinforrEtinyno_grad_C_get_tracing_staterandrFclampr4uniform_loglog1pfloor)r& sample_shaper$rKus r-samplezGeometric.samplets$$\2{{4::++,11 ]]_ =xx**,JJuDJJ,<,rus>" +9 A' -w w r.