bi6ddlZddlmZmZddlZddlmZmZmZddlm Z m Z ddl m Z ddl mZmZddlmZdgZGd de Zy) N)OptionalUnion)infnanTensor)Chi2 constraints) Distribution)_standard_normal broadcast_all)_sizeStudentTc TeZdZdZej ej ej dZej ZdZ e de fdZ e de fdZ e de fdZ dd ee efd ee efd ee efd eeddf fd Zdfd Zej,fdede fdZdZdZxZS)ra Creates a Student's t-distribution parameterized by degree of freedom :attr:`df`, mean :attr:`loc` and scale :attr:`scale`. Example:: >>> # xdoctest: +IGNORE_WANT("non-deterministic") >>> m = StudentT(torch.tensor([2.0])) >>> m.sample() # Student's t-distributed with degrees of freedom=2 tensor([ 0.1046]) Args: df (float or Tensor): degrees of freedom loc (float or Tensor): mean of the distribution scale (float or Tensor): scale of the distribution )dflocscaleTreturnc|jjtj}t||j dk<|S)N memory_format)rclonetorchcontiguous_formatrrselfms W/home/cdr/jupyterlab/.venv/lib/python3.12/site-packages/torch/distributions/studentT.pymeanz StudentT.mean*s2 HHNN)@)@N A$''Q,c|jSN)r)rs rmodez StudentT.mode0s xxr c|jjtj}|j|jdkDj d|j|jdkDz|j|jdkDdz z ||jdkD<t ||jdk|jdkDz<t||jdk<|S)Nrr)rrrrrpowrrrs rvariancezStudentT.variance4s GGMM(?(?M @ JJtww{ # ' ' *ggdggk" #wwtww{#a' ) $''A+ -0477args7 " ""19E ,o |o r