B s=ba @snddlZddlZddlmZddlmZejejejdddZddZ dd d Z d d Z ddZ ddZ dS)N)nn) functional)plog_plog_qcCstj|||ddS)N)dim)torchsum)rrrr 9/Users/wangjiarui/Desktop/Learn/CS236/HW/HW2_VAE/probs.pyKL_categoricalsr cCs@dtjt|t|d||t|||ddS)aE Compute the KL divergence of two scaled (NOT TILTED) multivariate Gaussian KL( N(mu1, diag(var1)) || N(mu2, diag(var2)) ) :param mu1: torch.Tensor, of shape [...,dim] :param var1: torch.Tensor, of shape [...,dim] :param mu2: torch.Tensor, of shape [..., dim] :param var2: torch.Tensor, of shape [..., dim] :return: g?r)r)r r logsquare)Zmu1Zvar1Zmu2Zvar2r r r KL_gaussians s r c Cs`g}|jd}|jd}x5sz0sample_from_mixture_gaussian..)r)rr%randomchoicearangedetachnumpyr enumerater rrrsamplercat) rrwsrkcountsr Z gaussian_idnumberzr )r'r sample_from_mixture_gaussian,s "r6cCsHtjtttjd tt|t||d|ddS)z Compute the log of Gaussian pdf :param mu: torch.Tensor, of shape [..., dim] :param var: torch.Tensor, of shape [..., dim] :param x: torch.Tensor, of shape [..., dim] :return: r)r)r r r%rsqrtpir)rrxr r r log_gaussian_pdf>s<r;c Cst|jd}|ddddf}tj||dd}t|||}tj|ddd}|ttj|t||dddS)z Compute the log of mixture of Gaussian pdf :param mu: torch.Tensor, of shape [..., k, dim] :param var: torch.Tensor, of shape [..., k, dim] :param weight: torch.Tensor, of shape [..., k] :param x: torch.Tensor, pf shape [..., dim] :return: r.N)rr).N)rr repeat_interleaver;maxrr exp)rrweightr:r2Z log_gaussiansZlog_gaussian_maxr r r log_mixture_gaussian_pdfKs  rA)r)r-r%r rtorch.nnrFTensorr rr#r6r;rAr r r r s