Computes the differentiable MS-SSIM loss Reference: [1] https://github.com/jorge-pessoa/pytorch-msssim/blob/dev/pytorch_msssi

Computes the Inverse Multi-Quadratics Kernel between x1 and x2, given by k(x_1, x_2) = \sum \frac{C}{C + \|x_1 - x_2

Computes the Inverse Multi-Quadratics Kernel between x1 and x2, given by k(x_1, x_2) = \sum \frac{C}{C + \|x_1 - x_2

Computes the RBF Kernel between x1 and x2. :param x1: (Tensor) :param x2: (Tensor) :param eps: (Float) :retur

Computes the RBF Kernel between x1 and x2. :param x1: (Tensor) :param x2: (Tensor) :param eps: (Float) :retur

Computes the Sliced Wasserstein Distance (SWD) - which consists of randomly projecting the encoded and prior vectors and computing

Maps the given latent codes onto the image space. :param z: (Tensor) [B x D x H x W] :return: (Tensor) [B x C x H x W

Encodes the input by passing through the encoder network and returns the latent codes. :param input: (Tensor) Input tensor to

Encodes the input by passing through the encoder network and returns the latent codes. :param input: (Tensor) Input tensor to

Encodes the input by passing through the encoder network and returns the latent codes. :param input: (Tensor) Input tensor to

Encodes the input by passing through the encoder network and returns the latent codes. :param input: (Tensor) Input tensor to

Encodes the input by passing through the encoder network and returns the latent codes. :param input: (Tensor) Input tensor to

Encodes the input by passing through the encoder network and returns the latent codes. :param input: (Tensor) Input tensor to

Encodes the input by passing through the encoder network and returns the latent codes. :param input: (Tensor) Input tensor to

Encodes the input by passing through the encoder network and returns the latent codes. :param input: (Tensor) Input tensor to

Encodes the input by passing through the encoder network and returns the latent codes. :param input: (Tensor) Input tensor to

Encodes the input by passing through the encoder network and returns the latent codes. :param input: (Tensor) Input tensor to

Encodes the input by passing through the encoder network and returns the latent codes. :param input: (Tensor) Input tensor to

Encodes the input by passing through the encoder network and returns the latent codes. :param input: (Tensor) Input tensor to

Encodes the input by passing through the encoder network and returns the latent codes. :param input: (Tensor) Input tensor to

Encodes the input by passing through the encoder network and returns the latent codes. :param input: (Tensor) Input tensor to

Encodes the input by passing through the encoder network and returns the latent codes. :param input: (Tensor) Input tensor to

Encodes the input by passing through the encoder network and returns the latent codes. :param input: (Tensor) Input tensor to

Encodes the input by passing through the encoder network and returns the latent codes. :param input: (Tensor) Input tensor to

Encodes the input by passing through the encoder network and returns the latent codes. :param input: (Tensor) Input tensor to

Encodes the input by passing through the encoder network and returns the latent codes. :param input: (Tensor) Input tensor to

Encodes the input by passing through the encoder network and returns the latent codes. :param input: (Tensor) Input tensor to

Encodes the input by passing through the encoder network and returns the latent codes. :param input: (Tensor) Input tensor to

Used to fade in downscaled using avg pooling and output from CNN

Used to fade in downscaled using avg pooling and output from CNN

:param model: :return:

:param model: :return:

:param model: :return:

:param model: :return:

:param model: :return:

:param model: :return:

:param model: :return:

:param model: :return:

:param model: :return:

:param model: :return:

:param model: :return:

Returns random samples from latent distribution's (Gaussian) unit sphere for projecting the encoded samples and the distribut

:param critic: 判别器模型 :param real: 真实样本 :param fake: 生成的样本 :param device: 设备CUP or GPU :return: