output image : tensor to PIL

Create sinusoidal timestep embeddings. :param t: a 1-D Tensor of N indices, one per batch element. These ma

Drops labels to enable classifier-free guidance.

Update the reweighting using losses from a model. Sub-classes should override this method to update the reweighting using los

Get a numpy array of weights, one per diffusion step. The weights needn't be normalized, but must be positive.

r""" Function invoked when calling the pipeline for generation. Args: prompt (`str` or `List[str]`, *optional*):

r""" Function invoked when calling the pipeline for generation. Args: image: The image required for super

r"""Convenience getter. `collector[name]` is a synonym for `collector.mean(name)`.

Args: index (int): Index Returns: tuple: (image, target) where target is class_index of the target class.

Args: index (int): Index Returns: tuple: (sample, target) where target is class_index of the target class.

Args: index (int): Index Returns: tuple: (image, target) where target is class_index of the target class.

Estimate the manifold of given feature vectors. :param session: the TensorFlow session. :param row_batch_size: row batch siz

Args: query_dim: the dimension of the query. out_dim: the dimension of the output. dim_head: the dimensio