Apply the module to `x` given `emb` timestep embeddings.

Apply the block to a Tensor, conditioned on a timestep embedding. :param x: an [N x C x ...] Tensor of features. :param em

Apply QKV attention. :param qkv: an [N x (H * 3 * C) x T] tensor of Qs, Ks, and Vs. :return: an [N x (H * C) x T] tensor a

Apply QKV attention. :param qkv: an [N x (3 * H * C) x T] tensor of Qs, Ks, and Vs. :return: an [N x (H * C) x T] tensor a

Apply the model to an input batch. :param x: an [N x C x ...] Tensor of inputs. :param timesteps: a 1-D batch of timesteps

Apply the model to an input batch. :param x: an [N x C x ...] Tensor of inputs. :param timesteps: a 1-D batch of timesteps

Apply the model to an input batch. :param x: an [N x C x ...] Tensor of inputs. :param timesteps: a 1-D batch of timesteps

:param x: [B, C, T, n_bins] :return: validity: [B, 1], h: List of hiddens

Args: x (tensor): input mel, (B, c_in, T, n_bins). x_length (tensor): len of per mel. (B,). Returns:

:param x: [B, T, 80] :param cond: [B, T, cond_size] :param return_y_only: :return:

Standard forward.

Standard forward.

Input: (batch_size, data_length)

param x: tensor with shape:[B,C,mel_len,T]

Forward pass of the function. Applies the function to the input elementwise. Snake ∶= x + 1/a * sin^2 (xa)

Forward pass of the function. Applies the function to the input elementwise. SnakeBeta ∶= x + 1/b * sin^2 (xa)

r"""Load preprocessed audio and return a audio embeddings per batch

r"""Load preprocessed audio and return a audio embeddings per batch

:param x: img of size (bs, c, h, w) :return: n img crops of size (n, bs, c, kernel_size[0], kernel_size[1])

r"""Load preprocessed text and return text embeddings per batch

r"""Load preprocessed text and return text embeddings per batch